Industry 4.0 and the Digital Transformation of International Business 9811978794, 9789811978791

Table of contents :
Foreword
Preface
Acknowledgement
Contents
Editors and Contributors
The Global Impact of Pandemic 2020: A Critical Analysis and a Way Forward
1 Introduction
2 Review of Literature
3 Objectives of the Study
4 Research Methodology
5 Discussion and Analysis
5.1 Economic Impact of COVID-19’s on China and Its Various Industries
5.2 Industries and Economic Sectors that Have Been Negatively Affected by the Pandemic in China
5.3 Chinese Government’s Stimulus as a Relief Measure for COVID-19 to Different Sectors in the Economy (Chinese Government Websites)
5.4 Bounce Back and Re-opening of China’s Economy
6 COVID-19 Economic Impact on European Countries
6.1 Unemployment and Job Insecurity in Europe
6.2 Role of the Governments and Companies
7 Case study of Sweden and Denmark: A Comparison of Consumer Spending Habit of Sweden (Country with Lenient Home Quarantine Orders) with Denmark (Country that Imposed Strict Lockdown Measures)
8 Sectoral Impact
8.1 Industrial Sectors Negatively Impacted by the Coronavirus Outbreak
8.2 Industrial Sectors Positively Impacted by the Coronavirus Outbreak
9 Conclusion
References
Challenges of Adapting to the Fourth Industrial Revolution in Emerging Economies: A Bangladesh CASE
1 Introduction
2 Literature Review
2.1 Industrial Revolution 4.0
2.2 Industrial Implications of Industry 4.0
2.3 Implications of Industry 4.0 in Bangladesh
2.4 Barriers of Adapting to the Industry 4.0
2.5 Significance of Industry 4.0 for Bangladesh
3 Methodology
4 Results and Discussion
5 Recommendation and Scope for Future Research
References
“Entrepreneurship in the Digital Era. A Systematic Literature Review”
1 Introduction
2 Methods
3 Findings
3.1 Descriptive Statistics
3.2 The Analysis of the Contents of the Article
3.3 Theoretical Approaches
3.4 Methods
3.5 Thematic Analysis
4 Conclusion and Research Agenda
References
International Business and Block-Chain Ventures
1 Introduction
2 Governance Functions
3 The Application of Block-Chain Technology in International Finance
4 International Supply Chain Management and Logistics
5 International Marketing and Advertising
6 Impact of Block-Chain Applications on Global Governance
7 Protection of Property Rights
8 Internalization of Negative Externalities
9 Contributions and Suggestions Global Governance Suggestions
References
The Rise, Fall, and Rise Again of Parikarma Events
1 Introduction
1.1 Literature Review
1.2 Methodology
2 The Birth of an Entrepreneur
3 The Entrepreneurial Itch
3.1 The Journey Begins
3.2 About Parikarma Events
3.3 The Vision and Philosophy
3.4 The Innovations and Experiments
3.5 Inculcating Culture Change at Parikarma: The Ashish Style
4 Leadership and Management Style
4.1 The Transformation
4.2 The Rise of Parikarma
4.3 The Fall of Parikarma
4.4 The Rise from Fall of Parikarma
4.5 The Way Ahead
5 Conclusion and Recommendations
References
Industry 4.0—Its Advancement and Effects on Security of Whistle-Blowers on Dark Web
1 Introduction
1.1 Bitcoin Administrations
1.2 Darknet Markets
1.3 Hacking Gatherings and Administrations
1.4 Financing
1.5 Cause of Term
2 Literature Review
2.1 The Effect of the Dark Web on Web Administration and Cyber Security
2.2 Threat and Opportunities on the Dark Web
2.3 Whistleblowing Policies of Leading European Companies
3 Research Methodology
3.1 Source of Data
3.2 Poll
3.3 Testing
4 Conclusion and Recommendation
4.1 Conclusion
4.2 Recommendation
5 Limitation and Future Scope
5.1 Limitations
5.2 Future Scope
References
Artificial Intelligence and Its Impacts on Industry 4.0
1 Introduction
1.1 Industry 4.0
1.2 Industry 4.0 Technologies
2 Research Objectives
3 Artificial Intelligence
3.1 Industry 4.0 and Artificial Intelligence
4 Literature Review
5 Research Methodology
6 Industrial Application of AI
7 Findings
8 Discussion and Implications
9 Conclusion
10 Limitations and Future Recommendation
References
Rise of Digital Entrepreneurship During COVID-19 in India
1 Introduction
2 Objective
3 Literature Review
4 Need and Importance of the Study
5 Methodology Designed
6 Findings
7 Conclusion
8 Recommendations
9 Delimitations of the Study
10 Future Implications of Research
11 Relevant Links
References
A New RFM Model Approach: RFMS
1 Introduction
2 RFM Analysis
2.1 RFM Models
2.2 Scoring with RFM
2.3 Analyses that Can Be Used with RFM
3 PESTEL Analysis
4 Proposed Model: RFMS
4.1 Economic Sensitivity
4.2 RFMS Model
5 Customer Segmentation with RFMS
5.1 Dataset
5.2 Results for Classical RFM Models
5.3 Clustering with CHAID
5.4 PESTEL Analysis
5.5 BORUSANCAT RFMS Model
5.6 Test
6 Conclusion
References
Assessing the Impact of Artificial Intelligence in e-Commerce Portal: A Comparative Study of Amazon and Flipkart
1 Introduction
2 History of AI
2.1 Phases of Artificial Intelligence (1943–1952)
2.2 Birth of Artificial Intelligence (1952–1956)
2.3 The Golden Years-Early Enthusiasm (1956–1974)
2.4 The First AI Winter (1974–1980)
2.5 A Boom of AI (1980–1987)
2.6 The Second AI Winter (1987–1993)
2.7 The Emergence of Intelligent Agents (1993–2011)
2.8 Deep Learning, Big Data Analytics and Artificial Intelligence (2011-Present)
3 Artificial Intelligence Applications
3.1 Artificial Intelligence in e-Commerce
3.2 AI at Online Retail
3.3 AI at Flipkart
3.4 AI at Amazon
4 Comparative Analysis Between Flipkart and Amazon
5 Conclusion
References
International Production and Digital Economy
1 Introduction
1.1 International Production
1.2 International Product Strategies
1.3 International Product Decisions
1.4 Advantages of International Production
1.5 Product Life Cycle in International Market
1.6 Stages of a Product Life Cycle
1.7 International Product Branding
1.8 International Branding Adapting on the Spot
1.9 Digital Economy
2 Key Features
2.1 Company Roles Include Versatility
2.2 Network Effect
2.3 Multi-sided Market
2.4 Cashless Society
2.5 Recent Challenges
2.6 The Effect of Emerging Technology on International Production
2.7 Technological Advancements in International Trade
3 Characteristics of Digital Economy
4 Creating New Value and Shaping the Future of the Digital Economy
4.1 MNCs in Digital Economy
4.2 Scope of Digitalization in MNCs
5 Digital Economy Success Factors
5.1 Promoting Customer Engagement
5.2 Developing the Right Infrastructure
5.3 Adapting to New Technology
5.4 Amplifying Partnerships
5.5 Shifting from Control Strategy to Influence Strategy with Regards for Technology
5.6 India Set to Play a Vital Role in Web Economy
References
Changing Structure of Consumer Buying Behaviour and Expectation in the Digital Era
1 Introduction
2 Research Methodology
2.1 Objectives of the Study
3 Literature Review
3.1 Consumer Behaviour
3.2 Consumer Behaviour During Digital Age
3.3 Model of Consumer Decision-Making Process in the Digital Era
3.4 Findings
4 Conclusion
References
A Software Based on Modelling Solution Using Weibull Distribution and Depreciation, Applicable in MSM e-Business and e-Commerce Industry
1 Introduction
2 Objective
3 Notations
4 Numerical Illustration
5 Sensitivity Analysis
6 Findings
7 Conclusion
8 Future Scope
References
House Price Prediction: A Case Study for Istanbul
1 Introduction
2 Literature Summary
3 Material Method
3.1 The Hedonic Price Model
3.2 Artificial Neural Network (ANN)
4 The Research Findings and Discussion
5 Results
References
Government Implications of Infrastructural Development and CSR in Industry 4.0
1 Industry 4.0
1.1 Industry 4.0 in India
1.2 Sector Wise I4.0 Espousal in India
2 Indian Government Implications of Infrastructural Development for Industry 4.0
2.1 SAMARTH Udyog Bharat 4.0
3 ‘Make in India’ Initiative
4 Corporate Social Responsibility Initiatives
5 The Salient Role of the Government
6 Conclusion
References
The Post-pandemic Perspective of Rejigging the Gig Economy in India and the Issues of Returnees to Homeland
1 Introduction
2 Objectives of the Study
3 Analysis and Observation
3.1 Status of Migrant Workers’ Deaths
3.2 Role of States for Migrant Workers
3.3 Important Areas of PMGKY (Pradhan Mantri Garib Kalyan Yojana) Scheme
3.4 New Government Initiatives in Regard to the Migrant Labourers in India
4 Practical Implication of the Study
5 Conclusion
References
Work-Life Balance and Its Socio-cultural Inclination from Industry 1.0 to Industry 4.0
1 Introduction
2 Etymology of Work-Life Balance
3 Industrial Revolution and Work-Life Balance
4 Industry 1.0 and Work-Life Balance
5 Industry 2.0 and Work-Life Balance
6 Socio-cultural Enlightenment, Industrialisation, and Work-Life Balance
7 Industry 3.0 Work-Life Balance
8 Hours of Work and Work-Life Balance
9 Women Work Participation Rate-A Matter of Concern for Indian Women
10 Dual Carrier Culture Re-defining the Work-Family Culture
11 Work-Life Balance and the Legal Environment
12 Industry 4.0 and Work-Life Balance—The Road Ahead
13 Concluding Remarks
References
The Impact of Emotional Contagion on Managerial Efficiency: IIOT as a Moderator
1 Introduction
2 Objectives
3 Hypothesis Formulation
4 Research Methodology
5 Factors Affecting Emotional Contagion
6 Result and Analysis
7 Discussion
8 Future Research
References

Citation preview

Gurinder Singh Richa Goel Vikas Garg   Editors

Industry 4.0 and the Digital Transformation of International Business

Industry 4.0 and the Digital Transformation of International Business

Gurinder Singh · Richa Goel · Vikas Garg Editors

Industry 4.0 and the Digital Transformation of International Business

Editors Gurinder Singh Amity International Business School Amity University Noida, Uttar Pradesh, India

Richa Goel Amity International Business School Amity University Noida, Uttar Pradesh, India

Vikas Garg Amity Business School Amity University Greater Noida, Uttar Pradesh, India

ISBN 978-981-19-7879-1 ISBN 978-981-19-7880-7 (eBook) https://doi.org/10.1007/978-981-19-7880-7 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Foreword

With the new wave of technical innovation, institutional contexts emerged, resulting in variations in the standardizing method across the nations. The Industry 4.0 revolution is evolving fast, and firms and entrepreneurs in other industries are beginning to feel the impact. Industry 4.0’s primary effects include delivering real-time market knowledge to firms. Thus, the new technologies developed via Industry 4.0 have established new methods for businesses, in which their operational, economic, marketing, and social demands are clearly changed. Though many economists argue that technology as a tool is meant to make the world a decentralized place, the reverse is happening. Whether this integration of the digital age with international business is a boon or curse, it will be influenced by the strategies used by the global organizations. Thus, the interaction of information age like use of artificial intelligence, robotics, big data, algorithms, and neural networks with MNE strategies has become an important area of study for international business scholars. This book gives an outline of the most pertinent issues and effects that Industry 4.0 is expected to bring on to global organizations including MNEs to developed and specially to developing economies in future. This book analyzes the possible implications for international business practice and theory and investigates the wider repercussions on employment, development, and ethics. It also classifies a few key possible impacts or scenarios and defines some relevant questions for further research. This book also discusses how businesses across their organizations will use Industry 4.0 technology to improve customer relations and provide consumers and distributor partners with the new value. I assume that academicians, students, corporates, and masses in all fields can improve and expand their knowledge with the learning of the basic trends and activities in this book. This book offers a valuable guide to the intellectual and practical work and calls for the need to rethink that knowledge is needed in real time at the various levels of the product life cycle. I am pleased to write this foreword as the Editors of this Book has given fullhearted effort for a great solution and innovation. All chapters in this book have been selected based on peer review where reviewers were very much expert in the sector.

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Foreword

I do believe that the book will be a guideline for students, teachers, customers, businesses, and policymakers and for general people of globe. This book is a good step in that direction. I wish the best of luck to the Editors of this Book in this endeavor and working to their full potential. With Best Wishes Prof. Nick Petford Vice Chancellor University of Northampton Northampton, United Kingdom

Preface

The international business sector has been transformed entirely by Internet Age and Digitization. It is the transition to the Third Industrial Revolution according to some studies and many say it is the start of the Fourth Industrial Revolution. The new digital world or Industry 4.0 is redefining the oral limits of sectors, deconstruction, and the development of new sectors, thereby boosting flexibility for labor and employment practices. With this in mind, Industry 4.0 technologies are able to enhance the competitiveness of enterprises, leading to a new age of the Renaissance production. Industry companies need to establish a strong digital culture that encourages success via continuous leadership. While new technology becomes exponentially an advantage, how digital executives discover, manage, and communicate the process significantly depends on the performance of a new IQ firm. Digitization in this changing era is all designed to introduce a sense of effectiveness and efficiency rather than the use of traditional business principles. In the era of digitalization, the use of technology such as artificial intelligence has become such a paradigm. With Industry 4.0, digitalization breaks down industry boundaries and develops new business models, generating new ones and perhaps developing them. This book focused on how international businesses are integrated with the digital age and how these technologies have generated new ways to enterprise considering Industry 4.0 looking in an “entrepreneurial” approach at current trends. This book has a wider scope as it will not only cover the basic essential areas required to be studied by undergraduates, graduates, researchers, or academicians for higher learning but will also be helpful for organizations, businesses, and entrepreneurs to create global digital businesses in the new e-commerce era. This book is a first effort to answer some of the aforementioned areas. It is dedicated to explore the new opportunities and challenges for established MNEs, small and medium-sized enterprises, new global enterprises and start-ups, as well as developing

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and developed countries, which are influenced in some way by the new information and digital era. Noida, India Noida, India Greater Noida, India

Gurinder Singh Richa Goel Vikas Garg

Acknowledgement

We wish to express our sincere appreciation to those who have contributed to this book and supported us in one way or the other during this amazing journey. First and foremost, we would like to thank with utmost devotion and humility “The Almighty Lord” for clearing all the obstacles and making it rather opportunity than a problem for this valuable work. We would like to express our special thanks to Dr. Ashok K Chauhan, Founder President Amity Group for being the mentor, a guide and a source of encouragement and support. He has been a living role model to us, taking up new challenges every day, tackling them with all his grit and determination, and always thriving to come out victorious. It is his vigor and hunger to perform in an adverse situation, which has inspired us to thrive for excellence and nothing less. It is rightly said that you cannot teach a person anything, you can only help him to find it within himself. With a sense of regard and reverence, we take this opportunity to express our deep sense of gratitude to the Springer Publishing Editor, Ms. Nupoor, for her valuable guidance, perceptive encouragement, and indispensable suggestions throughout the journey of this book. We would like to acknowledge the immense role of our family in enabling us to complete this project. We consider ourself the luckiest in the world to have such a supportive family, standing behind us with their love and support. It is more difficult than we expected to write a book and more gratifying than we ever thought possible. Thanks a lot, to everyone who wants to develop and lead others, the world is a better place. It is even better for those who share with future leaders the gift of their time. Thank you to everyone who are trying to grow and help others to grow. To everybody who were a part of this book, finally. Many people played an important role in the development of this edition of the book, and we are deeply grateful to all of them. Dr. Gurinder Singh Dr. Richa Goel Dr. Vikas Garg

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Contents

The Global Impact of Pandemic 2020: A Critical Analysis and a Way Forward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Namita Sahay, Seema Sahai, and Paridhi Jain

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Challenges of Adapting to the Fourth Industrial Revolution in Emerging Economies: A Bangladesh CASE . . . . . . . . . . . . . . . . . . . . . . . . Quazi Tafsirul Islam, Faseeha Zabir, Md. Asif Hossain, and Rifat Iqbal

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“Entrepreneurship in the Digital Era. A Systematic Literature Review” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Michela Floris and Angela Dettori

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International Business and Block-Chain Ventures . . . . . . . . . . . . . . . . . . . . Namita Rajput, Vikas Garg, Emilia Alaverdov, Jyotsna, and Shivani G. Varmani

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The Rise, Fall, and Rise Again of Parikarma Events . . . . . . . . . . . . . . . . . . Harjit Singh and Neha Puri

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Industry 4.0—Its Advancement and Effects on Security of Whistle-Blowers on Dark Web . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Anita Venaik, Shourye Jain, and Anand Nayyar Artificial Intelligence and Its Impacts on Industry 4.0 . . . . . . . . . . . . . . . . . 123 Seema Garg, Navita Mahajan, and Jayanta Ghosh Rise of Digital Entrepreneurship During COVID-19 in India . . . . . . . . . . 135 Preeti Tewari A New RFM Model Approach: RFMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Semra Erpolat Ta¸sabat, Tayfun Özçay, Salih Sertba¸s, and Esra Akca Assessing the Impact of Artificial Intelligence in e-Commerce Portal: A Comparative Study of Amazon and Flipkart . . . . . . . . . . . . . . . . 173 Sachin Gupta, Shreya Singhvi, and Giuseppe Granata

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International Production and Digital Economy . . . . . . . . . . . . . . . . . . . . . . . 189 Namita Rajput, Vikas Garg, Jyotsna, and Shivani G. Varmani Changing Structure of Consumer Buying Behaviour and Expectation in the Digital Era . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 Sunanda Vincent Jaiwant A Software Based on Modelling Solution Using Weibull Distribution and Depreciation, Applicable in MSM e-Business and e-Commerce Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217 Pooja Tiwari, Shradha Goyal, Rudresh Pandey, and Esra Sipahi House Price Prediction: A Case Study for Istanbul . . . . . . . . . . . . . . . . . . . . 233 Semra Erpolat Ta¸sabat and Mert Ersen Government Implications of Infrastructural Development and CSR in Industry 4.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251 Teena Saharan and Anchal Pathak The Post-pandemic Perspective of Rejigging the Gig Economy in India and the Issues of Returnees to Homeland . . . . . . . . . . . . . . . . . . . . 273 Rabinarayan Patnaik and Sukanta Kumar Baral Work-Life Balance and Its Socio-cultural Inclination from Industry 1.0 to Industry 4.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287 Joshin Joseph The Impact of Emotional Contagion on Managerial Efficiency: IIOT as a Moderator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305 Tilottama Singh, Rajesh Upadhyay, and Abdullah Akhtar

Editors and Contributors

About the Editors Gurinder Singh is Group Vice Chancellor, Amity Universities; Director General, Amity Group of Institutions; and Vice Chairman, Global Foundation for Learning Excellence. He has an extensive experience of more than two decades in institutional building, teaching, consultancy, research and industry. A well-known scholar and academician in the area of international business, he holds the distinction of being the youngest Founder Pro Vice Chancellor of Amity University for two terms, the Founder Director General of Amity International Business School and the Founder CEO of Association of International Business School, London. He has been instrumental in establishing various Amity campuses abroad including at London, USA, Singapore, Mauritius & other parts of the world. Richa Goel is Assistant Professor of Economics and International business at Amity International Business School, Amity University, Uttar Pradesh, India. She has a PhD in Management and has an experience of more than two decades in academics and research apart from handling many PhD scholars under her guidance. She has to her credit several publications in reputed national and international journals accompanied with participation in conferences. She is serving as a member of review committee for conferences journals and acts as Editor of Annual International Scopus Referred Journal. She is Research Coordinator with Amity International Business School, and her own areas of interest include development economics, micro economics and diversity management. Vikas Garg is the Assistant Director Executive Programs Management Domain at Amity University Uttar Pradesh, India. He has an experience of more than two decades handling many PhD scholars under his esteemed guidance. He has numerous research publications with no of Scopus and ABDC indexed international and national journals and also acting as the Editor of few renowned SCOPUS journals. He

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has always been the lead organizer in conducting various International Conferences, Workshops, Case study Competitions and has been conferred National & International Awards for Being the Best Academician, Researcher & Employee. His area of interest includes Fintech, Financial Modelling, Sustainable Banking services and International Business with multidisciplinary approach.

Contributors Esra Akca Borusan R&D and Artificial Intelligence Solutions, Istanbul, Turkey Abdullah Akhtar Mazoon University, Muscat, Oman Emilia Alaverdov Georgian Technical University, Tbilisi, Georgia Md. Asif Hossain Department of Management, School of Business and Economics, North South University, Dhaka, Bangladesh Sukanta Kumar Baral Department of Commerce, Faculty of Commerce and Management, Indira Gandhi National Tribal University (A Central University), Amarkantak, Madhya Pradesh, India Angela Dettori University of Cagliari, Cagliari, Italy Mert Ersen Yıldız Technical University, Istanbul, Turkey Michela Floris University of Cagliari, Cagliari, Italy Seema Garg Amity University, Noida, Uttar Pradesh, India Vikas Garg Amity University, Greater Noida, Uttar Pradesh, India Jayanta Ghosh S.P. Jain School of Global Management, Sydney, Australia Shradha Goyal JIMS, Kalkaji, New Delhi, India Giuseppe Granata Business Management and Marketing, University Mercatorum, Rome, Italy Sachin Gupta Mohanlal Sukhadia University, Udaipur, Rajasthan, India Rifat Iqbal Department of Management, School of Business and Economics, North South University, Dhaka, Bangladesh Quazi Tafsirul Islam Department of Management, School of Business and Economics, North South University, Dhaka, Bangladesh Paridhi Jain KPMG, Gurugram, India Shourye Jain Amity University, Noida, Uttar Pradesh, India Joshin Joseph KMML (A Govt. of Kerala Undertaking), Kollam, India

Editors and Contributors

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Jyotsna Jagan Institute of Management Studies Sector 5 Rohini, GGSIPU University, Dwarka, New Delhi, India Navita Mahajan Amity University, Noida, Uttar Pradesh, India Anand Nayyar Graduate School, Duy Tan University, Da Nang, Vietnam Rudresh Pandey Institute of Management Studies, Ghaziabad, Uttar Pradesh, India Anchal Pathak Bule Hora University, Bule Hora, Ethiopia Rabinarayan Patnaik IBCS, SOA University, Bhubaneswar, Odisha, India Neha Puri Amity College of Commerce & Finance, Amity University Uttar Pradesh, Noida, India Namita Rajput Sri Aurobindo College, University of Delhi, New Delhi, India Seema Sahai Amity University Uttar Pradesh, Noida, India Teena Saharan MGM Group, Aurangabad, India Namita Sahay Amity University Uttar Pradesh, Noida, India Salih Sertba¸s Linktera Information Technologies, Istanbul, Turkey Harjit Singh Symbiosis Centre for Management Studies, Symbiosis International (Deemed University), Noida, India Tilottama Singh AssociateProfessor, Uttaranchal Institute of Management, Uttaranchal University, Dehradun, India Shreya Singhvi Faculty of Management Studies, Mohanlal Sukhadia University, Udaipur, Rajasthan, India Esra Sipahi Social Sciences University of Ankara, Ankara, Turkey Semra Erpolat Ta¸sabat Mimar Sinan Fine Arts University, Istanbul, Turkey Preeti Tewari Department of English (Law), Lloyd Law College, Greater Noida, India Pooja Tiwari School of Business Studies, Sharda University, Greater Noida, Uttar Pradesh, India Rajesh Upadhyay Graphic Era University, Dehradun, Uttarakhand, India Shivani G. Varmani Bhaskarachara College of Applied Sciences, University of Delhi, Dwarka, New Delhi, India Anita Venaik Amity University, Noida, Uttar Pradesh, India Sunanda Vincent Jaiwant School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India

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Faseeha Zabir Department of Management, School of Business and Economics, North South University, Dhaka, Bangladesh Tayfun Özçay Borusan R&D and Information Technologies, Istanbul, Turkey

The Global Impact of Pandemic 2020: A Critical Analysis and a Way Forward Namita Sahay, Seema Sahai, and Paridhi Jain

1 Introduction A pandemic is a scenario when a disease has spread across whole country or the world. We have witnessed many such pandemics in the past like the flu pandemic: 1889–1890 affecting Russia and Europe in major light, The Spanish flu: 1918–1920 which infected people from South Seas to the North Pole. Just like the COVID-19 impact, these past pandemics also had their toll on economies of many coun tries and led to recession. The latest pandemic, the Novel Coronavirus, COVID-19, has already infected people all around the world. China was the starting point of the deadly coronavirus. City Wuhan was the first epicenter of the virus, and then it started spreading in various other cities through community transition since it is highly contagious and slowly turned into a world pandemic, making its epicenter in different continents. In order to battle coronavirus, almost the entire world has done a global lockdown of actives from social events, schools to economic activities such as manufacturing units and offices as there was no vaccine avail-able for this. Lockdown in different countries has severely impacted their economies in a negative way. Recession refers to negative GDP growth rate for 2 or more quarters, and depression in economy is basically recession over a long period of time (−10% or worse GDP growth for 3+ years). The international monetary fund (IMF) has said that the economy worldwide has already been hit by recession, and they have also anticipated it to be the worst economic fallout since the great depression of 1930. Many pro found N. Sahay (B) · S. Sahai Amity University Uttar Pradesh, Noida, India e-mail: [email protected] S. Sahai e-mail: [email protected] P. Jain KPMG, Gurugram, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_1

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Fig. 1 V-shaped and U-shaped recession curve

economists are comparing the 2020 economic crisis with that of the great depression of 1930 when unemployment rate in USA went as high as 25%. ‘We are in a new world and that world is most similar to the 1930–45 world’—Ray Dalio. The estimates about the global GDP growth impact and the economic curve are changing every now and then. Many economists that were rooting for a V-shaped economic rebound curve (Fig. 1) in the earlier stage of COVID-19 are now unsure and expect a U-shaped economic rebound curve (Fig. 1) which signifies that economies are expected to face small duration stagnation and a slow growth rate or slowrebound. The worldwide lockdown has led to the disruption of supply chain management, since the countries are more globally integrated in terms of trade today, hence generating spillover effect throughout the supply chains. Key economic factors already indicate that the world is facing a prolonged recession. As seen in Fig. 2, unemployment in America is at its highest rate since the great depression that is 15%, but these losses will be felt unequally. The industries hit hardest by COVID-19 are labor intensive that rely on mass low paid workers, and it is these people who are likely to lose their jobs along with service sector employees. An American resident is already twice as likely to be made redundant if one is earning less than $20,000 a year, to $80,000 a year. More of such unprecedented changes are expected in future as an outcome of COVID-19 outbreak and worldwide lockdowns.

2 Review of Literature Fernandes (2020) discusses the economic impact and costs of COVID-19 across 30 countries and industries under different scenarios in his report. The losses are underestimated as the crisis is being compared to earlier pandemics which is not correct as times are different, and this time we are faced with both, shocks of demand

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Fig. 2 USA, unemployment rate %

and supply with limited economic tools. As per his report, GDP growth will take an extreme hit, and the global recession is very much expected in today’s strongly integrated world. In his report, he talks about the aftermath of COVID-19 on the service-oriented economies the most and also countries like Spain, Portugal and Greece which are relying on tourism. Besides, countries largely dependent on foreign trade will also be negatively impacted, and his reports estimate that each additional month of the crisis will cost around 2.2–3% of global GDP. He also talks about disruptions in global supply chains, changes in consumption patterns and job losses of millions of people due to lockdown, and layoffs. The global stock exchanges have also fallen sharply and the volatility there can be compared to the levels of 2008- 09 financial crisis. The forecasted growth estimates given by both IMF (global slowdown by 0.1% while that of China by 0.4%) and OECD (slowdown by 2.4%) may have to be revised. The report furthermore talks about an asymmetric impact on different sectors and countries. (Seric et al. 2020) talks about the disruptions of the global value chains (GVCs) for which China is the center along with Japan, USA and EU. This disruption of GVC will impact both consumers and producers in countries in that network of GVCs. This report emphasis on the need for a coordinated policy response as stated by UN and many multilateral institutions. It also discusses the impact of substantive regionalism and nationalism in terms of reduction of diversification benefits for suppliers and reduced opportunities for developing coun tries to take advantage of global economy integration. David et al. (2020) talks about reducing the impact of unemployment in Europe and safeguarding people’s livelihood. As per the report, the impact of COVID-19 is felt majorly on the labor market with nearly 60 million jobs at stake. This is likely to have far reaching social and economic consequences. The pressing priority is

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for governments and companies to examine the occupations, industries and demographics of most vulnerable and to protect their jobs with different strategies and also strategically plan for an exit from lockdown. Jordan et al. (2021)In this discussion paper, authors look into some of the key limitations of using EdTech (education and technology integration) at scale to support education in low-income countries at a time of crisis and highlight the opportunities that have appeared so far, in a rapidly changing context. Weber et al. n.d. This report sets out to assess the initial impact of COVID-19 crisis on employment in Europe (up to Q2 2020), including its effects across sectors and on different categories of workers. It also looks at measures implemented by policymakers in a bid to limit the negative effects of the crisis. It first provides an overview of policy approaches adopted to mitigate the impact of the crisis on businesses, workers and citizens. The main focus of the report is on the development, content and impact of short-time working schemes, income support measures for selfemployed people, hardship funds and rent and mortgage deferrals. Finally, it explores the involvement of social partners in the development and implementation of such measures and the role of European funding in supporting these schemes. Bureau of Labor Statistics (2020) As per the US Bureau of Labor Statistics report, there was a fall by 20.5 million in total non-farm payroll employment and a rise by 14.7% of the unemployment rate caused by the effect of COVID-19. In all major industries and sectors, there was a loss of jobs and fall in employment particularly in leisure and hospitality sector.

3 Objectives of the Study 1. To analyze the journey of China’s economy from the worst GDP fall to its bounce back to 90% normalcy and the reason for 10% gap in recovery. 2. To examine the economic crisis faced by European nations and its toll on the current employment scenario. 3. To analyze the spending pattern of people and to find how it differs from countries with strict lockdown compared to countries imposing easy and lenient home quarantine orders. (Case Study of Sweden and Denmark). 4. To analyze sectors that experienced the strongly impacted from COVID-19 along with the sectors that are expected to thrive despite the coronavirus outbreak.

4 Research Methodology This report is a descriptive and analytical study based on secondary data. It includes use of many statistical figures and graphs from highly reliable sources which are used to draw conclusion and better understanding of current scenario. This report also includes references from many articles, webinars and interviews of great economists

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and investment bankers, informative videos along with research papers on related topics. After keenly studying insights and takes off of many economists, analysis and insights on different economic scenarios have been made.

5 Discussion and Analysis 5.1 Economic Impact of COVID-19’s on China and Its Various Industries As discussed in the introduction, earlier China was the starting point of pandemic 2020 and it is also the second largest economy throughout the world. Being the global trade leader, it allows China the power to influence the economies all across the globe. However, since the Novel Coronavirus is highly contagious in nature, it led to temporary shutdown of businesses and other economic actives in the country to maintain social distancing as a precautionary measure. Following this scenario, China’s GDP for the first quarter of 2020 shrank by 6.8%. This is the first recorded negative growth ever since the reform started as China has never undergone any economic downturn since. A huge chunk of China’s economy is dependent on export and import trade. However, with US-China trade war, we are already seeing companies worldwide are diversifying their supply chains outside of china, and COVID-19 has just accelerated that trend. China experienced a massive drop of 6.6% (Business Today) in exports earlier this year in the month of March. Imports fell by 14.2% from a year earlier, the largest contraction since January 2016. The poor reading of imports was due to low domestic demand and dropping commodity prices. Outside China shutdowns also inflicted a strong supply shock on importers in the region.

5.2 Industries and Economic Sectors that Have Been Negatively Affected by the Pandemic in China 5.2.1

Small and Medium-Sized Enterprises (SMEs)

SMEs are majorly involved in export-oriented activities and may take a disproportionately large hit due to lockdowns in quarter 2. However, the government of China has shown support for these enterprises since they are vital to the economy. SMEs contribute to 80% of the total employment and approximately 70% of GDP. They tend to be more innovative as compared to their larger counterparts, thus are highly valuable to the government. Further, rising employment and income instability is exactly the greatest barrier to return to their uniform operation for the consumer goods and service sector.

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A recent consumer survey (Nordea and Mayan entertainment survey) showed that to a mild and severe magnitude, 65%of respondents expect a loss of income. That is possibly a significant concern for Beijing. In addition to assistance to small and medium-sized businesses, a part of the Lion’s fiscal stimulus goes to spending in infrastructure, which will take responsibility for generating growth as normal. Around half of the country’s provinces have declared a total CNY6.6tn (USD930bn) investment plan for 2020. Some of the projects were al-ready scheduled for 2020; however, it is expected that the overall size of the projects will be bigger by the end of this year. Various reports suggest that Beijing will continue to rely on fiscal stimulus and not monetary stimulus.

5.2.2

Pandemic Impact on the Rural China

When talking about China, we have to consider the rural China which makes up to 700 million of its population. Major lot of this population is involved in laborintensive jobs and live on daily or weekly wages. The employment of rural workers was essentially zero for a full month of February 2020 either because no one was interested in hiring or workers could not leave. 94% of them had to move out from the city since they were unable afford the rent anymore. Even after the quarantine measures were lifted, employment for rural workers was still low. In March, only 34% workers returned to their jobs. In April, the fraction of employed workers has risen to 46%; therefore, this suggests that recovery for a large fraction of rural workers will be very slow. There has also been a significant decline in income for rural families. Around 92% villagers reported a decline in income in Feb. and 85% in March. The magnitude of the decline ranges between 2000 and 5000 RNB per month for most families, which represents 15% of the average annual per capita income for rural families. In order to cope up with decreased income level, the rural people have cut down their spending on food by 55% and have reached out to friends and relatives for loan. A 10% and 9% decrease was also observed in spending on education and health care, respectively.

5.2.3

Impact on Different Economic Activities in China

The Rhodium China Activity Tracker (R-CAT) (Fig. 3) represents the changes in various sectors and activities for the time frame of August 2014–Feb 2020. It can be observed that there is a V-shaped graph around November 2019 in all the sectors. It also showcases that level of activity is just better by 2% in month March as compared to that in Feb. 2020. The worse hit has been taken by consumer goods sector, and this major repercussion of COVID-19 has drastically reduced the consumer buying power as people are more focused on income saving for medical and other contingencies.

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Fig. 3 Rhodium China activity tracker (R-CAT). Source National Bureau of statistics, Rhodium Group

However, to combat this, the government of China introduced consumption vouchers in their stimulus package, and these were distributed among individual mothers and fathers running households. These vouchers had an expiration date so they had to be consumed within the specific time limit of around 30 days or so as after that they will be worthless; therefore, this was expected to create an overnight demand for household products which will boost and revive the consumer goods sector.

5.2.4

Impact of Pandemic on the Housing Industry in China

The real estate sector in China counts around 15–12% of China’s gross domestic product and has been the singularly important engine for GDP growth in China for decades. Looking at the graphs (Fig. 4) and statistics, we can compare the market growth and sales of 2020 with the year 2019. The decline in property sales has started in January and took the biggest fall in February almost down by 100%. By March 2020, the gap has been reduced but it is still lower by 30% as compared to that of 2019. Small cities are witnessing weakest sales momentum, with implications of construction growth later in the year (President Kevin Rudd). At present due of pandemic 2020, the ratio of household debt to household income is 140% (as of April 2020) which is somewhat similar to the ratio America had during the housing crisis 2008.

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Fig. 4 Property sales—residential housing sales by area in 30 cities, 2020 versus 2019. Source Eastmoney and Soufun

Therefore, this could add more to the burden of economic downturn if nationwide prices keep falling, driving investment demand to the sidelines and hence reducing the financing for construction.

5.2.5

Impact on the Automobile Industry in China

The automobile industry was already suffering from new emissions standards imposed last July (2019), and it has furthermore taken the deepest hit from coronavirus related lockdowns. As we can observe in Fig. 5, sales were down by 80% in Feb. and just a minor recovery is visible in March. A dip in sales has a further chain effect that is major decline in industrial production in upcoming months as the dealers are not willing to re-stock inventories. Slowdown in the service sector and rise of unemployment will lead to decline in consumer credit growth which is likely to slow down auto sales later in the year as well (Asia society.)

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Fig. 5 Passenger car sales—weekly retail passenger car sales, growth rates Jan 2019-Apr 2020. Source China Passenger Car Association

5.3 Chinese Government’s Stimulus as a Relief Measure for COVID-19 to Different Sectors in the Economy (Chinese Government Websites) 5.3.1

General Economy

Under this, it has focused on easing monetary rates and reverse repo rate (RRR) cut. They have issued more local government special bonds and front loading construction projects which are expected to result in growth of infrastructure investment by 8–10% YoY. Easing of house- hold restriction is also a part of it such as the down payment requirement has been lowered to 20%.

5.3.2

Corporate Sector

To provide relief to the affected companies, major loans will be issued to them by the end of February, and a reduction of corporate tax for such companies has been done. Under this, they have also extended the loan payment period by one year for the affected loans, and the loans will not be classified as non-performing liability (NPL). In this stimulus, subsidies will be provided to the industries that are directly hit by the shutdown such as tourism, catering, etc. It has also cut costs such as rent, electricity and toll fees. Employer’s social insurance contribution will be lowered or waved for five months. Lastly, it also includes waving of port fees on export–import goods.

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Consumers

For the end-consumer or common man, the stimulus includes extending loans to people with lost income for one month along with cutting various costs such as school fees. In order to revive and increase the consumer buying power, the government has also announced various subsidies for consumption example: car purchase and consumption vouchers (discussed in detail later in the report.).

5.4 Bounce Back and Re-opening of China’s Economy In spite of everything, China was able to combat coronavirus and get it under control domestically, and the economy has begun to re-open, and authorities have waived off many restrictions including stay at home orders (The Economist). Therefore, China’s economy is bouncing back and is now functioning at 90% of normal levels. Educational institutions are opened with full force, restaurants are open, manufacturing units are functions and companies such as apple have also opened all its stores across China which were shut earlier. The trade sector in April rose by 3.5%, the first positive growth since December 2019. Nonetheless, the 10% gap is due to practice of social distancing and fear instilled among people and in a workplace until a full proof vaccine is introduced. Despite a 90% bounce back and 3.5% rise in overseas shipments, many manufacturing units are still struggling with canceled or postponed over sea orders as global demand remains low. Many manufacturers are facing problem of excess stockpiled inventory in comparison to demand and falling profits, some have laid off their workers as an effort of cost reduction. From Fig. 6, we can see that the consumer footfall has only recovered by 50%. Hotel occupancy is still down by around 50, and 75% less number of people are flying. Thus, from these numbers, we can observe that the service catering and aviation industry has taken the hardest hit and will take a very long time to recover.

6 COVID-19 Economic Impact on European Countries Europe became the second epicenter of coronavirus after China. Italy was the first country to be hit by this virus in Europe. Despite, having the best medical healthcare system, Italy failed to combat coronavirus and witnessed huge loss of human lives. After Italy, it started to spread in the UK and other European nations. This has vastly impacted the economy of the entire Europe. As we can see in Fig. 7, five of European nations in global stock market have dropped by average of -35% and also in Fig. 8—representing the top 10 negative performances out of which 4 are European nations.

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Fig. 6 Chi nese consumer ac tivity Jan. Source Eagle Alpha: Chinese transport ministry, STR

Fig. 7 Global stock markets’ performance 2020

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Fig. 8 Top 10 negative performances—global stock market performances in 2020

This indicates that European continent has been hit the hardest in terms of economy. Some sectors have already started to witness impact of this pandemic, as seen in the first quarter of the year the commercial tenants who paid their rent on time in Britain fell from 90 to 60%, with big firms like Burger King admitting they could not make rent on empty restaurants (Capital economics, property week). France reported an economic recession with 6% drop in first quarter (France 24). This is the worst performance in the history of France ever since World War II. In Germany, the economy is expected to shrink by 10% in quarter 2 (RTE).

6.1 Unemployment and Job Insecurity in Europe In Europe’s five largest economies, one in five workers is currently in a special scheme where the state pays their wages. The government has deployed 750 billion Euros to sustain companies and bail them from financial shortcomings or from filing bankruptcy. This shows the magnitude of financial crisis and its impact on employment rates of Europe (Figs. 9 and 10). Many companies had started to response to this crisis namely the Norwegian and Scandinavian airlines have laid off 90% of their employees in an effort to cut down operating cost of the company. According to a report by McKinsey, unemployment is expected to nearly double in upcoming months, with 57 million jobs being at risk as an impact of coronavirus (McKinsey consulting group). Prior to introducing precautionary measures such as national emergency and shutdown toward coronavirus, Eurozone’s unemployment rate was already at 7.3% in February, the lowest since March 2008. The most threatened jobs fall into the sector of customer service and sales, food service and builder occupations. Looking at figures: 1 14.6 million jobs Europe’s

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Fig. 9 Indication of job risk for various economic sectors of Europe

wholesale and retail sector, 8.4 million jobs in accommodation and food service and 1.7 million in arts and entertainment (Moody’s Occupational Employment service). 80% workers struggling and facing job insecurity do not have a university degree, while it can be feared that this may lead to a rise in gap between rich and poor. Rates of unemployment in the EU could hit 7.6% in 2020 and return to precrisis levels in the fourth quarter of 2021, while the worst-case scenario is that unemployment can peak at 11.2% in 2021, with a re-bound to 2019 levels by 2024.

6.2 Role of the Governments and Companies Reducing the number of jobs at risk in otherwise stable, successful industries due to the short-term impacts of the COVID-19 pandemic are critical—both for economic

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Fig. 10 European jobs potentially at risk, by industry sector. Source Labor Cube; US bureau of labor statistics

reasons and because work is vital to life satisfaction. Each job recovered and protected is going to have a positive chain effect—it will help in restoring and retaining productivity and consumption, less dependence on welfare related schemes and good health and mental well-being. The jobs in small business are at the highest risk with lowest rate of recovery; thus, the government should concentrate to reserve a part of its economic stimulus for heavy investing in order to minimize the risk to employment and road for fast recovery and reduced long-term costs to the economy and to the European governments. As a response to the driving factors that will place jobs at risk in the coming months of not being able to return to business quickly as nor mal, due to the nonessential nature of the tasks performed, high physical proximity, and, for example, short-term declines in demand of companies and governments need to take a range of steps to tackle this impact.

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Fig. 11 Consumer spending, % change during lockdown—Denmark and Sweden. Source Anderson et al. (2020)

7 Case study of Sweden and Denmark: A Comparison of Consumer Spending Habit of Sweden (Country with Lenient Home Quarantine Orders) with Denmark (Country that Imposed Strict Lockdown Measures) In Sweden, most people were not restricted by lockdown during the Pandemic; however, Swedish spending patterns over the past few months have mirrored those in neighboring Denmark which has been under strict lockdown. Daily restaurant turnover fell by 70% last month in Sweden as uncertainty over the economy and fear of infection led to fewer swedes ate out (The Economist). While overall Danish spending fell by 29% during lockdown, Swedes cut their spending by almost as much, as we can see in Fig. 11. Thus, this suggests that its people’s own voluntary decisions about how they behave that has larger influence in shaping economies, more than what the government is telling people to do. The lockdown itself is not really influencing behavior that much. However, the true economic impact of imposing lockdown will take time to emerge; like in China, it was after several months’ after the lockdown began to be lifted, when the bankruptcy numbers started to rise.

8 Sectoral Impact See Fig. 12.

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Fig. 12 World stock markets—different sector returns in 2020

8.1 Industrial Sectors Negatively Impacted by the Coronavirus Outbreak After an in-depth analysis of economic impact in China and Europe, it has been observed that both have been facing major downfall in service sector which is also indicated in the graph above. Figure 12 represents the most recent return for the industries that have been hit the hardest due to COVID-19 outbreak. Oil, gas and coal firms have the highest negative returns (on average 50% below start of the year prices); therefore, this is the result of tensions building among oil producing nations prior to the pandemic out-break. Even during the pre-crisis time, there was a cut-throat competition to maintain the lowest oil prices in the market, which had led to supply glut and surplus stockpile of oil inventories. The COVID-19 outbreak led to the decline in demand of oil all across the globe, leading to massive drop in oil prices as low as zero dollars per barrel and even reported negative prices. Thus, this has encouraged oil importing countries like India, Australia to stockpile large volumes of oil available at cheap prices. As anticipated travel and leisure (including restaurants, hotels etc.), aviation, mining, banks and media on an average have fallen by 35%. No sector has been left unharmed by this crisis and collapse in stock prices. Even traditionally stable sectors such as utilities, tobacco and pharmaceuticals are all down by 20%. In response to this Marriott, the world’s largest hotel company has slashed the salaries of their senior executives by 50% and has laid off almost 10,000 workers from their job (Business insider). This is just one case as there are many other companies doing the same. Real estate sector is also likely to suffer for a long time due to COVID-19 outbreak. This was also noticed in China and Europe where sales

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of household property have gone down and people in both China and Europe are struggling to pay rent and some are no more in state to afford such expenses. Along with this the introduction of work-from-home (WFH) culture which is a repercussion of rapid spread of coronavirus, many corporate entities are enjoying and looking at the benefits of this work style and the flexibility it offers. This may lead many companies to go for permanent WFH option and save on their corporate office space expenses. For example, Twitter recently informed its employees of new policy under which it allows them to work from home indefinitely. And many other companies are following these footsteps. All the sporting events have been either canceled or postponed and many people whose jobs are reliant on these events such as event organizers, and many other workers are now jobless. The Olympic Games which is a major event on an international level is now postponed due to COVID-19. These Olympic Games which were supposed to be held in Japan in 2020, will now be hosted in 2021. A prior budget is set for the Olympic Games and tremendous amount of work is put into its preparation. Olympics will now have to increase its budget due to the current delay of the event.

8.2 Industrial Sectors Positively Impacted by the Coronavirus Outbreak 8.2.1

Grocery Delivery Service Companies

They are experiencing a new high in demands this year with worldwide lockdown and fear on catching the virus when many people who were earlier into traditional buying are preferring home delivery. For instance, downloads for Alibaba’s grocery delivery app ‘Fresh Hema’ peaked on February 8, 2020, reaching nearly 100,000 downloads in a single day, compared to an average of approximately 29,000 per day during 2019 (sensor tower). 1. Online Education and Remote learning During this outbreak, almost every educational institution has switched to online classes as a medium to teach and reach out to their students, and not only institutions but also many individuals out of boredom and increase in leisure time have stated to learn something or other through online classes such as health related activities like Yoga or cooking classes. This was also evident when 2 TAL Education’s Zhang Bangxin, saw his wealth increase by $1.7 billion, giving him a current net worth of at least $10 billion (Sensor tower). TAL has partnered with more than 300 public schools across China to stream free classes, and its providing complementary K-12 online tutoring sessions. Thus, this shows that EdTech companies are all set to thrive in this pandemic. 2. Video Calling and Conferencing Applications

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The shutdown of offices and almost all companies doing work from home has led to more downloads and increase in client base of applications such as Microsoft teams, Zoom, Skype. 3. Online Streaming and Gaming Online streaming and gaming platforms are experiencing a huge boom as millions of people are stuck in home due nationwide lockdowns everywhere. A significant increase has been seen in downloads of mobile gaming apps. China recorded 222 million downloads of various games and apps from Apple’s app store since February 2, that was 40 percent more than the average weekly downloads in 2019 (App Annie—app analytics).

9 Conclusion After analyzing the current economic situation of various countries and industrial sectors, it can be concluded that following the China’s economic rebound which is 90% despite it being the second largest economy in the world, other countries are expected to experience a U-shaped economic rebound curve. There has been a huge supply chain disruption all around the globe. As evidence from different markets, the functioning of global supply of 13 chains has been disrupted by the current crisis. And this is generating spillover effects throughout different levels of supplier networks. As per the US Institute for Supply Management, 75% of companies report disruptions in their supply chains and lead times have doubled for several US companies (US institute supply management.) Furthermore, there have been shortages of raw materials and final products. All of this has been severely impacted by the shortage of air and ocean freight options to move products around the globe. Therefore, this will question just-in-time-strategy of companies worldwide, and how now they have to manage to minimize inventories at all cost. It also be concluded that now many companies will start to diversify their supply chains in more than one or two countries with the focus to find supplier near to their home country as a risk minimization strategy. However, this will open doors and more opportunities for countries with cheap labor cost other than China, such as Vietnam and India. The is also compelling governments to be more self-reliant in future which is likely to create more demand of domestic products and more opportunities for domestic manufacturers and suppliers. As observed, the service sector has been hit the hardest, and looking at China, the 10% gap is due to non-recovery of the service sector which shows that it is going to be in losses for a very long time and workers in this sector are not likely to secure their job anytime soon. From the case study of Denmark and Sweden, it could be concluded that lockdown does not have a major influence on people’s spending pattern, which suggests that even after lifting the lockdown, there is expected to be a major dip in ‘fun-spending’ for a long time.

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Further, the big time low in oil and gas prices and negative yield of this sector has encouraged oil importing countries all around the world to stockpile oil in excess which may further delay the adaption electric cars and other electric vehicles in these countries. Governments all around the world are plunging money into the economy and are pushing liquidity more than ever with historically low rates; this is expected to create a vicious circle of debt payment and disrupt the credit growth. There were also actions by central banks across the world. On March 15, the US Federal Reserve lowered its rates to 0–0.25%, as did the Bank of England and other banks. On March 18, the European Central Bank (ECB), which had already had negative rates for many years, increased the amount available for the quantitative easing program. Governments have also been rushing to announce liquidity enhancement programs. But the big question is about who is going to pay this debt and bear the losses. As a consequence of that, a setback in business confidence for investments could be very significant and that will have great effects. Not all countries are going to share losses equally. It can be anticipated that in the best scenario, GDP growth is likely to take a hit, ranging between 3 and 5% depending on the country. In other situations, GDP may fall as much by 10 percent. On an average, each new month of crisis is likely to cost 2–2.5% of global GDP. The cost of economic recession is unequally distributed. We are already aware of the worst affected sectors. Also in accordance with the study and analysis of prior crisis, younger and less educated employees are likely to lose their jobs. This crisis will widen the wealth gap between the rich and poor. The sole way for businesses and economies to survive in this environment will highly depend on their ability to adapt and innovate. No one can precisely estimate the final financial damage from COVID-19. This will depend on the timing and graveness of pandemic in future weeks or months, and countries’ policy responses. Also, hopes of a coronavirus vaccine discovery will be a welcome news. If the ongoing crisis lasts until the end of the summer, the global economy faces the gravest threat seen in the last two centuries.

References Bureau of Labor Statistics (2020) The employment situation—April 2020 David C, Julia K, Sebastian S, Tesfu S (2020) Safeguarding Europe’s livelihoods: mitigating the employment impact of COVID-19. McKinsey & Company, April. https://www.mckiney.com/industries/public-sector/our-insights/safeguarding-eu-ropes-livelihoods-mitigating-theemployment-impact-of-covid- 19 Fernandes N (2020) Economic effects of coronavirus outbreak (COVID-19) on the world economy Nuno Fernandes Full Professor of Finance IESE Business School Spain. SSRN Electron J, 0–29. ISSN 1556-5068

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Jordan K, David R, Phillips T, Pellini A (2021) Education during the Covid-19 crisis: opportunities and constraints of us ing EdTech in low-income countries 21:1–15 Weber T, Hurley J, Ad˘asc˘alit, ei D (n.d.) COVID-19: Implications for employment and working life

Challenges of Adapting to the Fourth Industrial Revolution in Emerging Economies: A Bangladesh CASE Quazi Tafsirul Islam, Faseeha Zabir, Md. Asif Hossain, and Rifat Iqbal

1 Introduction Humanity is at the peak of the fourth industrial revolution, which is also referred to as industry 4.0. It is different from the past industrial revolutions, which were the steam engines, hydro-based electricity generation, the electricity and assembly lines, and the computerization, respectively (Marr 2018). Without exception, each industrial revolution has brought improvements and prosperity along with several challenges to its origin country and the globe; these include not only the high economic growth and increased productivity but also the gap in wealth distribution (Morrar and Arman 2017). The fourth industrial revolution is different because it is fundamentally information technology-driven and has brought changes to the manufacturing systems (Lasi et al. 2014). These innovations in the field of technology have led to changes in organizational structures and have pushed industries to become more serviceoriented. Moreover, there has been a rise in different types of businesses adopting modern manufacturing processes and value-creation networks (Lasi et al. 2014). According to (Morrar and Arman 2017), they argued that the fourth industrial revolution would bring immense opportunities and significant socioeconomic changes via the systems, enabled by the Internet of things (IOT), communicating and cooperating with other systems and human beings in real time. Q. T. Islam (B) · F. Zabir · Md. Asif Hossain · R. Iqbal Department of Management, School of Business and Economics, North South University, Plot, 15, Block B, Kuril—NSU Road, Dhaka 1229, Bangladesh e-mail: [email protected]; [email protected] F. Zabir e-mail: [email protected] Md. Asif Hossain e-mail: [email protected] R. Iqbal e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_2

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There has also been a drastic fall in the dependency ratio in Bangladesh. From 62.4% in 2000, this number dropped to 41.2% in 2018 (Worldbank 2020). Meaning that fewer people are dependent on the working population of the country as there is a strong evidence of an increase in the working population of Bangladesh (Worldbank 2020; Financialexpress 2019). Bangladesh needs to adapt to industry 4.0 not only to accelerate production but also to intensify economic growth (Islam et al. 2018). According to CEBR (2019), it is estimated that Bangladesh’s economy will become the 30th largest economy by the year 2024. With Bangladesh’s economic growth rate at an all-time high and to reach the goals of vision of a digital Bangladesh, now it is a critical time as any to focus on the 4IR for Bangladesh to achieve sustainable growth. This report is prepared based on the responses of 10 interviewees. In order to ensure diversity, four of the respondents were from the SME sector, three were from the RMG sector, and the last three of them were employees working at multinational companies. The paper is structured in sections. Starting with the introduction of the fourth industrial revolution and its importance in the Bangladeshi economy, it goes on to literature review while looking into possible implications and barriers to the fourth industrial revolution in Bangladesh in Sect. 2, then explains the methodology briefly in Sect. 3. In Sect. 4, the discussion covers the essential findings and factors that came up from the extensive analysis of findings. Finally, Sect. 5 draws the concluding remarks and recommendations.

2 Literature Review 2.1 Industrial Revolution 4.0 In the last centuries alone, the world has experienced three distinct and different industrial revolutions, which led the economic and technological changes. The first industrial revolution takes us back to the late eighteenth century, which was vividly related to mechanical production (Frey and Osborne 2013). This industrial revolution was set by the invention of the steam engine (Hussain 2019). A way to mass produce electricity-based products in the nineteenth century was initiated by the second industrial revolution (Frey and Osborne 2013; Hussain 2019). Lastly, the birth of “knowledge economy” through the digital revolution, wave of information, and communication technologies (ICT) brought us to the third industrial revolution in the 1960s (Frey and Osborne 2013; Hussain 2019). In simple terms, it is established that third industrial revolution has helped the economies to take a leap toward automation (Islam et al. 2018). We are now standing on the brink of a new industrial revolution, namely the fourth industrial revolution or the industry 4.0. The idea of the fourth industrial revolution was coined in 2016 by Klaus Schwab, the founder and chairman of the World

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Economic Forum (Schulze 2019). According to Schwab, the fourth industrial revolution is a combination of technologies that are “blurring the lines between the physical, digital, and biological spheres.” Schwab characterized it by some key technologies, which include artificial intelligence (AI), genetics, biotechnology, nanotechnology, 3D printing, and cloud computing (cited in Hirschi 2018). The exceptionality of this particular revolution is that the current technology is concentrating on the replacement of cognitive work and human workers, rather than replacing physical labor and supporting humans in their respective works (Brynjolfsson and McAfee 2014 cited in Hirschi 2018). Some authors termed it as the second IT revolution (Lee et al. 2018). The concept covers a broad array of a shift in the global industrial scenario that includes changes like robotics, big data, cyber-physical systems, cloud manufacturing, Internet of things, Internet of services, and augmented reality (Pereira and Romero 2017). Rainer and Alexander (2014) explains the fourth industrial revolution as an inevitable force in the global domain that will happen, and economies can either adapt or fail to reap the benefits of it.

2.2 Industrial Implications of Industry 4.0 As far as the fourth industrial revolution is concerned, it will be bringing drastic changes for humankind and the world economy. Not only the production and management process will be affected, but it is expected to experience a wave of change felt in the way of life, thinking process, values, and norms (Hussain 2019). Also, the retailers, operation companies, and service providers are not out of the list of the possible impacts due to the innovations of the revolution (Rahman 2019). With the advent of the new industrial revolution, there will be new jobs, and horizons added, medical robotics, simulation engineers, and future forecasters are some among them (Hirschi 2018). Although, the certain benefits exist, there is also the possibility of certain negatives as well. There are possibilities of job disruption due to the fourth industrial revolution, which eventually will be impacting the tax revenues (Prisecaru 2016). This disruption will also have a direct impact on public pension funds and result in lowering the GDP (Prisecaru 2016). As PriceWaterhouseCoopers (PwC) estimated, the job displacement will likely to impact the world economy likely in three different phases (Alam 2019). The first phase, known as algorithm wave, has already started in the developed countries, which is powered by high functioning algorithms and is automating the simple digital tasks; this phase will be affecting mostly the financial, professional, and technical services, information and communication sectors (Alam 2019). By the end of the next decade, the second phase of the growth wave will likely get initiated where the agriculture, service, and repeated tasks in manufacturing will be eaten up by the machines (Alam 2019). Lastly, the third phase of the autonomous wave will get started in 2030 when there will be widespread use of AI and robotics; this is when more than half of the traditional jobs will be in jeopardy (Alam 2019). The revolution is quite challenging for the developed as well as developing nations, but it would be

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easier on the side of the developed nations to cope because of their skilled workforce, technological progress, specialized know-how, training, and experiences. Two significant changes are imminent. First, the political, economic, and social changes will cause an application push and lead to high innovation, shorter development period, customization, flexibility and resource efficiency resulting from decentralization; secondly, the technological pull will result into mechanization, automation, networking of machines, and creation of cyber-physical systems while the focus remains on Sustainability (Lasi et al. 2014). As Pereira and Romero (2017) explains it, the fourth industrial revolution will cause massive changes, especially in the manufacturing sector. Businesses will have to experience these changes in order to take advantage of the new set of opportunities. The authors describe how the paradigm shift will result in the birth of two new production concepts. In small and smart factories, integration, digitization, and the use of smart, flexible tools will produce smart products. Consumers will also face an impact, as they increasingly opt for goods and services, responsible consumerism will increase even more. Another critical factor will be sustainability of operations, which is crucial for industry 4.0 as it can save critical resources like water, gas, electricity by timely cross-utilization (Carvalho et al. 2018). As he Explains, the four major principles of fourth industrial revolution are going to be interoperability of machines, decentralization production and decision making, virtualization, real-time capability to collect, analyze data to make decision, modularity to be more adaptive to changing requirements, and service orientation which refers to the restructuring of how customers experience service.

2.3 Implications of Industry 4.0 in Bangladesh The civil society of Bangladesh has forecasted that the country will be facing challenges in much spectrum. Initially, there will be more challenges and fewer opportunities. First of all, the RMG sector for which Bangladesh is well known in the world economy would be one of the worst sufferers. According to Hussain (2019) and Masud, digitization and rapid automation of work will be having a significant impact on the current and future labor market of the country. As per one data of WEF, about 800 million people around the world might be losing their jobs by the year 2030. While on the other hand, approximately, 5.7 million unskilled Bangladeshi job holders might be losing their jobs both at home and abroad just because of their lack of technological skills. The large portion of unskilled labor will be leading the country toward an increasing unemployment rate and ultimately result in creating adverse consequence on the standard of living (Hussain 2019). In this regard, the policy advisor of the a2i project quoted: Garments will be the worst sufferer of industry 4.0 revolution as there is a possibility that 2.7 million or 6- percent of jobs of being lost. (Rahman 2019)

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As digital and technological transformation and advancements take place, the rising challenge regarding production will be the newly introduced complications in manufacturing systems such as design, processes, operations, and services (Pereira and Romero 2017). The changes will impact nations like Bangladesh the most as we are reliant on our workers who provide cheap labor but not necessarily smart labor; they also lack the resource flexibility. A major driver for the Bangladeshi economy is the income associated with exporting RMG sector and a few other industries that are still in a developing phase. Failure to adapt will have an impact on these industries and also hurt growth in our SME sector. As SMEs in Bangladesh still mostly use first or second industrial revolution innovations, the sustainability of those industries will become a significant challenge (Abdin 2019).

2.4 Barriers of Adapting to the Industry 4.0 As per the content analysis, there are barriers to the adaptation procedure for the fourth industrial revolution. Rahman (2019) gathered data from interviews where he listed a lack of government support, lack of knowledge and awareness, poor infrastructure, and expensive installation of technology as the main barriers to the progress. Similarly, Islam et al. (2018) described many challenges in the context of Bangladesh including poor infrastructure to support a smooth adoption of technology, availability of cheaper labor causing a lack of interest in adoption of more efficient machines, expensive installation of technology, lack of government support to nurture the shift, and overall lack of knowledge about the global alterations taking place among stakeholders. One significant barrier for Bangladesh is the shortage of skilled labor as industry 4.0 will require advanced level human–machine interaction. The new formula combining a mix of technology and innovation combined with people that is unprecedented and unseen globally would cause concern in an emerging economy (Romero et al. 2016). Very few Bangladeshi organizations so far have the awareness and have thus taken the essential steps to make changes to welcome automation and more modern production approaches. The leading export-oriented sector in Bangladesh happens to be RMG and textile, where many organizations reported an increase in the total number of employees in recent years instead of possible automation taking the number down (Bangladesh government, businesses are ‘not worried’ about 4IR 2020). Whereas a study conducted in 2018 by ICT division of Bangladesh indicated that by 2041, there would be a loss of around 2.7 million jobs only the RMG sector of Bangladesh (Reskilling, up-skilling vital to avert 4IR backlash: Experts|daily sun 2020).

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2.5 Significance of Industry 4.0 for Bangladesh The significance of the fourth industrial revolution is immense for Bangladesh as it will be threatening the different aspects of society. Defeminization of the manufacturing workforce is one of the imminent threats to the economy of Bangladesh (Alam 2019). Especially, the female workforce in Bangladesh is more vulnerable in losing their jobs to the gulp of the fourth industrial revolution because of the lack of technological skills. A primary concern for Bangladesh and its economy is going to be the possibility of losing a large amount of foreign revenue or the fall of tax income resulting from not being able to adapt to the fourth industrial revolution successfully. For Bangladesh, the challenge might not be just to produce or produce enough, but it might be a challenge of technological unemployment, where we fail to provide enough jobs. In this era, even skilled workers are becoming obsolete (Peters 2017). As the topic of the fourth industrial revolution itself has not been around for long, and researchers have only started to research said subject in the last few years, it is only logical that there has not been a notable publication in the said arena. An increasing number of publications are being published in the last year alone. Although, researchers like Jones and Pimdee (2017) studied the implication of the fourth industrial revolution in Thailand carefully and came up with possible models that would fit in and transform Thai agriculture, SME, and other service labors to adapt and take benefits of the fourth industrial revolution. It is yet not well studied thoroughly in the con text of emerging economies like Bangladesh.

3 Methodology In order to explore into fourth industrial revolution in Bangladesh and the possible barriers to adapting to the fourth industrial revolution, a comprehensive literature review has been conducted. Sources like Elsevier, Scopus, Emerald Insight, Springer, and JSTOR were studied in an attempt to find out journal articles, conference papers, and other documents. Documents selection was made using a time frame of 2011– 2019. The intention was to establish distinct features of the fourth industrial revolution, its implications, and especially the challenges and barriers in emerging economy perspective from literature. This study is a qualitative one in nature where semi-structured interviews were conducted. Interviews were transcribed before being analyzed to ascertain certain patterns and findings. Researchers were able to approach ten individuals who are academics, industry experts, business owners, and consultants with a minimum of five years of exposure in their given sector. A convenience sampling method was used to approach and schedule an interview with these individuals. These individuals were selected based on their expertise in the given field. Such a method has been approached and utilized in the past in similar research (Islam 2018).

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We interviewed these ten individuals due to time constraints and came up with similar results from all of them. A semi-structured interview process was adopted, as multiple authors interviewed different individuals (Bryman 2016). We analyzed the findings and interview data with a thematic analysis, where we attempted to identify critical factors and categories from their interview and conclude on findings (Ryan and Bernard 2003).

4 Results and Discussion While taking the interview, we observed that not all respondents had the same awareness level about 4IR. Some had existing knowledge and were well aware, while majority of respondents needed a little background of what 4IR is, although their business processes use several components of 4IR such as automation and digitization. We also realized that the use and application of artificial intelligence are almost absent in regular operations of those businesses. From the interview response, it is evident that the practice and preparedness for 4IR is not far-fetched in Bangladesh anymore. We tried to gather perspectives from the practitioners and industry representatives about the challenges and barriers that may interrupt the successful adoption of 4IR. The participant response provided us with insights into the challenges mentioned in Table 1. Almost similar responses were recorded from all the participants that automation can result in an array of possible positive changes. The changes could be ease of business operations aiding better decision making capacities, reduced duplication of error in business processes, creating prospects for emerging and developing countries like Bangladesh. However, some of the respondents expressed concerns about the possibility of the elimination of traditional jobs in the future, which may create high unemployment rate in these economies if due measures are not initiated in due time. Poor infrastructure with inadequate internet, especially in rural areas, was a significant concern for the majority of the respondents. Respondent 1 stated, “The infrastructure in Bangladesh is not ready for 4IR. It happens to be the case that, businesses in Bangladesh are still in the age of 3IR.” Respondent 3 quoted, “We lack knowledge of how to use artificial intelligence or even simple things like 3D printers. In Bangladesh, only very few high tech places have 3D printers, it would be a mere dream for a consumer to own it.” The majority of the respondents claimed that even if companies would go for automation, they faced troubles as their environment was not supportive enough. The majority of the suppliers did not have the technology to complement the automation system. For example, Respondent 1, who works for an investment company, mentioned: “We still face struggles/difficulties in valuing companies for investment as we are using traditional methods to keep track of our financial data.” The respondent further added that this was an issue mostly for the senior/older generation of entrepreneurs. Resistance to change toward the traditional way of business operations is also another leading challenge. One of the respondents has stated, resistance to change

Availability of cheap labor

8/10

Lack of awareness

8/10

Poor infrastructure

10/10

Table 1 Industry 4.0 challenges in Bangladesh

8/10

Resistance to change 10/10

Lack of government support 6/10

Lack of organizational capability

10/10

Lack of readiness of leader-ship

10/10

Lack of skilled workforce

28 Q. T. Islam et al.

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or slower acceptance to adopt technology could be because of the socio-cultural aspect of Bangladesh. All the respondents experienced resistance to change from the management, their workers, and other stakeholders. Respondent 2 informed, “Workers are not ready to learn and adopt new skills to automate tasks,” and Respondent 4 mentioned, “Owners are not ready to invest due to risk-averse attitude, they want to maintain the status quo because they assume that automation might make things complex.” Almost all the respondents raised concerns over the lack of government support. There has been inadequate initiatives from the side of the government despite several promises to ease and accelerate automation. One of the respondents even blames the government bureaucracy for the issue. Respondent 3 stated, “While the support exists, very few areas are aware of it. Government can push more toward technological advancements such as data mining, AI, etc. The government can organize events, workshops as we are still stuck in understanding digital processes.” Each respondent expressed a significant doubt on the availability of skilled labor. Unavailability of skilled labor can create an enormous barrier toward automation. Respondent 4, opined that “We need more and more competent graduates with knowledge of automation and digitization along with certain soft skills, such as leadership skills, problem-solving skills, communication skills, and empathy.” Others agree when they say, “The labors are not ready as they do not have the proper education and awareness to understand the importance of automation.” Although, the lack of skilled labor is a concern raised by majority respondents, the availability of cheap labor is another significant reason why Bangladesh is still slow in adopting automation and digitation. As the respondents state, cheap labor in Bangladesh still accounts for being a great alternative to automating business operations. For instance, respondent 8 expresses, “Cheap labor is the reason why automation process may take more time in Bangladesh.” When it comes to the matter of organizational capabilities to embrace the automation processes, majority respondents have established that the organizations should be more resourceful and need to be aware of the changes and implications of 4IR. Some organizations prefer to invest their limited capital somewhere else than technology as it would yield a quick return. Respondent 10 added, “The business needs to cater to other areas which sometimes makes it hard to invest in automation.” Lack of readiness of leadership is also creating a substantial barrier. The majority of the leaders are not prepared or even technically sound to drive such changes, and as respondent 5 informed, “There are some supervisors despite having adequate skills, create resistance to transfer that knowledge to their subordinates as they have a fear of losing their power and influence.” Among other factors that were assumed, data security threat and high installation cost of technology were discarded as there were not many prominent responses gathered from the respondents. Figure 1 was created based on the respondent’s answers. Figure 1 shows the seven different variables that act as barriers to why Bangladesh is failing to adapt to industrial automation (4th IR). Among the ten respondents, all ten of them agreed that poor infrastructure, lack of organization capacity, lack of readiness of leadership, lack

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Lack of Readiness Poor infrastructure

Lack of Government

Lack of Organizational

Industry Automation

Traditional

Availability of Cheap Labor

Lack of Skilled

Resistance Lack of Aware

Fig. 1 Variables affecting successful industry automation (4th IR)

of government support, and lack of skilled workforce strongly affected Bangladesh’s effort toward automation. Whereas for lack of awareness, availability of cheap labor and resistance of change was agreed to be a barrier by 8 out of 10 respondents. Therefore, it could be said that if these variables could be addressed, the transaction toward automation of industry would be much more swift for Bangladesh.

5 Recommendation and Scope for Future Research There might be numerous drawbacks of fourth IR; however, improvement in technology is inevitable. Therefore, the government should be heavily involved in pushing toward more automation involving 4IR to create more sustainable growth for the economy. They can do this by organizing seminars, workshops, and events through ICT Bangladesh to inform the working population on the anticipated changes in future. The government should invest in institutes offering courses for skill development in the future. They could also organize idea/problem-solving competitions where creative minds can participate in coming up with creative solutions, which will push further innovation. One of the limitations of this research was that due to lack of funding and lack of time, it was not possible to look into different industry sectors. This research would give a more concrete result if this research’s focus can be divided into different industries to understand the effect better. For example, the results of automation in the technology sector would give a different result compared to how it affects the RMG sector. Further, interviewing government officials would give a bit more insight

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into the plans of the government’s role in managing the 4IR in Bangladesh, which would help to understand the direction toward automation for Bangladesh better. If the workforce in Bangladesh is not ready with appropriate skills required for the implementation of 4IR, there will be a massive spike in unemployment in the future. The result of such increased rate of unemployment might direct toward further inequality, and an increase in power distance which is an issue Bangladesh is desperately trying to overcome.

References Abdin M (2019) 4th industrial revolution and reality of industrialisation in Bangladesh. Available at SSRN 3319582 Alam S (2019) Industry and trade under the fourth industrial revolution. The Financial Express. Retrieved from https://thefinancialexpress.com.bd/views/views/industry-and-tradeunder-the-fourth-industrial-revolution-1560783179 Bangladesh government, businesses are ‘not worried’ about 4IR (2020) Retrieved 30 Jan 2020, from https://bdnews24.com/business/2019/03/13/bangladesh-gov-ernment-businesses-are-notworried-about-4ir Bryman A (2016) Social research methods. Oxford University Press Carvalho N, Chaim O, Cazarini E, Gerolamo M (2018) Manufacturing in the fourth industrial revolution: a positive prospect in sustainable manufacturing. Procedia Manuf 21:671–678 CEBR (2019) World economic league table 2020. CBER, London. Retrieved from https://cebr. com/wp-content/up-loads/2019/12/World-Economic-League-Table-Report-2020-Fi-nal.pdf?fbc lid=IwAR25LD3seH6Y3Rwau34kzzPWFrm8Ny JFFEbB7lHera6Oo8P0Odn3vCTR6hk Financialexpress (2019) Working age population rises to 62.7 per cent. Retrieved 25 Jan 2020, from https://thefinancialex-press.com.bd/economy/bangladesh/working-age-population- rises-to-627per-cent-1555498587 Frey CB, Osborne MA (2013) The future of employment: how susceptible are jobs to computerisation? Retrieved from University of Oxford, Oxford Martin School web-site: https://www.oxf ordmartin.ox.ac.uk Hirschi A (2018) The fourth industrial revolution: Issues and implications for career research and practice. Career Dev Q 66(3):192–204 Hussain A (2019) Fourth industrial revolution and Bangladesh. daily sun. Retrieved from https:// www.daily-sun.com/post/420255/Fourth-Industrial-Revolution-and-Bangladesh Islam A, Jantan A, Hashim H, Chong C, Abdullah M, Rahman A, Hamid A (2018) Fourth industrial revolution in developing countries: a case on Bangladesh. J Manag Inf Decis Sci 21(1) Jones C, Pimdee P (2017) Innovative ideas: Thailand 4.0 and the fourth industrial revolution. Asian Int J Soc Sci 17(1):4–35 Lasi H, Fettke P, Kemper H-G, Feld T, Hoffmann M (2014) Industry 4.0. Bus Inf Syst Eng 6(4):239– 242. https://doi.org/10.1007/s12599-014-0334-4 Lee M, Yun J, Pyka A, Won D, Kodama F, Schiuma G, Park H, Jeon J, Park K, Jung K, Yan MR (2018) How to respond to the fourth industrial revolution, or the second information technology revolution? Dynamic new combinations between technology, market, and society through open innovation. J Open Innov Technol Market Complex 4:3–21 Marr B (2018) The 4th industrial revolution is here—are you ready? (2018). Retrieved 1 Feb 2020, from https://www.forbes.com/sites/bernardmarr/2018/08/13/the-4th-in-dustrial-revolu tion-is-here-are-you-ready/#1bc41b72628b Morrar R, Arman H (2017) The fourth industrial revolution (industry 4.0): a social innovation perspective. Technol Innov Manag Rev 7(11):12–20. https://doi.org/10.22215/timreview/1117

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Pereira AC, Romero F (2017) A review of the meanings and the implications of the industry 4.0 concept. Procedia Manuf 13:1206–1214 Peters MA (2017) Technological unemployment: educating for the fourth industrial revolution. J Self-Gov Manag Econ 5(1):25–33 Prisecaru P (2016) Challenges of the fourth industrial revolution. Knowl Horiz Econ 8(1):57–62 Rahman A (2019) Introducing ‘Industry 4.0’ to Bangladesh. Textile Today. Retrieved from https:// www.textileto-day.com.bd/introducing-industry-4-0-bangladesh/ Rainer D, Alexander H (2014) Industrie 4.0: hit or hype? Ind Electron Mag 8(2):56–58 Reskilling, up-skilling vital to avert 4IR backlash: experts | daily sun (2020) Retrieved 30 Jan 2020, from https://www.daily-sun.com/post/439939/Reskilling-upskilling-vital-to-avert- 4IRbacklash:-Experts Romero D, Stahre J, Wuest T, Noran O, Bernus P, Fast-Ber- glund Å, Gorecky D (2016) Towards an operator 4.0 typology: a human-centric perspective on the fourth industrial revolution technologies. In: International conference on computers and industrial engineering (CIE46) proceedings Ryan GW, Bernard HR (2003) Techniques to identify themes. Field Methods 15(1):85–109 Schulze E (2019) Everything you need to know about the fourth industrial revolution. CNBC. Retrieved from https://www.cnbc.com/2019/01/16/fourth-industrial-revolu-tion-explai ned-davos-2019.html Worldbank (2020) Population growth (annual %)—Bangladesh | Data. Retrieved 23 Jan 2020, from https://data.worldbank.org/indica-tor/SP.POP.GROW?locations=BD

“Entrepreneurship in the Digital Era. A Systematic Literature Review” Michela Floris and Angela Dettori

1 Introduction Digitalisation is one of the most relevant trends producing revolutionary changes in society and business (Parviainen et al. 2017; Stolterman and Fors 2004). Scholars sustain that digitalisation has significantly impacted human social areas than the Industrial Revolution (Degryse 2016). Its pervasive effects as a widespread social phenomenon (Stolterman and Fors 2004) affecting culture and human behaviours (Isensee et al. 2020; Karpova and Proskurina 2021), education (Bejinaru 2019), communication (Gray and Rumpe 2015), and business model evolution (Bouwman et al. 2018; Rachinger et al. 2019) underline that the current era can be rightly called the digital era (Eshet 2012). Adopting technological devices or means is not sufficient, while new and most articulated technical, sociological and cognitive skills to perform successfully in the digital environment are required (Eshet 2004; Palan and Schober, 2021; Zillien and Hargittai 2009). In such a scenario, firms have to enhance their ability and propensity to benefits from digitalisation opportunities (Floris and Dettori 2020; Hervé et al. 2020), intending with digitalisation “the use of digital technologies to innovate a business model and provide new revenue streams and value-producing opportunities” (Parida et al. 2019, p. 6). Under this perspective, digitalisation becomes a strategic imperative for businesses since they operate and evolve in an environment radically changed by the digital and extraordinarily challenging (Matt et al. 2015). Social networks, big data, and digital technologies in a broad sense influence firms in all industries in terms of organisational structures, products, production, market shares, selling strategies, and as a result, firms have to establish management tools M. Floris (B) · A. Dettori University of Cagliari, Cagliari, Italy e-mail: [email protected] A. Dettori e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_3

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and practices to face these challenges (Matt et al. 2015). Contemporarily, digitalisation increases pressure competition globally (Westerman et al. 2011), sometimes compromising large firms’ leadership positions (Sebastian et al. 2017), probably due to the difficulties met by many firms in moving to digital (Hess et al. 2016; Sklyar et al. 2019). In sum, digitalisation impacts entrepreneurship in several ways and to obtain benefits and catch opportunities for its powerful effects, firms, both large and small, have to increase their attention, moving towards thinking digital (Bharadwaj et al. 2013). Since digitalisation, although pervasive, is a relatively young phenomenon, the literature on the subject appears to be significantly fragmented and, above all, based on theories and theoretical approaches “borrowed” from other lines of research and disciplines. Especially regarding the relationship between digitalisation and entrepreneurship, many scholars have tried to extend the theoretical framework used in the entrepreneurship field of research to analyse the phenomenon of digitalisation. Exemplifying, the well-known phenomenon of the entrepreneurial ecosystem has been extended in the digital environment and called “digital entrepreneurial ecosystem” (Elia et al. 2020; Song 2019; Ughetto et al. 2019), demonstrating the role that digital is exercising throughout firms’ reality. Similar claims can be made regarding institutions and policymakers’ role in promoting an entrepreneurial mindset to create opportunities for firms. In the current digital era, policymakers have to conceive policies to sustain the enhancement of a digital entrepreneurial mindset, by promoting digitalisation as a key to help local development, also for disadvantaged areas (Dong 2019; Fernandes et al. 2019; Geissinger et al. 2019). Participating in the fervid debate around digitalisation phenomenon and effects on entrepreneurship and intrapreneurship, this study intends to answer the following research questions: a. What are the main opportunities that digitalisation offers to entrepreneurship? b. How does the digital revolution influence entrepreneurship phenomenon? c. Why does digitalisation represent a new avenue for overall development? To answer the mentioned research questions, this study adopts a Systematic Literature Review method to analyse the fragmented and unpuzzled academic literature from 1990 to 2020, to understand whether a new field of research is boring, frame state of the art, and propose a research agenda for further studies. The dataset comprises 141 articles published in leading journals that deepen the analysis on digitalisation and entrepreneurship or intrapreneurship. Findings show interesting insights, highlighting an increasing amount of scholarly contributions in the last years due to the galloping development that digital is having in social and entrepreneurship contexts. This interest of scholars and practitioners appears to suggest that a new research field is emerging. Literature review results and the research agenda are presented in the next sections. Specifically, this chapter is organised into three main sections. The first part exposes in details the method adopted, by underlying step-by-step the procedure followed. The second section presents the findings, through descriptive statistic tools, to understand the trend of

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publications in terms of years, institutions engaged, countries, authors, and journals, and through the analysis of the content. The third part, which concludes the chapter, presents the research agenda, suggesting new research questions to further studies.

2 Methods This chapter follows a Systematic Literature Review (SLR) method. SLR is a scientific method oriented to reduce systematic bias, by identifying, analysing, and synthesising all relevant studies in a defined research field (Petticrew and Roberts 2008). SLR is not new in the management and entrepreneurship fields (Campopiano et al. 2017; Di Vaio et al. 2021; Floris et al. 2019; Liñán and Fayolle 2015; Pittaway and Cope 2007; Schmitz et al. 2017), and, unlike from other literature reviews, employs a transparent and replicable process (Tranfield et al. 2002, 2003). Close adhering to SLR guidelines, our review covers the last 30 years of scholarly contributions on the topic and consists of three steps: data collection, data refinement, and data analysis for clustering scholarly contributions and suggesting a research agenda. The review began with consulting Clarivate Analytics’ Web of Science database, one of the world’s premier scientific search, discovery, and analytical information platforms, used by scholars for large-scale data-intensive studies across many academic fields, because of the large number of bibliographic records (Li et al. 2018). Following Busenitz et al. (2003)’s guidelines, we restricted our search to articles published in scholarly journals (excluding book chapters, proceedings, and unpublished works), to ensure publications quality due to the clear and transparent peer-review process obtained. Additionally, we selected only articles in the English language. Our data collection started using the following search string: (“Entrepreneur* OR “Intrapreneur*), present in the title, abstract and/or keywords of the article. We inserted the asterisks to include many terms with different suffixes. This search gave back 45,538 articles. Then, we proceeded with the following search string: (“digital era” OR “digital*), and we found 340,030 articles. We combined the search strings, obtaining 975 articles. We then included only the WoS categories “Business”, “Management”, and “Economics”, and we found 230 articles. Finally, we included only papers published in journals listed in the ABS List 2019, and the selected articles became 141. Finally, two independent readers read titles, abstracts, and keywords to carried out a blind systematic pre-analysis and, after comparing their results, they agreed that all identified articles deserved to be included in the dataset. Then, 141 articles were considered relevant for the search criteria, as listed in Table 1.

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Table 1 List of selected articles #

Year

Authors

Title

1

2020

Chen, L; Wang, MM; Cui, L; Li, SL

Experience base, Strategic Management strategy-by-doing and new Journal product performance

Journal

2

2020

Koo, WW; Eesley, CE

Platform governance and the rural-urban divide: sellers’ responses to design change

Strategic Management Journal

3

2020

Gfrerer, A; Hutter, K; Fuller, J; Strohle, T

Ready or not: managers’ and employees’ different perceptions of digital readiness

California Management Review

4

2020

Torres, P; Augusto, M

Digitalisation, social entrepreneurship and national well-being

Technological Forecasting and Social Change

5

2020

Ghezzi, A

How entrepreneurs make Technological Forecasting sense of lean startup and Social Change approaches: business models as cognitive lenses to generate fast and frugal heuristics

6

2020

Li, K; Kim, DJ; Lang, KR; Kauffman, RJ; Naldi, M

How should we understand Electronic Commerce the digital economy in Research and Applications Asia? Critical assessment and research agenda

7

2020

Flowers, S; Meyer, M

How can entrepreneurs benefit from user knowledge to create innovation in the digital services sector?

8

2020

Prufer, J; Prufer, P

Data science for Small Business Economics entrepreneurship research: studying demand dynamics for entrepreneurial skills in the Netherlands

9

2020

Ceipek, R; Hautz, J; De Digital transformation Massis, A; Matzler, K; through exploratory and Ardito, L exploitative internet of things innovations: the impact of family management and technological diversification*

Journal of Business Research

Journal of Product Innovation Management

(continued)

“Entrepreneurship in the Digital Era. A Systematic Literature Review”

37

Table 1 (continued) #

Year

Authors

Title

Journal

10

2020

Lanamaki, A; Vayrynen, K; Laari-Salmela, S; Kinnula, M

Examining relational digital transformation through the unfolding of local practices of the Finnish taxi industry

Journal of Strategic Information Systems

11

2020

Vassilakopoulou, P; Grisot, M

Effectual tactics in digital Journal of Strategic intrapreneurship: a process Information Systems model

12

2020

Fink, L; Shao, JH; Lichtenstein, Y; Haefliger, S

The ownership of digital infrastructure: exploring the deployment of software libraries in a digital innovation cluster

Journal of Information Technology

13

2020

Rossi, M; Festa, G; Devalle, A; Mueller, J

When corporations get disruptive, the disruptive get corporate: Financing disruptive technologies through corporate venture capital

Journal of Business Research

14

2020

Allard, G; Williams, C

National-level innovation in Africa

Research Policy

15

2020

Jain, S

Fumbling to the future? Socio-technical regime change in the recorded music industry

Technological Forecasting and Social Change

16

2020

Sansone, G; Andreotti, P; Colombelli, A; Landoni, P

Are social incubators Technological Forecasting different from other and Social Change incubators? Evidence from Italy

17

2020

Nzembayie, KF; Buckley, AP

Entrepreneurial process European Management studies using insider action Review research: opportunities & challenges for entrepreneurship scholarship

18

2020

Cennamo, C; Dagnino, GB; Di Minin, A; Lanzolla, G

Managing digital California Management transformation: scope of Review transformation and modalities of value co-generation and delivery

19

2020

Ughetto, E; Rossi, M; Audretsch, D; Lehmann, EE

Female entrepreneurship in the digital era

Small Business Economics

(continued)

38

M. Floris and A. Dettori

Table 1 (continued) #

Year

Authors

Title

Journal

20

2020

Oggero, N; Rossi, MC; Ughetto, E

Entrepreneurial spirits in women and men. The role of financial literacy and digital skills

Small Business Economics

21

2020

Lusoli, A; Turner, F

It’s an ongoing bromance: counterculture and cyberculture in silicon valley-an interview with Fred Turner

Journal of Management Inquiry

22

2020

Antonopoulou, K; Begkos, C

Strategising for digital innovations: value propositions for transcending market boundaries

Technological Forecasting and Social Change

23

2020

Vicente-Saez, R; Gustafsson, R; Van den Brande, L

The dawn of an open exploration era: emergent principles and practices of open science and innovation of university research teams in a digital world

Technological Forecasting and Social Change

24

2020

Shi, XH; Li, F; Chumnumpan, P

Platform development: emerging insights from a nascent industry

Journal of Management

25

2020

Huang, W; Meoli, M; Vismara, S

The geography of initial coin offerings

Small Business Economics

26

2020

Eesley, C; Wu, L

For start-ups, adaptability Mis Quarterly and mentor network diversity can be pivotal: evidence from a randomised experiment on a mooc platform

27

2020

Bouncken, R; Ratzmann, M; Barwinski, R; Kraus, S

Co-working spaces: Empowerment for entrepreneurship and innovation in the digital and sharing economy

Journal of Business Research

28

2020

Zuzul, T; Tripsas, M

Start-up inertia versus flexibility: the role of founder identity in a nascent industry

Administrative Science Quarterly

29

2020

Wang, F

Digital marketing capabilities in international firms: a relational perspective

International Marketing Review

(continued)

“Entrepreneurship in the Digital Era. A Systematic Literature Review”

39

Table 1 (continued) #

Year

Authors

Title

Journal

30

2020

Hornuf, L; Klus, MF; Lohwasser, TS; Schwienbacher, A

How do banks interact with fintech start-ups?

Small Business Economics

31

2020

Guo, H; Wang, C; Su, ZF; Wang, DH

Technology push or market pull? Strategic orientation in business model design and digital start-up performance*

Journal of Product Innovation Management

32

2020

Katsikeas, C; Leonidou, Revisiting international L; Zeriti, A marketing strategy in a digital era opportunities, challenges, and research directions

International Marketing Review

33

2020

Aridi, A; Hayter, CS; Radosevic, S

Windows of opportunities for catching up: an analysis of ICT sector development in Ukraine

Journal of Technology Transfer

34

2020

Prugl, R; Spitzley, DI

Responding to digital Journal of Management transformation by external Studies corporate venturing: an enterprising family identity and communication patterns perspective

35

2020

Schuckes, M; Gutmann, Why do start-ups pursue T initial coin offerings (ICOs)? The role of economic drivers and social identity on funding choice

36

2020

Garud, R; Kumaraswamy, A; Roberts, A; Xu, L

Liminal movement by Strategic Management digital platform-based Journal sharing economy ventures: the case of uber technologies

37

2020

Wenzel, M; Kramer, H; Koch, J; Reckwitz, A

Future and organization Organisation Studies studies: on the rediscovery of a problematic temporal category in organisations

38

2020

Mero, J; Tarkiainen, A; Tobon, J

Effectual and causal reasoning in the adoption of marketing automation

39

2020

Drummond, C; Digital engagement O’Toole, T; McGrath, H strategies and tactics in social media marketing

Small Business Economics

Industrial Marketing Management European Journal of Marketing (continued)

40

M. Floris and A. Dettori

Table 1 (continued) #

Year

Authors

40

2020

Saiedi, E; Brostrom, A; Global drivers of Ruiz, F cryptocurrency infrastructure adoption

Title

Journal Small Business Economics

41

2020

Ghezzi, A; Cavallo, A

Agile business model innovation in digital entrepreneurship: lean start-up approaches

Journal of Business Research

42

2020

Butler, JS; Garg, R; Stephens, B

Social networks, funding, Information Systems and regional advantages in Research technology entrepreneurship: an empirical analysis

43

2020

Cahen, F; Borini, FM

International digital competence

Journal of International Management

44

2020

Denicolai, S; Previtali, P

Precision medicine: implications for value chains and business models in life sciences

Technological Forecasting and Social Change

45

2020

Palmie, M; Wincent, J; Parida, V; Caglar, U

The evolution of the Technological Forecasting financial technology and Social Change ecosystem: an introduction and agenda for future research on disruptive innovations in ecosystems

46

2020

McAdam, M; Crowley, C; Harrison, RT

Digital girl: Small Business Economics cyberfeminism and the emancipatory potential of digital entrepreneurship in emerging economies

47

2020

Yeh, CH; Wang, YS; Hsu, JW; Lin, SJ

Predicting individuals’ digital autopreneurship: does educational intervention matter?

48

2020

Elia, G; Margherita, A; Passiante, G

Digital entrepreneurship Technological Forecasting ecosystem: how digital and Social Change technologies and collective intelligence are reshaping the entrepreneurial process

49

2020

Shaheer, NA; Li, SL

The CAGE around Journal of Business cyberspace? How digital Venturing innovations internationalise in a virtual world

Journal of Business Research

(continued)

“Entrepreneurship in the Digital Era. A Systematic Literature Review”

41

Table 1 (continued) #

Year

Authors

Title

50

2020

Jean, RJ; Kim, D; Cavusgil, E

Antecedents and outcomes Journal of World Business of digital platform risk for international new ventures’ internationalisation

Journal

51

2020

Vadana, II; Torkkeli, L; Kuivalainen, O; Saarenketo, S

Digitalisation of International Marketing companies in international Review entrepreneurship and marketing

52

2020

Orser, B; Coleman, S; Li, YH

Progress or pinkwashing: who benefits from digital women-focused capital funds?

Small Business Economics

53

2019

Bouncken, RB; Kraus, S; Roig-Tierno, N

Knowledge- and innovation-based business models for future growth: digitalised business models and portfolio considerations

Review of Managerial Science

54

2019

Logue, D; Grimes, M

Platforms for the people: enabling civic crowdfunding through the cultivation of institutional infrastructure

Strategic Management Journal

55

2019

Ben Arfi, W; Hikkerova, L

Corporate Small Business Economics entrepreneurship, product innovation, and knowledge conversion: the role of digital platforms

56

2019

Song, AK

The digital entrepreneurial Small Business Economics ecosystem-a critique and reconfiguration

57

2019

Cumming, D; Meoli, M; Vismara, S

Investors’ choices between Research Policy cash and voting rights: evidence from dual-class equity crowdfunding

58

2019

Eiteneyer, N; Bendig, D; Brettel, M

Social capital and the digital crowd: involving backers to promote new product innovativeness

59

2019

Miric, M; Boudreau, KJ; Jeppesen, LB

Protecting their digital Research Policy assets: the use of formal & informal appropriability strategies by App developers

Research Policy

(continued)

42

M. Floris and A. Dettori

Table 1 (continued) #

Year

Authors

Title

Journal

60

2019

Nambisan, S; Wright, M; Feldman, M

The digital transformation of innovation and entrepreneurship: progress, challenges and key themes

Research Policy

61

2019

Wang, WX; Mahmood, The evolution of equity A; Sismeiro, C; Vulkan, crowdfunding: insights N from co-investments of angels and the crowd

Research Policy

62

2019

Konig, M; Ungerer, C; Baltes, G; Terzidis, O

Different patterns in the evolution of digital and non-digital ventures’ business models

Technological Forecasting and Social Change

63

2019

Van Le, H; Suh, MH

Changing trends in internet start-up value propositions, from the perspective of the customer

Technological Forecasting and Social Change

64

2019

Gupta, G; Bose, I

Strategic learning for Technological Forecasting digital market pioneering: and Social Change examining the transformation of Wishberry’s crowdfunding model

65

2019

Geissinger, A; Laurell, Digital entrepreneurship C; Sandstrom, C; and field conditions for Eriksson, K; Nykvist, R institutional change-investigating the enabling role of cities

66

2019

Delacroix, E; Parguel, B; Benoit-Moreau, F

Digital subsistance Technological Forecasting entrepreneurs on Facebook and Social Change

67

2019

Rippa, P; Secundo, G

Digital academic entrepreneurship: the potential of digital technologies on academic entrepreneurship

68

2019

McAdam, M; Crowley, C; Harrison, RT

To boldly go where no Technological Forecasting [man] has gone and Social Change before—institutional voids and the development of women’s digital entrepreneurship

Technological Forecasting and Social Change

Technological Forecasting and Social Change

(continued)

“Entrepreneurship in the Digital Era. A Systematic Literature Review”

43

Table 1 (continued) #

Year

Authors

Title

69

2019

Dong, JQ

Moving a mountain with a Technological Forecasting teaspoon: toward a theory and Social Change of digital entrepreneurship in the regulatory environment

Journal

70

2019

Ghezzi, A

Digital start-ups and the Technological Forecasting adoption and and Social Change implementation of lean start-up approaches: effectuation, bricolage and opportunity creation in practice

71

2019

Vega, A; Chiasson, M

A comprehensive framework to research digital innovation: the joint use of the systems of innovation and critical realism

Journal of Strategic Information Systems

72

2019

Cavallo, A; Ghezzi, A; Dell’Era, C; Pellizzoni, E

Fostering digital entrepreneurship from start-up to scale-up: the role of venture capital funds and angel groups

Technological Forecasting and Social Change

73

2019

Del Giudice, M; Scuotto, V; Garcia-Perez, A; Petruzzelli, AM

Shifting wealth II in Chinese economy. The effect of the horizontal technology spillover for SMEs for international growth

Technological Forecasting and Social Change

74

2019

Galindo-Martin, MA; Castano-Martinez, MS; Mendez-Picazo, MT

Digital transformation, digital dividends and entrepreneurship: a quantitative analysis

Journal of Business Research

75

2019

Ferreira, JJM; To be or not to be digital, Fernandes, CI; Ferreira, that is the question: firm FAF innovation and performance

76

2019

Cenamor, J; Parida, V; Wincent, J

Journal of Business Research

How entrepreneurial Journal of Business SMEs compete through Research digital platforms: the roles of digital platform capability, network capability and ambidexterity (continued)

44

M. Floris and A. Dettori

Table 1 (continued) #

Year

Authors

77

2019

Warner, KSR; Wager, M Building dynamic capabilities for digital transformation: an ongoing process of strategic renewal

Title

Journal Long Range Planning

78

2019

Bellesia, F; Mattarelli, E; Bertolotti, F; Sobrero, M

Platforms as entrepreneurial incubators? How online labor markets shape work identity

Journal of Managerial Psychology

79

2019

Browder, RE; Aldrich, HE; Bradley, SW

The emergence of the maker movement: Implications for entrepreneurship research

Journal of Business Venturing

80

2019

Symon, G; Whiting, R

The sociomaterial Journal of Management negotiation of social Studies entrepreneurs’ meaningful work

81

2019

Kim, K; Hann, IH

Crowdfunding and the democratization of access to capital-an illusion? Evidence from housing prices

82

2019

Fernandes, J; Mason, K; Chakrabarti, R

Managing to make market Journal of Business agencements: the Research temporally bound elements of stigma in favelas

83

2019

Pergelova, A; Manolova, T; Simeonova-Ganeva, R; Yordanova, D

Democratising entrepreneurship? Digital technologies and the internationalisation of female-Led SMEs

84

2019

Sousa, MJ; Carmo, M; Goncalves, AC; Cruz, R; Martins, JM

Creating knowledge and Journal of Business entrepreneurial capacity Research for HE students with digital education methodologies: differences in the perceptions of students and entrepreneurs

85

2019

Fisch, C

Initial coin offerings (ICOs) to finance new ventures

Information Systems Research

Journal of Small Business Management

Journal of Business Venturing (continued)

“Entrepreneurship in the Digital Era. A Systematic Literature Review”

45

Table 1 (continued) #

Year

Authors

Title

Journal

86

2018

von Briel, F; Recker, J; Davidsson, P

Not all digital venture ideas are created equal: implications for venture creation processes

Journal of Strategic Information Systems

87

2018

Du, WY; Mao, JY

Developing and maintaining clients’ trust through institutional mechanisms in online service markets for digital entrepreneurs: a process model

Journal of Strategic Information Systems

88

2018

Liu, JY; Nandhakumar, J; Zachariadis, M

When guanxi meets structural holes: exploring the guanxi networks of Chinese entrepreneurs on digital platforms

Journal of Strategic Information Systems

89

2018

Ryu, S; Kim, YG

Money is not everything: a Journal of Strategic typology of crowdfunding Information Systems project creators

90

2018

Arvidsson, V; Monsted, Generating innovation T potential: how digital entrepreneurs conceal, sequence, anchor, and propagate new technology

Journal of Strategic Information Systems

91

2018

Burtch, G; Carnahan, S; Can you gig it? An Greenwood, BN empirical examination of the gig economy and entrepreneurial activity

Management Science

92

2018

Kammerlander, N; Konig, A; Richards, M

Why do incumbents respond heterogeneously to disruptive innovations? The interplay of domain identity and role identity

Journal of Management Studies

93

2018

Ojala, A; Evers, N; Rialp, A

Extending the international new venture phenomenon to digital platform providers: a longitudinal case study

Journal of World Business

94

2018

Ashman, R; Patterson, A; Brown, S

‘Don’t forget to like, share Journal of Business and subscribe’: digital Research autopreneurs in a neoliberal world (continued)

46

M. Floris and A. Dettori

Table 1 (continued) #

Year

Authors

Title

Journal

95

2018

Li, L

China’s manufacturing locus in 2025: with a comparison of Made-in-China 2025 and Industry 4.0

Technological Forecasting and Social Change

96

2018

Tumbas, S; Berente, N; vom Brocke, J

Digital innovation and institutional entrepreneurship: chief digital officer perspectives of their emerging role

Journal of Information Technology

97

2018

Nambisan, S; Siegel, D; On open innovation, Kenney, M platforms, and entrepreneurship

Strategic Entrepreneurship Journal

98

2018

Eckhardt, JT; Ciuchta, MP; Carpenter, M

Open innovation, information, and entrepreneurship within platform ecosystems

Strategic Entrepreneurship Journal

99

2018

Cano-Kollmann, M; Hannigan, TJ; Mudambi, R

Global innovation networks—organisations and people

Journal of International Management

100

2018

Ratzinger, D; Amess, K; Greenman, A; Mosey, S

The impact of digital start-up founders’ higher education on reaching equity investment milestones

Journal of Technology Transfer

101

2018

Zeng, J; Glaister, KW

Value creation from big data: looking inside the black box

Strategic Organization

102

2018

Srinivasan, A; Venkatraman, N

Entrepreneurship in digital Strategic Entrepreneurship platforms: a Journal network-centric view

103

2018

Autio, E; Nambisan, S; Digital affordances, spatial Strategic Entrepreneurship Thomas, LDW; Wright, affordances, and the Journal M genesis of entrepreneurial ecosystems

104

2018

Kuester, S; Konya-Baumbach, E; Schuhmacher, MC

Get the show on the road: Journal of Business go-to-market strategies for Research e-innovations of start-ups

105

2018

Thompson, N

Hey DJ, don’t stop the music: institutional work and record pooling practices in the United States’ music industry

Business History

(continued)

“Entrepreneurship in the Digital Era. A Systematic Literature Review”

47

Table 1 (continued) #

Year

Authors

106

2018

Holland, CP; A taxonomy of SME Gutierrez-Leefmans, M E-commerce platforms derived from a market-level analysis

Title

Journal International Journal of Electronic Commerce

107

2018

von Briel, F; Digital technologies as Davidsson, P; Recker, J external enablers of new venture creation in the IT hardware sector

Entrepreneurship Theory and Practice

108

2017

Towse, R

Economics of music publishing: copyright and the market

Journal of Cultural Economics

109

2017

Nambisan, S

Digital entrepreneurship: toward a digital technology perspective of entrepreneurship

Entrepreneurship Theory and Practice

110

2017

Venkatesh, V; Shaw, Networks, technology, and Academy of Management JD; Sykes, TA; Wamba, entrepreneurship: a field Journal SF; Macharia, M quasi-experiment among women in rural india

111

2017

Autio, E

Strategic entrepreneurial internationalization: a normative framework

Strategic Entrepreneurship Journal

112

2017

Amit, R; Han, X

Value creation through novel resource configurations in a digitally enabled world

Strategic Entrepreneurship Journal

113

2017

Benner, MJ; Ranganathan, R

Measuring up? Persistence Organisation Science and change in analysts’ evaluative schemas following technological change

114

2017

Sussan, F; Acs, ZJ

The digital entrepreneurial Small Business Economics ecosystem

115

2017

Scuotto, V; Del Giudice, M; Carayannis, EG

The effect of social networking sites and absorptive capacity on SMES’ innovation performance

116

2017

Spiekermann, S; Korunovska, J

Towards a value theory for Journal of Information personal data Technology

117

2017

Nambisan, S; Lyytinen, Digital innovation K; Majchrzak, A; Song, management: reinventing M innovation management research in a digital world

Journal of Technology Transfer

Mis Quarterly

(continued)

48

M. Floris and A. Dettori

Table 1 (continued) #

Year

Authors

118

2017

Wallin, AJ; Fuglsang, L Service innovations breaking institutionalised rules of health care

Title

Journal Journal of Service Management

119

2017

Smith, C; Smith, JB; Shaw, E

Embracing digital networks: entrepreneurs’ social capital online

Journal of Business Venturing

120

2016

Ansari, S; Garud, R; Kumaraswamy, A

The disruptor’s dilemma: Strategic Management TiVo and the US television Journal ecosystem

121

2016

Day, GS; Schoemaker, PJH

Adapting to fast-changing markets and technologies

122

2016

Nelson, AJ

How to share a really good Organisation Science secret: managing sharing/secrecy tensions around scientific knowledge disclosure

123

2015

Sandeep, MS; Ravishankar, MN

Social innovations in outsourcing: an empirical investigation of impact sourcing companies in India

Journal of Strategic Information Systems

124

2015

Feldman, M; Lowe, N

Triangulating regional economies: realising the promise of digital data

Research Policy

125

2015

Ernkvist, M

The double knot of Technological Forecasting technology and and Social Change business-model innovation in the era of ferment of digital exchanges: the case of OM, a pioneer in electronic options exchanges

126

2015

Alford, P; Page, SJ

Marketing technology for Service Industries Journal adoption by small business

127

2015

Ho, JC; Lee, CS

A typology of technological change: technological paradigm theory with validation and generalisation from case studies

128

2015

Parvinen, P; Oinas-Kukkonen, H; Kaptein, M

E-selling: a new avenue of Electronic Commerce research for service design Research and Applications and online engagement

California Management Review

Technological Forecasting and Social Change

(continued)

“Entrepreneurship in the Digital Era. A Systematic Literature Review”

49

Table 1 (continued) #

Year

Authors

Title

129

2015

Srivastava, SC; Shainesh, G

Bridging the service divide Mis Quarterly through digitally enabled service innovations: evidence from indian healthcare service providers

Journal

130

2014

Potstada, M; Zybura, J

The role of context in science fiction prototyping: the digital industrial revolution

131

2014

Henfridsson, O; Yoo, YJ

The liminality of trajectory Organisation Science shifts in institutional entrepreneurship

132

2014

Hadida, AL; Paris, T

Managerial cognition and the value chain in the digital music industry

Technological Forecasting and Social Change

133

2013

Burtch, G; Ghose, A; Wattal, S

An empirical examination of the antecedents and consequences of contribution patterns in crowd-funded markets

Information Systems Research

Technological Forecasting and Social Change

134

2013

McGrath, RG

Transient advantage

Harvard Business Review

135

2012

Gino, F; Staats, BR

The microwork solution

Harvard Business Review

136

2010

Tsatsou, P; Elaluf-Calderwood, S; Liebenau, J

Towards a taxonomy for Journal of Information regulatory issues in a Technology digital business ecosystem in the EU

137

2009

Davis, CH; Creutzberg, T; Arthurs, D

Applying an innovation cluster framework to a creative industry: the case of screen-based media in Ontario

Innovation-Management Policy & Practice

138

2007

Howe, N; Strauss, W

The next 20 years: how customer and workforce attitudes will evolve

Harvard Business Review

139

2007

Zucker, LG; Darby, Minerva unbound: MR; Furner, J; Liu, RC; knowledge stocks, Ma, HY knowledge flows and new knowledge production

140

2005

Christensen, JF; Olesen, MH; Kjaer, JS

Research Policy

The industrial dynamics of Research Policy open innovation—evidence from the transformation of consumer electronics (continued)

50

M. Floris and A. Dettori

Table 1 (continued) #

Year

Authors

Title

141

2001

Hargadon, AB; Douglas, Y

When innovations meet Administrative Science institutions: Edison and the Quarterly design of the electric light

Journal

3 Findings 3.1 Descriptive Statistics Before analysing the articles’ contents, we conducted a descriptive analysis of the final dataset, with the intent of observing the time trend of publications (Table 2), the leading journals (Table 3), the most prolific authors (Table 4), as well as countries/regions (Table 5) and, finally, the most productive universities and/or centres of research (Table 6). Table 2 illustrates the increasing attention that scholars are paying to the study of entrepreneurship/intrapreneurship in the digital era, especially in 2020 (publications are more than doubled in less than two years and increased 50-fold in the last ten years). This result highlights the topic’s relevance and underlines the rapid change that entrepreneurship has, due to digitalisation. Thus, deepening the analysis about it is a consequent need to uncover and suggest how obtaining benefits of this refreshing change of development, production, and communication paradigms. Table 2 Time trend of publications Date of publication

No. of articles

%

2020

50

35.46

2019

35

24.82

2018

22

15.60

2017

12

8.51

2016

3

2.13

2015

7

4.96

2014

3

2.13

2013

2

1.42

2012

1

0.71

2010

1

0.71

2009

1

0.71

2007

2

1.42

2005

1

0.71

2001

1

0.71

“Entrepreneurship in the Digital Era. A Systematic Literature Review”

51

Table 3 List of journals Journals

No. of articles

%

Technological Forecasting and Social Change

25

17.73

Journal of Business Research

12

8.51

Small Business Economics

12

8.51

9

6.38

Journal of Strategic Information Systems Research Policy

9

6.38

Strategic Entrepreneurship Journal

6

4.25

Strategic Management Journal

5

3.55

Journal of Business Venturing

4

2.84

Journal of Information Technology

4

2.84

California Management Review

3

2.13

Harvard Business Review

3

2.13

Information Systems Research

3

2.13

International Marketing Review

3

2.13

Journal of Management Studies

3

2.13

Journal of Technology Transfer

3

2.13

Mis Quarterly

3

2.13

Organisation Science

3

2.13

Administrative Science Quarterly

2

1.41

Electronic commerce research and Applications

2

1.41

Entrepreneurship Theory and Practice

2

1.41

Journal of International Management

2

1.41

Journal of Product Innovation Management

2

1.41

Journal of World Business

2

1.41

Academy of Management Journal

1

0.71

Business History

1

0.71

European Journal of Marketing

1

0.71

European Management Review

1

0.71

Industrial Marketing Management

1

0.71

Innovation Management Policy Practice

1

0.71

International Journal of Electronic Commerce

1

0.71

Journal of Cultural Economics

1

0.71

Journal of Management

1

0.71

Journal of Management Inquiry

1

0.71

Journal of Managerial Psychology

1

0.71

Journal of Service Management

1

0.71

Journal of Small Business Management

1

0.71 (continued)

52

M. Floris and A. Dettori

Table 3 (continued) No. of articles

Journals

%

1

Long Range Planning

0.71

Management Science

1

0.71

Organization Studies

1

0.71

Review of Managerial Science

1

0.71

Service Industries Journal

1

0.71

Strategic Organization

1

0.71

Table 4 Most prolific authors Authors

No. of articles

%

Nambisan S

5

3.55

Ghezzi A

4

2.84

Autio E

2

1.42

Burtch G

2

1.42

Cavallo A

2

1.42

Crowley C

2

1.42

Davidsson P

2

1.42

Del Giudice M

2

1.42

Feldman M

2

1.42

Garud R

2

1.42

Harrison Rt

2

1.42

Kraus S

2

1.42

Kumaraswamy A

2

1.42

Li Sl

2

1.42

Mcadam M

2

1.42

Meoli M

2

1.42

Parida V

2

1.42

Recker J

2

1.42

Rossi M

2

1.42

Scuotto V

2

1.42

Ughetto E

2

1.42

Vismara S

2

1.42

Von Briel F

2

1.42

Wincent J

2

1.42

Wright M

2

1.42

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Table 5 Countries/regions Countries/regions

No. of articles

%

Countries/regions

No. of articles

%

USA

53

37.59

South Korea

3

2.13

England

37

26.24

Switzerland

3

2.13

Italy

19

13.48

Taiwan

3

2.13

Germany

17

12.06

India

2

1.42

China

12

8.51

Singapore

2

1.42

Finland

9

6.38

Brazil

1

0.71

France

9

6.38

Bulgaria

1

0.71

Netherlands

9

6.38

Cyprus

1

0.71

Canada

8

5.67

Estonia

1

0.71

Scotland

8

5.67

Iceland

1

0.71

Spain

7

4.96

Israel

1

0.71

Sweden

7

4.96

Liechtenstein

1

0.71

Australia

6

4.25

Mexico

1

0.71

Denmark

5

3.55

New Zealand

1

0.71

Ireland

5

3.55

North Ireland

1

0.71

Austria

3

2.13

Poland

1

0.71

Belgium

3

2.13

Thailand

1

0.71

Norway

3

2.13

Wales

1

0.71

Portugal

3

2.13

Table 3 delineates the leading journals that appear to be particularly interested in published studies on this research field. What is particularly curious from this descriptive analysis is that over 50% of all articles selected are published in the first six journals of the list, that is Technological Forecasting and Social Change, Journal of Business Research, Small Business Economics, Journal of Strategic Information Systems, Research Policy, and Strategic Entrepreneurship Journal. This is very useful for scholars who find themselves having to choose the outlet for their research, to focus their attention on those that, more than others, show an apparent sensitivity towards the topic. Table 4 reports the authors who have published at least two articles among those in the dataset. The scholar Nambisan emerges among all and is the author or coauthor of five articles out of the 141 selected. The amount of Nambisan’s articles is not surprising because deepening the scholar’s scientific production through Google Scholar, the researcher’s commitment to the subject is immediately evident (13,469 citations and H-index of 37). Moreover, Nambisan comes from the Case Western Reserve University that, as underlined by Table 6, is listed as the second among the most prolific organisations on the topic. Following Nambisan, the Italian scholar Ghezzi, coming from the Polytechnic University of Milan (this University is second with a tie with several other organisations), has an H-index of 25, demonstrating

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Table 6 Most productive organisations Organisations enhanced

No. of articles

%

Pennsylvania Commonwealth System of Higher Education

5

3.55

University of London

5

3.55

Case Western Reserve University

4

2.84

Copenhagen Business School

4

2.84

Imperial College London

4

2.84

Polytechnic University of Milan

4

2.84

State University System of Florida

4

2.84

University of California System

4

2.84

University of North Carolina

4

2.84

University of North Carolina Chapel Hill

4

2.84

City University London

3

2.13

Jonkoping University

3

2.13

Polytechnic University Of Turin

3

2.13

Stanford University

3

2.13

Temple University

3

2.13

Tilburg University

3

2.13

University of Cambridge

3

2.13

University of Mannheim

3

2.13

University of Minnesota System

3

2.13

University of Minnesota Twin Cities

3

2.13

University of Pennsylvania

3

2.13

University of Turin

3

2.13

University of Vaasa

3

2.13

University of Warwick

3

2.13

University of Wisconsin System

3

2.13

his high productivity, and experience in the subject. The other listed authors have published at least two articles among those selected, while scholars that do not appear in Table 4 result authors of one article among selected. Table 5 shows the academic prolificacy on the topic paying particular attention to the country and/or region. The USA’s prevalence is immediately evident compared to other areas of the world, but this is not surprising in light of many well-known scholars and universities known worldwide. However, it is fascinating that the first four countries on the list (USA, England, Germany, and Italy) generate about 90% of the entire dataset. This data also highlights the results of public policies aimed at promoting digitalisation and entrepreneurial development through development paths more in line with current needs.

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Finally, Table 6 summarises the universities and/or research centres most committed to studying digital and the consequent opportunities in terms of entrepreneurial development and the acquisition of competitive advantages. The Pennsylvania Commonwealth System of Higher Education and the University of London, with five published articles, occupy the first place. Simultaneously, the Case Western Reserve University (from which the most prolific author comes) and the Polytechnic University of Milan (from which the second most prolific author comes) are in the second position with other influential organisations.

3.2 The Analysis of the Contents of the Article After these descriptive analytics of our dataset, we read each article carefully to understand the theoretical approaches and methods. In a second step, we grouped the articles on the basis of common emergent themes. Finally, we identified a research agenda with several research questions to address further studies.

3.3 Theoretical Approaches Concerning theoretical approaches, the selected articles applied a wide range of theories and literature background. For instance, several articles ground their studies on the dynamic capabilities approach (Day and Schoemaker 2016; Shi et al. 2020; Warner and Wäger 2019). Others adopted the institutional perspective (Geissinger et al. 2019; Logue and Grimes 2019; Torres and Augusto 2020). Business model literature has been adopted in several dataset articles (Ghezzi 2020; Ghezzi and Cavallo 2020; Gupta and Bose 2019). Not surprisingly, social media and e-commerce literature have been used in several articles (Drummond et al. 2020; Holland and GutiérrezLeefmans 2018). Generally, articles have proposed their theoretical or empirical analysis relying on digital entrepreneurship literature, digital entrepreneurial ecosystem, digital technologies, digital marketing capabilities, platform design. As clearly appears, the lack of a defined theoretical framework to deepen the analysis on digital induces scholars to capture the essence of theories used in the entrepreneurship field and to adopt these in studies on digital. In our SLR, there were interesting articles of a theoretical nature oriented to the conception of a useful theoretical framework to be adopted in the research line of entrepreneurship and digital autopreneurship (Flowers and Meyer 2020; Kim and Cavusgil 2020; Nambisan 2017; Song 2019; Sussan and Acs 2017; Vega and Chiasson 2019).

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3.4 Methods The selected articles have adopted several methodological approaches. The most adopted methods used was qualitative, with a specific reference to single or multiple case studies, inductive approaches, naturalistic inquiries, historical approaches, etc., to discover new insights about the phenomenon of entrepreneurship in the digital era, and conceive framework based on a set of propositions. On the opposite side, quantitative analysis adopted many statistical and inferential tools to test hypotheses, analyse linear regressions, generalise results, or evaluate frameworks’ effectiveness. Other studies adopted mixed methods by collecting data from both in-depth interviews with knowledgeable agents, other secondary data sources, and questionnaires submitted to several respondents to analyse recurring statistical tools. Several articles adopted a theoretical approach to order the fragmented theoretical framework that characterises this specific and nascent research field. These articles’ main contributions were interpretive frameworks that intersect many impulses from other fields and disciplines to delineate changes, dynamics, digital entrepreneurship trends, and digital in entrepreneurship development. Finally, a few papers proposed a literature review. Among this, Rippa and Secundo (2019) proposed a novel contribution regarding the emerging concept of Digital Academic Entrepreneurship; Vadana et al. (2020) focused on the literature in international marketing and international entrepreneurship to explore the types of digitalised companies, how measuring the what extent of digitalisation and the degree of internationalisation.

3.5 Thematic Analysis The selected papers underlined the pervasive role and disruptive effects of the digital phenomenon in the whole of the social life and, thus, in entrepreneurship too, in terms of market opportunities, customer relationship management, innovation, internationalisation, new venture creation, product development, human resource management, disadvantages areas development, the inclusion of weak categories of people (e.g. female), and social entrepreneurship. However, to delineate state of the art and a research agenda of this field, we grouped the articles for common themes, representing different research streams. Since numerous articles contain different facets of the phenomenon of digitisation, the placement of an article in a cluster rather than another was not simple. Still, it has derived from the prevalence of one theme rather than another. We found eight main streams of research, as follows: a. Institutional, context, social, and gender perspectives b. Finance and financing opportunities

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Table 7 Thematic groups Groups

Articles #

Institutional, context, entrepreneurial ecosystem, social and gender perspectives

2; 4; 6; 10; 14; 16; 19; 20; 21; 33; 36; 38; 46; 52; 54; 65; 68: 69; 71; 73; 80; 82; 83; 96; 101; 103; 105; 110; 114; 120; 123; 1; 129; 130; 136; 137; 139; 141

Finance and financing opportunities

13; 25; 30; 35; 40; 45; 57; 58; 61; 81; 85; 91; 133

Opportunities for and effects on innovation, 1; 3; 7; 9; 11; 12; 15; 18; 22; 24; 26; 27; 37; 38; corporate strategy, corporate entrepreneurship, 44; 55; 56; 59; 60; 66; 74; 75; 76; 78; 79; 90; and organisation 92; 96; 97; 98; 106; 108; 109; 1; 113; 115; 116; 117; 119; 121; 126; 127; 1; 132; 134; 135; 138; 140 Consumer-oriented perspective

39; 63; 87; 104; 128

Business models changes and evolution

5; 41; 53; 62; 64; 125

Education role

8; 17; 23; 47; 67; 84; 100; 122

Internationalisation opportunities

29; 32; 43; 49; 50; 51; 93; 99; 111

New venture creation, intrapreneurship, autopreneurship, and digital start-ups

28; 31; 70; 72; 86; 94; 102; 107; 118

c. Opportunities for and effects on innovation, corporate strategy, corporate entrepreneurship, and organisation d. Consumer-oriented perspective e. Business models changes and evolution f. Education role g. Internationalisation opportunities h. New venture creation, intrapreneurship, autopreneurship, and digital start-ups Table 7 defines the different groups and relative articles.

3.5.1

Institutional, Context, Entrepreneurial Ecosystem, Social and Gender Perspectives

The 40 articles in this thematic group have analysed the opportunities digitalisation presents for disadvantaged areas’ entrepreneurial and social development, rural areas, and developing ones (Del Giudice et al. 2019; Li 2018; Liu et al. 2018; McAdam et al. 2020). Furthermore, again in this group, several articles highlighted the benefits that women can obtain from digital, in terms of entrepreneurship, intrapreneurship, and autopreneurship (McAdam et al. 2019, 2020; Oggero et al. 2019; Orser et al. 2020; Pergelova et al. 2019; Ughetto et al. 2019). More in detail, authors generally sustain that digitalisation can stimulate women entrepreneurship to emancipate themselves, especially in emerging and rural economies (McAdam et al. 2020; Venkatesh et al. 2017), and help them in capital access (Orser et al. 2020), and the international

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expansion (Pergelova et al. 2019), even if sometimes the male counterparts continue to gain most opportunities (Oggero et al. 2019). In addition, particular attention was given to the deepening of the transition from an entrepreneurial ecosystem to the entrepreneurial digital ecosystem, under the growing use of digital platforms that present undisputed development opportunities (Autio et al. 2018; Song 2019; Sussan and Acs 2017; Tsatsou et al. 2010). For this reason, the role of institutions has been recalled several times, in various articles, as an engine for the diffusion of digital architectures and, consequently, as a drive to create business development based on digital (Geissinger et al. 2019). In line with this, Torres and Augusto (2020), intending to determine the combination of institutional conditions that can affect national well-being, focused on the importance of digitalisation and social entrepreneurship. The authors found that digitalisation represents a fundamental part of the solution to achieving high levels of national well-being. Synthesising articles’ contents, this group reveals a scenario in which digitalisation fulfil a decisive role to stimulate local entrepreneurial development by spreading a digital entrepreneurial system, to enhance the development of emerging, rural and disadvantaged economies, to spread positive effects on social entrepreneurship, to call into action institutions and policymakers, to promote women entrepreneurship.

3.5.2

Finance and Financing Opportunities

This thematic group (14 articles) deepens the digitalisation analysis in entrepreneurship, focusing on the opportunities for finance and financing dynamics. Specifically, the articles in this cluster have analysed the Initial Coin Offering (ICO) (Schückes and Gutmann 2020), shedding light on why ICOs are more pervasive in some countries rather than in others (Huang et al. 2020); cryptocurrency (Saiedi et al. 2020) crowdfunding platforms (Eiteneyer et al. 2019; Kim and Hann 2019), highlighting that differences in firms’ ownership (family vs. non-family) can affect the success of the offering (Cumming et al. 2019). Crowdfunding is also considered a digital platform for market-oriented innovation and product development, enlarging social capital and relationships with customers (Cumming et al. 2019). Wang et al. (2019), focusing on equity crowdfunding platforms as keys to the digital transformation of early-stage venture funding, found evidence of information flows in crowdfunding platforms between angels and angels to the crowd. In detail, while angels play a relevant role in the funding of large ventures, the crowd plays a crucial role in the funding of small ones. Moreover, Ryu and Kim (2018), addressing their study on how crowdfunding projects characteristics differ from the creator type and which characteristics are critical for enhancing project performance, suggest platform operators attracting and promoting different types of project creators to gain high benefits from the crowd. The articles in this group have underlined the potential digitalisation in finance and financing opportunities, especially for small firms that generally have difficulties accessing the credit market.

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Opportunities for and Effects on Innovation, Corporate Strategy, Corporate Entrepreneurship, and Organisation

Digitalisation, jointed with other phenomena, contributes to rediscovery the future and changing organisation and strategic studies (Wenzel et al. 2020). For this assumption, this thematic group is the most numerous and contains a miscellaneous of topics (50 articles). The articles within this cluster have focused on digitalisation opportunities for and effects on entrepreneurship in innovation proclivity and strategic and organisational perspectives. These articles have analysed in depth what, how, and why digitalisation and digital platforms affect the entire firms’ lifecycle, practising revolutionary changes in the workplace (Bellesia et al. 2019), in innovation proclivity (Arfi and Hikkerova 2019), and in acquiring new competitive advantages (Ferreira et al. 2019), especially for small- and medium-sized firms (Cenamor et al. 2019). Several articles have also focused on opportunities in co-working space, as a redesign of organisations and workspace, to empower entrepreneurship and innovation in the digital and sharing economy (Bouncken et al. 2020). Antonoupoulou and Begkos (2020), exploring what and how digital entrepreneurs design and rethink value propositions to gain opportunities for transcending market boundaries, have identified that the constant enactment of four specific strategies— excogitating functionality, self-reverberating benefits, designating interdependencies, and conforming intentionalities—acts as a driver to redesign the value proposition in overside markets. Focusing on the mobile computing industry, Chen et al. (2020) have found that frequent iterations of product design over the product’s lifecycle produce new product success and induce a continuous search of product portfolio diversity. In this sense, digital pulls a constant enhancement of new products. Fascinating is the article of Flowers and Meyer (2020). The authors argued that entrepreneurship’s notion needs to be developed to consider the disruptive impact that the Internet produces on access to user knowledge. Their qualitative paper has proposed a theoretical contributions reappraisal the notion of spillovers, user knowledge, and firm boundaries in the digital services industry. Galindo et al. (2019), deepening the effects of digital transformation on entrepreneurial activity, found that entrepreneurial innovations and digital transformations generate higher value creation and digital dividends, that, in turn, stimulate entrepreneurial activities, motivating entrepreneurs to continue innovating and generating more digital transformation. In sum, the articles in this group have focused on the opportunities and the pervasive effects that digitalisation and digital platforms generate on entrepreneurial orientation and innovation in workplaces, underlining that tiny and medium firms can obtain particular benefits from digital.

3.5.4

Consumer-Oriented Perspective

Assuming that almost all of the 141 articles analysed highlighted the benefits that digitisation offers to improve and intensify relationships with customers, also to

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create and co-creating value deriving from the dense network of relationships that can develop thanks to technologies and digital platforms, the five articles present in this cluster have adopted a different perspective of analysis, mainly oriented towards the customer. Drummond et al. (2020), intending identifying digital engagement strategies and tactics in developing social media marketing capability, have found many strategies and tactics for defining layers of social media marketing capability, named, connect, engage, co-ordinate, and collaborate. Val Le and Suh (2019) have observed and compared Internet start-ups’ value propositions from the customer’s perspective. They found that trends of value proposition changed during three decades. From this point, they have predicted the development of value proposition trends for the future, as a reference for future start-ups, supporting them in a value proposition more effective to meet customer expectation. Also Kuester et al. (2018), focusing on the adoption of e-innovation, have proposed interesting suggestions for start-ups in designing go-to-market strategies, highlighting the fundamental role of trustworthiness and usability. Focusing on e-selling as the computer–human dialogue consisting of the digital locus, the online persuasion, and the value perception, in which consumers are central, Parvinen et al. (2015) have conceived a theoretical and conceptual model, to open new research streams oriented to online service design and user engagement.

3.5.5

Business Models Changes and Evolution

The six articles in this group have claimed that digitalisation has produced changes in business models, necessary to adapt firms strategies and behaviour to the revolution of the digital era, shifting from non-digital to digital business models (König et al. 2019). Specifically, the articles have deepened Lean Start-up Approaches (Ghezzi 2020), as agile business models innovation (Ghezzi and Cavallo 2020); knowledge and innovation-based business models, as digitalised business models (Bouncken et al. 2019); strategic learning as a core driver for business model transformation (Gupta and Bose 2019); and techno-social transformative process as new business models in finance to overcome prohibitive regulatory barriers for new entrants in defined markets (Ernkvist 2015).

3.5.6

Education Role

The eight articles in this group have debated the role of education and teachability of digital and entrepreneurial skills, founding interesting and sometimes controversy results. Specifically, the articles focused on scientific knowledge, digital skills, capabilities, and entrepreneurial skills (Nelson 2016; Prüfer and Prüfer 2020); entrepreneurial studies (Futonge et al. 2020); open science and innovation developed by research teams at University (Vicente-Saez et al. 2020); comparison among

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the effects of personal extrinsic and intrinsic motivations, and educational interventions on autopreneurial intention (Yeh et al. 2020); the emergent concept of Digital Academy Entrepreneurship (Rippa and Secundo 2019); digital educational methodologies to improve entrepreneurial skills (Sousa et al. 2019); founder’s higher education and effect on finance (Ratzinger et al. 2018). Prüfer and Prüfer’s findings (2020) were fascinating. Based on a dataset of 95% of all job vacancies in the Netherlands over a 6-year period with 7.7 million data points, the authors showed that demand for entrepreneurial and digital skills has increased for apical positions. The firsts were more demanded that the second ones, despite the impact of datafication on the labour market. In sum, the articles in this cluster have generally supported the relevance of increasing digital and entrepreneurial competencies and skills through higher education, despite Yeh et al. (2020), in their survey involving 304 respondents, have found that educational interventions fail to augment the relationships between the two types of motivation and autopreneurial intention.

3.5.7

Internationalisation Opportunities

Despite digitalisation as an opportunity to conceive internationalisation strategies was a theme treated in several articles, the nine articles inserted in this group have deepened the topic more straightforwardly. Cahen and Borini (2020) have evaluated firms’ capabilities for internationalising digital products. They have developed the concept of “international digital competence”, consisting of four critical capabilities: cross-cultural programming skills, global virtual networks, cross-border digital monetising adaptability, and international business model reconfiguration. Possessing and developing international digital competences enables digital firms to expand abroad with an online presence. Kim and Cavusgil (2020) have developed and tested a theoretical model to underline drivers and digital platform risk outcomes for international new ventures. Katsikea et al. (2019) have provided a complete reconfiguration of international marketing strategies in the current digital era, analysing the necessary organisational resources and capabilities. The other articles have focused on international expansion through digital platforms (Ojala et al. 2018); digital marketing capabilities in international firms (Wang 2020); and the what extent digitalisation influences the degree of internationalisation (Vadana et al. 2020). Synthesising, the articles in this group have agreed on the role digitalisation plays in supporting firms to internationalise their offer.

3.5.8

New Ventures, Intrapreneurship, Autopreneurship, and Digital Start-Ups

The nine articles inserted in this group have mainly focused on digital opportunities to create new ventures, improve existing business activities, and propose digital

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start-ups. The authors have deepened the strategic view of digital start-ups (Guo et al. 2020); the role of founders in impressing flexibility or inertia to their start-ups (Zuzul and Tripsas 2020); how angel group and venture capital funds impact on the digital new ventures growth both in start-up and in scale-up steps (Cavallo et al. 2019); digital start-ups and lean start-ups approaches (Ghezzi and Cavallo 2020); how and when digital technologies stimulate new venture creation processes (von Briel Davidsson et al. 2018a); how digital artefacts composition affects venture creation processes (von Briel Recker et al. 2018b); how new ventures break institutional barriers to introduce digitally enables service innovation (Wallin and Fuglsang 2017); how digital technologies affect heroic entrepreneurs (Ashman et al. 2018). Detailing some articles, Guo et al. (2020) have proposed a strategic orientation view to investigate the impact of strategic orientation in business model design on digital start-ups’ performance. They found that technology and consumer orientations benefit start-ups’ performance, even if seeking an equilibrium between strategic orientation in business model design could be damaging. Zuzul and Tripsas (2020) have found that start-ups, generally considered innovative and flexible, can exhibit inertial behaviour due to the founder’s self-view. Specifically, whether founders consider themselves as “revolutionaries”, novel ventures were created to drive radical change; while founders saw themselves as “discoverers”, they create successful businesses. Acting in a manner consistent with their self-views, revolutionary founders committed to and actively reinvested in radical venture concepts, rejecting adaptive changes that they felt compromised novelty. In contrast, discoverer founders prioritised experimentation and change in reaction to shifting conditions. Srinivasan and Venkatraman (2018) have introduced a network-centric view to understanding how third-party developers entrepreneurs support digital platforms. They have developed a set of propositions concerning a dynamic perspective of the main steps of competition in digital platforms, initial launch, and scale-up.

4 Conclusion and Research Agenda Aimed to answer to the following research questions What are the main opportunities that digitalisation offers to entrepreneurship? (RQ1), How does the digital revolution influence entrepreneurship phenomenon? (RQ2), and Why does digitalisation represent a new avenue for overall development? (RQ3), this study has adopted a Systematic Literature Review of 141 articles published in leading journals. Recently, the number of articles around the themes of digitalisation and entrepreneurship or intrapreneurship has notably increased, underlining that scholars are paying particular attention to the topic because of its extraordinary impact on each aspect of social life and entrepreneurship particular. Findings allow us to find suitable answers to our research questions. Concerning the RQ1, we found that digitalisation offers several possibilities to entrepreneurship

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development, in terms of strategic orientation, overcoming market barriers, flexibility, ability in developing relationships, creation of novel workspace and workplace architectures, foundations of new ventures or innovating old ones, accessibility on financing and new ways to obtain financial capitals, and enrichingentrepreneurship educational programmes. The thematic analysis has underlined how digitalisation affects entrepreneurship (RQ2). The found eight main research streams— Institutional, context, social and gender perspectives; Finance and financing opportunities; Opportunities for and effects on innovation, corporate strategy, corporate entrepreneurship, and organisation; Consumer-oriented perspective; Business models changes and evolution; Education role; Internationalisation opportunities; New venture creation, intrapreneurship, autopreneurship and digital start-ups. These themes have evidenced the multiplicity of ways digitalisation has changed and is changing entrepreneurship’s physiognomy by introducing new paths and promoting new tools for firms, especially for small- and medium-sized firms. Finally, digitalisation can represent a new avenue for promoting rural and disadvantaged areas’ development and allowing women and other weak people to emancipation (RQ3). Despite many studies on the topic, several aspects still need to be analysed on which future studies could focus. First, it would be interesting to investigate whether and how digitalisation could represent a useful tool to support businesses, especially tiny ones, during and after the COVID-19 pandemic. Therefore, an interesting research question could be: How digital platforms and digitisation can support firms in crises such as the current one, characterised by lockdown and forced closures of several entrepreneurial activities? Another aspect that has not emerged from the analysis of the articles is the role that digitalisation has towards the recreationalcultural sector such as, for example, museums or historical monuments which, in the current historical time are significantly penalised. How could digitalisation allow for more excellent usability of the cultural experience? What could digital strategies implement and develop the cultural sector? Many articles have explored the role of digitalisation in developing disadvantaged areas and offering opportunities for people with difficulties. However, further studies are necessary to create a digital entrepreneurial mindset that can support the design of digital-based integrated development models. How can digitisation allow local development of developing countries? What tools can be used? How and through what strategies is it possible to promote disadvantaged individuals’ inclusiveness in the digital world? How is it possible to guarantee their job placement? Finally, carrying out new studies related to digital entrepreneurship education is urgent, to ensure new digital entrepreneurs acquire the potential to come from digital and prepared them to use the various digital platforms. Therefore, Is it possible that entrepreneurship education is moving towards digital entrepreneurship education? What are the training and educational paths and practices most suited to developing a digital entrepreneurial mentality? At what age could digital entrepreneurship skills begin to spread? This study has many limitations. First, the examined literature is not exhaustive because we used only the WoS database and focused exclusively on articles. Future research can consult other databases and combine them to obtain a more inclusive

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dataset, additionally considering books, proceedings, and other documents that can improve the analysis.

References Antonopoulou K, Begkos C (2020) Strategizing for digital innovations: value propositions for transcending market boundaries. Technol Forec Soc Chang 156:120042 Arfi WB, Hikkerova L (2019) Corporate entrepreneurship, product innovation, and knowledge conversion: the role of digital platforms. Small Bus Econ, 1–14 Ashman R, Patterson A, Brown S (2018) ‘Don’t forget to like, share and subscribe’: digital autopreneurs in a neoliberal world. J Bus Res 92:474–483 Autio E, Nambisan S, Thomas LD, Wright M (2018) Digital affordances, spatial affordances, and the genesis of entrepreneurial ecosystems. Strateg Entrep J 12(1):72–95 Bejinaru R (2019) Impact of digitalization on education in the knowledge economy. Manag Dyn Knowl Econ 7(3):367–380 Bellesia F, Mattarelli E, Bertolotti F, Sobrero M (2019) Platforms as entrepreneurial incubators? How online labor markets shape work identity. J Manag Psychol Bharadwaj A, El Sawy OA, Pavlou PA, Venkatraman NV (2013) Digital business strategy: toward a next generation of insights Bouncken R, Ratzmann M, Barwinski R, Kraus S (2020) Co- working spaces: empowerment for entrepreneurship and innovation in the digital and sharing economy. J Bus Res 114:102–110 Bouncken RB, Kraus S, Roig-Tierno N (2019) Knowledge- and innovation-based business models for future growth: digitalized business models and portfolio considerations. Rev Manag Sci, 1–14 Bouwman H, Nikou S, Molina-Castillo FJ, de Reuver M (2018) The impact of digitalization on business models. Digit Policy Regul Gov 20(2):105–124 Busenitz LW, West III GP, Shepherd D, Nelson T, Chandler GN, Zacharakis A (2003) Entrepreneurship research in emergence: past trends and future directions. J Manag 29(3):285–308 Cahen F, Borini FM (2020) International digital competence. J Int Manag 26(1):100691 Campopiano G, De Massis A, Rinaldi FR, Sciascia S (2017) Women’s involvement in family firms: progress and challenges for future research. J Fam Bus Strat 8(4):200–212 Cavallo A, Ghezzi A, Dell’Era C, Pellizzoni E (2019) Fostering digital entrepreneurship from startup to scale-up: the role of venture capital funds and angel groups. Technol Forecast Soc Chang 145:24–35 Cenamor J, Parida V, Wincent J (2019) How entrepreneurial SMEs compete through digital platforms: the roles of digital platform capability, network capability and ambidexterity. J Bus Res 100:196–206 Chen L, Wang M, Cui L, Li S (2020) Experience base, strategy-by-doing and new product performance. Strateg Manag J Cumming D, Meoli M, Vismara S (2019) Investors’ choices between cash and voting rights: evidence from dual-class equity crowdfunding. Res Policy 48(8):103740 Day GS, Schoemaker PJ (2016) Adapting to fast-changing markets and technologies. Calif Manage Rev 58(4):59–77 Degryse C (2016) Digitalisation of the economy and its impact on labour markets. ETUI research paper-working paper Del Giudice M, Scuotto V, Garcia-Perez A, Petruzzelli AM (2019) Shifting wealth II in Chinese economy. The effect of the horizontal technology spillover for SMEs for international growth. Technol Forecast Soc Chang 145:307–316 Di Vaio A, Palladino R, Pezzi A, Kalisz DE (2021) The role of digital innovation in knowledge management systems: a systematic literature review. J Bus Res 123:220–231

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Dong JQ (2019) Moving a mountain with a teaspoon: toward a theory of digital entrepreneurship in the regulatory environment. Technol Forecast Soc Chang 146:923–930 Drummond C, O’Toole T, McGrath H (2020) Digital engagement strategies and tactics in social media marketing. Eur J Market Eiteneyer N, Bendig D, Brettel M (2019) Social capital and the digital crowd: involving backers to promote new product innovativeness. Res Policy 48(8):103744 Elia G, Margherita A, Passiante G (2020) Digital entrepreneurship ecosystem: how digital technologies and collective intelligence are reshaping the entrepreneurial process. Technol Forecast Soc Chang 150:119791 Ernkvist M (2015) The double knot of technology and business- model innovation in the era of ferment of digital exchanges: the case of OM, a pioneer in electronic options exchanges. Technol Forecast Soc Chang 99:285–299 Eshet Y (2004) Digital literacy: a conceptual framework for survival skills in the digital era. J Educ Multimedia Hypermedia 13(1):93–106 Eshet Y (2012) Thinking in the digital era: a revised model for digital literacy. Issues Informing Sci Inf Technol 9(2):267–276 Fernandes J, Mason K, Chakrabarti R (2019) Managing to make market agencements: the temporally bound elements of stigma in favelas. J Bus Res 95:128–142 Ferreira JJ, Fernandes CI, Ferreira FA (2019) To be or not to be digital, that is the question: firm innovation and performance. J Bus Res 101:583–590 Floris M, Dessì C, Dettori A (2019) Women’s roles in family businesses: specifics, contradictions, and reflections. In. IGI global Floris M, Dettori A (2020) Is social media adoption a powerful means to reach high performance in small-and medium- sized firms? An empirical investigation. Int J Market Stud 12(2):50–61 Flowers S, Meyer M (2020) How can entrepreneurs benefit from user knowledge to create innovation in the digital services sector? J Bus Res 119:122–130 Futonge Nzembayie K, Buckley AP (2020) Entrepreneurial process studies using insider action research: opportunities & challenges for entrepreneurship scholarship. Eur Manag Rev 17(3):803– 815 Galindo-Martín M-Á, Castaño-Martínez M-S, Méndez-Picazo M-T (2019) Digital transformation, digital dividends and entrepreneurship: a quantitative analysis. J Bus Res 101:522–527 Geissinger A, Laurell C, Sandström C, Eriksson, K, Nykvist R (2019) Digital entrepreneurship and field conditions for institutional change–investigating the enabling role of cities. Technol Forecast Soc Change 146:877–886 Ghezzi A (2020) How entrepreneurs make sense of lean startup approaches: business models as cognitive lenses to generate fast and frugal heuristics. Technol Forecast Soc Chang 161:120324 Ghezzi A, Cavallo A (2020) Agile business model innovation in digital entrepreneurship: lean start-up approaches. J Bus Res 110:519–537 Gray J, Rumpe B (2015) Models for digitalization. Softw Syst Model (SoSyM) 14(4):1319–1320 Guo H, Wang C, Su Z, Wang D (2020) Technology push or market pull? Strategic orientation in business model design and digital start-up performance. J Prod Innov Manag 37(4):352–372 Gupta G, Bose I (2019) Strategic learning for digital market pioneering: examining the transformation of Wishberry’s crowdfunding model. Technol Forecast Soc Chang 146:865–876 Hervé A, Schmitt C, Baldegger R (2020) Digitalization, entrepreneurial orientation and internationalization of micro-small-and medium-sized enterprises. Technol Innov Manag Rev 10(4):5–17 Hess T, Matt C, Benlian A, Wiesböck F (2016) Options for formulating a digital transformation strategy. MIS Q Executive 15(2) Holland CP, Gutiérrez-Leefmans M (2018) A taxonomy of SME e-commerce platforms derived from a market-level analysis. Int J Electron Commer 22(2):161–201 Huang W, Meoli M, Vismara S (2020) The geography of initial coin offerings. Small Bus Econ 55(1):77–102

66

M. Floris and A. Dettori

Isensee C, Teuteberg F, Griese K-M, Topi C (2020) The relationship between organizational culture, sustainability, and digitalization in SMEs: a systematic review. J Cleaner Prod, 122944 Karpova D, Proskurina A (2021) The need for sociotechnical turn in the study of society digitalization. KnE Soc Sci 711–720 Katsikeas C, Leonidou L, Zeriti A (2019) Revisiting international marketing strategy in a digital era: opportunities, challenges, and research directions. Int Market Rev Kim D, Cavusgil E (2020) Antecedents and outcomes of digital platform risk for international new ventures’ internationalization. J World Bus 55(1):101021 Kim K, Hann I-H (2019) Crowdfunding and the democratization of access to capital—an illusion? Evidence from housing prices. Inf Syst Res 30(1):276–290 König M, Ungerer C, Baltes G, Terzidis O (2019) Different patterns in the evolution of digital and non-digital ventures’ business models. Technol Forecast Soc Chang 146:844–852 Kuester S, Konya-Baumbach E, Schuhmacher MC (2018) Get the show on the road: go-to-market strategies for e-innovations of start-ups. J Bus Res 83:65- 81 Li K, Rollins J, Yan E (2018) Web of Science use in published research and review papers 1997– 2017: a selective, dynamic, cross-domain, content-based analysis. Scientometrics 115(1):1–20 Li L (2018) China’s manufacturing locus in 2025: with a comparison of “Made-in-China 2025” and “Industry 4.0.” Technol Forecast Soc Chang 135:66–74 Liñán F, Fayolle A (2015) A systematic literature review on entrepreneurial intentions: citation, thematic analyses, and research agenda. Int Entrepreneurship Manag J 11(4):907–933 Liu J, Nandhakumar J, Zachariadis M (2018) When guanxi meets structural holes: exploring the guanxi networks of Chinese entrepreneurs on digital platforms. J Strateg Inf Syst 27(4):311–334 Logue D, Grimes M (2019) Platforms for the people: enabling civic crowdfunding through the cultivation of institutional infrastructure. Strateg Manag J Matt C, Hess T, Benlian A (2015) Digital transformation strategies. Bus Inf Syst Eng 57(5):339–343 McAdam M, Crowley C, Harrison RT (2019) “To boldly go where no [man] has gone before”institutional voids and the development of women’s digital entrepreneurship. Technol Forecast Soc Chang 146:912–922 McAdam M, Crowley C, Harrison RT (2020) Digital girl: cyberfeminism and the emancipatory potential of digital entrepreneurship in emerging economies. Small Bus Econ, 1–14 Nambisan S (2017) Digital entrepreneurship: toward a digital technology perspective of entrepreneurship. Entrep Theory Pract 41(6):1029–1055 Nelson AJ (2016) How to share “a really good secret”: managing sharing/secrecy tensions around scientific knowledge disclosure. Organ Sci 27(2):265–285 Oggero N, Rossi MC, Ughetto E (2019) Entrepreneurial spirits in women and men. the role of financial literacy and digital skills. Small Bus Econ, 1–15 Ojala A, Evers N, Rialp A (2018) Extending the international new venture phenomenon to digital platform providers: a longitudinal case study. J World Bus 53(5):725–739 Orser B, Coleman S, Li Y (2020) Progress or pinkwashing: who benefits from digital women-focused capital funds? Small Bus Econ 55(2):363–387 Palan N, Schober A (2021) The Need for (Increased) ICT Skills in the era of digitalization. In: IT and the development of digital skills and competences in education. IGI Global, pp 34–55 Parida V, Sjödin D, Reim W (2019) Reviewing literature on digitalization, business model innovation, and sustainable industry: past achievements and future promises. Sustainability 11(2):1–1 Parviainen P, Tihinen M, Kääriäinen J, Teppola S (2017) Tackling the digitalization challenge: how to benefit from digitalization in practice. Int J Inf Syst Proj Manag 5(1):63–77 Parvinen P, Oinas-Kukkonen H, Kaptein M (2015) E-selling: A new avenue of research for service design and online engagement. Electron Commer Res Appl 14(4):214–221 Pergelova A, Manolova T, Simeonova-Ganeva R, Yordanova D (2019) Democratizing entrepreneurship? Digital technologies and the internationalization of female-led SMEs. J Small Bus Manag 57(1):14–39 Petticrew M, Roberts H (2008) Systematic reviews in the social sciences: a practical guide. Wiley

“Entrepreneurship in the Digital Era. A Systematic Literature Review”

67

Pittaway L, Cope J (2007) Entrepreneurship education: a systematic review of the evidence. Int Small Bus J 25(5):479–510 Prüfer J, Prüfer P (2020) Data science for entrepreneurship research: studying demand dynamics for entrepreneurial skills in the Netherlands. Small Bus Econ 55(3):651–672 Rachinger M, Rauter R, Müller C, Vorraber W, Schirgi E (2019) Digitalization and its influence on business model innovation. Technol Manag 30(8):1143–1160 Ratzinger D, Amess K, Greenman A, Mosey S (2018) The impact of digital start-up founders’ higher education on reaching equity investment milestones. J Technol Transf 43(3):760–778 Rippa P, Secundo G (2019) Digital academic entrepreneurship: the potential of digital technologies on academic entrepreneurship. Technol Forecast Soc Chang 146:900–911 Ryu S, Kim Y-G (2018) Money is not everything: a typology of crowdfunding project creators. J Strateg Inf Syst 27(4):350–368 Saiedi E, Broström A, Ruiz F (2020) Global drivers of cryptocurrency infrastructure adoption. Small Bus Econ, 1–54 Schmitz A, Urbano D, Dandolini GA, de Souza JA, Guerrero M (2017) Innovation and entrepreneurship in the academic setting: a systematic literature review. Int Entrepreneurship Manag J 13(2):369–395 Schückes M, Gutmann T (2020) Why do startups pursue initial coin offerings (ICOs)? The role of economic drivers and social identity on funding choice. Small Bus Econ, 1–26 Sebastian IM, Ross JW, Beath C, Mocker M, Moloney KG, Fonstad NO (2017) How big old companies navigate digital transformation. MIS Q Exec 16(3):6 Shi X, Li F, Chumnumpan P (2020) Platform development: emerging insights from a nascent industry. J Manag, 0149206320929428 Sklyar A, Kowalkowski C, Tronvoll B, Sörhammar D (2019) Organizing for digital servitization: a service ecosystem perspective. J Bus Res 104:450–460 Song AK (2019) The digital entrepreneurial ecosystem—a critique and reconfiguration. Small Bus Econ 53(3):569–590 Sousa MJ, Carmo M, Gonçalves AC, Cruz R, Martins JM (2019) Creating knowledge and entrepreneurial capacity for HE students with digital education methodologies: differences in the perceptions of students and entrepreneurs. J Bus Res 94:227–240 Srinivasan A, Venkatraman N (2018) Entrepreneurship in digital platforms: a network-centric view. Strateg Entrep J 12(1):54–71 Stolterman E, Fors AC (2004) Information technology and the good life. In: Information systems research. Springer, pp 687–692 Sussan F, Acs ZJ (2017) The digital entrepreneurial ecosystem. Small Bus Econ 49(1):55–73 Torres P, Augusto M (2020) Digitalisation, social entrepreneurship and national well-being. Technol Forecast Soc Chang 161:120279 Tranfield D, Denyer D, Smart P (2002) Undertaking systematic review: developing an evidencebased approach for management research. In: Academy of management conference, Denver Tranfield D, Denyer D, Smart P (2003) Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br J Manag 14(3):207–222 Tsatsou P, Elaluf-Calderwood S, Liebenau J (2010) Towards a taxonomy for regulatory issues in a digital business ecosystem in the EU. J Inf Technol 25(3):288–307 Ughetto E, Rossi M, Audretsch D, Lehmann EE (2019) Female entrepreneurship in the digital era. Small Bus Econ, 1–8 Vadana I-I, Torkkeli L, Kuivalainen O, Saarenketo S (2020) Digitalization of companies in international entrepreneurship and marketing. Int Mark Rev 37(3):471–492 Van Le H, Suh M-H (2019) Changing trends in internet start-up value propositions, from the perspective of the customer. Technol Forecast Soc Chang 146:853–864 Vega A, Chiasson M (2019) A comprehensive framework to research digital innovation: the joint use of the systems of innovation and critical realism. J Strateg Inf Syst 28(3):242–256

68

M. Floris and A. Dettori

Venkatesh V, Shaw JD, Sykes TA, Wamba SF, Macharia M (2017) Networks, technology, and entrepreneurship: a field quasi-experiment among women in rural India. Acad Manag J 60(5):1709–1740 Vicente-Saez R, Gustafsson R, Van den Brande L (2020) The dawn of an open exploration era: emergent principles and practices of open science and innovation of university research teams in a digital world. Technol Forecast Soc Chang 156:120037 von Briel F, Davidsson P, Recker J (2018a) Digital technologies as external enablers of new venture creation in the IT hardware sector. Entrep Theory Pract 42(1):47–69 von Briel F, Recker J, Davidsson P (2018b) Not all digital venture ideas are created equal: implications for venture creation processes. J Strateg Inf Syst 27(4):278–295 Wallin AJ, Fuglsang L (2017) Service innovations breaking institutionalized rules of health care. J Serv Manag Wang F (2020) Digital marketing capabilities in international firms: a relational perspective. Int Market Rev Wang W, Mahmood A, Sismeiro C, Vulkan N (2019) The evolution of equity crowdfunding: insights from co- investments of angels and the crowd. Res Policy 48(8):103727 Warner KS, Wäger M (2019) Building dynamic capabilities for digital transformation: an ongoing process of strategic renewal. Long Range Plan 52(3):326–349 Wenzel M, Krämer H, Koch J, Reckwitz A (2020) Future and organization studies: on the rediscovery of a problematic temporal category in organizations. Organ Stud 41(10):1441–1455 Westerman G, Calméjane C, Bonnet D, Ferraris P, McAfee A (2011) Digital transformation: a roadmap for billion- dollar organizations. MIT Center for digital business and capgemini consulting, vol 1, pp 1–68 Yeh C-H, Wang Y-S, Hsu J-W, Lin S-J (2020) Predicting individuals’ digital autopreneurship: does educational intervention matter? J Bus Res 106:35–45 Zillien N, Hargittai E (2009) Digital distinction: status-specific types of internet usage. Soc Sci Q 90(2):274–291 Zuzul T, Tripsas M (2020) Start-up inertia versus flexibility: the role of founder identity in a nascent industry. Adm Sci Q 65(2):395–433

International Business and Block-Chain Ventures Namita Rajput, Vikas Garg, Emilia Alaverdov, Jyotsna, and Shivani G. Varmani

1 Introduction Block-chain technology is improving beyond the realm of password-protected money and through the arena of international commerce. According to Gartner, 30% of the worldwide customer base will be made up of actors that use block-chain as either a key technology for performing commercial operations by 2030. As per a World Economic Forum poll from 2015, by 2027, a proportion of global gross domestic product will be kept on the block-chain. Originally implemented in the context of password money, block-chain applications are locked into traditional businesses, start-ups, and everyday life. For example, it is used to provide payment options other than credit cards or PayPal for e-commerce and international money transfers (Antonopoulos 2017). With merchant loyalty points and gift card monitoring to simplifying and automating transaction finance, not just financial institutions and banks, but also many other firms such as Samsung, Deloitte, RWE, and IBM have benefited. It is executed through a variety of apps, resulting in a decentralized power trading market (Buterin N. Rajput (B) Sri Aurobindo College, University of Delhi, Delhi, India e-mail: [email protected] V. Garg Amity University, Greater Noida, Uttar Pradesh, India e-mail: [email protected] E. Alaverdov Georgian Technical University, Tbilisi, Georgia Jyotsna Jagan Institute of Management Studies, GGSIPU University, Delhi, India e-mail: [email protected] S. G. Varmani Bhaskarachara College of Applied Sciences, University of Delhi, Delhi, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_4

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2016). It was also utilized by smartphone firms like HTC and Foxconn, which provide block-chain support phones for Siemens and other vendors and customers to pay for energy sharing or grid management in password money. Some tech start-ups inefficient and heavily intervened focused on destroying the banking industry while using the technology of other start-ups to build face-to-face consumer services. Through performing as a Digital Decentralized Public Director, block-chain technology is transforming traditional business operations, streamlining procedures, improving credibility, and saving companies time and money. Its application disrupts the existing quo and encourages new methods of doing business across a wide range of industries, businesses, and corporate functions. Smart contracts can automate procedures and save time, allowing firms to operate more effectively. Reduce or eliminate the large budgets available, as well as the requirement for mediation, document processing, and contract enforcement. The most successful industry will be centralized. It also reduces the risk of fraud and data security because the central entity does not have to acquire or manage the central entity. Block-chains may change rules and norms that affect global governance while changing international business practices. I’ve always been interested in how companies can apply block-chain technology to a variety of business activities. Furthermore, block-chain applications have a worldwide impact on the governance of these activities. International business is generally controlled by a mix of the central government, international organizations, and non-governmental organisations, which establish guidelines and norms in the form of regulatory law, as well as widely recognized norms and expectations. Blockchain technology changes traditional business processes and helps businesses trade across borders, allowing businesses to go beyond established legal and governance frameworks. As this disruptive technology gains momentum, it has a significant impact on the environment of businesses and institutions. The way businesses interact and the roles of employees, shareholders, and institutions can change radically. For example, current technology regulations are limited and companies claim to be innovating new types of businesses that are not yet regulated. And that is how government works. It implies that private firms, rather than governments and public institutions, were increasingly setting the agenda, and that the problem of collective action upon that supply of global public goods is being emphasized, and that others were supporting it., Discusses the dangers of cleaning and the benefits of tax exemption. Simultaneously, block-chain applications decrease errors, lowering transaction costs (Antonopoulos 2017; Campbell-Verduyn 2018; Davidson et al. 2018) Industry reputation can be harmed (Berg et al. 2019). As a result, even without the intervention of central authority, block-chain apps may coordinate economic activities (Atzori 2015). Throughout recent years, blockchain technology had gotten a lot of interest in the fields of information technology and legal studies (De Filippi and Wright 2018). In addition, there is literature there in domains of economics and finance, block-chain applications discussed the impact on financial markets and monetary policy.

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Conversely, block-chain technology is rarely discussed in international business research. Major international journals to date lack a comprehensive analysis of blockchain. The current literature is still technical and does not consider the implications of technology for global governance (Campbell-Verduyn 2018). Considering the limitless nature of block-chain and the significant amount of situations where it interacts with multinational firms’ varied activities, this is unexpected. The critical concerns of global regulation of international commercial operations based on blockchain technology, in particular, are almost completely disregarded. Haber and Stornetta introduced the concept of block-chain, which Satoshi Nakamoto, who is still anonymous, introduced in a white paper often cited in Bitcoin in 2008. As follows, Nakamoto explains the new peer-to-peer electronic money system. Peer Bitcoin and other electronic payment systems based on cryptographic proofs rather than trust should joyfully allow both sides to engage directly with one another with no need for a trusted third party. Bitcoin being produced electronically as digital tokens and the technology that allows these transactions to take place is the director of a huge digital distribution. The block-chain technology, on the other hand, has nothing to do with Bitcoin. It is sometimes used as a digital and trustworthy decentralized director from anywhere, a strategy utilized through enterprises in a variety of industries as a decentralized agreement tool (Antonopoulos 2017). In the digital director or database, the block-chain preserves an immutable record of all activities and transactions (Drescher 2017). Because this leger is distributed, all information about these jobs and transactions is kept throughout the network rather than being in a single spot. The job is done anonymously through multiple parties on the block-chain network, and the transaction records are confirmed and published to the whole distribution network. The word block-chain comes from the fact that transactions are organized into blocks that also are linked by a chain and a timestamp. Chirls (2018) is a new type of database that allows block-chain to see transactions and data in a way that distributed user groups are centralized, even if third parties don’t trust each other. These data reside on the block-chain and are made public. Transactions performed on the block-chain write code to securely transfer the messages detailed by Diffie and Hellman (1976). It is based on encryption, which is a technology that solves the problem. Block-chain can be distinguishing between public and private types. Public and unblocked block-chains are open to all participants and those who trade anonymously, while private and approved block-chains are more included and know the user’s identity you need to make sure that you are. Participation is permitted by individual parties or consortiums, acting as gatekeepers. As will be detailed later, the majority of applications in international business are private block-chains with limited access. Among the most significant advantages of block-chain technology is whether it eliminates the need for a middleman to handle data or carry out activities. This is due to the fact that the data relating to the operations and transactions carried out on the block-chain network is preserved indefinitely. There is no centralized point of data execution, no central weaknesses that may abuse the network, and no way to alter the data with a medieval or trustworthy

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third-party personality. And as a result, transactions performed using block-chain technology is this secure and transparent. When applied to business, cost savings, time savings, streamlined processes, system reliability, increased security, increased transparency, reduced interruptions and fraud, reduced audit requirements, reduced overhead, hands various benefits such as reduced human error due to the process of work. Reduction of transaction costs and other costs. After block-chain gained traction, Buterin (2016) launched Ethereum, a revolutionary computer breakthrough. It is based on the very same block-chain technology as block-chain, but somehow it adds a layer of functionality that allows users’ coding apps, such as smart contracts, to operate on it. Whenever the conditions of a contract are satisfied, a smart contract is a digital protocol that automatically verifies or enforces the contract (Cong and He 2019). Executing contracts that are part of the programme code through these smart contracts, and executing previously synchronously granted contracts, is now manual. Not only does the company distribute smart contracts to save time and money, but it also automatically executes contracts when specified conditions are met, reducing some transaction costs associated with doing business. It has been removed to provide a balance with additional security between the contracting parties. The company can customize smart contracts to suit individual needs using various conditions and inputs; these inputs are pre-programmed protocols stored on the blockchain for financial transactions. You can encourage them to perform various tasks automatically, such as performing them or sending commands to smart devices. Global Governance Functions: A Conceptual Framework They need a deeper knowledge of governance and its main functions until we can investigate the influence of block-chain applications within the worldwide business of global governance. Governance may be seen as a way of bringing order to a situation, resolving problems, and obtaining mutual benefit. The Global Governance Commission (1995: 2) is the sum of the various ways public and private individuals and institutions manage collaborative work. It conflicts and meets other interests and cooperates. It is an ongoing process in which action can be taken. It includes formal measures as well as informal measures that consider whether a person and the institution have agreed for the best of their benefit. Is to use financial and regulatory tools to promote superiority and ensure effective economic outcomes.

2 Governance Functions The preservation of property rights seems to be the primary obligation of government (Alchian 1989; Allen et al (2018, p. 117), the capacity of others to participate in the very same sort of activity is the right of individuals who could acquire and transfer valuable resources through agreed-upon transactions. It’s been regarded as unconstructive for a long time. It is the foundation of individual liberty and human success. The property might be physical or immaterial in this sense. Transfers of property law,

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which are typically protected by law, are subject to additional transaction expenses. Complexity, unpredictability, and contract execution costs are all part of the transaction costs. Such costs decide whether business operations are carried out on the open market or inside the context of the business. To promote the interchange of products and services, costs must be lowered. When a dominant organization that coordinates economic activity faces unfavourable externalities, price mechanisms might not provide the desired effects. Externalities are unfavourable outcomes of commercial operations that impact unrelated parties, including pollution, public health hazards, and systemic economic risks. Since it is not governed by that of the market, we feel it is critical to be regulated through governance and regulation. The prevention of monopoly rights is another essential duty of governance. When a firm controls the majority of the supply of products and services upon that market and provides unfair benefits to its customers, it is said to have a monopoly. This needs regulation since it has the potential to raise prices and create obstacles to entry for other suppliers, both of which are undesirable to customers and rivals. Furthermore, it is a government responsibility to maximize societal welfare. The term social welfare can also be used to describe a variety of situations. The growth of social welfare with technology may be ascribed to factors impacting the quality of life, such as the environment, health, social services, economics, and happiness. Avoid harmful external effects on society and the environment, on the other hand.

3 The Application of Block-Chain Technology in International Finance International finance is the most obvious business area that block-chain technology can secure due to the popularity of the password currency Bitcoin. As a payment option, it interfered with e-commerce and international money transfers. However, the entire industry, which is the same as a financial transaction clearinghouse or a real estate ownership company, can be exchanged, which requires cost and time to complete the transaction. With the introduction of the Barclays block-chain, the time required to carry out a capital exchange has been reduced from a typical week to less than 10 days to less than a day. With both the help of start-up Wave, Barclays will be able to leverage block-chain technology to execute real-time global trade transactions between the two firms. Block-chain, according to Baghdadi, Barclays Global Head of Trade and Working Capital, seems to have the potential to speed up trade transactions, lower expenses for firms throughout the world, improve internal banking procedures, and minimize the danger of documentary fraud. They’ll collaborate with other banks to promote the system’s adoption and enhance trade document management across the sector. Other businesses are attracted to the quick movement of cross-border payments.

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From Signature Bank, SignetTM allows commercial customers in a bank to send free security payments to other commercial customers in an unrestricted bank for at least 5 s, Google, and Goldman Sachs. Veem, a start-up supported by, allows businesses to send and receive payments in multiple currencies but uses Bitcoin as an intermediary asset. With this system, the algorithm automatically handles the most efficient payment method without the need for trading partners to hold Bitcoin directly. More than half of the transactions that Veem processes rely on password money on behalf of the other party. While moving to a personal level in business, Santander has released a mobile app called One Pay FX on a forex service that uses Ripple block-chain technology, allowing individuals to make money to other individuals immediately or on the same day. Insurers are leveraging block-chainbased contract execution to automatically stimulate the claim processing process to provide greater trust and transparency between policy holders. AXA uses smart contracts to process late flight claims. This allows you to store and process insurance payments based on smart contracts connected to the Global Air Traffic Control Database. This means that rewards will be triggered automatically if a delay of 2 h or more is registered. In just this example, block-chain helps AXA enhance client interactions by simplifying vendor and customer procedures (Business Insider 2017). For flight delay insurance, Allianz uses block-chain to implement similar auto-billing payments. In complicated transactions, block-chain technology is often utilized to ease document management and processing. The Northern Trust, for example, automates the majority of legal papers linked with private-equity fund transactions. Use Hyperledger Fabric in particular can handle the management of private-equity operations, such as initial sales or fund clearing. On a broader scale, the Depository Trust and Clearing Corporation would employ a block-chain to track credit derivatives inside the Trade Information Warehouse. The system serves as the worldwide financial industry’s previous infrastructure, providing lifetime transaction processing services for approximately 98% of the world’s credit derivatives, which amount to $11 trillion (Coindesk 2018). The successful implementation of this new block-chain-based system reduces a lot of redundancy and can provide this core person with a simpler process in the global financial ecosystem.

4 International Supply Chain Management and Logistics Supply Chain Management (SCM) has long been considered in terms of business ethics for ethical and responsible sustainable sourcing practices. In this area, the advent of block-chain will allow enterprises to further increase the transparency, efficiency, and responsibility of their product sources. This allows companies to track product history from raw material supply to point of sale throughout the supply chain. Businesses may utilize the Provenance platform to make business supply chains more transparent, create more educated consumers, and expedite their transition to sustainable consumption (According to Accenture 2018). Provenance verifies

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supply chain and processes through integrating such services into the company’s procurement process and making that information available to customers via its websites and apps. The firm or product’s worth is raised as a result. Provenance’s (2019) purpose is to assist companies and merchants in gaining consumer confidence via transparency. Provenance, a block-chain-based system, allows customers to select their items. IBM is now also experimenting with block-chain technology to boost supply chain efficiency. IBM had eliminated the requirement for third-party verification during freight by establishing a platform similar to Provenance to give Jinwison to all supply chain players in conjunction with Maersk. To present, more than 100 organizations have signed over to the TradeLens platform, which will track tens of millions of shipping containers each year (Accenture 2018). This programme’s goal is to lower worldwide shipping costs, increase supply chain visibility, and remove inefficiencies associated with paper-based procedures, such as delays and fraud. From metal components to food to diamonds, block-chain supply chain tracking applies to all sorts of items. Toyota joined the R3 block-chain consortium to enhance SCM by using technology to track car components as they moved between nations and plants. Supply chain interruptions caused by catastrophes such as tsunamis and earthquakes, lead to inefficiency and logistical difficulties. The IBM-Everledger cooperation has traced diamonds from the mine to the jewellery retailer and documented their journey. The programme is intended to offer purchasers transparency and to filter stones so that forced labour is not utilized in public locations or to collect cash for violent crime. Everledger Kemp CEO explains: Most diamond trades nowadays are affected by paper-based modifications or counterfeiting. Within the 150-year-old sector, individuals trade with confidence. Consumer peace of mind is connected the with an ethical supply of diamonds, and block-chain gives trust in dependable systems. IBM has partnered with Walmart as well. The two firms will collaborate to track food movements across Walmart’s supply chain. Among the first significant initiatives would have been to track pig movement in China’s supply chain to improve system stability and make goods safer from one of the world’s largest meat marketplaces. Many supply chains are pretty long, so it’s difficult to introduce fraud since no one knows everyone else in the chain, as according to IBM’s global supply chain specialist Chang. Walmart will indeed be responsible for tracking tainted pork suppliers and closely monitor these on the road as a result of this effort. They’ve also created the Blockchain Food Safety Alliance to increase the efficiency, openness, and authenticity of the food supply chains, with plans to roll it out globally. In fact, according to current research by Walmart, using block-chain to track food cut the time taken to trace a mango box from a farm to fill to 2 s. It was reduced to one second in a day or weeks. Starting this year, Walmart requires all direct suppliers of spinach and lettuce to record product shipments via the block-chain. To track the food supply chain, the following proceedings are companies like Nestle testing services in Europe to help consumers track the procurement of Gerber ingredients. Starbucks is piloting the Bean to Cup initiative to track coffee production

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in Costa Rica, Colombia, and Rwanda farmers so that customers can track the origin of coffee (Cointelegraph 2019). Bumble Bee, with the help of SAP, is a South Pacific fisherman using the block-chain of the supply chain to track Albacore tuna to US grocery stores. Throughout terms of contemporary health and environmental problems, this helps to establish trust in product safety and sustainability. The openness that block-chain integration gives inside the supply chain is crucial to reliability as well as a competitive advantage for firms that adopt it, especially as consumer demands for standards of ethics rise. It indeed gives firms that use it another competitive edge and allows them to charge a higher price.

5 International Marketing and Advertising Block-chain technology improves the transparency of advertising firms by providing more full images of advertising features including such advertising time and success in the sphere of international marketing and advertising. It also provides transparency to consumers who are notified by the block-chain public director to record information about how data is used and sold. An example is Comcast. The company works with industry partners to give viewers more targeted advertising with more control over data about advertisers’ crimes without disclosing the viewer’s personal information. This platform was created to increase the efficiency and efficacy of television marketing and advertising. The added benefit is that each Blockgraph participant’s data stays in its system, allowing participants to follow user choices about data use while continuing to safeguard the data and manage the user’s personal information. As a result, it is the protection of the personal data of consumers (Business Wire 2018). Facebook is another company that is interested in using block-chain to implement block-chain-based credentials to log in to its website and provide users with more personal information. These systems can affect the monitoring of Facebook user data. CEO Zuckerberg says that such a new login system will replace Facebook Connect with fully deployed to access the app’s users want and share their favourite amount of data without an intermediary. Said to be able to. However, since the Cambridge Analytica scandal, which leaked data from about 90,000 users, Facebook has faced doubts and pressures on protecting user data. Both advertisers and consumers will benefit from advertising innovation based on the Algebraix block-chain. The ALX app is a privileged advertising platform inspired by ALX signals (Algebra 2019). Marketers post content on the network and specify target customers. ALX then transfers the content to the appropriate users on the network. Potential customers who interact with the content are paid-for tokens. After all, marketers get an anonymous analysis for their targeted customers. In short, individuals use their data and are motivated to reward their advertising consumption. The platform protects personal information and data rights while providing value to marketers and customers. As a result of the use of block-chain

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in the quest for more efficient marketing and advertising, consumer privacy has increased.

6 Impact of Block-Chain Applications on Global Governance Table 1 highlights the preceding section’s examples of block-chain uses in international business. The commercial ramifications are numerous and varied, with varying governance results. Technology can interfere with business activities and therefore affect our ability to control and regulate such activities. Based on a conceptual framework, we analyse the potential implications of the five major functions of global governance, such as protecting property rights, reducing transaction costs, internalizing externalities, preventing monopoly, and maximizing social welfare.

7 Protection of Property Rights The block-chain applications discussed in the preceding section demonstrate how block-chain technology may affect ownership protection in several ways. First and foremost, it is about safeguarding your personal information. Implementing an advertising block-chain, for example, allows Facebook to withhold personal information from advertisers, enabling users to select how much information their share without third parties. You can enhance the protection of personal information and personal data. Money can also be thought of as a protected asset. The parties receiving the payment are better protected, as shown by the instances from Barclays, Signature Bank, and Veem, that there are no longer any fraudulent billing fraud or payment cancellation possibilities. The validity and transparency of logistical records are indeed influenced by technology. The cargo information can indeed be tampered with it or recorded once this is stored on a block-chain-based system (e.g. IBM-Maersk). Block-chain interruptions can provide an opportunity to strengthen the protection of property rights and encourage stricter regulations and record-keeping and reporting for data privacy. Some examples of transaction costs are existing types of control, where block-chain-based smart contracts provide the option for companies to automate and perform complex and uncertain activities outside the company through contract enforcement. It shows that the uncertainty of the existing regulatory body, which is the contract of, will be removed to a large extent. It also eliminates contractual hold-up issues and the risk of trading partners. If the paying party manages to use the seller after making a particular investment or consuming resources to fulfil its contractual obligations.

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Table 1 Examples of the impact of block-chain applications and governance Area

Example

Business implications

Governance implications

International Finance, Banking, and Insurance

Barclays

Quicker transactions, reduced costs, and fraud

Transaction costs, externalities

Signature Bank

Quicker B2B Property rights transactions (real time)

Veem

No foreign currency exchange needed

Santander

Quicker individual Property rights, social transactions (real time) welfare

AXA, Allianz

Automated processes, increased consumer trust

Transaction costs, social welfare, monopolistic power

Northern Trust

Automated processes and paperwork

Transaction costs, externalities

Finance, Banking, and Depository Trust& Insurance Clearing Corporation

Reduced paperwork, reduced time, streamlined processes

Transaction costs, externalities

International Marketing and advertising

Provenance

Increasedtransparency and trust

Socialwelfare, transaction costs

IBMMaersk

Increased transparency Property rights, social and efficiency, reduced welfare, transaction costs costs, externalities, monopolistic power

Toyota

Increased logistics efficiency

Transaction costs

Everledger

Increasedtransparency and trust

Socialwelfare, transaction costs

International

Walmart

Increased reliability and product safety, time savings

Social welfare, transaction costs, externalities, monopolistic power

Marketing and advertising

Nestle, Starbucks, bumblebee

Increased Social welfare, transparency, trust, and externalities product safety

International Marketing and Advertising

Comcast

Improved efficiency, increased consumer privacy

International

Property rights, social welfare

Property rights, social welfare

Facebook

Increased data privacy

Property rights

Algebraix

Improved efficiency, increased consumer privacy

Property rights, social welfare

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This is especially true for AXA auto insurance claim payments, as smart contracts eliminate transaction uncertainty and are automatically paid to customers when flights that exceed the contract threshold are delayed. Block-chain-based smart contracts are no longer needed brokers and audits to prove key agent costs and automated contract execution and insurance fraud due to contract conflicts of interest. Reduce the expense of human overhead. Money transfers finance, and supply chains are all examples of case studies as well as other uses. Furthermore, block-chain applications on platforms like Provenance enable transparency, which reduces the ambiguity of both the data on which supply chain transactions are based. It is still obvious that block-chain technology has the potential to cut transaction costs; this instance also demonstrates some competing factors. Standards are a key concern in the adoption of international inter-company block-chain technology. Block-chain applications were currently created on a case-by-case basis in each business and sector. As a result of the business’s competitive nature, fragmented, incompatible technology and applications emerge. As such, especially in terms of block-chain interoperability, an institution of the organization is needed to determine the contract with the standard (Accenture 2018, p. 7). To achieve mutual benefit, it is necessary to build a network of industries in general (Carson et al. 2018).

8 Internalization of Negative Externalities The application of block-chain technology is due to the high level of energy consumption required to pass through it. Environmental protection is clear. In the example discussed, carbon emissions are not generally available, but observers argue that miners require vast amounts of computing power to perform block-chain transaction calculations. While block-chain-based solutions in supply chain management and finance are more effective, transparent, and use fewer paper and resources, portals are acceptable in terms of energy usage and regulation. As the use of block-chain technology becomes more prevalent in global business, these concerns grow. The example of block-chain application in an international business that prevents monopoly power shows that this new technology is mainly adopted by multinational companies. There seems to be a concern that even these large and strong actors may exploit the technological and financial acumen of minor market players like suppliers and consumers to advance their interests and create barriers to entry for market competition. As a result, regulators may give small businesses financial and technical help to avoid the possibility of monopoly rights being exercised by big block-chain pioneers. Block-chain and smart contracts, on the other hand, through automating contract execution based on pre-programmed terms, can assist suppliers of all sizes in trading among supplier purchasers. This promotes fairness and competition among small and medium-sized providers by preventing larger parties from pressuring weaker parties to change contract conditions (Cole et al. 2019). Increasing social well-being, finally, the advantages of block-chain technology have a significant influence on global trade. The impact on supply chain management affects people associated with the entire

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system. For example, Walmart and Starbucks can help transform the entire system into more ethical practices to increase the integrity and reliability of the supply chain. Consumers can make more educated decisions and buy ethically by having greater transparency and knowledge about the items they buy, such as Bumble Bee, Nestle baby food, and Ever ledger diamonds, thanks to block-chain. You may be able to swap purchases with your goods. With mainstream in SCM, block-chain may also intervene in this field of governance to tighten supply chain regulation and delegate a wider ethical base. Consumer trust and pleasure are other areas of social welfare influenced by the block-chain. The block-chain-based billing automation systems used by AXA, Allianz, and Northern Trust, for example, improve customer confidence by preventing insurers from using consumers or suspending bill payments. Comcast, for example, uses block-chain-based advertisements to hide personal data from advertisers and, in some circumstances, determine whether or not people participate in the ad and how much information they provide, as well as privacy and trust. These developments can lead to tighter regulations for data protection and personal information protection through governance. Consumer satisfaction has been improved based on the impact of the block-chain of financial companies using technology that allows the transformation of immediate cross-border calls without foreign exchange fees of the old-fashioned core person. These block-chain applications, on the other hand, are beneficial to people since they are unregulated and not supervised by central banks, which might lead to governance difficulties. Transactions in which an individual abuses privileges to evade taxes, conduct corruption, substitute products, and services on the black market, or transfer cash to malevolent parties reduce governance’s potential.

9 Contributions and Suggestions Global Governance Suggestions In this study, we aimed to explore the impact of block-chain technology on international business and the associated global governance challenges. Long since, blockchain technology had surpassed password money limits and has reached other fields of international trade, for example, international finance, banking, insurance, supply chain management, logistics, marketing, and ads. It’s been. The growth of various block-chain applications has diverse consequences for global governance. Certain functions for governance are harder to do, while others would rely on block-chain. The research indicates, more precisely, that now the protection of property rights may be increased and transaction costs can be decreased. A central organization must not be acquired or managed to reduce the risk of fraud and data security. Therefore, block-chain technology moves to confident mathematical calculations in confident people and institutions (Atzori 2015) to decrease the level of uncertainty As block-chain technology evolves and technological standards evolve, such potential will indeed be fully realized. The impact of block-chain applications on these

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other global governance functions in international business is much less clear. The negative externalities resulting from the high levels of energy consumption required to perform block-chain transaction calculations are a major challenge. The study also focuses on the dangers that multinationals can take advantage of the technical and financial advantages of small market participants as early adopters on the blockchain. Therefore, regulators must take effective measures to prevent the emergence of monopoly rights. Applying international business block-chain technology can increase transparency, consumer satisfaction, and social welfare in all the industries studied. However, this requires regulation and oversight to prevent user anonymity against illegal activities such as corruption, tax evasion, inorganic or drug trafficking. These governance issues are similar to those of various electronic payment systems (Böhme et al. 2015). Also, the structure of the block-chain decentralized director is to identify and prosecute malicious activities (Allen et al. 2018) and to identify and prosecute central entities when such activities occur. In addition, it creates additional difficulties and hinders the implementation of governance rules and control functions. In this perspective, you must consider the key distinctions between public block-chains (such as Bitcoin) and private block-chains, which are widely used in international trade. The majority of prior research has been focused on public block-chain; however, our findings demonstrate that private block-chain governance has unique problems. It enhances private sector power to limit access to certain parties, raises the danger of monopoly rights, and lowers the creation of social welfare, for example. At the same time, decentralized technologies like block-chain may speed up direct government action. As a result, a sort of cooperative regulation of formal institutions and informal activities is necessary. In this context, policy entrepreneurs’ engagement is crucial, who work and compete with traditional regulators, can help with the best governance. Reyes stated, Regulators, establish dual control of laws and regulations based on laws and regulations, and the laws and regulations are a repetitive and cooperative process with core development, based on the concept. We propose a theory of intrinsic governance implemented in the code. Regulations are uniformly integrated into the technically enforced decentralized director technology and applications based on technology and network agreements proposes that technology leaders, business innovation, and policy entrepreneurs voluntarily involve public bodies in drafting, implementing, and enforcing norms. This is very important in this area to enable various rapidly changing industries. The rapid evolvement of block-chain technology and applications will affect block-chain governance in global businesses, in the future. Most of the samples analysed are yet in the starting stage, in this research. One is required to continually monitor technology and business creations and flexible regulatory compliance, to keep up with these dynamic technologies. A multilateral characteristic is another challenge for block-chain governance. Most of the early adopters of IT technology, as can be seen from the analysed examples, are multinational companies operating worldwide. This allows you to evaluate and move activities to the most appropriate settings and jurisdictions as needed to pursue the benefits of arbitration. Block-chains

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show positive efficiency in international finance, banking, insurance, supply chain management, logistics, marketing, and advertising, emphasizing the need for more empirical research in these areas. Future research will, for example, look at how companies create smart contracts to make strategic decisions as well as the effect of automated strategic decisions on performance, as well as comparative studies for user tradition but instead block-chainbased recognition inside the international supply chain. As a result, more study into the regulatory implications of block-chain is required, to determine few suggestions for resolving complicated international governance problems.

References Accenture (2018) Block-chain in logistics: perspectives on the upcoming impact of block-chain technology and use cases for the logistics industry. Available at: https://www.logistics.dhl/con tent/dam/dhl/global/core/documents/pdf/glo-core-block-chaintrend-report.pdf Alchian AA (1989) Property rights. In: Eatwell J, Milgate M, Newman P (eds) The invisible hand. Palgrave Macmillan, London, pp 232–238 Algebraix (2019) ALX. Available at: https://algebraix.io/alx/ Allen D, Berg C, Novak M (2018) Block-chain: an entangled political economy approach. J Public Fin Public Choice 33(2):105–125 Antonopoulos A (2017) Mastering bitcoin: unlocking digital cryptocurrencies, 2nd edn. O’Reilly, London Atzori M (2015) Block-chain technology and decentralized governance: is the state still necessary? SSRN. https://doi.org/10.2139/ssrn.2709713 Berg C, Davidson S, Potts J (2019) Understanding the block-chain economy: an introduction to institutional cryptoeconomics. Edward Elgar, Cheltenham-Northampton Böhme R, Christin N, Edelman B, Moore T (2015) Bitcoin: economics, technology, and governance. J Econ Persp 29(2):213–238 Business Insider (2017) AXA turns to smart contracts for flight-delay insurance. Available at: https://www.businessinsider.com/axa-turns-to-smart-contracts-for-flight-delay-insura nce-2017-9?IR=T Business Wire (2018) Comcast collaborates with industry partners on blockgraph software to jumpstart the use of secure data sharing for advanced TV advertising. Available at: https://www.businesswire.com/news/home/20181221005530/en/Comcast-Collaborates Industry-Partners-Blockgraph-Software-Jumpstart Buterin V (2016) What is Ethereum? coincenter.org. https://coincenter.org/entry/what-is-ethereum Campbell-Verduyn M (2018) Bitcoin and beyond cryptocurrencies, block-chains and global governance. Routledge Taylor & Francis Group, London Carson B, Romanelli G, Walsh P, Zhumaev A (2018) Block-chain beyond the hype: what is the strategic business value? Available at: https://www.mckinsey.com/business-functions/digitalmc kinsey/our-insights/block-chain-beyond-the-hype-what-is-the-strategic-business-value Chirls N (2018) Block-chain and the decentralization of finance featured session at SXSW 2018, Video. Available at: https://www.sxsw.com/interactive/2018/block-chain-and-the-decent ralization-offinance-featured-session-at-sxsw-2018/ Coindesk (2018) 15 Banks join DTCC post-trade block- chain as project enters testing. Available at: https://www.coindesk.com/15-banks-join-dtcc-post-trade-block-chain-as-project-enters-testing Cointelegraph (2019) Starbucks working with Microsoft for block-chain-based coffee tracking platform. Available at: https://cointelegraph.com/news/starbucks-working-with-microsoft-for-blockchainbased-coffee-tracking-platform

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Cole R, Stevenson M, Aitken J (2019) Block-chain technology: implications for operations and supply chain management. Supply Chain Manag Int J 24(4):469–483 Commission on Global Governance (1995) Our global neighbourhood. Oxford University Press, Oxford Cong LW, He Z (2019) Block-chain disruption and smart contracts. Rev Fin Stud 32(5):1754–1797 Davidson S, de Filippi P, Potts J (2018) Block-chains and the economic institutions of capitalism. J Inst Econ 14(4):639–658 De Filippi P, Wright A (2018). Block-chain and the law: the rule of code. Harvard University Press, Cambridge Diffie W, Hellman ME (1976) New directions in cryptography. IEEE Trans Inf Theory 22(6):644– 654 Dobrovnik M, Herold DM, Fürst E, Kummer S (2018) Block-chain for and in logistics: what to adopt and where to start. Logistics 2(3):1–14 Drescher D (2017) Block-chain Basics: a non-technical introduction in 25 Steps. Apress, New York

The Rise, Fall, and Rise Again of Parikarma Events Harjit Singh

and Neha Puri

Issues The case is designed to attain the following teaching aims: . To comprehend the distinctive qualities of a successful entrepreneur. . To comprehend the issues and challenges in managing growth and business continuity of an event management company. . To appreciate the role of innovation, creativity, and freedom to employees in shaping the future of a company. . To investigate how a company can use technology to solidify a competitive advantage. . To evaluate how a customer-centric ethos can help in the growth of an event company. Don’t worry about mistakes and misunderstandings as they are bound to happen. You need to think, how to turn customers’ complaints into a compliments. Your life is also a movie for others, make certain, it is worth appreciable. Ashish Kalra

H. Singh (B) Symbiosis Centre for Management Studies, Symbiosis International (Deemed University), Noida, India e-mail: [email protected] N. Puri Amity College of Commerce & Finance, Amity University Uttar Pradesh, Noida, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_5

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1 Introduction This case study is about Ashish Kalra, who after doing his higher secondary education was planning to do his graduation from management stream. As those days there were no private colleges and universities, getting admission in government universities and colleges of repute was a herculean task. Therefore, vis-à-vis Bachelor of Business Administration (BBA), he applied for Bachelor in Commerce (B. Com) programs also. But perhaps his fate was somewhat different. Here he was planning to go to college, where on the other side luck had thought of something else. His grandfather, who was running ‘Tent and Catering’ business, got ill. As Ashish’s father was in Armed Forces, it was not feasible for him to take care of his sick and helpless father. Seeing the ailing grandfather and taking care of family business in his absence, everything came over his head. At the academic front, the results of Ashish’s graduation entrance were coming to close, but at family front, his grandfather’s health was deteriorating day by day. Some colleges had even started publishing the admission lists, but here Ashish’s one leg was hanging in hospital and other in taking care of his grandfather’s ‘Tent and Catering’ business. When colleges started displaying admission lists and when the last one went, he did not know anything. After fighting with illness for about two months, one midnight his grandfather suddenly left for heavenly abode in March 2007. But before leaving this world, his grandfather took the promise that after he left this world, he (Ashish) would not let his business die. Ashish loved his grandfather so much that just to fulfill his last wish, he sacrificed his dreams and decided to abandoned his studies. Ashish did not take much time to learn how to run a ‘Tent and Catering’ business effectively and prudently but also how to stay ahead in competition. Within short span, Ashish realized that over and above all the general business skills, the success of ‘Tent and Catering’ business depends upon hard work, resilience, and expertise.

1.1 Literature Review Event management is a growing phenomenon in the world and more notably, in developing countries like India. Though the present study is to determine the factors affecting the rise, fall, and again rise of an event management company, the literature review lays the foundation to discuss much talked but less understood issue of successful entrepreneurship especially in tough and fast-changing business environment. There are plenty of studies around the world that highlight some inherent characteristics of entrepreneurs’ vis-a-vis the stands taken by entrepreneurs to face adversities and coming out of adverse situation and proving that successful entrepreneurs never give up. The noticeable among them are self-motivation, passion, zeal, and art

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of networking to move ahead. Commitment to self and self-motivation (Inner motivation) have emerged as major dimensions of modern-day entrepreneurs. Baldoni (2005) also emphasized that the successful entrepreneurs have been involved in risk-taking and are inventive and pioneering. Forecasting and assessing the emerging prospects signify the start of the entrepreneurial journey (Clark and Oswald 1994). The bourgeoning entrepreneurs identify or shape business opportunities attained through family business enterprises, usually by financing of capital for that business firm or merely selling inventive thinking (Cacioppe 1998). The top-level managers or the strategic experts of outsized firms have to reinvent their companies every day, by creating new business opportunities and taking it to new height (Gaglio and Katz 2001). Generally, the individuals working in the multi-national corporations have found indulged in healthier bargaining skills and Liaisoning with the outsiders (Leith et al. 2012). Their outcome and efficiency are enhanced when entrepreneurs are competent of unified actions and access over the data and facts and symbolize a substantial substituting cost for the company, if they were to switch over (Singh and Aggarwal 2013). Kihlstorm (1979) endorsed the entrepreneurship’s notion as an avenue and platform to transform business ideas in to realities and creating wealth. Déjean et al. (2004) suggested that the overall initiatives of the entrepreneurs of the first generation are essentially competitive. Therefore, the competition is integral part of the business process and entrepreneurial market space. Or in other words, the entrepreneurial inner self-conscious and proactive approach are imperative toward becoming global. According to Katz and Kahn (1978), Kumar et al. (1993), and Murphy et al. (2006) opine that modern entrepreneurs are innovative, technology savvy, risk-takers and implement business ideas in to realities with efficient and prudent skill set. Therefore, the concept of entrepreneurship refers to the capability of an individual to take risk, putting plans into actions, and owning skills such as innovation, uniqueness, risktaking, and competence to design and control the deeds in view of accomplishing the projected objectives. Churchill (1999) recognizes entrepreneurship effective if during each stage of venture-ship, business traits such as taking initiatives, education, spirit, and moving forward are influenced from self-motivation. Qualities such as self-discipline and decision-making have evolved as two imperative key dimensions of entrepreneurs’ personality, in addition to the traditional style of risk-taking and unique thinking (Hersey et al. 2001).

1.2 Methodology To set the tone of the case and achieve underlying objectives, data has been collected from both the primary and secondary sources. The protagonist, Ashish Kalra, was interviewed both face to face and telephonically plenty of times. Besides this, existing

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literature and subject experts were consulted for the lucidity of the concept and case constructing.

2 The Birth of an Entrepreneur Variety is the recipe of life for event managers. One day you are busy in planning a wedding ceremony, and the next movement you may end up your day in organizing corporate seminar. Whether you are in need of a star night in Mumbai or political rallies in Delhi, the event management company will bring them to you. Event management companies are engaged in smooth execution of ideas and dreams into reality. Event managers brace themselves whenever they encounter some emergency. Since childhood, Ashish was a soft-spoken who would walk with everyone. Everyone loved him. He used to participate in almost all the functions of school. Though he was an average student, but he was liked by all the teachers and classmates. Ashish remembers that he used to take all his schoolmates together from the very childhood. Perhaps, this is why Ashish probably wanted to become Human Resource Manager. But compulsions made Ashish to handle his family business. When Ashish was preparing for admission in Graduate Program, his grandfather got hospitalized, and after struggling for two months, he died. But his grandfather’s admission to the hospital changed Ashish’s life. The precious time during which, he could apply for higher education and competitive exams, destiny kept him busy in hospital or in taking care of his family business.

3 The Entrepreneurial Itch An individual who never thought of doing business was getting up today with the customers. Though initially Ashish did not take any interest in his ‘Tent and Catering’ business but having no option, he realized that by working mindfully, the work that is done becomes interesting and we start taking interest in it. The reason for his disinterest was that Ashish used to consider that ‘Tent and Catering’ business is a business of illiterate people for whom it is very common to abuse and fight on very small matters. But as he entered the business, all of his beliefs proved to be wrong. Therefore, he started enjoying it. After this, he never looked back. This was Ashish’s hard work that within short span of time, he was now known for his creative work. Ashish always assured that not only his designed tents and catering services but all the associated services also become the best culinary experience for his customers. Though Ashish tried to offer different set of services to different customers, but he realized that there is very less scope of innovation in his ‘Tent and Catering’ business. Though he wanted to offer different layouts and presentation themes to customers, but he realized that most of the customers wanted no change in the traditional and

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regular setups. Perhaps, this was the reason for Ashish’s frustration to have same designs and almost same party halls one after the other. Therefore, in 2011, Ashish started an event management company with the name Parikarma Events in Chandigarh, joint capital of Haryana and Punjab states. This was also the time when Indian middle class’s income was on its high. Now people were spending enough money on the marriage of their son and daughter. Not only on the wedding ceremonies, people used to search for reasons to spend money and throwing parties to their near and dear. Further multi-national culture and rise in employment, fueled event management business all over the country and Parikarma was not an exception. In the same year, Ashish’s father also got retired from Indian Air Force and started helping Ashish in his ‘Tent and Catering’ business for which Ashish did lot of hard work to took it to a level where business orders were more, but less hands were there to handle it. Therefore, Ashish recruited new pool of graduates from b-schools and strengthened his existing work force. Further, to run his company effectively, Ashish took all necessary steps like right person at right job, created a system and culture where everyone knows what is expected from him. To whom they have to take instructions and report. So it did not take much time for Ashish’s father to handle the ‘Tent and Catering’ business.

3.1 The Journey Begins Having relieved from the worries of handling parental business, Ashish could give enough time to his new venture of event management. It was Ashish soft-spoken attitude and hospitality that within three years, Ashish started offering services to almost all types of events. From grand weddings to themed parties, to corporate event planning, sports tournaments, outdoor party planning, children’s birthday parties, Ashish offered. Menus were customized to the client’s budget and preferences. All of his catering designs and solutions were of high quality that enhanced events to new heights of gourmet food and whimsical presentations. His well-trained managers left no stone unturned to assure that customers’ wedding, as well as all its other related events, become the best culinary experience. By 2016, Parikarma Events had become well-known brand in event management industry of Northern India. Though its main office was in Chandigarh, but they used to cater their services all over the country. Food and decoration was one of the most acclaimed aspects of Ashish’s events. His ‘Tent and Catering’ subsidiary made sure that customers get the best services, with delightful flavors, prepared by well-trained chain of chefs and with well-organized and well-mannered serving staff. It offered both the indoor and outdoor services and also offered world class decoration to add more glamor and color to the event. Parikarma now could cater up to 10,000 guests at a time and ensured that each of their guests is contented with their service irrespective of location and occasion. Everything was moving smoothly. Ashish was earning by leaps and bounds. His company had advance bookings for more than six months. Depending upon the

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size of the event, employees were outsourced and the strength used to go beyond 750. Now Ashish solicited bids for almost all the major events happening in the country. He had developed good contacts with venues and service providers all over the country. Ashish who had no degree or diploma in the area of ‘Event Management’, now was providing training to b-school graduates. He was giving lectures and training sessions on Event Planning and Coordination, Event Logistics and Finances, Staff Management Entrepreneurship and Leadership Skills, Guest Reservations and Arrangement, Venue Selection, Setup, Design, and so on. Be at domestic front, personal, family, or business, Ashish was doing well. His finances were on rise. He was well-known figure among political and administrative setups. He also had become good Liaisoning executive. Probably, God had approved something else. In August 2017, he got hospitalized due to continuous weight loss and unbearable back pain. Ashish was diagnosed with renal cell carcinoma (RCC), commonly called kidney cancer. Hearing this news, his world changed. His family was shattered. Ashish was hospitalized for past three weeks, suffering from acute body ache and loss of blood before the tumor was detected and tested for cancer. But Ashish was late, as by then, cancer had spread and he was declared to have entered in stage III. The doctors showed their helplessness in removing tumor as veins and arteries could puncture. Only hope was chemotherapy, but considering his deteriorating health, chemotherapy looked so aggressive that doctors warned Ashish that he might not be able to bear it and may collapse. The medical condition of Ashish was deteriorating day by day. No one was there to take care of his event management empire in his absence. Most of his key employees started their own event management companies and started giving competition to Parikarma Events, which was now handled by his retired father. Though his father did his level best to maintain the customer base but could not retain key valuable employees. Ultimately in just six months, his business hit the ground from the sky. All the warning signs such as bad word of mouth, bills/paychecks were not paid on time, clients disappearing, communication gaps, falling employee’s morale, good employees’ quitting, no long-term planning or goals, perks and benefits change, toxic employees causing problems, unhappy employees, promotion of wrong people, that his company was in trouble starting depicting. Consequently, Ashish was surrounded by troubles from all sides. The main shock he faced was the detachment of his key employees. Some of his employees did not leave Ashish in trouble, but started their own firms and catering to clientele of Parikarma Events. Within one year, Parikarma’s revenues came to halt. Except local and small-sized events, almost all national level and big-sized events went to competitors. Expenses were on rise, and visibility of Parikarma was almost disappeared from newspapers and television channels. It was such a situation that any strong man would fall apart. He would have surrendered himself in front of such grave situation. But in front of the desire to live, Ashish fought with this deadly disease with courage and faith in almighty and ultimately defeated the disease and returned back to home in March 2018. Ashish underwent chemotherapy, spinal taps, surgeries, blood and platelet transfusions, and life-threatening procedures. After treatment of approximately one year,

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Ashish not only recovered from the cancer but also took charge of Parikarma Events again. Ashish says that cancer gave him a new perspective on life. Cancer gave him the chance to live his life in the moment, with objective. After two years, by March 2020, though Ashish was still not able to recover fully but brought up his dream company Parikarma on the right track. Though the damage which had happened could not recovered, but Ashish tried his level best to recover seventy percent of his clientele back. Though still he was taking medicines and regularly going to doctors, but perhaps he was left destined to fight, fall, and stand still.

3.2 About Parikarma Events Parikarma Events is one of the India’s leading event management companies located in Chandigarh, North India, but has been offering services at Pan-India Level. It was established by Ashish Kalra in 2011. Ashish had a team of young employees who laid the foundation of Parikarma with an objective to make people’s events spectacular and that is at an affordable price. Prior to setup Parikarma Events, Ashish had an experience of approximately two years in the line of ‘Tent and Catering’ with plentiful contacts and works to boast about. Though initially Parikarma handled social events such as weddings, birthday, and religious ceremonies but later offered plethora of services such as Corporate Events, Destination Weddings, Venue, Theme Decor, Entertainment, Photography, Catering, Hospitality, Promotional Roadshows, Bridal. Since inception, Parikarma belonged to the field of mass communication and journalism, therefore, it had an upper hand in technicality. By keeping himself technically update, Ashish always focused on perfection while working in each and every field. All the staff members at Parikarma did not left any stone unturned to offer world class services to their clients. In short, what is expected from a good event management company, Parikarma offered. Parikarma helped in organizing a number of events that an organization or individual may be interested in hosting. From personal ceremonies, celebrations, inaugurations, product launches, product presentations, conferences, seminars, workshops to national and international level events, Parikarma organized successfully.

3.3 The Vision and Philosophy Entrepreneurship is said to be the pillar of a nation’s economy and the order for the wealth of its budding enterprises. Entrepreneurship is at the core of business community and industrial existence (Carland and Carland 1997). The entrepreneur is one who initiates the process of economic growth and facilitates the inputs and outputs of the economic system (Singh et al. 2018).

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Effective entrepreneurship is all about visualizing and dreams and possibly even a sprint of irrationality (Hennessey 1998). Successful entrepreneurs found to devote most of their creative time in out of the box thought process and findings solution for the problems faced by consumers or general public (Howell and Avolio 1993). They perceive the ecosphere what it should be, not what it is. They think beyond boundaries and give shape to their ideas. The great idea that pushed the Wright Brothers to create a flying machine to the irrationality that motivated Bill Gates to shape advance computers is the sole of true entrepreneurship (Singh et al. 2012). The main reason to establish Parikarma Events was to offer one-stop solutions to all event management needs in India in cost-effective and timely manner without compromising to the quality. Parikarma Events always worked dedicatedly with a vision to help customers celebrate their events in best possible manner. Parikarma believed in clients’ satisfaction and long-term association. Therefore, even their vision envisaged that every event undertaken has to be perfect social, technical, and creative fit with their 360-degree collaborative approach (Low and Macmillian 1988).

3.4 The Innovations and Experiments Business competition can be severe in those market places where either traders have been continuously inventing and implementing new ideas or consumers’ spending has gone down. He brought up following innovations and experiments in the company: (i) Be the best Paymaster Ashish knew from his Tent and Catering business that salary is unquestionably one of the most significant motivators for the modern employees. He considered employees as an asset and understood the significance of keeping them happy and operating at peak performance. He always made certain that his workforce is always engaged, appreciated, respected, and acknowledged, and benefits such realized are sustainable and incredibly high. Therefore, along with paying handsome salary, he took care of their safety and well-being. By providing timely training and development programs, he ensured that his staff is always updated with market changes and technological adaptions. (ii) Know your customers (KYC) Customer expectations are tend to change with the change in technology and passage of time. So, devise methods to understand the consumers’ changed likings and disliking. Know what today’s customers want. Are the price sensitive or quality conscious, overall presentation or something else, an event manager must know before the conduct of an event. Therefore, Ashish did not give his customers any reason to shop around or consider switching to a competitor. He and his staff created culture to consider all the touch points customers have with them before booking of an event and during the conduct of the event. Ashish went one step ahead from its

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competitors when he realized that what matter most of the customers at present may change over time. So his R&D staff looked after to visualize those needs and address them. (iii) Differentiation Differentiation allows event mangers to offer great value to clients and at a reasonable price, near to his place of requirement, resulting in enhanced profitability and sustainability of your trade. In the line of event management though majority of clients are interested in the quality and presentation of your event’s content and the networking potential, they are also looking for surprising experiences. Whether it is about enjoyment, originality, or awesomeness, to differentiate himself from the competition, Parikarma always designed the emotional layer to each and every event irrespective of its size. For instance, to get his attendees to engage in different experiences, Parikarma set up non-traditional event venues, such as rural settings, local culture, vineyards, or open spaces which are difficult to think in metro cities. (iv) Mixing creativity with fun and craftsmanship Apart from providing differentiation, unique environments, and experiences, Parikarma always planned a series of remarkable dynamics. To make clients’ event stand out from others (so that people should applause the experience and recommend it to their nears and dears), Parikarma intertwines the feedback, knowledge, and interaction sessions with some fun activities. For instance, one could plan a craftsmanship workshop or a wine degustation. These unusual dynamics are capable to transform one’s event into a memorable one and make guests want to attend the next edition. (v). Event goals At Parikarma, Ashish made it necessary that before locking any business deal, efforts should be taken to understand their needs first and offer them customized needs that match their needs and come in their budget. Therefore, staff must first define the goals of the underlying event and: . . . . .

Collect feedback after each project or event accomplished Conduct one to one workshops for existing clients Boost each other’s morale Gain new customers Know customer’s intention to hold an event.

Further, in order to define the event’s goals, Ashish created a four-point strategy to follow: Parikarma four-point strategy 1. Identifying audience Know your audience Is the event has the potential to attract new customers? How many attendees are expected and would it serve a training session for existing employees? (continued)

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(continued) 2. Defining content

What are the projected takeouts? Do we educate or inspire attendees about specific products and services? Can an event may substitute employees a training platform?

3. Organizing event

How does the event align with Parikarma’s objectives? List down the short and long-term goals for organizing an event? Establish uniqueness and recognize hard working employees by due recognition

4. Measuring goals

How many leads did you generate? What is actual ROI? How and when it require cost–benefit analysis?

Source Created by authors on the basis of inputs provided by the company.

(vi) Supply Chain Management For having effectiveness of supply chain performance, it is imperative to understand the upcoming market trends with regard to consumer demand, customer service, mode and availability of transport, pricing, and general market trends such as packaging and presentation of goods during transit. All these aspects tend to change frequently and occasionally unpredictably, and hence, an organization must comprehend this reality and be equipped to structure the supply chain consequently. But appropriate structuring of supply chain needs an in-depth understanding of the competitive patterns, demand trends, service-level standards, distance considerations, cost elements, and other associated factors. (vii) Little Management Little management is the process by which the activities of an event are distributed or delegated to various teams as per their caliber and interest profile. From ‘Tent and Catering’ business, Ashish learnt that in order to progress in event management, company should have management layers as few as possible. Therefore, in Parikarma, he changed his role from hierarchical overlord to a serving leader who gives staff experience and shares information. (viii) Social innovation Event management employees know how to be more inventive and client focused. By connecting them more in organizational strategy, they experience more connected which impacts their commitment and dedication. Ashish made the most of the innovations and thoughts of their employees. It worked well. When employees found their work directly impacts the performance of the company, they felt a sense of pride which impacted their work engagement.

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3.5 Inculcating Culture Change at Parikarma: The Ashish Style Successful entrepreneurship warrants inspiration, dedication, leadership, innovation, focus and over and above, perseverance (Finkle 2006). Sometimes entrepreneurs are born, sometimes they are made. While some people become entrepreneurs because they see it as an obligatory journey to take. Adversities forced them to jump into parental business. Ashish is not an exception. His family circumstances forced him to join family business. Though initially he worked half-heartedly but later having no option to come out, he decided to consider it the destiny and do excel in the ‘Tent and Catering’ business. In 2011, when Ashish incepted Parikarma Events, he followed ‘line organization structure’ like other event management companies. Therefore, he appointed general manager to report to him for the day to day activities. Though the organization was moving in right direction, in terms of revenues and customers’ order, but Ashish realized that Parikarma was caught in a bureaucratic tradition. There was lack of coordination, communication, initiative, and specialization among staff members. There was also a lack of grooming the new employees for taking up important work. Hence, Ashish replaced line structure with lean structure which was committed to its clients and works to reduce waste by focusing all of its resources on serving the best possible value for its clients. Similarly, as per established rule, the staff especially marketing staff was expected to follow a particular dress code while on duty. Staff was not supposed to wear any type of jeans and casual clothes. Understanding the employees’ unspoken reservation, Ashish changed the dress code manual and made it just, “Dress appropriately.” This way, Ashish tried to amend or withdraw any rule and regulation that hampered the growth of his employees. He developed a system where each employee could approach to his high-ups as and when required. Besides this, he created a culture where in case of any mishap to his employee during the job, provisions were made to compensate in best possible way. Be it giving paid leaves or work at home, everything was no possible under Ashish leadership.

4 Leadership and Management Style Peers recognized that Ashish demonstrated all the necessary traits of an exemplary leader. He had remarkable qualities of entrepreneurship, resourcefulness, resilience, inventiveness, and ingenuity. He always emphasized creativity, expansion, and collaboration. He considered every event a business opportunity. Ashish had an exceptional set of interpersonal skills that differentiated him from others. Ashish focused customers’ satisfaction as an ultimate motto of Parikarma. He relied on team building initiatives, time management skills and emphasized on collecting feedback and keeping criticism and consumers complaints to nil. Describing Ashish’s

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leadership style, Mr. Singh, Parikarma’s General Manager, who is associated with Parikarma for more than 11 years in different capacities, said “Ashish is multi-talented and self-starter who always puts several hats at the same time—he is a creator, risktaker, project manager, a finance manager, a marketer, a serving boy. And that is not all.” Even his competitors admit that Ashish is a risk-taker, innovative, and possess unique mind-set that enable him to win bid bids and managing diverse teams.

4.1 The Transformation Entrepreneurs are said to be crazy individuals. They locate and exploit opportunities. They invest their personal resources, create employment, and contribute in national building initiatives (Fiet 2001). This creates public wealth and permits individuals to derive value from the entrepreneurial success and mushrooming businesses. The pooled capital generated such way is imperative for economic development of a nation (Mair and Marti 2006). In 2015, Ashish made it mandatory for entire permanent staff to go for periodical training to enhance their skills and update with latest technologies. This helped Parikarma to face and prepare itself for upcoming challenges. But differing to expectations, initially Ashish confronted enormous disapproval as majority of his employees objected to attend training program. Secondly, his resolution to bring ‘performance-based appraisal system’ for annual increment and career growth was unwelcomed. Initially, all of his managers and employees informed him to stop work and later go on long strike as viewed it as an instrument of firing non-performing employees and staff. All of his efforts to convince employees to introduce ‘performance appraisal’ for the betterment of the employees went in vein. Neither the managers nor employees were able to have meeting on the said topic. Due to this disturbance, Ashish lost 2–3 precious business deals also. So Ashish changed his strategy and tried to convince his managers on ‘one to one’ basis. The strategy worked well. He was able to win confidence of most of his managers that performance appraisal of employees will save their valuable time, reduce conflicts, ensure efficiency and consistency in performance. Convinced managers were able to convince their departmental employees for not opposing the company’s new initiatives. Side by side, Ashish also convinced multiple times in each and every meeting that it is not to punish non-performers but to improve their performance, development, correct deficiencies, career growth, and unbiased promotion, they allowed to do this experiment. And ultimately Ashish was successful in proving that ‘performance appraisal’ is just like an employee report card depicting how one has been performed during the past year and nothing else. Within two years, all felt contented and contributed with great zeal and honest dedication. Business cards are part of the branding exercise that marketers take up to beat the competition (Singh et al. 2018). Therefore, even in the computer age, Ashish provided well-designed business cards to each and every employee with his or her name, irrespective of their designation. Strategy worked well and helped in increasing

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revenues due to the power of personal networking. With such solid networking plan, Parikarma built very strong brand identity and a huge chain of personal relationship in very short span of time. As a next step in its makeover plan, Parikarma created R&D division and recruited some professionals offering secretarial services, managing social media campaign, competitors’ analysis, collecting feedback and to conduct post-event market research. Their work also involved considering at the potential of the market and seeing where Parikarma could venture in the future. Research showed that the brand ‘Parikarma’ was synonymous with ‘trust and quality’, and the comprehensive portfolio of products was seen as a source of its marker strength.

4.2 The Rise of Parikarma

Fig. 1 Parikarma’s key success factors. Source Created by authors on the basis of inputs provided by the company

"Parikarma's Elements of Event Planning"

Passion to always stay ahead and moving next step on corporate ladder keep entrepreneurs moving and visible. This tendency to stay ahead and staying in limelight persuade budding entrepreneurs to build dreams and working toward excellence (Stogdill 1998; Van Knippenberg et al. 2005). Though there is no short cut or full proof strategy to stay tuned, but this so-called inner motivation helps others to stay motivated and achieving goals (House 1977). Ashish implemented a hands down approach for growing business. He firmly believed that every kind of event (big or small) needs a proper plan, process, and attention to achieve organizational goals. Hosting an event is always a challenging task until it is not over. Therefore, from his experience and with the help of R&D division, he created an eight-point strategy to make any event a gala success (Fig. 1). For most event management companies like Parikarma, networking was always at the top priority in terms of developing a strong client base. In Parikarma, Ashish emphasized on strong networking which helped Parikarma in two ways. First, if people have met him and know what Parikarma is meant for, they could refer his company to others. Secondly, networking with hotels, caterers, printers, transporters

1. To know the purpose of the Event 2. To know your audience 3. Selecting venue that suits event not your company 4. Irreversible and Immutable 5. Prepare a blueprint of the plan anf follow timeline strictly 6. Create content that attracts target audience and suits the event 7. Design the message to share that you value your attendees 8. Plan how to capture leads of potential prospects

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helped, Ashish and his company to seek their assistance whenever their services were required. Ashish also made virtual contact with hundreds of vendors that helped in expanding his business tremendously. By 2017, Ashish also started holding international events and spread his business in every part of the country. His plans worked well, and hence, he effectively forayed into bid for government and multi-national tenders for conducting events of repute.

4.3 The Fall of Parikarma Ashish was very successful in his event industry and was instrumental in organizing some large events of Northern India. Under his able leadership, Parikarma Events was able to achieve growth due to the quality of its services and unbelievable hospitality. Once asked by Media that what is the secret of your success, he replied “I’ve relied only on clientele feedback and satisfaction surveys. Both have been valuable for my start-up, helping me gain a better understanding of clients’ requirements and concerns.” By closely monitoring customer feedback and satisfaction surveys, Ashish improved and altered his products and standard of services. It resulted in customer loyalty and protecting revenue and profitability. With rising profits and fall in customers’ complaints, Ashish thought of opening branches in other parts of the country so to cater diverse and remote clientele. But then it all came crashing down a sudden when he got hospitalized and diagnosed with kidney cancer. In August 2017, he had to move to hospital for his first set of chemotherapy treatment. He had to spend days in bed, and the situation around him was perennially gloomy. Physically Ashish was and most of the times bedridden. Though there was general manager and other operating managers were there to look after his business. But event management is a business where you have to be active 24 × 7. Employees are concerned with only their working hours and nothing else. Parikarma’s revenues declined sharply. Though in March 2018, his father stepped into the business and started handling Parikarma Events. But it was too late. By that time, business had collapsed. Parikarma did not organize any major event in the first quarter of 2018. Be it print media or local TV channels, there was no visibility of Parikarma. Most of his key employees left the company and joined competitive firms. While some of employees opened their firms on the lines of Parikarma. Ashish was so unlucky that his insurance lapsed one month before he was diagnosed with cancer. He had to spend all his savings on his treatment.

4.4 The Rise from Fall of Parikarma At 5.10 ft tall and weighing 75 kg, Ashish always had an infinite energy and an unwavering self-confidence and self-reliance. But due to kidney cancer, he dropped

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more than 20 kg and was often too exhausted to sit up for more than an hour at a time. He was reduced to consuming a liquid diet, and that took him hours to take. Doctors threatened to interfere medically by putting a tube into his stomach to feed him externally if he did not start to gain weight. From August 2017 to June 2019, he was either hospitalized or at home under medication. During this period, he was very weak and most of the hours, bedridden. Ashish did not know that he would survive or die, but he decided not to surrender. He accepted that he could be physically beaten down and defeated, but for his family, for his company, he would keep his attitude positive and upright. Ashish admitted, “It was an extraordinarily gratifying thing to learn,” but “it was an unreasonable painful lesson of his life.” But in his hard time, so many people (many unexpected) came forward and offered their help and support. And then an inquisitive thing began to happen. Ashish recognized that while there was nothing he could do about the desolation his body was experiencing, he had full control over his emotions. Along the way, he raised a family—a son and a daughter, now 9 and 7, respectively—and developed a wide circle of friends. Quitting, he said, has just never been in his nature. His children, wife, parents, friends—all of them have seen Ashish battling cancer and have been the best support he could have asked for. Though on bed, in July 2019, Ashish signed up clients through video calls or FaceTime. His family, his brothers, his parents, his wife, and kids were rock solid behind him and looking forward to a fresh lease of life. Failure is a part and parcel of business. Only few entrepreneurs ever make it big without initial experiencing some considerable failures (Clark and Oswald 1994). Whether it be ruining an established business into the ground, losing cliental, or even going to jail, a number of successful entrepreneurs have seen enormous failures before ever achieving their goals. But Ashish was an exception. He failed because of his bad luck! When he did not want to be an entrepreneur, adversities forced him to do so, and when he decided to stay standstill, adversities forced him to go away. But where was he to give up. In the last week of August 2019, Ashish got discharge from the hospital. As advised, he took bed rest for one more week, and then in September 2019, he joined Parikarma after approximate two years of first hospitalization. Things were entirely different at Parikarma. It had a deserted look. Ashish realized that a lot of his employees used to get scared when they got to know that Ashish had cancer and still under medication. But Ashish could not do anything about it except dreaming that he could hug them and tell them that, “I’ am okay!”

4.5 The Way Ahead It is a proven fact that the path to entrepreneurial success is often exciting but very worthwhile (Baldoni 2005). Having right attitude, focused goals, working hard are

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all indispensable aspects of being staying ahead in corporate race. The strong relationship Ashish had developed in his good times with the key people in the industry worked well and played vital role in getting his lost orders and events to some extent. Ashish’s future challenge would lie in attaining sophisticated scale of business operations. His short-term challenge will be to gain previous cliental vis-à-vis to rehire boomerang employees as they are already familiar with the culture of the company and do not require as much training as new hires. Besides this, he/she may have gained new skills, experience, and perspective while working outside the Parikarma. Though it seems difficult in the present circumstance but with the precise strategy and a focused approach to employees and cliental, there is no reason why Parikarma cannot add opportunity and scale to their operations.

5 Conclusion and Recommendations i.

ii.

iii.

iv.

v.

The essence of entrepreneurship is rise, fall, and then rise from the adversities. Entrepreneurs should remember that the entrepreneurial path and struggle are not smooth. A business has to pass through various litmus tests before proving itself worth-while. The obstacles and road barriers though stop you to moving ahead but you will have to stay adamant. Sooner or later, you will realize that this bad phase was also temporary. You just need to stay calm and work for overall development. Sharpening personal and entrepreneurial skills to face adversity is what will keep your business moving (Pierre et al. 2014). The findings also entail unique qualities of an entrepreneur that every individual in his entrepreneurial journey experiences (such as risk-takers, self-motivated, unique thinking, time management). But only few achievers accept that this is just a rite of passage on the road to accomplishment (Leith et al. 2012). The approach with which Ashish joined his company after recovering from cancer and was successful in achieving 40% of his lost cliental, findings justify and support the findings of the previous studies (Singh et al. 2018, Stogdill 1998) that if the vertical climb to success seems intimidating, make it easier by taking small steps and having a plan to follow helps you stay focused when times get tough. Previous studies are also in align with the present findings and emphasize that entrepreneurial framework and the ‘never give up’ attitude of an entrepreneur are indispensable for the continuity and growth of effective entrepreneurship (Singh and Aggarwal 2013, Cacioppe 1998 and Van Knippenberg et al. 2005). The present study moves one step ahead and provoke the importance of ‘successionplanning’ in family entrepreneurship to thwart any uncertainty of a firm (Kuratko 2005). Besides this, ‘keeping your spirits high’, ‘don’t let failure floor you’, and taking small and one step at a time especially when tie gets tough are approving. Uncertainty, sudden challenges, and facing tough times are natural in each and every entrepreneurial journey and, therefore, should be talked with boldness and promptness.

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References Baldoni J (2005) Motivation secrets: great motivation secrets of great leaders, Online Edition. Available on http://govleaders.org/motivation_secrets.htm Cacioppe R (1998) An integrated model and approach for the design of effective leadership development programs. Leadership Org Dev J 19(1):44–53 Churchill GA (1999) Marketing research: methodological foundations, 7th edn. Dryden Press, USA, Fort Worth Clark AE, Oswald AJ (1994) Unhappiness and unemployment. Econ J 104:648–659 Déjean P, Gond J, Leca B (2004) Measuring the unmeasured: an institutional entrepreneur strategy in an emerging industry. Human Relations 57(6):741–764 Fiet JO (2001) The pedagogical side of entrepreneurship theory. J Bus Ventur 16:101–117 Finkle (2006) Corporate entrepreneurship theory and practice. J Manage Theory Pract 2(3):13–22. ISBN 716-7089 Gaglio CM, Katz JA (2001) The psychological basis of opportunity identification: entrepreneurial alertness. Small Bus Econ 16:95–111 Harjit S (2012) Tupperware: achieving sustainable development goals through elevating socioeconomic status of women in India. Int J Bus Perform Manage. https://doi.org/10.1504/IJBPM. 2012.044862 Hennessey JT (1998) Reinventing government: does leadership make the difference? Public Adm Rev 58(6):522–532 Hersey P, Blanchard K, Johnson DE (2001) Management of organizational behavior, 8th edn. Prentice Hall, Englewood Cliffs, NJ, USA House RJ (1977) A 1976 theory of charismatic leadership. In: Hunt JG, Larsons LL (eds) Leadership: the cutting edge. Southern Illinois University Press, Carbondale, IL, pp 189–207 Howell JM, Avolio BJ (1993) Transformational leadership, transactional leadership, locus of control, and support for innovations: key predictors of consolidated-business-unit performance. J Appl Psychol 78(6):891–903 Katz D, Kahn RL (1978) The social psychology of organizations, 2nd edn. John Wiley and Sons, New York, NY Kihlstorm et al (1979) A general equilibrium entrepreneurial theory of firm formation based on risk aversion. J Polit Econ 87(4):719–748 Kumar N, Stern LW, Anderson JC (1993) Conducting inter-organizational research using key informants. Acad Manag J 36(6):1633–1651 Kuratko DF (2005) The emergence of entrepreneurship education: development, trends, and challenges. Entrepreneurship Theory Pract 29(5):577–598 Leith et al (2012) The development of entrepreneurial leadership: the role of human, social and institutional capital. https://doi.org/10.1111/j.1467-8551.2011.00808.x. www.onlinelibrary. wiley.com Low MB, Macmillian IC (1988) Entrepreneurship: past research and future challenges. J Manage 14(2):139–161 Mair J, Marti I (2006) Social entrepreneurship research: a source of explanation, prediction, and delight. J World Bus 41:35–44 Murphy et al (2006) A conceptual history of entrepreneurial thought. J Manage History 12(1):12–35 Pierre et al (2014) Rise and fall of the Lyon silk cluster: a case study about entrepreneurial sustainability. Entrepreneur Sustain 2(1):1–11 Singh H, Aggarwal N (2013) Achieving sustainable development goals through elevating socioeconomic status. Compet Rev 23(4/5):398–407. https://doi.org/10.1108/CR-04-2013-0042 Singh H et al (2018) Leadership and entrepreneurship: a case of Redhill Herbals Pvt. Ltd. Serb J Manage 13(1). https://doi.org/10.5937/sjm13-13334 Stogdill RM (1998) Personal factors associated with leadership. J Psychol 25:35–71 Van Knippenberg B, van Knippenberg D, De Cremer D, Hogg MA (2005) Research in leadership, self, and identify: a sample of the present and a glimpse of the future. Leadersh Q 16:495–499

Industry 4.0—Its Advancement and Effects on Security of Whistle-Blowers on Dark Web Anita Venaik, Shourye Jain, and Anand Nayyar

1 Introduction The dark web is the World Wide Web page that exists on darknets: It overlays networks and makes utilization of web unlimited with its vast scope of exploration Through the dark web, private straphanger organizations can convey and direct business secretly without unveiling distinguishing data, like a client’s area, its fund flow, and many more. The dark web frames a little piece of the profound web, a piece of the online data not recorded by web crawlers, albeit now and again the term profound web erroneously wants to allude explicitly to the dark web. The darknets which establish the dark web incorporate little, companion to-companion distributed organizations. Additionally it is huge and enormous and connected to mainstream network makes it vulnerable too. Clients of the dark web ask the ordinary web as Clearnet because of its decoded nature. The Tor dark web or Onionland utilizes the traffic anonymization strategy of onion steering under the organization’s high level area addition in its unaffected zone. In the paper of Kaur and Randhawa, published in January, an overview of dark web and various browsers which are used to access dark web are presented. An insight into various aspects of dark web such as features, advantages, disadvantages, and browsers is discussed.

A. Venaik (B) · S. Jain Amity University, Noida, Uttar Pradesh, India e-mail: [email protected] A. Nayyar Graduate School, Duy Tan University, Da Nang, Vietnam © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_6

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1.1 Bitcoin Administrations Bitcoin administrations like tumblers are regularly accessible on Tor and many other online sections—like Grams. As per Jean-Loup Richet, a pursuit individual at ESSEC Bitcoin, individuals can shroud their goals likewise as their character. A standard methodology was used to utilize a computerized cash exchanger administration which changed over Bitcoin into a web game cash (e.g., gold coins in World of Warcraft) which will later be changed over back to cash.

1.2 Darknet Markets In Business world darknet is involved for unlawful actions and payments to avail any legalities and but law in dark, pulled in critical media inclusion, beginning with the acknowledgment of Silk Road Different business sectors sell programming endeavours and weapons unlawfully…the unlawful medications virtue is found to fluctuate from the information showed on their particular postings.” It uses a new technology called Onion Routing, which is an anonymous bi-directional communication between devices on Internet where the source and destination cannot be determined by third party and can never be located. A network using the Onion Routing technique is given a name as a darknet.

1.3 Hacking Gatherings and Administrations Software professionals who use unethical practices sell their solution as a neighborhood of gatherings which incorporate xDedic, hack discussion, Trojan produce, Mazarakis, darkle, and subsequently the Real Deal darknet market. Some are known to follow and coerce clear. Cyber crimes and hacking try to utilize Internet-scale DNS Distributed Reflection Denial of Service (DRDoS) through dark web. There are numerous tricks. Onion locales are additionally present which end up giving devices for download that are tainted with deceptions or indirect accesses.

1.4 Financing The president Scott Dueweke father of Zebryx Consulting states that Russian electronic cash like Web Money and astounding Money are behind the main part of the illicit activities. In April 2015, Flashpoint got a 5-million-dollar venture to help their customers assemble insight from the deep and dark web. In this world of dark web the people use unethical practices to administer various jobs unethically. The insight

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into the profit margins are huge as aim is to earn illegally report distinguished 12 classes of instruments or administrations that would introduce a danger inside such an organization break or information bargain. Disease or assaults, including malware, circulated disavowal of administration (DDoS), and botnets. . . . . . . . . . . .

Access, including far off access Trojans (RATs), keyloggers, and endeavors. Undercover work, including administrations, customization, and focusing on. Backing administrations like instructional exercises. Qualifications. Phishing. Discounts. Client information. Operational information. Monetary information. Licensed innovation/proprietary advantages. Other arising dangers. The report additionally sketched out three danger factors for each class:

. Cheapening the venture, which could incorporate sabotaging brand trust, reputational harm, or losing ground to a contender. . Disturbing the venture, which could incorporate DDoS assaults or other malware that influences business activities. . Cheating the endeavor, which could incorporate IP burglary or reconnaissance that hinders an organization’s capacity to contend or causes a prompt misfortune. Ransomware-as-a-administration (RaaS) packs are accessible on the dark web for quite a long while; however, those contributions turned out to be substantially more perilous with the expansion of criminal gatherings like REvil or Grand Crab. These gatherings build up their own complex malware, at times joined with prior instruments, and disperse them through “subsidiaries.” The subsidiaries circulate the ransomware bundles through the dark web. These assaults frequently incorporate taking casualties’ information and taking steps to deliver it on the dark web if the payoff is not paid. This plan of action is fruitful and worthwhile. IBM Security X-Force, for example, detailed that 29% of its ransomware commitment in 2020 included REvil. The criminal gatherings that built up the malware get a cut of the subsidiaries’ income, commonly somewhere in the range of 20 and 30%. IBM gauges that REvil’s benefits inside the previous year were $81 million.

1.5 Cause of Term U.S. Metropolis dissident Ralph Nader is professed to have begat the adage; however, he placed a fine turn on the term in the mid-seventies to keep away from the terrible

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meanings located all in all like “supply” and “nark.” Be that as it can, the roots of the phrase go back to the nineteenth century. The word is attached to using a whistle to alarm popular society or a set of multiple lousy instances, just like the fee of a criminal offense or the disrupting of norms during a sport. The expression informant linked itself to authorization authorities in the nineteenth century because they utilized a whistle to caution the general population or character police. Sports refs, who make use of a whistle to factor an unlawful or wickedness, likewise were referred to as informants. An 1883 tale within the Janesville Gazette referred to as a police officer who utilized his whistle to alarm citizens more than one mobs an informant, without the hyphen. Constantly in 1963, the expression had turned out to be a hyphenated word, informant. The word started out to be used by columnists in the 1960s for individuals that exposed terrible conduct, as Nader. It in the end developed into the compound phrase informant.

2 Literature Review 2.1 The Effect of the Dark Web on Web Administration and Cyber Security Profound web means a grouping of substance on the web that, for various reasons, is not recorded through web lists. The dim web may be a piece of the profound web that has been purposely concealed and is closed off through standard web programs. A by and large known focal point for content that harps on the dull web is inside the Peak association. Pinnacle engages customers to cross the online in close absolute lack of definition by encoding data bundles and sending them through a couple of association center points, called onion switches. Like any advancement, from pencils to cells, haziness is oftentimes used for both extraordinary and horrible. Customers who fear financial or political requital for their exercises address the dim web for cover. Dark web for the criminals, for undergoing various criminal activity like drug trading, extortion, blackmailing has become a big norm these days. Taking into account that the dull web contrasts from the conspicuous web, it is fundamental to make instruments which will satisfactorily screen it. Confined noticing is oftentimes refined today by arranging the covered organizations’ library, customer data checking, social site noticing, disguised help checking, and semantic assessment. The profound web might potentially have an unavoidably high number of malignant organizations and activities. The overall multi-accomplice neighborhood ponders its impact while inspecting the more broadened term of web organization. In his advancement inside the Clash of the Persian Entryway in 331 BC, Persian officers on one or the other side down-poured stones and darts down on the interlopers. The Macedonians persevered through considerable misfortunes, losing entire organizations, and needed to pull out.

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To outline entire strategies and preparations for overseeing the web, it is miles critical to recall reviews on its farthest reaches—the deep dark web. This paper attempts to supply a greater tremendous comprehension of the dark web and its impact on our lives. Twitter, Facebook, and WhatsApp were the command-and-manipulate organizations of choice for mental militant and lawbreakers. Hannigan’s assertions were the various finest disparaging of Yankee innovation firms with the aid of the very best point of a true perception and, greater essentially, an inside and out accomplice. “The allegation went past what US government has said to date stated about Apple, Google, and so on, which are currently advancing closer to present-day encryption of increasingly data on telephones and email frameworks. This disclosure became firmly trailed through a function of protection submit by means of Facebook advising clients that it is currently facilitated straightforwardly on the Tor organization.” The Tor join—https://facebookcorewwwi.Onion/—was portrayed greater as an examination via the company, to empower it to discover over the longer term through giving an onion address1 to Facebook’s flexible web site. Unexpectedly, Facebook is the major US tech goliath to supply reliable help for Tor, a corporation worked to permit residents to ride the net without being followed and distribute content material that likely will no longer seem in regular net indexes. Hannigan’s comprehension of the way the coupling of Internet-based media and along these lines the darkish web may want to make very floor-breaking, encoded, decentralized and unknown purposeful publicity networks for psychological militant associations may want to likewise be what provoked him to training session. The new flood inner the quantity of European nationals thoughtful to or efficaciously helping institutions like ISIL or al-Qaeda in Syria and Iraq is unquestionably a massive explanation for pressure for Western famous governments. Online media ranges have substantiated themselves large enrollment instruments for missions, the entirety being identical. It is far of little surprise, at that factor, that recently, worry-based totally oppressor bunches like alQaeda and ISIL have effectively applied Twitter to enlist volunteers and circulate in supporting their motivation. The reason is evidently to “humanize” the improvement and phone greater full-size crowds. Past promulgation, the Internet lets in gatherings to unfold facts in new and inventive manners. Khan Academy to help kids round the world research math and technology have additionally given mental oppressor bunches extraordinary strategies to talk about and scatter techniques, methods, and techniques. Plans for explosives are directly accessible at the Internet, and dread gatherings have utilized the net to proportion plans for advert libber touchy devices quickly across battle zones from Syria to Afghanistan. The apparent aspect of the web includes locations with a purpose to be located through a general pursuit, at the same time as the imperceptible aspect—the deep web—incorporates locales or groups that cannot be gotten to by customary techniques. This includes information units, scholarly diaries, personal organizations, and so on. The more part of the substance located within the deep web exists in web sites that need an enquiry that is not verifiably illegal. Nonetheless, an extreme inquiry will find the dark web. The darkish web is probably a touch segment of the deep web that has been purposefully blanketed up. The dark web is the section of the deep web that has been intentionally covered up and is blocked off via well-known Internet customers for whom obscurity

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is extensive, seeing that they deliver assurance from unapproved customers, yet in addition normally contain encryption to end checking. A surprisingly regarded hotspot for content material that lives on the darkish web is determined within the Tor company. The Tor network is a mysterious enterprise which is probably gotten to with an outstanding software, referred to as the Tor program. First regarded due to the fact that the Onion Routing challenge in 2002 via the USA Naval lab, it has been a path for conveying on the Internet namelessly. Another employer, I2P, offers big numbers of an equal detail that Tor does. Web, with traffic last contained in its lines. In any case, I2P which becomes intended to be an organization within the I2P gives a more powerful and reliable community within the agency. Silk Road changed into an Internet industrial middle that tended to stash medicines, opiates, and guns. US Federal Bureau of Investigation gets together the Internet web site. However, tons similar to the legendary Hydra, the Internet site restored as Silk Road 2. Going inside the problem it took months together to understand and evaluate the problem are and searching the intruders is a challenging job for the law makers. It took the FBI one greater 12 months to observe down its chairman and employees. It should try to be noticed that Tor engages any person who desires electricity over their online impression. The effective estimation of such an equipment is giant for a couple of gatherings, like informants who document information that groups would possibly need to smother, common liberties laborers combating toward harsh governments, and oldsters trying to make a secure direction for his or her youngsters to investigate at the Internet.

2.2 Threat and Opportunities on the Dark Web 2.2.1

Dark Web Ethnographic Ways

An ethnography of a dark web has been some methodological problems. The dark web looks similar to web, but amazing it is not so, It is unpredictable and vast too. The darkish net is a part of the net that cannot be gotten to by using standard programming. It contains shrouded locales that end in “. Onion” or “. I2p” or different Top-Level Domain names just accessible through adjusted packages or particular programming. Getting to I2P locales calls for a unique guidance software. Getting to non-wellknown Top-Level Domains through Open NIC calls for the client to differ the DNS employee addresses on their transfer. Getting to . Onion destinations requires Tor (for an academic exercise on Tor and . Onions (Hoffman 2012)). Besides, people who run dark web sites that result in . Onion is organized to hide their personalities and regions from maximum, if no longer all, Internet customers (Dingledine et al. 2004). Much of the time, a guest to a . Onion web site online will no longer have a clue about the persona of the host, nor will the host recognize the character of the guest. That is often definitely exclusive from the same old Internet, where locales are often diagnosed with an enterprise or place (e.g., google. Com is related

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with the company settled in Mountain View, CA), and guests are frequently diagnosed and discovered through diverse following improvements like treats, account enlistments, Flash treats, IP places, and geolocation. Albeit these specialized situations try for ethnography, they are not superb inside the ethnographic writing. While taking it seriously it is not a perception but a reality too that dark web is darker than it looks from outside (Boellstorf’s 2008). Boellstorf’s calls for Second Life on its personal terms; he attempts now not to interface Second Life symbols to their “proper international” companions to have practical enjoy in regular life in that digital global. He regards Second Life as its own area, with its very own ideas and lifestyle, instead of as expressed with “this gift fact” outside of the virtual. That is frequently a methodological decision of Boelstorf’s, as in opposition to crafted by, as an example, Dinah Boyd (intrigue), who considers web-based media clients each at the net and disconnected. As a common man one feels he is probably involved in cyber crimes through dark web. During this feel, I targeted at the management and association elements of the location in much a similar way as Lovink’s (2003) investigations of the Amsterdam Digital City and nettime (however with no disconnected contact with DWSN people). That is, I interested in member perception, zeroing in at the crossing factor between web site layout and component sports within the vein of advanced ethnography as elucidated through, tuning in to “one-of-a-kind edges of have a look at, records, and consequently the nearby settings and lived encounters of computerized media” (p. 488). The major possibility is that dark web makes world more darker. Although the exacting namelessness of the DWSN limited the quantity of my paintings (in that I changed into unable to invite DWSN individuals disconnected), an ethnography of any SNS should also be engaged. Despite being less open than “clean Internet” SNSs like Facebook or Twitter, the DWSN has indicated evidence of improvement on account that it is establishing in 2013. During my belief of the area over a time of 10 months, the DWSN’s range of facts advanced from 3000 to extra than 24,000, with more than 170 gatherings, many weblog entries, and a big range of miniature weblog entries. Albeit these are not numbers on the dimensions of Facebook or Twitter, they are noteworthy, if locating the DWSN is truly not an easy remember of Googling for it. More to the motive, it very well may be difficult to look at or talk with a huge range of people. To center my examination, I searched for focal points (or “instructions,” as might call them) with which to enlighten sports at the DWSN. The two if abuse are pressure and opportunity. To begin with, there is the origination of the darkish net as absolutely crafted from illegal or no-no physical activities and desiring policing. Second, there may be the concept the darkish web can protect an esteemed liberal opportunity: the proper to speak freely of discourse. Accordingly, what shows up at some stage in this media philosophy is probably a “proportional and contrary” connection among pressure and possibility. The famous media inclusion of the darkish Internet is reminiscent sentimental frenzies which might be associated with Internet culture in the route of new year’s, much like the rush about PC programmers and smartphone phreaks in 1980s (coming approximately within the seize of the numerous youthful PC customers); the USA Congress’ Communications Decency Act of 1996, welcomed on by using a moral frenzy approximately erotic entertainment at the web; and subsequently

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the Congress Deleting Online Predators Act of 2006, inspired via conviction based totally frenzies over on Myspace. Particularly for the reason that media inclusion of the Silk Road drug marketplace bust and consequently the Freedom Hosting teen pornography (CP) bust, each in 2013 (Borland 2013), the dark Internet is proper now motivating comparable frenzies fixating on apprehensions of CP, the medicine and firearm alternate, and executioners for recruit. One Sun feature is probably a progression of modifiers that dilemma the dark web with CP: “Kid sex darknet targeted on” (Wooding 2013). As a outlooker of this dark web, it takes a huge lot of efforts to learn how to use dark web for best use in the organisational growth. The darkish web is “a middle for illegal corporations that promote or deliver tablets” (Pagliery 2014). Gizmodo profiled the darkish net firearm store. The Armory, asking “Could a band of unknown weapon mongers plan me and 19 fanciful countrymen for illicit combating? On the off threat that you have an extra million around, looks like the arrangement is sure” (Biddle 2012). The Daily Mail considers Tor a “fuming lattice of encoded web sites” wherein one ought to enlist hired gunmen for US$10,000. “In this way, for those hoping to kill a difficult colleague, all they want to attempt to be enter the deep web—recognized likewise in mild of the reality that the ‘dark web’ or the ‘Undernet’—and seek ‘employed gunman for recruit’” (Mail Online 2013). Understood all through this inclusion is probably a name for extra policing of the darkish Internet (e.g., Biddle 2012; Bingham 2013; Gillespie 2013; Henry 2013; Murad and Hines 2012). Three practices at the DWSN. The DWSN has to be promptly perceived as a SNS: It takes into attention singular information, with adjustable component pages, associations via “friending,” social applause within the kind of “preferring,” and a Twitter-like miniature publishing content to a weblog framework, among exceptional highlights. As a SNS, there are nonexclusive and building barriers and affordances incorporated into the product, and these are used by executives and people to form the web site online way of lifestyles. Like different SNSs, the DWSN has terms of management (TOS) and a safety approach.

2.2.2

Mysterious/Long Range Interpersonal Communication

It is remarkable that the supported press inclusion of the dark web investigated above does not examine SNSs. SNSs, it shows up, are outside the media philosophy of the dark web. For writers covering the dark web, the possibility of dark web clients taking part in long range interpersonal communication in the nonexclusive structures was presently perceived. Various techniques used in Dark Web for Confidentiality and Anonymity of the users Both anonymity and confidentiality are the key factors based on which the dark web is purely relied upon because of the following points as mentioned. (i)

Proxy: It is a service in which the requests are collected from clients and then forwarded to the destination on the behalf of the requestors. After receiving

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the replies, the proxy sends the information back to the requestor. It acts as an intermediate between sender and receiver. For filtering and bypassing, such Internet filtering proxies can be used. (ii) Tunneling: It is well known that VPN is a most viable for network tunneling. A private network provides inter-connectivity to exchange information between various groups on VPN. (iii) Bypassing: The intruders use a mechanism in which translation of domain names to IP addresses takes place. It makes access easier. As for accessing a web site address is to be known, remaining will be taken care by DNS. (iv) Onion Routing: A new designed networking mechanism ensures that contents and data transferred on Internet are completely encrypted during transmission till it reaches to the destination. It hides identity of both receiver and the sender by providing anonymous connections. The connection takes a long route so that traceability is impossible from source to destination B on the complete encrypted chain, which is called as Onion, hidden like a mystery with several layers.

2.3 Whistleblowing Policies of Leading European Companies In the U.S., the Sarbanes-Oxley Act turned into actualized on July 30, 2002. Area 301 of SOX states: Each review board set up techniques for the receipt, maintenance, and treatment of grumblings and got with the aid of the guarantor to recognize bookkeeping, inner bookkeeping controls, or comparing matters, and along these traces, the categorized, unknown accommodation by way of people of the backer of worries with respect to sketchy bookkeeping or examining related topics. This component properly calls for systematized whistleblowing, and companies are liberal to apply these methodologies to distinctive sorts of infringement covered via sets of standard policies or morals arrangements. Area 806 of the Act shields informants from counter with the aid of giving them the possibility of valid interest after detailing an infringement of protections legal guidelines to a regulation implementation organization, Congress, or an indoor individual with administrative role. At last, Section 1107 makes counter in opposition to representatives uncovering a Federal offense (potentially) performed by the corporate to an implementation respectable, a criminal demonstration to be rebuffed with a first-rate or a restrict of 10 years of detainment. Preceding SOX, Federal informant regulations virtually implemented to the public vicinity, or to extra express sorts of infringement like ecological contamination and 26 Harold Hassink et al. Using the web browser is itself having safety feature which is missing to a larger extent. SOX is extra enormous and more forceful than those beyond rules. In the U.K., the general public Interest Disclosure Act 1998 shields each outside and inside divulgences from reprisal yet does not urge businesses to standardize whistleblowing. The review advisory organization ought to audit plans via which personnel of the corporate may additionally, in truth, enhance concerns approximately capability mistakes in difficulty of monetary revealing or distinctive

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issue. The assessment panel’s intention needs to make sure that sport plans are in situ for the proportionate and unfastened examination of such topics and for correct next activity. The Combined Code does no longer have the reputation of law; however, all U.K. Groups recorded at the London Stock Exchange are needed with the aid of the Financial Reporting Council (FRC) ”to put in writing approximately how they have carried out the requirements of the code, and both to verify that they need conformed to the code’s preparations or—in which they need now not—to supply a rationalization.” In the Netherlands, the corporation Governance Code became drafted by way of a panel lead by way of Morris Tabaksblat, the past CEO of Unilever, and became embraced on December 9th, 2003. The “Tabaksblat Code’” incorporates of fashionable requirements of extraordinary company management that Dutch recorded corporations are needed to follow, and exceptional exercise arrangements which are viewed as elaborations of those standards which they will decide to not follow. The factor of the code is to modernize Dutch corporate law and to enlarge the allure of Netherlands from a hypothesis viewpoint (Ministry of Justice 2004). The code got compelling on January 1st, 2005 and Dutch recorded corporations are legitimately had to both observe the easiest practices that are consolidated inside the code or clarify why they digress from them. Organizations that provide an all-around hooked up rationalization, affirmed by using the buyers, for rebelliousness with pleasant exercise arrangements and satisfy the basic rule in an unexpected way, are yet in consistence with the code (Tabaksblat 2003). Whistleblowing is incorporated in the code as excellent practice arrangement II.1. Asserted inconsistencies concerning the working of the executive’s board people will be accounted for to the administrator of the executive board. The guides of movement for informants will on any event be published on the organization’s Internet site. In Belgium, the Code on Corporate Governance, drafted by way of the Lippens Committee and allotted on December 9, 2004, is carefully corresponding to in construction to the Tabaksblat Code within the Netherlands. It contains 9 requirements all groups need to hang to, and arrangements portraying the exceptional method to use the requirements. Following the model of the U.K. Joined Code, Belgian recorded businesses “are relied upon to accept as true with these arrangements or make clear why, thinking about their precise condition, they may be doing now not consent”. Moreover, there are policies for expertise and usage of the preparations. These are not structured upon the “consent or clarify” framework. The code’s whistleblowing association, which is nearly tons the same as the one inside the U.K. Joined Code, expresses: The evaluate board of trustees should audit the precise sport plans made, by using which personnel of the company may, in certainty, enhance concerns approximately ability indecencies in issue of money-related detailing or special trouble. Whenever taken into consideration large, game plans need to be made for proportionate and self-sufficient examination of such subjects, for becoming next pastime and publications of action whereby personnel can educate the director regarding the assessment advisory institution straightforwardly. In Germany, the corporation Governance Code, offered on February 26, 2002 by means of the Croome Committee and revised on June 2, 2005, has all of the more expressly been given an impact nearly like regulation for a chunk of its substance, inspite of the truth that it additionally follows the Contents of Whistleblowing Policies

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27 “pass alongside or make clear” line of idea: The proposals of the Code are set apart in the content material with the aid of utilization of the word “will.” Organizations can stray from them yet are obliged to discover this each year. This presents agencies to mirror vicinity and undertaking specific conditions. Subsequently, the Code adds to extra adaptability and greater self-guiding principle inside the German corporate constitution. Besides, the Code contains proposals, which might be digressed from without revelation; for this, the Code utilizes phrases like “have to” or “can.” The leftover entries of the Code now not set apart by these phrases include arrangements that undertakings are restricted to look under pertinent regulation. There is no whistleblowing arrangement during this code. The public corporate administration codes of any closing international locations blanketed for the duration of this examination (i.e., Switzerland, France, Sweden) observe the “go alongside or clarify” idea, but none of them includes a whistleblowing association. Despite this clear absence of interest out of doors the U.K., Belgium, and thusly the Netherlands in controlling whistleblowing preparations on a public stage, endeavors are made in France and Switzerland to carry it into the economic area. In 2005, the Commission Bancaire, the French financial controller, made assortment of proposition to regulate Regulation 97-02, the present-day guideline on interior controls applying to the 2 banks and hypothesis firms. A non-obligatory whistleblowing measure (whistleblowing is authorized on every occasion considered sizable by the expert, but now not wished) turned into certainly one of these propositions. The new Regulation 97-02 has been a hit since January 1st, 2006. A similar late pastime in Switzerland became much less powerful. In the spring of 2005, Swiss Federal Banking Commission (SFBC) gave a draft circular referred to as “Internal Surveillance and Control,” containing a whistleblowing proviso. In August of the very 12 months, Swiss Bankers Association (SBA) disregarded this provision on rule, expressing it “could profoundly change the interior tradition of banks too when you consider the weather within the operating environment” and “there are nowadays different and simpler techniques with which to manipulate and oversee risk” (SBA 2005). In a world putting, SOX should be trailed by way of auxiliaries of US-primarily based recorded companies, and by way of European businesses recorded at the New York economic change. In France, in any case, this has demonstrated to be risky. On May 26, 2005, the French National Commission for Data Protection and Liberties (CNIL) concluded that the mysterious informant hotlines McDonald’s and CEAC/Exide Technologies had to actualize as a bit of their new implicit rules and had been dismissing the Data Protection Law. As per Chertoff and Simon (2015), The dark web is the portion of the deep web that has been intentionally hidden and is inaccessible through standard web browsers. Dark web sites serve as a platform for Internet users for whom anonymity is essential, since they not only provide protection from unauthorized users, but also usually include encryption to prevent monitoring. As per Hassink et al. (2007), the more specific violations most frequently mentioned were criminal offenses and dangers to health and safety or the environment.

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3 Research Methodology 3.1 Source of Data There can be various wellsprings of information collection mediums, for example, factual and non-measurable sources. The information is gathered from all sources that are essential information (for this, both fundamental and helper data are used). This information utilized is blended according to the need of the investigation. This information has various benefits and faults and fills our need of the exploration study.

3.2 Poll Poll fills four crucial requirements: (1) (2) (3) (4)

Accumulate the fitting data, Make data basically indistinguishable and affable to assessment, Limit inclination in characterizing and presenting request, and To make addresses interfacing with and varied.

For our investigation reason, loads of requests have been set up to accumulate information regarding the assessment. In this examination, a coordinated poll has been used with different sorts of requests, for instance, shut completed and open wrapped up. Unprecedented case has been taken to pick the scales for the requests for arrangement of responses satisfactorily.

3.2.1

Exploration Methods

For assortment of essential information for this exploration work, review strategy has been utilized.

3.2.2

Overview Method

Overview is utilized to gather quantitative data about things in a populace. Overviews are utilized in various regions for gathering the information even out in the open and private areas. An overview might be led in the field by the specialist.

3.3 Testing (a) Introduction

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Survey Study and Literature Review Browser for implementation Graphical Analysis

Protection Act

Information is to be gathered from the respondents. They have been chosen arbitrarily. So separated irregular examining has been utilized for the investigation. Keeping in view the appropriate portrayal of each section of populace and sensible size of the example, the example size chosen is 400 (Fig. 1). Analytics and Interpretation Part A of this research is based on the data collected through the survey and interprets why the knowledge is required to work on the dark web while using the Tor browser. In Fig. 2, we could judge that dark web is answer; out of 400 people, 40.3% people has selected as they know the reason from where the deep web is related and there is 4.3% people who says that the surface web keeps the unknown segment of deep web hidden which tells that there are more people who do not know difference in surface web and the deep web or the dark web. Figure 3 shows the percentage of people in the IT industry know about the onion router and what it prevents it doing people doing it from. As we could clearly see that 52.2% people clearly shows that the Tor is used for encryption or the connection of data from one computer to other, but people also select the web link or the web site which Tor prevents from doing the work. In Fig. 4, we could see that the question strictly gives a clear hint of the tool which is important for entering data in the dark web and the Tor services and network and Fig. 2 Representing unknown segment of Dark Web

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Fig. 3 The onion router way

Fig. 4 Tool to enter dark web

the tool clearly tell the Tor browser is specifically used for this specific reason and people has chosen other browser as well which clearly shows that people in the IT industry. As we see in Fig. 5, the common terminology “name of the scientist” who stated the word “deep web” to the world. So, the people have picked various options but to this question the relevant answer is Mr. Michael K. Bergman who was the first person who talked about the dark web and its components. In Fig. 6, we can make out that people have got confused while seeing the question and it also shows some lack of information as it talks about the way where people can do business in the darknet market and no one can get to know who is dealing with all kind of illegal market, so people were close to get the answer as 29.9% correctly talks about the road where this type of illegal market is. People also talks about the dark road which is partially correct toward the question asked but it still shows that there are few information people do not have till now. In Fig. 7, we could see that both IP address and encryption tools are the right answer but still only one correct answer to this question is the encryption tools that Fig. 5 Image of deep web to world

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Fig. 6 Dark Web as illegal site to sell

help to know the hidden IP address of the dark web and 43.3% people rightly talks about the way to the entrance of in the dark web. In Fig. 8, the question is to find the dark web pages through a way that no one knows, so 41.8% people points that someone must tell the IP address, but it is not going to work as we must find someone and track him down, and while doing it, we do not know where IP address will be located or is there someone really existing in this world who will just tell the IP address. So, to find the page, one must track it by his way using the IP tracker which is used in the Tor browser and tools of the Tor which will help in getting the IP address (Fig. 9). Fig. 7 Representing IP address and encryption tools

Fig. 8 Government on Dark Web

Fig. 9 Illegal activities on Dark Web

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Fig. 10 Way to find Dark Web

Fig. 11 Most prevalent activity on Dark Web

According to Whistle Blowers Protection Act, 2014, parliament has stated the use of the dark web illegal if he/she wants to establish more corruption or transfers information to other countries. Else they can get information for security reasons (only in certain circumstances) so that there is no war, terrorist, or another other aggression or information in the civilization and the citizens (Fig. 10). As in Fig. 10, we see that 40.3% people correctly says that illegal activities should not be there, but it cannot be completely stopped, and as to get information for illegal terrors, people must use this web for transmitting the information. In Fig. 11, we could see that all are the illegal activities that are well happening on the dark web and are well established, so there is no prevention toward any of the illegal activities. But there is only one which is live stream of torture and murder as this can be sent to the web else the person who sees this video will viral it and government will get to know all the information regarding this. Part B of the research paper is based on the Protection Act that the countries had taken to stop the working of whistle-blower over certain sites and browser. As per Gehl (2014), DWSN is accessible through onion router only. As indicated with the aid of Indian law reports, the invoice has faced vast analysis due to the fact its locale is constrained to the govt. Vicinity consists of just the ones that are working for the government of India or its workplaces; it does not cover the nation-authorities’ representatives. Be that as it can, the draft invoice pointed closer to securing informants is considered as an invitation pass. The lack of debate and assembly at the bill appears to point its peril becoming any other “paper tiger.” Commonly, services presenting draft enactment consist of an interplay of public counsel to provide the general population a possibility to painstakingly scrutinize its arrangements. All through this situation, a specific risk has been denied to the overall population, which has no longer long past undetected. The proposed regulation has neither association to empower whistleblowing (financial motivating forces)

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nor manages company informants; it does not stretch out its purview to the nonpublic vicinity (an unusual exclusion, after the extortion at Satyam). The Directorate of evaluation Intelligence and Criminal Investigation is one in every of the sole organizations engaged for informant insurance. The invoice plans to regulate the want to display authentic authorities from badgering with ensuring human beings unveiling an interest revelation. It diagrams sanctions for bogus protests. In any case, it does not give a punishment to assaulting a complainant. The Central Vigilance Commission (CVC) made several notifications to get public attention and interest; there some hundred protests for each annum. The preparations of the bill are almost much like that of the aim. Accordingly, it is miles-fetched that the degree of protests will range essentially. The workplace of the CVC is confined to creating tips. It cannot pressure punishments, in place of the forces of the Karnataka and Delhi Lookouts. The bill consists of a restrained that means of revelation and would not signify exploitation. Different international locations (such considering the USA, UK, and Canada) characterize divulgence all of the extra broadly and represent exploitation. These include non-affirmation of unknown objections and shortage of punishments for government who exploit informants. Whenever ordered, the law to monitor informants will help with distinguishing debasement, ensuring higher data circulation and making ready for fruitful arraignment of degenerate human beings through clear and watched measures. Notwithstanding, the overall populace in India have a coffee level of agree with in struggling with debasement when you consider that they dread counter and terrorizing against those that record grievances. Another challenge pertains to the deferral in disposing of those cases. Without banter on the preparations of this proposed regulation, it appears that evidently humans cannot quantify its adequacy while the draft price comes into electricity as law. Part C involves implementation of dark web (Fig. 12). Fig. 12 Way to find safety

Knowledge extraction Fulfilling the system requirement Configure the browser according to the IP address Expert in hacking and VPN creation

TOR Browser

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4 Conclusion and Recommendation 4.1 Conclusion We could conclude that whistle-blowers are not safe for using dark web as this will go against the law that the government has stated and this will make it difficult for everyone to transfer legal information and prevents terrorism on the world. Further to this, we could also state that people should have full knowledge of the work they are doing and also get other information on this web browser and web net that will help them to gain access. The present findings also conform that this belongs to different professionals in the IT industry; also, it gives domain specific people who have knowledge of the cyber security and dark web in the industry.

4.2 Recommendation In the recent years, deep web aka dark web is known to people who are into security but if people from different areas, professionals can come to know the aspect of dark web and they will get to know how much crucial is the Internet they are using and the information they are exchanging will lead to something different. So, the following are the recommendations that we would like to give and people can follow: . Gaining knowledge of every aspect we do is essential and having half the knowledge will only result in terror. . In this matter having theoretical knowledge is well suited for the people who are not from IT background. . Practically implementing the dark will take days to new implementor, and how to properly implement the right code is also not possible for anyone who do not know the cons of dark web. . As the factor we talk about growth in this field, we would say that have a dual aspect in life while implementing proper functions and codes. Lastly, whistle-blowers should not bring their way into the dark web as they will not keep it safe from the world we all live in.

5 Limitation and Future Scope 5.1 Limitations Following are the limitations that we get to know while doing the research:

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. School or college student should play with Tor browser or he will suffer from the prevention act that is implemented by the government. . Using browser other than the Tor will be implemented as the cyber crime and full action will be taken in respect of the countries and their cyber policies. . Tracking IP address is not easy, have to give day and night from tracking accurate IP address of the dark web.

5.2 Future Scope Following are the scopes that one could get while doing more research in the deep web and whistle-blower safety: . Gaining information is good and doing project/research for future will get to know that people have the interest in the cyber security. . Doing different courses and learning more about security will be helping government in taking actions against all the illegal activities going in the world. . In difficult times, people will seek advice from the lawmakers to understand how unethical practices can be curbed in this borderless web, called Dark web.

References Biddle S (2012) The secret online weapons store that’ll sell anyone anything Bingham J (2013) Cameron wins FBI support for “dark web” war on paedophiles Boellstorf T (2008) Coming of age in second life: an anthropologist explores the virtually Borland J (2013) For tor, publicity a mixed blessing Chertoff M, Simon T (2015) The impact of the dark web on internet governance and cyber security. The Centre for International Governance Innovation and Chatham House, pp 1–18. https://www. cigionline.org/sites/default/files/gcig_paper_no6.pdf Dingledine R, Mathewson N, Syverson P (2004) Tor: the second-generation onion router Gehl RW (2014) Power/freedom on the Dark Web: a digital ethnography of the Dark Web social network. SAGE J:1219–1235. https://doi.org/10.1177/1461444814554900 Gillespie I (2013) Cyber cops probe the deep web Hassink H, de Vries M, Bollen L (2007) A content analysis of whistleblowing policies of leading European companies. J Bus Ethics. https://doi.org/10.1007/s10551-006-9236-9 Henry R (2013) Inside the murky world of the deep web Hoffman C (2012) How to find active onion sites and why you might want to https://doi.org/10.1007/s10551-006-9236-9 https://www.pwc.com/cz/cs/assets/pdf/StaySecure_DarkNet_external_EN.pdf Lovink G (2003) Dark fiber: tracking critical internet culture Murad A, Hines N (2012) Drugs, guns and passports for sale on “Dark Web.” Online M (2013) The disturbing world of the Deep Web, where contract killers and drug dealers Pagliery J (2014) The deep web you don’t know about Wooding D (2013) Child sex dark web targeted. https://doi.org/10.1007/s11277-020-07143-2

Artificial Intelligence and Its Impacts on Industry 4.0 Seema Garg, Navita Mahajan, and Jayanta Ghosh

1 Introduction Artificial Intelligence is applicable to all the basic areas and facets of day-to-day life from medicine to health care, sustainable environment, manufacturing, value chains, climate, education, security including cyber-security, trade, global services, inventory management, capacity optimization, forecasting, and accuracy for quality management; hence, every sector would witness improvement with launch of number of AI-based machines. Artificial Intelligence has capacity to solve difficult problems in order to facilitate human inventiveness and develop a collaborative culture. Driven by the new norms of industrial revolution that has led to Industry 4.0, AI has become the most disruptive technology that further revolutionized the business management practices of organizations through multiple designs solutions. It is utmost essential that ethics become vital part of human behaviour. There may be serious concerns on security, privacy, and ethical concerns, which may draw lot of attention (Garg et al. 2022). The continuous shift from traditional automation processes to cyber-physical systems, real-time production models, and industry information networks has imposed new modern regimes of competitiveness in the market. The sophisticated algorithms created by machine learning and neural networks have optimized the production systems through unsupervised learnings and automations. AI and Industry 4.0 would be a game-changer to bring economic, technological, and industrial revolution in near future.

S. Garg (B) · N. Mahajan Amity University, Noida, Uttar Pradesh, India e-mail: [email protected] J. Ghosh S.P. Jain School of Global Management, Sydney, Australia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_7

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1.1 Industry 4.0 Various advancements in technology have brought number of digital transformations during various stages and customized solutions which can be termed industrial revolutions. Each industry revolution from Industry 1.0 to 4.0 represents the innovation, mechanization, and revolution in manufacturing process. Each revolution changed the way about working in industry in various phases. The journey beyond Industry 4.0 can be well understood through how we have reached here in the first three industrial revolutions.

Source: Industry 4.0 incorporates IoT and other digital technologies [Source: IB Times UK]

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1.2 Industry 4.0 Technologies Industry 4.0 mentions the current growing trend towards new age technologies and data exchange and processes within the manufacturing industry, including . . . . . . .

Internet of Things (IoT) Cyber-physical systems (CPS) Smart manufacture Smart factories Cloud computing Cognitive computing Artificial Intelligence.

2 Research Objectives (1) To study the multidimensional innovations in the industry with respect to AI (2) To study the scope and the impact of AI in businesses specifically Industry 4.0.

3 Artificial Intelligence Study of Artificial Intelligence (AI) is nothing but creating intelligent machines, which directly and indirectly has transformed our lives since it is used in so many aspects of daily life. It assists us in the creating machines for speeding up our job by decreasing human effort and ensuring precise results. It is that branch of computer science which tries to replicate natural intellect, human skill, and automated capabilities with machines with different software and basic computer platforms. It makes advantage of technology that has improved our intelligence and productivity while also changing the way we communicate, learn, shop, and play. Artificial Intelligence advances are enabling computing systems to catch and learn with reasoning, opening up new areas for improving health care and education, and ensuring a more safe and green future. Artificial Intelligence has a number of advantages, one of which is that it is based on facts and databases rather than emotions. It has seen that human emotions have a negative impact on human decisions. There are a variety of AI applications in all human activities, such as expert systems and neural networks. In industry, it has a broader applicability in marketing, HRM, customer behaviour, machine learning, payrolls, IT systems, inventory management, and other cross-functional areas.

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3.1 Industry 4.0 and Artificial Intelligence AI is a new forthcoming technology that is currently being used by producers to increase the quality, efficiency, and reduce operational costs. The study of human– robot collaboration is a field that has benefited from the usage of Artificial Intelligence in the production process. AI automation process collects and analyses all types of data, including photos, and categorizes fixed field text that is made up of connected production processes that include diverse machines that all communicate with each other. The stages of the industrial revolution are divided into four categories. The first revolution began in eighteenth century, which was mechanical industry based on water and steam. Then, in the twentieth century, the second industrial revolution began with the advent of conveyor belts and mass production. The third revolution started with the introduction of digital automation through the use of electronics and information technology systems during the manufacturing process as a whole. With the increase in autonomous robots, modern automation, IoT, the Internet of services, and other technologies, the industrial landscape is once again being changed and promoted into the fourth stage of revolution. Industrial robots, which are one of Industry 4.0’s primary drivers, have come a long way since the last decades of the twentieth century. As per the information, the USA is using the term “Industry 4.0” to refer to the Internet of Everything. Also in other sphere of interpretation, the phrases “Advanced Manufacturing” and “Predictive Manufacturing” refer to a broader range of manufacturing modernization trends. The key component of Industry 4.0 is considered to be as advanced manufacturing. Industry 4.0 is defined as an intelligent manufacturing system that focuses on product creation, manufacturing, and supplying personalized products and services based on individual needs. It promotes the integration of a variety of intelligent manufacturing systems as well as innovative information technologies. Industry 4.0 brings innovative change in the way of manufacturing plants work. Therefore, this collaboration between machines and humans has the potential to have a social impact on the lives of future workers, particularly in terms of decision-making optimization. Businesses can benefit from cloud computing when Artificial Intelligence is used. Cloud computing has numerous advantages. It has the potential to enhance personalized buying experiences and aids in the detection of patterns in customers’ browsing and purchase habits. Artificial Intelligence is capable of making personalized offers to each customer. Currently, most consumer contacts, including as emails, social media talks, online chat, and phone calls, require human participation. Customer contacts are automated using Artificial Intelligence.

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4 Literature Review Industry 4.0 encompasses robotics, driverless transportation and manufacturing machinery, 3D printers, Internet of Things, 5G mobile connectivity, analytics, system integration, cloud computing, data analytics, and data science and simulation. These technologies are employed in the manufacture of high-quality items with improved product diversity, and in many cases, cheaper prices attained through optimization and smart manufacturing procedures (Gunal 2019) Peres (2020) and Lee et al. (2018) concludes Artificial Intelligence is a platform that has arisen from numerous scientific narratives that are changing transform innovative. The world needs to create and execute Artificial Intelligence applications in a more methodical manner if it is to benefit from the next era of industrial systems, coined Industry 4.0. Further to this, Peres (2020) focuses that manufacturing contexts are becoming increasingly highly volatile, linked but also fundamentally complicated to a greater extent with increased interdependencies and huge amounts of data produced because of the Industry 4.0 efforts. Recent breakthroughs in Artificial Intelligence in industrial have demonstrated on technology’s possibility of assisting manufacturers in addressing issues related to transformation of digital cyber-technologies owing to its extrapolative analytics, based on data coupled with ability to aid in the decision-making process in highly complex situations. As per Dhanabalan and Sathish (2018), automation and robotics, as part of Industry 4.0, can introduce a higher paradigm of competitiveness, allowing companies to avoid high labour expenses inland. Investments in new technologies, new products, and services should have the positive consequences (approximate 10 million employment), and we may strike a balance by increasing the percentage of Industry 4.0 solutions in industry. Zhong et al. (2017) has shared their viewpoint on intelligent manufacturing and its importance in Industry 4.0. Simple resources are redesigned to be able to perceive, act, and react in a smart environment as a result of this. Patel (2018) in their work found that when AI techniques are integrated with current breakthroughs like IoTs, Web linkages, and Web Semantics that are collectively referred to Semantic Web, Industry 4.0 becomes a reality. IT technologies can aid with cross-sector and domain system incorporation as well as the development of intelligent cum smart applications for smart manufacturing, which can help Industry 4.0 difficulties to a greater extent. After the adoption of Industry 4.0 and the vast capabilities of AI, world economy could see rapid growth. High levels of Industry 4.0 development and Artificial Intelligence readiness do not result in high rates of economic growth. One of the reasons for this is the objective challenges that come with implementing Industry 4.0 and AI. These roadblocks are monetary, technological, and institutional, as per Vyshnevskyi (2019). As per Boichuk (2020) in the context of Industry 4.0 solutions in a SME, it can be claimed that a company can leverage from characteristics such as complex equipment,

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big data analysis, and cloud-based tools. The outcomes of these investigation showed that improvement in technology can significantly boost a production company’s output. The fourth industrial revolution’s “gravitational pull” is aided by increased globalization, technical advancements, digital tools, Internet-centric data flow, competitiveness, and other drivers and crosscurrents (Hwang 2016). Success in the era of Industry 4.0 centres on the inclusive vision coupled with a compelling business model embodied with a decisive strategy and defined fundamental principles, regardless of a specific strategic planning. Another contrary view on this was by Nascimento (2019) was that Artificial Intelligence is not just a hypothesis or a potential. AI has shown to be beneficial to the world for decades. In a multitude of fields, such as health care, business, and governance, it has a substantial impact on our lives. However, because of a phenomenon known as the odd paradox in which AI experts produce advanced technologies that can be quickly assimilated and grasped by practical applications and advancements. As a result, adequate attention is not given to AI, and AI experts continue to work on difficult problems that are yet unsolved leading to false beliefs that AI is futuristic and has yet to make important contribution. However, according to Nishant et al. (2020), AI will revolutionize business methods and industries and can solve fundamental societal issues, such as sustainable development. Artificial Intelligence (AI) can assist in the development of traditional suitable executive processes and selfpractices which lower down the use of available resources and intensify the human activities. How Artificial Intelligence helps society, lowers energy, water, and land use intensities apart from helping and supporting environmental governance at a higher level? According to Gilchrist (2016) in order for enterprises to adapt to the notions of the industrial Internet, they must first understand their existing position in terms of progressions, methodologies, principles, and approaches. On the basis of millennials, Cresnar (2019) suggests that millennials are more prone to ideals related to personal grooming and anxiety freedom, as well as ready to accept and change. Due to openness, understanding, collaboration, acceptance, and greater support, these concepts can have a significant impact on shaping the future of Industry 4.0, resulting in a clear millennial effect. Under the auspices of Industry 4.0, the future of intelligent manufacturing will go beyond “smart”, achieving true “intelligent” status. Also Koh et al. (2019) had discussed the increasingly in-depth understanding of industry 4.0, and its research potentials to combine industry 4.0 with other research fields in their study to further investigate the industry 4.0 with a wider scope.

5 Research Methodology The research is based on secondary information. It is mostly concerned with secondary data sources. The data for the study was gathered from reviews of Artificial

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Intelligence in general and Industry 4.0 in specific. Furthermore, the study included and evaluated McKinsey studies on AI adoption.

6 Industrial Application of AI At a high level of abstraction, a framework for categorizing industrial AI applications can be built on two main categories: (i) industrial efficiency and performance enhancement procedures and (ii) increasing human–machine collaboration. The first was concerned with increasing efficiency and performance through intelligent monitoring applications, as well as optimization or control programmes that could make decisions automatically in respect to industrial processes. This classification is based on the degree of automation that each AI application requires, with “monitoring” requiring the least and “control” requiring the most. Monitoring: In industrial contexts, monitoring the performance of systems and processes is required in order to detect or predict failures. Machine learning can be used to anticipate future performance and circumstances of systems based on a set of data. Monitoring is also important for quality control, as AI may be able to visually verify objects on assembly lines, resulting in fewer defects. AI may also be used to perform predictive maintenance, which involves isolating problems and failures before they influence the production line using data from the manufacturing processes. Because maintenance is only performed when it is predicted rather than at regular intervals, predictive maintenance can result in a reduction in maintenance activities. Operations: Apart from monitoring the performance of existing industrial processes to verify they are operating as planned, another option would be to use AI to enable improved company operations based on a plan and the fulfilment of business requirements. Product design is one area where AI may help with this type of optimization in an industrial setting; designers may be able to input restrictions within a product, allowing the AI system to generate design alternatives using machine learning methods. As a result, AI can assist in determining whether a designer’s work is manufacturable, obviating the requirement for production testing, and reducing testing time (minimum/reduced). Furthermore, optimization techniques may be able to offer alternate designs for existing items based on product deficiency data (Yuan 2019). Control: To reap the full benefits of automation, control systems are required. Some of the goals of AI control applications include responding to changes in the environment inside an industrial process, as well as increasing production and productivity, lowering labour costs, and reducing waste. A few examples of industrial applications that benefit from AI-based control systems include autonomous mobile robots in factories that can help with material movement, supply chain management, and inventory management in warehouses. In many circumstances, Artificial Intelligence allows robots to accomplish activities more effectively and efficiently than humans while maintaining human safety.

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7 Findings It is found through the study of Microsoft study that 71% of the business executives have faith that AI has potential that it will show a significant impact on their business (may be any type). And 50% of companies that rely on AI and work on it within 5–7 years may increase their cash flow to double. 64% of the industrial companies have already started to invest in providing AI solution to the problems. 36% of industrial companies fear integration and compatibility problems with AI solutions.

From the data using secondary sources, it has been predicted that Artificial Intelligence technologies are main driving source of the economy as a whole, and in 2025, the site of the Artificial Intelligence market is expected to reach 101.7 billion dollars (Konnikov, Konnikova, events, 2019, Tucker et al. 2016). The recent developments in AI technologies in combination with hubs for innovations in Artificial Intelligence and machine learning (ML) create favourable conditions for AI to transform manufacturing stream and take Industry 4.0 to the next level. As AI technologies grow hence attain maturity and more manufacturers and industrialist adopt the IoT, its use for smart and safe production expands and makes it a staple in the industry. Industry 4.0 has the capability to show economic growth and can be predicted to sum up between value of $500 billion and $1.5 trillion value to reach the global economy at certain level, i.e. between 2018 and 2022 (report by Capgemini). Only 25% of worldwide organizations who are already employing AI solutions have defined an enterprise-wide AI strategy, according to a new IDC poll. Many businesses are turning to Artificial Intelligence (AI) to boost their productivity.

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8 Discussion and Implications Industry 4.0 is the technological label that is leading us to Industry 4.0 paradigms to drive efficiencies and bring revolution AI, Internet of Things, robots with smart machines, etc., all have created new infrastructure for enhancing this technological development. These technologies have been so beneficial for the companies that investment in this infrastructure is part of company’s expansion and diversification strategies at corporate levels. The reduction in production cost, reducing processing times, and reducing wastages are some of the main features of Industry 4.0 from its technologies. With Artificial Intelligence, companies can supply and produce their products only in précised quantities. Artificial Intelligence has capability to transform world’s economy by providing leverages to innovations in field of technology, scientific knowledge, and entrepreneurship.

9 Conclusion The Global Climate Change is the most important concern of United Nations, and here the digital solutions are expected to give hope for a better future and environmental sustainability. The unique techniques of Artificial Intelligence such as predictive technologies, drone systems, and monitoring can help mitigating the environmental problems and identify vulnerable hotspots during any natural calamity. The capabilities of Artificial Intelligence in decreasing carbon dioxide emissions, control on massive data, fossil fuel life cycle controls, and overall improving of renewable scheduling are some of the major contributions in environment conservation. Another key feature is the development of assistance technologies for elders and disabled people, advancement in toys, and gaming industry, thus providing cognitive and emotional support to different age groups. The transition to a virtually connected world has shaped the industry since early 2020; apart the pandemic-driven digitalized society is getting better acquainted with Industry 4.0 which is based on three pillars such as connectivity, knowledge, and intelligent sensing. There is no doubt that AI is capable of solving the difficult and unsolvable problems. With the continuous industrial revolutions, AI technologies are readily available for industrial solutions. The confinement of Artificial Intelligence in only few regions of world is also leading to digital divide, which is non-participation from some countries and may create economic inequalities, cultural, and social gaps. Although Artificial Intelligence impact on Industry 4.0 has been discussed primarily in this paper, but as the technical advancement keeps on happening, there are plentiful scopes of future research in this topic. Meanwhile, with the increase in deep understanding of Industry 4.0, there are more research potentials to combine Industry 4.0 and Artificial Intelligence with other research fields to further investigate the Industry 4.0 with a wider scope.

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10 Limitations and Future Recommendation The biggest flaw in this work is that it is primarily based on a literature review with no primary research data. Because the majority of the authenticated data has concentrated on the scope and influence of AI on Industry 4.0 elements, the study may contain some bias. Furthermore, no cultural, geographic, or industry-specific case studies were included in research. Because the industry is now transitioning to Industry 5.0, with additional innovations, there is a lot of room for this study to be expanded with more industry-specific examples and applications. Other than this, the study is considered to further be diversified into various cross-functional areas with domain-specific challenges and solutions in reviving economies, new normal, and virtual management styles. The various scientists, experts, and subject specialist are discovering innovations and new applications of Artificial Intelligence in various fields; hence, categorization based on region, territory, and socio-economic sector is another area which can be explored.

References Boichuk N (2020) Identification and evaluation of industry 4.0 solutions in the automotive industry– ´ aska, (147 Modernity a case study. Zeszyty Naukowe. Organizacja Zarz˛adzanie/Politechnika Sl˛ of industry and services), 53–64 Cresnar R (2019) The millennials’ effect: how can their personal values shape the future business environment of industry 4.0? Naše gospodarstvo/Our Econ 65(1):57–65 Dhanabalan T, Sathish A (2018) Transforming Indian industries through artificial intelligence and robotics in Industry 4.0. Int J Mech Eng Technol 9(10):835–845 Garg S, Mahajan N, Ghosh J (2022) Artificial intelligence as an emerging technology in global trade: the challenges and possibilities. In: Handbook of research on innovative management using AI in Industry 5.0. IGI Global, pp 98–117 Gilchrist A (2016) Industry 4.0: the industrial internet of things. Apress Gunal MM (2019) Simulation for Industry 4.0: past, present, and future. Springer Hwang JS (2016) The fourth industrial revolution (industry 4.0): intelligent manufacturing. SMT Mag 3:616–630 Koh L, Orzes G, Jia F (2019) The fourth industrial revolution (Industry 4.0): technologies’ disruption on operations and supply chain management. Int J Oper Prod Manage 39(6/7/8):817–828. ISSN 0144-3577. https://doi.org/10.1108/IJOPM-08-2019-788 Lee et al (2018) Industrial artificial intelligence for industry 4.0-based manufacturing systems. Manuf Lett 18:20–23 Nascimento AM (2019). Artificial intelligence and industry. The next frontier in organizations. BAR Braz Admin Rev 15(4):e180152. Epub. 10.1590/1 Nishant R et al (2020) Artificial intelligence for sustainability: challenges, opportunities, and a research agenda. Int J Inf Manage 53:102104. ISSN 0268-4012. https://doi.org/10.1016/j.ijinfo mgt.2020.102104 Patel P (2018) From raw data to smart manufacturing: AI and semantic Web of Things for Industry 4.0. IEEE Intell Syst:79–86 Peres R (2020) Industrial artificial intelligence in Industry 4.0—systematic review challenges and outlook. IEEE Access 8:220121–220139. https://doi.org/10.1109/ACCESS.2020.3042874

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Vyshnevskyi OL (2019) The impact of Industry 4.0. and AI on economic growth. Scien Papers Silesian Univ Technol 140:391–400 Zhong RY et al (2017) Intelligent manufacturing in the context of Industry 4.0: a review. Eng 3(5):616–630

Rise of Digital Entrepreneurship During COVID-19 in India Preeti Tewari

1 Introduction A lot of people have ideas, but there are few who decide to do something about them now. Not tomorrow. Not next week. But today. The true entrepreneur is a doer, not a dreamer. —Nolan Bushnell Starting a company is like eating a glass and starting into abyss. If you feel like you are up for that, then start a company. —Elon Musk

An entrepreneur is a person who possesses the energy and the intention to realise their passion in the most innovatively conceptualised manner. Not many have the kind of love for their work as an entrepreneur. That is, most probably, because of the fact that the venture is his/her brainchild. It has been ideated and nurtured with utmost patience only by an entrepreneur. Digital entrepreneurship is a term that generally refers to entrepreneurs who specialise in digital media and digital world. They create digital media for clients covering diverse aspects such as podcasts, videos, images, web series or other digital assets that they sell online or show to their audience on a digital platform/OTT. Bhaarat has had a history of bearing the unbearable in all adverse circumstances. The citizens of this nation too are known to emerge as the survivors, and as a result, we have been paving ways for the others to tread. Nonetheless, even the present government has forayed into the avenues which were never explored earlier. None of us ever in the living memory of history/their existence would have ever faced a situation like this. It is the vision of the present-day government that has emphasised upon digitalisation of most of the things. This Digital India project has made even a small vendor think on the lines of an entrepreneur. P. Tewari (B) Department of English (Law), Lloyd Law College, Greater Noida, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_8

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Be it demonetisation or other revolutionary grave steps, the country had begun to realise the significance and necessity to be digitally educated. And, this awareness has, chiefly, made us understand the immediate significance of looking for opportunities even in misery. Aapda mein Avasar is a slogan given by our Hon’ble Prime Minister Sri. Narendra Damodardas Modi in one of his speeches delivered via video conferencing on 11 June 2020 during the inaugural address on the event of the 95th annual plenary session organised by Indian Chamber of Commerce (ICC). He is the visionary who even promoted entrepreneurship by giving us another slogan Aatmanirbhar Bhaarat! On the other hand, CEOs and other organisational heads from the worldwide corporate segments have all agreed to the challenging situation(s) being faced by all major and minor sectors across the board. Hence, they have been struggling all this while to find a feasible solution for this problem. Since, it is neither a temporary situation nor a regional one. But, it is only when one starts to think about the issue and its repercussions at length that one shall be able to begin the various probable way outs to the problem too. Interestingly, this is the time to explore all possible avenues in order to get a wide gamut of opportunities.

2 Objective The study has the following major objectives: 1. To delve into the study of rise of digital entrepreneurship during COVID-19 in India. With the changing scenario, and the new demands rising every day, it becomes obligatory to register these and work in the required direction. 2. To realise the emerging needs and demands and the pre-requisites to the digital entrepreneurship during and post-COVID-19 era. It is seen that various businesses have reworked their business model to meet the online mode of operation. 3. To study the impact of growth of digital entrepreneurship that has taken place over a period of time and how this sector is the major donor to a number of enterprises, production, employment, exports and technological advancements as a consequence of the pandemic scenario in India.

3 Literature Review The complete literature appraises that digital entrepreneurship is surely on the rise given the need to survive and sustain economic state of affairs. In order to validate the necessity of present study, the researcher reviewed the below given literature:

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De et al. in a study addressed the consequences and causes of the digital divide apart from examining the potential scenarios in this gush in information technology practice through and after the pandemic. Qermane and Mancha (2020) observed in a case-based study about WHOOP, Inc., a digital start-up in the field of fitness technology, its response to the COVID-19 pandemic, and its business model’s embryonic stage and its scope in the aggressive wearables trade. Aiyede (2020) examined the shift in the economy from offline to online mode. He concludes by asking the entrepreneurs to accept the emerging urgent need of digitalisation in order to combat the “Corona virus” as well as “Schumpeterian virus” because only this way would they be able to survive in the longer run. The study is specifically based in Nigeria.

4 Need and Importance of the Study Enabling digital entrepreneurs in emergent nations is particularly essential as this allows for the creation of new markets, the optimum utilisation of existing markets and integration into large-scale value chains worldwide, especially during the COVID-19 pandemic situation. The digital entrepreneurs have, rather, changed the complete business segment. Precisely, digital entrepreneurs are entrepreneurs who are entirely focused on managing activities related to digital commerce. Simultaneously, digital commerce can be said to be a division of the e-commerce platform. Digital commerce is used for recognising companies or agencies delivering digital products as well as services. A number of the common digital commerce things are e-books, downloadable software, online education materials, web hosting services and so on. This study intends to lay bare the fact that even a pandemic of the given magnanimity cannot stop a passionate person with the acumen of an entrepreneur. You just need to gauge the given scenario and patiently and constantly walk towards your pre-decided aim in order to be able to give wings to your dreams.

5 Methodology Designed This paper is absolutely a conceptual one which essentially comes from varied secondary sources like research articles, published academic papers and books, various international and local journals, newspapers and websites. The study covers, majorly, a period from (December) 2019 to (January) 2021. The present research is qualitative and exploratory in nature. Various secondary sources have laid bare the concept and need of rise of digital entrepreneurship with every passing day. These have further showcased the way this field got defined and emerged as the new norm.

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The secondary sources too seconded the notion that all major as well as minor trade and commerce sectors have reworked and are still in the process of re shaping their respective business model(s) just to be able to align themselves with that of the new demands. Further, it was evident in various websites/newspapers at other sources that many people who either lost their job or had been procrastinating the decision of being an entrepreneur one fine day quickly took to learning the norms of the game and landed being an entrepreneur in a digital world. Stories, articles and several other media roar of such instances and life-changing episodes. The researcher has also shared her views on digital entrepreneurship explicitly during the pandemic in the Indian context, specifically.

6 Findings a. COVID-19 turned out to be a boon for the digital economy globally. b. According to an IAMAI-Nielsen Report (Nielsen 2019) on Digital India, as of November 2019, the total number of internet users in India stood at 504 million, out of which 433 million internet users were above the age of 12 (Short et al. 1976; Iivari et al. 2016). c. A number of new ventures emerged due to the pandemic scenario. d. As per a report (Agarwal et al. 2009) by RedSeer Consulting, in 2019, while India’s fashion market was growing at a Compound Annual Growth Rate (CAGR) of 11%, the online fashion segment was growing faster at a CAGR of 32%. e. Worldwide, people have begun to doing almost all the major buying via the online mode only. f. E-commerce had never seen such a boom in the industry g. Be it ordering food online to ordering medicines/groceries/clothes etc. have all seen a surge in the business. h. All the OTTs witnessed a leap in their subscriptions as well as downloading and watch time. i. Clearly, the no. of gadgets and other such materials has been sold at an all-time high.

7 Conclusion An inadvertent by product of the lockdown is that digital acceptance has augmented multifold in India. The country, similar to other developing countries, would have otherwise taken a lot more time to adopt this transformation. But, as was destined to happen, we were left with no other choice but to adopt and adapt with respect to the urgent need of the hour. As a result of losing their jobs too, many people had to resort to finding new ways of starting their venture that too using the digital tools and apps.

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It could be said to be a forced alternative to abiding by an everyday 9–5 or 10–6 job. Though, many always dreamt of starting something of their own. Not, everyone has the guts to leave and otherwise mundane yet rewarding job for an absolutely new field. In addition, even the not so gutsy (professionally speaking) home-makers have begun to start small businesses which are catering creatively to the essential needs of the families in their immediate society neighbours/area at other levels too. The kids have got time to learn and master either musical instruments or complete some other technically advanced courses and start their own start-ups thereby becoming digital entrepreneurs at a very tender age/in their formative years. Neil Patel (owner of Kissmetrics and Quicksprout, Saurabh Bhatnagar (internet marketing expert and business mentor) and Sorav Jain (founder of echoVme and Digital Scholar) are the foremost three (3) digital marketing entrepreneurs in India. Priyanka Subarno who was jobless in May 2020 in Delhi had launched with her ex-colleague Manna Beck, Tribespun, with an objective to revive indigenous art forms on its last legs. Whether forced or voluntarily adopted, the rise in the digital entrepreneurship has been quite evident in all the spheres across sectors.

8 Recommendations a. With the swelling COVID-19 cases, and the need to stay indoors (unless mandatory to move out) as a major preventive measure, more digital entrepreneurs would be required in coming days in the fields which have not yet been explored b. Digital divide in the country needs to be lessened/bridged as soon as possible c. Government policies are many and quite sufficient. Still their implementation remains a problem d. Rural and backward parts of the country need speedy work to ensure better networks and connectivity e. Digital education is also required f. Community trainings and sessions must be started g. Availability of the necessary resources is to be taken care of by the local bodies/agencies h. Regular seminars/workshops, etc. must be conducted in remote places too i. A comprehensive report must be submitted by the local authorities to the state/central government on regular intervals j. Young entrepreneurs could be encouraged by giving job opportunities in government sectors to these experts who would be responsible for disseminating digital education nationally and later globally too k. A radio show on digital education, entrepreneurship opportunities could be a good step l. Only practical knowledge and trainings can bridge the gap between knowing and implementing a skill learnt.

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9 Delimitations of the Study 1. Empirical analysis of data is needed to suggest any policy changes 2. Primary sources always help in getting a validation needed to check the reliability of the whole research 3. Particular case studies need to be researched upon which this paper lacks 4. A global study could have given a clearer picture to compare the statistics and understand where we as a country stand.

10 Future Implications of Research The present study which is limited to India and that too is an outcome of the pandemic circumstances can be further taken considering the wider spectrum where the rise of digital entrepreneurship worldwide can be studied on a larger scale and in a comprehensive manner. The various types of entrepreneurship could also be studied either independently or/and comparatively. The said research could even facilitate the researchers understand the importance of making the most of a given situation for any kind of an entrepreneur in a proactive manner. Further, the said research would lay a foundation to explore myriad avenues which could be studied in different scenarios too.

11 Relevant Links www.google.com Wikipedia: www.en.wikipedia.com. https://www.digitalwissen.com/pivoting-ina-pandemic-in-sights-from-two-veteran-ceos-on-transforming-a-business-in-crisis/ http://www.wlac.edu/online/documents/otl.pdf https://yourstory.com/smbstory/small-business-entrepreneurs-jobs-success https://www.researchgate.net/publication/335702702_The_age_of_digital_entr epreneurship https://redseer.com/newsletters/online-fashion-market-in-india/ https://www.researchgate.net/publication/309242001_Digital_Entre-preneu rship_Research_and_Practice

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References Agarwal R, Animesh A, Prasad K (2009) Research note—social interactions and the “digital divide”: explaining variations in internet use. Inf Syst Res 20(2):277–294 Aiyede J (2020) Coronavirus versus Schumpeterian virus: the rise of digital entrepreneurship in Nigeria, 1, 1 Iivari N, Juustila-Molin T, Kinnula M (2016) The future digital innovators: empowering the young generation with digital fabrication and making. Proc. ICIS Nielsen (2019) Digital in India 2019 round 2 report. IAMAI-Nielsen. Retrieved from https://cms. iamai.in/Content/ResearchPapers/2286f4d7-424f-4bde-be88-6415fe5021d5.pdf Qermane K, Mancha R (2020) WHOOP, Inc.: digital entrepreneurship during the Covid-19 pandemic. Entrepreneur Educ Pedag. https://doi.org/10.1177/2515127420975181 Short J, Williams E, Christie B (1976) The social psychology of communication. John Wiley, New York

A New RFM Model Approach: RFMS Semra Erpolat Tasabat, ¸ Tayfun Özçay, Salih Sertbas, ¸ and Esra Akca

1 Introduction The amount of data produced and stored at the global level is unimaginable and growing day by day. Converting these data stacks into meaningful data and enabling them to help in making useful decisions is only possible by clearing up, organizing, modelling and interpreting them with scientific analysis techniques. The modelling stage of this process, which can be described as data mining in short, can be carried out via data analysis. The set of methods that converses the accumulated data into logical, useful and effective results using proper models are called basically data analysis. The models and methods in question may differ according to the decision issue dealt with. RFM is one of the popular methods used in data analysis. As a part of the decision support system, RFM is a useful, simple and powerful consumer, Customer Relationship Management (CRM) application model that has been used for nearly half a century to find the target audience in the most accurate way by segmenting the customers. RFM analysis is an applicable marketing model for behavioural customer segmentation. On the other hand, another analysis called PESTEL is an effective method used in strategic planning. S. E. Ta¸sabat (B) Mimar Sinan Fine Arts University, Istanbul, Turkey e-mail: [email protected] T. Özçay Borusan R&D and Information Technologies, Istanbul, Turkey e-mail: [email protected] E. Akca Borusan R&D and Artificial Intelligence Solutions, Istanbul, Turkey e-mail: [email protected] S. Sertba¸s Linktera Information Technologies, Istanbul, Turkey e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_9

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The effect of economic sensitivity was included by adding the sensitivity variable to the classical RFM model using the proposed model in the study. Thanks to this new model called RFMS, customers can be grouped according to their transaction history as “how close”, “how often”, “for how much have they purchased” and “what are their economic sensitivities”. In this way, customers’ tendencies towards the company were identified and customer profiles with higher probability of responding to campaigns and services could be identified. With the RFMS model, it is aimed to prevent customer losses and to make predictions on the future behaviour of the consumer on the basis of products and services. In this way, companies are provided convenience in the field of marketing and shown the way for saving costs and time in particular. Managing big data and extracting meaningful information from data are very important for companies to survive. In this way, it is possible to recognize customers and to increase customer sustainability and loyalty. In the following sections, first, information about RFM and PESTEL analyses will be provided, and then, the RFMS model developed by integrating the economics effect of PESTEL analysis into the RFM model will be detailed. This developed model will be tested on the monthly data of Borusan Cat Machinery and Power Systems company between 01.2014 and 09.2019.

2 RFM Analysis First introduced to the literature by Bult and Wansbeek (1995), RFM analysis is today among the models that have an important place in data mining. It has become a very useful model particularly in revealing successful results in customer relations and is generally used in the development of discount and campaign strategies in e-commerce and marketing, and in crediting and stock sales in banking. RFM is formed from the combination of the initials of Recency-FrequencyMonetary variables. Recency refers to the customer’s most recent shopping, frequency refers to the customer’s shopping frequency, and monetary refers to the customer’s total amount of shopping. At the core of the RFM model lies the Pareto Principle. According to the Pareto principle, 80% of results arise from 20% of causes. Similarly, 20% is based on the view that customers contribute to 80% of the total revenue. This indicates that focussing on key customer segments can provide a higher return on investment. In general, RFM analysis aims to make appropriate decisions by finding answers to questions such as the following: Who is your customer? Which of your customers profit the most? Which of your customers have visited you recently? Which of your customers are the most loyal? Which customers did react how to which campaigns? Which of your customers are missing? Which of your customers are on the brink of losing?—RFM reduces marketing costs as a result of optimum targeting and reduces negative reactions from customers thanks to controlled targeting. In the literature “Pregnancy Prediction Score” application of Target Company, one of the most important retailers of the USA is the best-known study in the literature

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according to RFM analysis. In the application, first, an identification number (ID) is assigned to each customer. Thus, all shopping done is associated with this customer ID and recorded. 25 different products purchased according to the stage of pregnancy are determined by examining the history. Association and interpretation continue as the customer buys from these products. When the target score is reached, product promotion and discount coupons are sent to the relevant customer. Target Company has managed to increase its revenue by 23 billion dollars between 2002 and 2010 thanks to this application (Internet: Necip Murat 2017). It is possible to find different applications of RFM in the literature. One of them is the applications that perform clustering with RFM. Hossaini et al. combined the weighted RFM model with K-Means to improve customer relationship management (CRM) (Hosseini et al. 2010). In their study, Chuang and Shen used the RFM model and K-Means method in the customer value analysis they have developed for an employer in Taiwan to reinforce the loyalty of long-term profitable customers. In the method, firstly, the importance weights of the variables R, F and M are determined via Analytical Hierarchy Process (AHP) and customers are evaluated with the calculated customer life values (Chuang and Shen 2008). Then, they created similar customer segments with cluster analysis. Various studies conducting grading with RFM have also been performed. One of them is the study conducted by Olson et al. (2009), and this study uses grading and RFM models to analyse the customers’ response probabilities to a particular product introduction. Another is the study by Cheng and Chen (2009). This study handles with the relative change of customer segmentation among three data mining techniques: logistic regression, decision trees and neural network algorithms. Ha (2007) used the classification decision tree technique to estimate the RFM values of the next customers from the current values, to see the changes in RFM values over time and their transition paths. Birant (2011) proposed an integrated model into data mining in his study. The proposed model consists of five main parts: data pre-processing, RFM analysis, customer evaluation processes, segmentation and estimation. Each part of the approach is applied one after the other. The output of each track is the input to the next section(s) (Birant 2011).

2.1 RFM Models It is possible to calculate RFM analysis using different methods and formulas. There are different variants of the RFM analysis model in the literature. It is possible to evaluate these models in two different categories. The first of these are models (First Category Models) where different terms other than Recency, Frequency and Monetary are used or added to these terms which contain the classical RFM model (First Category Models), while the models that constitute the second category are those created by determining the weights of the terms in the classical RFM in different

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ways (Second Category Models). These differences are mostly derived from the function of the model. These categories are briefly described below. (a) First Category Models: The classical RFM model consists of the terms Recency, Frequency and Monetary as stated before. It is possible to derive a modified model by changing one of these terms or adding an additional term to these terms. In some studies, conducted under this category in the literature, different model approaches have been used. One of these modified models is RFD, which is the combination of the initials of Recency-Frequency-Duration variables. “Duration” is the model’s variable, which differs from the classical RFM and represents the time spent. Another modified model is the RFE, which is the combination of the initials of Recency-Frequency-Engagement variables. The “Engagement” variable in the model may correspond to a value depending on the time spent on the page, pages per visit, bounce rate, social media engagement, etc. It is a particularly useful model for online businesses. Another modified RFM model in the literature is the FRAT model, which is the combination of the initials of Frequency-Recency-Amount-Type variables. This model is an extension of classical RFM. (b) Second Category Models: While the terms containing the classical RFM model are included in the models in this category exactly the same way, the difference is due to the determination of the weights for these terms. The classical calculation approach of RFM is given in Formula (1). (Recency Score × Recency Weight) + (Frequency Score × Frequency Weight) + (Monetary Score × Monetary Weight) (1) “Recency Score, Frequency Score, Monetary Score” in Model (1) is calculated by dividing dates, frequencies and amounts into 5 intervals of 20% each, and giving 5 points for the highest 20%, 4 for the highest 2nd, 3 for the highest 3rd, 2 for the highest 4th part and 1 point to the remaining 20% last or the lowest part. Other models developed are based on this logic. Thus, the weight values for each variable in the formula given in Model (1) may differ according to people and theories. Formula (2) includes the model in which different weight values are acknowledged for Recency, Frequency and Monetary variables. According to Model (2), the most important variable in RFM analysis was considered as Recency followed by Frequency and finally Monetary. The minimum score is calculated as 111 and the maximum score as 555 within the scope of this model (Fan 2016). Recency Score × 100 + Frequency Score × 10 + Monetary Score

(2)

Another model is given in Formula (3). Formula (3) was published by Miglautsch in The Journal of Database Marketing on May 28. It was introduced in 2000 (Miglautsch 2000). Within the logic of Model (3), the closest shoppers give more power to return and also give some support to the frequency. The logic behind increasing the frequency can be explained this way: in case of two customers having

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the same rate of recession, they would have the same ratio, but if one orders several times while the other orders only once, the more frequent shopper is more likely to respond. The minimum score is calculated as 6 and the maximum score as 30 within the scope of this model. Recency Score × 3 + (Frequency Score × 2) + (Monetary Score × 1)

(3)

Model (4), given by Formula (4), is based on a 100-point scale. Scores between 19.8 and 99 points are obtained for the units handled according to the model. Equation (4) was developed by Tsai and Chiu (2004). Instead of multiplying Recency, Frequency and Monetary variables by 3, 2 and 1, respectively, as in Model (3), a composite number is obtained by multiplying them by 9.9, 6.6 and 3.3, respectively. The minimum score is calculated as 19.8 and the maximum score as 99 within the scope of this model. Recency Score × 9.9 + (Frequency Score × 6.6) + (Monetary Score × 3.3) (4) Model (5) in Formula (5) proposes to obtain a general score by summing the scores of the Recency, Frequency and Monetary variables without making any weight multiplication (Internet: Yenilik analizi, Sıklık analizi ve Parasal (RFM) analiz ayarlama 2017). The minimum score is calculated as 3 and the maximum score as 15 within the scope of this model. (Recency Score) + (Frequency Score) + (Monetary Score)

(5)

2.2 Scoring with RFM There is a scale consisting of numbers from 1 to 5, which is frequently used in RFM analysis and called customer value criterion. These scale values are as follows: 1: Weakest customer, 2: Weak customer, 3: Medium customer, 4: Important customer and 5: The most important customer. These scale values assigned to customers are assigned in line with the expert opinion of the company where the analysis will be carried out and are included in the analyses. As companies can decide which ranges are ideal for innovation, frequency and monetary values make changes accordingly where they deem necessary. However, today, package programmes that perform RFM analysis can assign the scale value to the units without requiring expert opinion. These programmes separate the 100% value into 20% sub-parts while assigning the scale value to the units. The details of this process, which is called the score assignment process, are given in Table 1 (Cheng and Chen 2009).

148 Table 1 RFMS score scale

S. E. Ta¸sabat et al. Score

R—Recency (%)

F—Frequency (%)

M—Monetary (%)

5

0–20

0–20

0–20

4

20–40

20–40

20–40

3

40–60

40–60

40–60

2

60–80

60–80

60–80

1

80–100

80–100

80–100

2.3 Analyses that Can Be Used with RFM Analyses can be made more powerful and detailed by using different statistical or machine learning approaches with the help of the scores obtained from the RFM analysis result. For example, decision tree, principal components or cluster analyses can be performed with the obtained RFM scores. Important units (customers) can be identified with the help of analysis of principal components, and similar classes (customer segments) can be created with clustering or decision tree analysis. In the study, the segmentation process was carried out via CHAID (Chi-squared Automatic Interaction Detector) decision tree algorithm. The CHAID algorithm is a frequently used model for dividing categorized data into clusters and is based on the Chi-square test. With the help of this model, the data are divided into homogeneous subgroups.

3 PESTEL Analysis The word PESTEL, which is the combination of the initials of the words Political, Economic, Social, Technological, Environmental and Legal, is the name given to the analysis used to create a framework by using environmental factors in determining the probability of success or failure of a strategy. In Fig. 1, variables of the PESTEL analysis are given. We can briefly explain these terms that form the word PESTEL as follows: the term “Political” provides information about the effects of states on the business environment. The term “Economic” focuses on the extent to which organizations are affected directly and in the long run. Depending on the economic situation in the relevant country, amounts of companies’ performance increase or decrease are analysed. Economic growth, exchange rate, inflation rates, interest rates, the amount of disposable income of the business and the consumer can be analysed under the term of Economic. The term Social refers to cultural effects and demographics. Population growth, age distribution, gender ratios, behavioural patterns, career approaches and health conditions can be cited as examples of socio-cultural factors. The term “Technological” examines the effects of technology. Advancing technology, innovations

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Fig. 1 Variables of the PESTEL analysis

made and R&D activities are added to the technological factors in the sector that an enterprise is interested in. The term Environmental generally focuses on “green” issues. Issues such as the environmental pollution or wastes or the amount of raw material can be handled within the scope of the Environmental factor. The term “Legal” handles legal restrictions or changes. Factors such as health, safety laws, environmental law, labour law, advertising law, commercial law, tax law and getting royalties are covered by the “Legal” term. After evaluating variables according to country and impact levels, companies can reach more effective and strategic results supported by external analysis in terms of future predictions by using them in relevant analyses and models. By taking advantage of change, the chances of being successful in activities that resist change increase. Good use of PESTEL analysis helps you avoid actions that will condemn you to failure due to reasons outside of your control in Vuca (Volatility, Uncertainty, Complexity and Ambiguity) environment. In short, it is about understanding the environment, taking advantage of opportunities and enabling to make decisions at the right time to reduce the risks.

4 Proposed Model: RFMS In this study, a new hybrid model is proposed, which has the characteristics of both the first and second category models among the above-mentioned RFM models. This proposed model is named as RFMS and is derived from the result of a combined evaluation of the RFM and PESTEL analyses. The effect of the economic term included in the PESTEL analysis has been attempted to be adapted on the RFM analysis as “sensitivity”. In addition, a suggestion is made for the scores of the terms

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that form the model. The approach taken as a basis for deriving this proposed model is detailed below.

4.1 Economic Sensitivity Although economics has different meanings in the literature, the common definition the economists agree on has been: “the study of people’s and societies’ preferences to use scarce production resources to produce various goods over time by using money or by not using money and to distribute them between individuals or groups in society to consume them now or in the future”. Development and growth are directly proportional to the economy. It is of enormous significance to carefully monitor the speculation and fluctuations on exchange rates and interest rates. Exchange rate change can create a big change in the markets. In the study, it was attempted to obtain a modified model by adding economic sensitivity to the classical RFM model. In this way, it is aimed to better recognize the customers and thus increase the quality. In that, it is possible to offer more accurate marketing options to customers through economic dynamism by following the developments in the economy. For this purpose, in this study, it has been attempted to obtain reasonable results by examining the effects of former fluctuations in exchange rates and interest rates on customer sales frequencies. For this purpose, customer sales frequency data were divided into monthly, quarterly and annual periods, and it was examined whether the exchange rate and interest rate change percentage have a significant effect on sales. Thus, the sensitivity coefficient in Formula (6) was obtained. Sensitivity Score = Exchange Rate/Mortgage Loan Interest Rate

(6)

4.2 RFMS Model In the study, adding the Sensitivity variable to the classical RFM model would be considered to be correct, based on the idea that using the effect of the economy factor in the classical RFM model will increase the sensitivity of the calculations, since it is a component of development and growth and PESTEL analysis. Thus, the effects of economic reflection could be included in the model. Although there are different modified RFM models in the literature, no modified model including economic sensitivity has been found. The proposed RFMS model was created as shown in Formula (7). (Recency Score × Recency Weight) + (Frequency Score

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151

× Frequency Weight) + (Monetary Score × Monetary Weight) + (Sensitivity Score × Sensitivity Weight)

(7)

5 Customer Segmentation with RFMS In this section, the operation and results of the RFMS model proposed within the scope of the study and included in Formula (7) will be discussed.

5.1 Dataset The data considered in the study include the original data of BORUSANCAT Machinery and Power Systems company between 01/01/2014 and 30/09/2019. Product filters selected for use in the study from the data stack of BORUSANCAT customers: new products and second-hand products. In the dataset determined within the scope of the study, some assumptions were made to increase the prediction accuracy of the available data, depending on the expert opinions for incomplete or missing, extreme or incompatible values. So that: Incomplete or Missing Values: In the data group obtained as a result of filtering, it was decided to remove this unit (customer) from the dataset in the event that there are no data in at least one variable belonging to any unit (customer) by taking expert opinion during the data correction and editing stage. Although it is possible to replace the missing data with statistical methods, the units with missing values were excluded from the analysis as a customer-oriented analysis was requested within the scope of the study; in other words, rather than a general comment for all customers of the company, it was aimed to make a customer-specific comment for each customer. Extreme or Incompatible Values: Within the scope of the study, extreme or incompatible values were excluded from the analysis. In that, it is taken into consideration that the three variables handled are not related to each other and each of them makes sense on a unit basis even by themselves, the probability that they may be meaningful since their containment of incompatible or extreme values can mean that they are sales data, and the probability that the extremes or incompatibilities in any variable may become meaningful along with other variables. Purpose: A new service to be provided by BORUSANCAT is to identify customers who are open to a suggestion or campaign and who are likely to respond to it. Dataset consists of six different segments: KAM (Key Account Management), MMM (Mining Mineral Marble), GCP (General Construction and Public), Retail, Marine and Electric Power. The total number of shopping data is 11,650, and the number of customers is 3261. In order for the data to be evaluated in its original form

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with the RFM and the proposed RFMS models, the edited form is given in Table 2a–c, respectively. The variable explanations in the edited form of the data are as follows: Customer ID: Each customer who does shopping from the company, Division: Status of the product: Segment: Intracompany customer classes, Recency: The last shopping date of each customer, Frequency: The shopping frequency of each customer, Monetary: The total amount paid by each customer at the end of shopping, Sensitivity: Average quarterly USD and mortgage loan interest rate before the date of purchase. (Dollar is the CBRT effective buying exchange rate).

5.2 Results for Classical RFM Models IBM Watson Studio was used to conduct analyses within the scope of the study. IBM Watson Studio provides tools to create and train models to scale, based on collaboration and easy operation with data. In this way, it is possible to realize data science in a shorter time. Predictive analytics help streamline machine learning processes and speed up the time to obtain value. Predictive analytics uses advanced analytics capabilities including statistical analysis, predictive modelling, data mining, text analytics, optimization, real-time scoring and machine learning. These tools help organizations explore patterns within the data and predict what will happen in the next step, beyond knowing what happened in the past (https://www.ibm.com/tr-tr/ marketplace/watson-studio). In the study, once the data were transferred to IBM Watson Studio, the analyses were initiated by selecting Modeler flow (Fig. 2). The decision diagram was created by integrating the classical RFM analysis model into the dataset transferred to the programme in Fig. 3. The obtained results are requested to be given in the form of a table and point chart. In the programme, it is possible to calculate scores for different RFM models by writing different variable weights according to the RFM models to be applied to the parameter fields of the RFM analysis. Below, using different graphing methods for the handled data, the calculations for the Model (2), Model (3), Model (4) and Model (5) from the second category RFM models included in Sect. 2.1 are given. It has been observed that the 20% scale and 5-point scoring scale in all graphics are common for all models, but also that there are differentiations in the weights of the formula coefficients in the models. Results of Model (2) Table 3 includes sample customer scores obtained as a result of Model (2).

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Table 2 a Original dataset b Sensitivity score data c Edited dataset a Customer ID

Division

Segment

Income

Date

ID 1

New product

GIKA

EUR 200,782.66

07.2017

ID 2

Second hand

KAM

EUR 70,122.96

05.2018

ID 3

Second hand

MARINE

EUR 146,430.01

07.2015

ID 4

New product

RETAIL

EUR 180,030.00

05.2019

ID 5

New product

RETAIL

EUR 459,312.01

04.2016

ID 6

Second hand

MMM

EUR 150,000.00

04.2015

ID 7

Second hand

GIKA

EUR 120,130.00

03.2016

ID 8

Second hand

KAM

EUR 145,220.14

02.2016

ID 9

New product

ELECTRIC POWER

EUR 100,110.00

01.2017

ID 10

New product

RETAIL

EUR 60,450.01

05.2017

–

–

–

–

–

ID 3252

Second hand

KAM

EUR 76,198.00

03.2018

ID 3253

Second hand

MARINE

EUR 123,986.00

08.2017

ID 3254

Second hand

RETAIL

EUR 145,000.00

09.2015

ID 3255

New product

RETAIL

EUR 290,000.00

01.2015

ID 3256

New product

KAM

EUR 164,000.00

07.2016

ID 3257

Second hand

ELECTRIC POWER

EUR 65,489.00

08.2016

ID 3258

Second hand

RETAIL

EUR 87,650.00

03.2016

ID 3259

Second hand

KAM

EUR 102,560.00

09.2017

ID 3260

New product

ELECTRIC POWER

EUR 45,750.00

04.2015

ID 3261

New product

RETAIL

EUR 78,500.00

01.2016

b Date

Exchange rate of Dollar

Mortgage loan interest rate

01.2014

2.22

11.3

02.2014

2.22

13.03

03.2014

2.23

13.51

04.2014

2.13

13.52

05.2014

2.1

12.94

06.2014

2.12

12.29

07.2014

2.13

11.46

08.2014

2.17

11.06

09.2014

2.21

10.91

10.2014

2.27

10.75

–

–

–

10.2018

6.39

25.18 (continued)

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S. E. Ta¸sabat et al.

Table 2 (continued) b Date

Exchange rate of Dollar

Mortgage loan interest rate

11.2018

5.88

28.95

12.2018

5.39

28.63

01.2019

5.32

27.82

02.2019

5.39

26.22

03.2019

5.28

22.98

04.2019

5.46

18.16

05.2019

5.75

17.7

06.2019

6.07

20.45

07.2019

5.83

21.81

c Customer ID

Recency

Frequency

Monetary

Sensitivity

ID 1

08.2018

22

EUR 2,180,424.32

−0.05

ID 2

12.2018

35

EUR 8,120,111.90

−0.25

ID 3

11.2016

2

EUR 300,360.76

0.21

ID 4

07.2019

17

EUR 1,320,444.11

−0.17

ID 5

07.2018

3

EUR 2,012,344.67

0.03

ID 6

05.2016

11

EUR 500,360.76

0.03

ID 7

04.2017

4

EUR 1,590,424.32

−0.01

ID 8

05.2016

5

EUR 5,321,043.10

0.03

ID 9

01.2018

9

EUR 890,980.33

−0.05

ID 10

06.2018

5

EUR 300,122.00

0.35

–

–

ID 3252

01.2019

3

EUR 291,875.00

0.01

ID 3253

12.2017

2

EUR 535,000.00

0.06

ID 3254

11.2017

10

EUR 4,832.987.00

0.05

ID 3255

04.2018

11

EUR 5,202,765.00

0.03

ID 3256

12.2016

4

EUR 300,330.00

0.25

ID 3257

09.2018

12

EUR 5,100,900.13

−0.28

ID 3258

05.2018

3

EUR 500,367.00

0.24

ID 3259

11.2018

2

EUR 467,980.00

−0.38

ID 3260

12.2017

8

EUR 465,976.44

0.06

ID 3261

01.2019

13

EUR 1,678,124.22

0.01

Fig. 2 IBM Watson studio modeler flow

–

A New RFM Model Approach: RFMS

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Fig. 3 IBM Watson studio decision flow

Table 3 Model (2) sample customer scores

Customer ID

RFM score

ID 1

452

ID 2

125

ID 3

231

ID 4

345

ID 5

111

ID 6

332

ID 7

345

ID 8

131

ID 9

453

ID 10

551

–

–

ID 3252

342

ID 3253

125

ID 3254

325

ID 3255

435

ID 3256

121

ID 3257

345

ID 3258

435

ID 3259

412

ID 3260

534

ID 3261

551

156

S. E. Ta¸sabat et al.

Fig. 4 Model (2) modeler RFM score graph

Figure 4 shows the RFM score graph for Model (2). As can be seen in the graph, an average of 303.978 was calculated for Model (2). The normality distribution is shown in blue, and the core density estimate is represented in green. Results of Model (3) Table 4 includes sample customer scores obtained as a result of Model (3). Figure 5 shows the graph of the RFM scores of Model (3). In the graph, it is seen that the scores are divided into more segments due to the weighting coefficients of the terms in the model. The graph also shows that, for Model (3), the RFM score distributions according to the field sizes of the colours in the image are distributed around approximately the same weights due to the homogeneous distribution of the customer value criterion. Here, the field sizes of the colours display the frequencies of the scores. Results of Model (4) Table 5 includes sample customer scores obtained as a result of Model (4). The graphic of Model (4) is shown in Fig. 6. In the graph, it is seen that the customer score distribution frequencies of the scores are more closely distributed compared to Model (2) and Model (3). The length of the bars represents the customer frequency distribution in the respective score. Results of Model (5) Table 6 includes sample customer scores obtained as a result of Model (5). In Fig. 7, frequency distributions according to RFM scores are given with a different graphic representation. From the graph, it can be said that the lowest

A New RFM Model Approach: RFMS Table 4 Model (3) sample customer scores

157

Customer ID

RFM score

ID 1

24

ID 2

12

ID 3

13

ID 4

22

ID 5

6

ID 6

17

ID 7

22

ID 8

10

ID 9

25

ID 10

26

–

–

ID 3252

19

ID 3253

12

ID 3254

18

ID 3255

23

ID 3256

8

ID 3257

22

ID 3258

23

ID 3259

16

ID 3260

25

ID 3261

26

customer frequency belongs to score 11 and the highest frequency belongs to score 6. The largest circle in the figure is 6. The smallest circle is 11. The circle sizes in the figure represent the customer frequency distributions included in the scores. From the above results, it is seen that the RFM score distributions according to the field sizes of the colours in the image are distributed around approximately the same weights due to the homogeneous distribution customer habits in general. In order to show how the RFM score ranking is done based on results of the analyses from 3261 customers, which have been handled so that they would not occupy lots of storage—the results of the customers who are ranked in the first 10 and the last 10 are given in Table 7. The important thing in Table 7 is the sorting of the score values, not their numerical value. As a result of sorting the scores in descending order, a ranking is obtained from the most important customer to the least important customer. Upon examining the results for the applied four RFM models, it was observed that the rankings of the scores obtained for all models between themselves were close, even though the components and weights of the RFM models were different. Since these four models are prepared for the same purpose under the RFM analysis logic, it is normal for their results to be similar to each other.

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S. E. Ta¸sabat et al.

Fig. 5 Model (3) data refinery flow RFM score graph

Formula differentiation and use in the RFM model depend on the company’s purpose, the number and structure of the target audience it wants to reach. Model (4) should be selected for less audience and stronger customer group. It is the model with the highest score dissociations. With this model, it can be said that the scores are more similar and similarly distributed. Model (2) will play an active role when bigger audience and less strength ratio are required. Score dissociations are high, and the number of clusters based on scores is less. It can be said that customers with similar RFM scores will have similar behaviour and opinions. Following the transactions, related services can be offered to customers who are considered to contribute to the goal the most. In the next stage, since fewer customer clusters are targeted in the company, the RFM scores of Model (2) are divided into categories using the CHAID algorithm, one of the clustering and decision tree methods.

5.3 Clustering with CHAID CHAID analysis is a technique that repeatedly breaks the variation in the dependent variable into different subgroups or sections, with a minimum variation within sections and a maximum variation between sections (McCarty and Hastak 2007). The number of clusters can be adjusted depending on the demands and requests of the companies. In the study; RFM scores of Model (2) are divided into three clusters as “low-medium-high” by CHAID analysis for six segments within BORUSANCAT.

A New RFM Model Approach: RFMS Table 5 Model (4) sample customer scores

159

Customer ID

RFM score

ID 1

79.2

ID 2

39.6

ID 3

42.9

ID 4

72.6

ID 5

19.8

ID 6

56.1

ID 7

72.6

ID 8

33

ID 9

82.5

ID 10

85.8

–

–

ID 3252

62.7

ID 3253

39.6

ID 3254

59.4

ID 3255

75.9

ID 3256

26.4

ID 3257

72.6

ID 3258

75.9

ID 3259

52.8

ID 3260

82.5

ID 3261

85.8

Fig. 6 Model (4) data refinery flow RFM score graph

160 Table 6 Model (5) sample customer scores

S. E. Ta¸sabat et al. Customer ID

RFM score

ID 1

11

ID 2

8

ID 3

6

ID 4

12

ID 5

3

ID 6

8

ID 7

12

ID 8

5

ID 9

12

ID 10

11

–

–

ID 3252

9

ID 3253

8

ID 3254

10

ID 3255

12

ID 3256

4

ID 3257

12

ID 3258

12

ID 3259

7

ID 3260

12

ID 3261

11

In the study, the CHAID algorithm was used as a method to find interactions or associations within the scores. For this purpose, clusters within the company segments were calculated with IBM SPSS Statistics program by using RFM scores related to Model (2). Table 8 includes the results of the respective analysis. In the table, “N” indicates that the number of customers is 208, “Per cent” indicates that the percentage announced in the data is 100.0%, that is, there are no missing or unexplained data. “Mean” indicates the mean RFM score of the data. RFM score averages calculated in other segments of the company: 324 in the KAM segment, 142 in the Retail segment, 312 in the MMM (Mining Mineral Marble) segment, 245 in the GCP (General Construction and Public) segment, 125 in the Marine segment and 213 in the Electric Power segment. Table 9 shows the number of customers of the three clusters requested by the management of the KAM (Key Account Management) segment. The table denotes that the missing value is 0.000 and the clustering is carried out over the full data number excluding missing data. Results indicate that a total of 208 customers, 37 in the first cluster, 85 in the second cluster and 86 in the third cluster, were assigned to three clusters.

A New RFM Model Approach: RFMS

161

Fig. 7 Model (5) RFM score graph

Table 10 shows SPSS Statistics-CHAID method-Retail segment where Table 11 shows the number of customers for the three clusters requested by the management of the Retail segment. The table denotes that the missing value is 0 and the clustering is carried out over the full data number excluding missing data. Results indicate that a total of 1084 customers, 300 in the first cluster, 412 in the second cluster and 372 in the third cluster, were assigned to three clusters. Table 12 shows SPSS Statistics-CHAID method-MMM segment. The number of customers for the three clusters requested by the management of the MMM segment is shown in Table 13. The table denotes that the missing value is 0 and the clustering is carried out over the full data number excluding missing data. Results indicate that a total of 407 customers, 90 in the first cluster, 211 in the second cluster and 106 in the third cluster, were assigned to three clusters. SPSS Statistics-CHAID method-Marine segment is shown in Table 14. Table 15 shows the number of customers for the three clusters requested by the management of the Marine segment. The table denotes that the missing value is 0 and the clustering is carried out over the full data number excluding missing data. Results indicate that

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Table 7 Score grading of 4 different RFM models for the first and last 10 customers Customer ID

RFM score model 1

Customer ID

RFM score model 2

Customer ID

RFM score model 3

Customer ID

RFM score model 4

ID 43

455

ID 43

27

ID 43

89.1

ID 43

14

ID 36

455

ID 36

27

ID 36

89.1

ID 36

14

ID 124

454

ID 124

26

ID 124

85.8

ID 124

13

ID 44

454

ID 44

26

ID 44

85.8

ID 44

13

ID 99

454

ID 99

26

ID 99

85.8

ID 99

13

ID 65

451

ID 25

25

ID 25

82.5

ID 25

13

ID 25

445

ID 643

25

ID 643

82.5

ID 643

13

ID 643

445

ID 532

24

ID 532

79.2

ID 532

12

ID 532

444

ID 65

23

ID 65

75.9

ID 86

11

ID 86

443

ID 86

23

ID 86

75.9

ID 65

10

–

–

–

–

–

–

–

–

ID 600

131

ID 24

12

ID 24

39.6

ID 24

8

ID 24

125

ID 300

11

ID 300

36.3

ID 300

7

ID 300

124

ID 56

11

ID 56

36.3

ID 56

7

ID 56

124

ID 600

10

ID 600

33

ID 43

6

ID 43

123

ID 43

10

ID 43

33

ID 111

6

ID 111

123

ID 111

10

ID 111

33

ID 600

5

ID 27

122

ID 27

9

ID 27

29.7

ID 27

5

ID 67

113

ID 67

8

ID 67

26.4

ID 67

5

ID 88

112

ID 88

7

ID 88

23.1

ID 88

4

ID 93

111

ID 93

6

ID 93

19.8

ID 93

3

Table 8 SPSS statistics-CHAID method-KAM segment

Gain summary for nodes Node

N

Per cent

Mean

0

208

100.0

324

Growing method: CHAID Dependent variable: RFM score Table 9 SPSS statistics-clustering for KAM segment

Number of cases in each cluster Cluster

Valid Missing

1

37

2

85

3

86 208 0

A New RFM Model Approach: RFMS Table 10 SPSS statistics-CHAID method-retail segment

163

Gain summary for nodes Node

N

Per cent

Mean

0

1084

100.0

142

Growing method: CHAID Dependent variable: RFM score

Table 11 SPSS statistics-clustering for retail segment

Number of cases in each cluster 1

Cluster

300

2

412

3

372 1084

Valid

0

Missing

Table 12 SPSS statistics-CHAID method-MMM segment

Gain summary for nodes Node

N

Per cent

Mean

0

407

100.0

312

Growing method: CHAID Dependent variable: RFM score

Table 13 SPSS statistics-clustering for MMM segment

Number of cases in each cluster Cluster

1

90

2

211

3

106 407

Valid

0

Missing

a total of 346 customers, 57 in the first cluster, 132 in the second cluster and 157 in the third cluster, were assigned to three clusters. In Table 16, SPSS Statistics-CHAID method-Electric Power segment is shown. Table 17 shows the number of customers for the three clusters requested by the Table 14 SPSS statistics-CHAID method-marine segment

Gain summary for nodes Node

N

Per cent

Mean

0

346

100.0

245

Growing method: CHAID Dependent variable: RFM score

164 Table 15 SPSS statistics-clustering for marine segment

S. E. Ta¸sabat et al. Number of cases in each cluster Cluster

1

57

2

132

3

157 346

Valid

0

Missing

management of the Electric Power segment. The table denotes that the missing value is 0 and the clustering is carried out over the full data number excluding missing data. Results indicate that a total of 423 customers, 97 in the first cluster, 105 in the second cluster and 221 in the third cluster, were assigned to three clusters. Table 18 shows SPSS Statistics-CHAID method-GIKA segment. Table 19 shows the number of customers for the three clusters requested by the management of the GIKA segment. The table denotes that the missing value is 0 and the clustering is carried out over the full data number excluding missing data. Results indicate that a total of 793 customers, 257 in the first cluster, 275 in the second cluster and 261 in the third cluster, were assigned to three clusters. In Table 20, score and cluster distributions of the clusters calculated on the basis of intracompany segments are included, regardless of segment division. Table 16 SPSS statistics-CHAID method-electric power segment

Gain summary for nodes Node

N

Per cent

Mean

0

423

100.0%

125

Growing method: CHAID Dependent variable: RFM score

Table 17 SPSS statistics-clustering for electric power segment

Number of cases in each cluster Cluster

1

97

2

105

3

221 423

Valid Missing

Table 18 SPSS statistics-CHAID method-GIKA segment

0

Gain summary for nodes Node

N

Per cent

Mean

0

793

100.0

213

Growing method: CHAID Dependent variable: RFM score

A New RFM Model Approach: RFMS Table 19 SPSS statistics-clustering for GIKA segment

165

Number of cases in each cluster Cluster

1

257

2

275

3

261 793

Valid

0

Missing

Table 20 SPSS statistics-clustering summary

Customer ID

RFMS score

Segment

Cluster

ID 43

4552

KAM

1

ID 36

4551

GIKA

1

ID 124

4545

MMM

2

ID 44

4544

KAM

1

ID 99

4541

KAM

1

ID 65

4511

RETAIL

2

ID 25

4453

MMM

1

ID 68

4452

GIKA

2

ID 93

4441

MARINE

1

ID 86

4432

ELECTRIC POWER

2

–

–

–

–

ID 54

1313

MARINE

2

ID 24

1255

GIKA

3

ID 965

1242

RETAIL

3

ID 56

1241

KAM

3

ID 27

1225

GIKA

3

ID 43

1234

KAM

3

ID 76

1233

MMM

2

ID 67

1131

ELECTRIC POWER

3

ID 88

1124

RETAIL

3

ID 867

1115

GIKA

3

5.4 PESTEL Analysis The “Economic” variable, one of the influencing factors in the PESTEL analysis, was found to be significant by Borusan CAT Machinery and Power Systems, and the RFMS model (Formula (7)) was created by incorporating the variable into the RFM model. With this variable, it is aimed to measure the effect of economic sensitivity dynamically.

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5.5 BORUSANCAT RFMS Model The decisive factor in the development of the model has been the customer sales data of the BORUSANCAT company. When the shopping habits of the customers were examined according to the PESTEL analysis factors, it was seen that it was directly proportional to the economic variables. As a result, sensitivity coefficient has been added to the RFM model. This model, called RFMS, has been developed based on Model (2). Before this selection, experiments were made with Model (2), Model (3), Model (4) and Model (5), and since the closest result to the real sales numbers was obtained with Model (2), Model (2) was used as base model in the development of the RFMS model. As a result of the calculated scores, the request of the company that shows interest for the subject focussed, to make marketing strategies for its customers played a critical role in selecting Model (2). Thus, the RFMS model for BORUSANCAT customers was created as in Formula (8). (Recency Score × 1000) + (Frequency Score × 10) + (Monetary Score) + (Sensitivity Score × 100) (8) Comparison of PESTEL variables with their shopping frequencies played an effective role in determining customer habits. The effect of economic reflection on customers, which is included within the PESTEL variables, has been a determining factor. With the Sensitivity variable, economic sensitivity is aimed to be reflected in the model. In the company data used for the study, it was approved to use USD exchange rate and mortgage loan interest rate as PESTEL analysis variables. Instead of these variables, in line with decisions and uses, it is possible for companies to use different economic factors that they are under the influence of, e.g. Commodity exchange, exchange rate quantitative, etc. These variables vary according to the factors that companies are most affected by. In the model, as in other score weights, the sensitivity coefficient is also divided into 5 parts at the rate of change according to the 20% scale in itself, and scores are formed accordingly. Thus, the lower the change percentage, the higher the sales expectation. The high change percentage will cause a decrease in customer frequencies in future as it did in the past. For this reason, the change percentage is expected to be low. The response of customers’ purchasing status to fluctuations in the economic factor will be measured. The model will help to make more accurate decisions in identifying future customers with the economic conjuncture. Before this addition, the percentage change of monthly, quarterly, annual USD sales rate and mortgage loan interest rates were calculated on the monthly sales frequencies of the data. It has been found that the most sensitive change criterion reflected on sales in terms of explanation is the 3-month change rate. Below, the monthly and quarterly reflection of the USD exchange rate on frequencies is shown in Figs. 8 and 9, respectively.

A New RFM Model Approach: RFMS Monthly Average USD

167 Frequency 50 45 40 35 30 25 20 15 10 5 0

7.00 6.00 5.00 4.00 3.00 2.00 1.00 01.2014 03.2014 05.2014 07.2014 09.2014 11.2014 01.2015 03.2015 05.2015 07.2015 09.2015 11.2015 01.2016 03.2016 05.2016 07.2016 09.2016 11.2016 01.2017 03.2017 05.2017 07.2017 09.2017 11.2017 01.2018 03.2018 05.2018 07.2018 09.2018 11.2018 01.2019 03.2019 05.2019

0.00

Fig. 8 Monthly average USD-frequency

3 Month USD Range Rate

Frequency

40%

140

30%

120 100

20%

80 10% 60

-10%

01.2014 03.2014 05.2014 07.2014 09.2014 11.2014 01.2015 03.2015 05.2015 07.2015 09.2015 11.2015 01.2016 03.2016 05.2016 07.2016 09.2016 11.2016 01.2017 03.2017 05.2017 07.2017 09.2017 11.2017 01.2018 03.2018 05.2018 07.2018 09.2018 11.2018 01.2019 03.2019 05.2019

0%

-20%

40 20 0

Fig. 9 3 Month USD range rate-frequency

When the graphic is analysed, it is observed that the number of sales between 01-2014 and 07-2019 was negatively correlated with the USD exchange rate. It can be said that the changes in the USD exchange rate have a significant impact on sales numbers and that the economic reflection factor has been selected correctly. Monthly customer frequencies were compared with these results. With the emerging graph breakages, the 3-month USD change percentage, which is more effective on sales, was preferred for the prediction in accordance with the RFMS model. It can be said that exchange rate of dollar and the 3-month change percentage of the mortgage loan interest rate have more breakages than the 1-month change percentage, and these breakages provide high accuracy in the prediction. At the same time, as the 1-month change percentage has smoother fluctuations, it will affect the prediction at a lower accuracy rate. It is normal for the 3-month percentage change of the used variables to predict the next month more accurately. In short, upon examination of the

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S. E. Ta¸sabat et al.

Table 21 RFM model S (Sensitivity) positioning model samples—sales status summary Customer ID RFMS score RFMS score RFMS score RFMS score Realization status of sales ID 143

5354

5345

5435

4535

1

ID 336

3142

3124

3214

2314

1

ID 24

4243

4234

4324

3424

1

ID 440

4235

4253

4523

5423

0

ID 990

3143

3134

3314

3314

1

ID 651

5314

5341

5431

4531

1

ID 253

4453

4435

4345

3445

0

ID 177

3242

3224

3224

2324

0

ID 708

4143

4134

4314

3414

1

ID 860

4133

4133

4313

3413

1

monthly and 3-month USD change charts, it is determined that the sharp decreases and increases are observed more clearly in the 3-month chart. Figure 9 shows the 3-month change rate of the USD exchange rate before the sale date and the course of sales frequencies. The reason for using a 3-month change rate in the model is that it reflects economic indicators in the most appropriate way and has the closest explanation on sales. By integrating into the model with different coefficients in order to position the “S” (Sensitivity) correctly in the RFM model, past sales dated 01.2014 and 07.2019 have been tested. According to the calculated different score results, it was decided that the closest sensitivity effect was in Formula (8) in the relevant model equation. Table 21 is sample 10 according to the sales situation of customers on 07.2019. In the RFM model, different S positioning and sales realization situations are given. The conclusion is that the score positioning in Formula (8) is more meaningful. In Table 22, the data prepared for RFMS analysis of the first and last 10 customers in the dataset are provided. RFMS scores were calculated using the Python programming language over the data prepared using this method. Table 23 shows the sample list of the first and last 10 customers regarding the results. In Table 23, some of all customers that have been graded are given as an example. It can be aimed to reach customers by making score selections in line with the relevant strategies and objectives.

5.6 Test In order to see the effectiveness of the RFM model, following necessary data arrangements, the RFM scores were calculated with Model (2) using sales data on different

A New RFM Model Approach: RFMS

169

Table 22 Dataset prepared for RFMS analysis Customer ID

Recency

Frequency

Monetary

Sensitivity

ID 1

08.2018

22

EUR 2,180,424.32

−0.05

ID 2

12.2018

35

EUR 8,120,111.90

−0.25

ID 3

11.2016

2

EUR 300,360.76

0.21

ID 4

07.2019

17

EUR 1,320,444.11

−0.17

ID 5

07.2018

3

EUR 2,012,344.67

0.03

ID 6

05.2016

11

EUR 500,360.76

0.03

ID 7

04.2017

4

EUR 1,590,424.32

−0.01

ID 8

05.2016

5

EUR 5,321,043.10

0.03

ID 9

01.2018

9

EUR 890,980.33

−0.05

ID 10

06.2018

5

EUR 300,122.00

0.35

–

–

–

–

–

ID 3252

01.2019

3

EUR 291,875.00

0.01

ID 3253

12.2017

2

EUR 535,000.00

0.06

ID 3254

11.2017

10

EUR 4,832.987.00

0.05

ID 3255

04.2018

11

EUR 5,202,765.00

0.03

ID 3256

12.2016

4

EUR 300,330.00

0.25

ID 3257

09.2018

12

EUR 5,100,900.13

−0.28

ID 3258

05.2018

3

EUR 500,367.00

0.24

ID 3259

11.2018

2

EUR 467,980.00

−0.38

ID 3260

12.2017

8

EUR 465,976.44

0.06

ID 3261

01.2019

13

EUR 1,678,124.22

0.01

segments of customers at different dates. As a result, a comparison of the relevant dates and frequencies was made. Table 24 is the sales status and RFM scores of sample 10 customers on the respective date. Based on this, it can be said that “the best predictor of future customer behaviour is past customer behaviour” (Swearingen 2009). When the Variant (8) Borusan CAT RFMS model, which is the newly developed method and proposed in the RFM and study in different segment groups, was tested, it can be observed that the RFMS model success rates increase significantly to 76%, 79%, 83%, 72%, 86% and 75%, respectively, compared to the prediction success rates of the RFM model (Table 25). Consequently, it can be said that the efficiency of the Borusan CAT model is higher.

6 Conclusion Data analysis contains important points regarding the accurate, effective and proper use of data and what to do with information rather than the data size. Analysing data

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Table 23 RFMS scores results Custome r ID

Recency

Sensitivity

Frequency

Monetary

RFMS score

ID 1

4

3

5

2

4352

ID 2

1

2

2

5

1225

ID 3

2

5

3

1

2531

ID 4

3

5

4

5

3545

ID 5

1

4

1

1

1411

ID 6

3

3

3

2

3332

ID 7

3

1

4

5

3145

ID 8

1

1

3

1

1131

ID 9

4

2

5

3

4253

ID 10

5

1

5

1

5151

–

–

–

–

–

–

ID 3252

3

5

4

2

3542

ID 3253

1

2

2

5

1225

ID 3254

3

3

2

5

3325

ID 3255

4

3

3

5

4335

ID 3256

1

4

2

1

1421

ID 3257

3

4

4

5

3445

ID 3258

4

5

3

5

4535

ID 3259

4

2

1

2

4212

ID 3260

5

2

3

4

5234

ID 3261

5

1

5

1

5151

is essential so that we can make smart and future-oriented decisions. The process of scanning by separating useful information from accumulated information is the summary and importance of data mining. Analysing data with methods in accordance with the purpose of the company will enable a great return. Today, data analysis has gained importance and value through development of Industry 4.0 and tendency to “customized product”. Companies also tend to make analyses using appropriate techniques. In this study, where the RFMS analysis is included in data mining techniques, customers are segmented according to their purchasing value on the RFMS scale based on customers’ purchasing habits. As a result, potential customers who could contribute the most to campaigns and services were determined. Evaluations and suggestions relating to customers’ behaviour are included. As can be seen from the test results, Model (8) correctly predicts the customers whom sales have been made in the next month with an average success rate of 78.5%. With this method, the relevant strategy can be applied by focussing on high-potential customers. As a result, the biggest action to be taken is offering campaigns and services to users known to be

A New RFM Model Approach: RFMS Table 24 RFMS scores test results

Table 25 RFM-RFMS test success rates according to the segments between 01.2014 and 10.2019

Customer ID

171 RFM score

Realization status of sales

ID 1

452

1

ID 2

125

0

ID 3

231

0

ID 4

345

1

ID 5

111

0

ID 6

332

0

ID 7

345

1

ID 8

131

0

ID 9

453

1

ID 10

551

1

–

–

–

ID 3252

342

0

ID 3253

125

0

ID 3254

325

0

ID 3255

435

1

ID 3256

121

0

ID 3257

345

0

ID 3258

435

1

ID 3259

412

1

ID 3260

534

1

ID 3261

551

1

Segment

RFM-success rate

RFMS-success rate (%)

KAM

70

76

GIKA

65

79

MMM

68

83

RETAIL

59

72

MARINE

76

86

ELECTRIC POWER

71

75

valuable. Thus, creating a beneficial seller-customer relationship with the speed of sales transactions is aimed by re-targeting customers in less time.

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References Birant D (2011) Data mining using RFM analysis, knowledge-oriented applications in data mining. Prof. Kimito Funatsu (ed). InTech. ISBN: 978-953-307-154-1 Bult JR, Wansbeek T (1995) Optimal selection for direct mail. Mark Sci 14(4):378–394. ISSN: 0732–2399 Cheng CH, Chen YS (2009) Classifying the segmentation of customer value via RFM model and RS theory. Cilt 36(3) (April 2009):4176–4184. ISSN: 0957-4174 Chuang H, Shen C (2008) A study on the applications of data mining techniques to enhance customer lifetime value—based on the department store industry. In: Proceedings of the 7th international conference on machine learning and cybernetics, Kunming, China, July 2008, IEEE, pp 168–173. ISBN:978-1424420964 Fan Y (2016) RFM analysis in R Math 3201 data mining foundation Ha SH (2007) Applying knowledge engineering techniques to Customer analysis in the service industry. Adv Eng Inf 21(3) (July 2007):293–301. ISSN:1474-0346 Hosseini SM, Maleki A, Gholamian MR (2010) Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty. Expert Syst Appl 37(7) (July 2010):5259–5264. ISSN:0957-4174 Internet: IBM Watson Studio ile yapay zekanın gücünden istedi˘giniz ölçekte yararlanın. https:// www.ibm.com/tr-tr/marketplace/watson-studio Internet: Necip Murat (2017) Hamileden Önce Hamileli˘gi Bilen Marka Target. https://pazarlama syon.com/hamileden-once-hamileligi-bilen-marka-target/ Internet: Yenilik analizi, Sıklık analizi ve Parasal (RFM) analiz ayarlama (2017). https://docs.mic rosoft.com/tr-tr/dynamics365/unified-operations/retail/set-up-rfm-analysis McCarty JA, Hastak M (2007) Segmentation approaches in data-mining: a comparison of RFM, CHAID, and logistic regression. J Bus Res 60:656–662 Miglautsch J (2000) The journal of database marketing on May 28 Olson DL, Cao Q, Gu C, Lee D (2009) Comparison of customer response models. Ser Bus 3(2):117– 130. 10.1007/s11628-009-0064-8 Swearingen C (2009) 101 powerful marketing strategies for growing your business now! SmallBiz marketing services, pp 24–27 Tsai C-Y, Chiu C-C (2004) A purchase-based market segmentation methodology. Expert Syst Appl

Assessing the Impact of Artificial Intelligence in e-Commerce Portal: A Comparative Study of Amazon and Flipkart Sachin Gupta, Shreya Singhvi, and Giuseppe Granata

1 Introduction Artificial Intelligence can be defined as a stimulation of human intelligence in mechanical things in which they are made to perform like human beings enabling the behavior related to thinking and acting like human beings. The enabling of AI can also inculcate analytical and problem-solving techniques in machines. In his article, “Artificial Intelligence,” Copeland defined AI as “AI is the capability of a computer to act like a human mind and take decisions intelligently. The computer develops the ability to reason, figure out meanings and act like human characteristics.” (Copeland 2020). The graph (Fig. 1) shows the growth in technology based on AI in various countries in which India still needs to make a striving space.

2 History of AI AI has existed in our surroundings since the ancient Egyptian and Greek times. Some milestones in the history of AI and its path through different generations are enlisted below (Fig. 2).

S. Gupta (B) Mohanlal Sukhadia University, Udaipur, Rajasthan, India e-mail: [email protected] S. Singhvi Faculty of Management Studies, Mohanlal Sukhadia University, Udaipur, Rajasthan, India G. Granata Business Management and Marketing, University Mercatorum, Rome, Italy © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_10

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Fig. 2 History of AI Source JavaTpoint

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2.1 Phases of Artificial Intelligence (1943–1952) . 1943: In 1943, AI first came into picture and was introduced by Warren McCulloch and Bruno Walter Pits. They proposed the model of artificial neurons. . 1949: Donald Hebb developed the Hebbian learning rule and also incorporated changes in defining strength between neurons . 1950: Alan Mathison Turing was an associate English scientist at World Health Organization and introduced Machine learning in 1950. Alan Mathison Turing printed “Computing Machinery and Intelligence” to take a look at how the machine’s ability will behave to exhibit intelligent behavior (JavaTpoint 2017).

2.2 Birth of Artificial Intelligence (1952–1956) . 1955: Allen Newell and musician A. Simon created the “first AI program” that was named as “Logic Theorist.” The program researched 38 out of 52 arithmetic theorems and observed the changes and deviations in a few theorems. . 1956: John McCarthy at the Dartmouth College Conference coined the term “Artificial Intelligence” and became the author of AI and introduced AI for educational purpose. Finally, AI started enjoying the heights and getting recognized as a booming field (JavaTpoint 2017).

2.3 The Golden Years-Early Enthusiasm (1956–1974) . 1966: The first chatbot was ELIZA developed by Joseph Weizenbaum. . 1972: An intelligent robot was built in Japan named as WABOT-1 (JavaTpoint 2017).

2.4 The First AI Winter (1974–1980) . The time period from 1974 to 1980 was the first AI winter which indicated shortage of funds for AI research (JavaTpoint 2017).

2.5 A Boom of AI (1980–1987) . 1980: At the end of this era, AI grew with “Expert System.” Professional technology was designed for enhanced decision-making. . In 1980, the first national conference of the Yankee Association of Computing was held at Stanford University.

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2.6 The Second AI Winter (1987–1993) . AI again saw a setback between 1987 and 1993. . In this period, Investors and government stopped in funding for AI analysis as the cost involved in research was very high (JavaTpoint 2017).

2.7 The Emergence of Intelligent Agents (1993–2011) . 2002: For the first time, AI entered the households with Roomba, a vacuum cleaner with AI technology (JavaTpoint 2017). . 2006: AI expanded its wings to the Business world and become an integral part at companies like Facebook and Netflix (JavaTpoint 2017).

2.8 Deep Learning, Big Data Analytics and Artificial Intelligence (2011-Present) . 2011: In 2011, IBM developed Watson which won Risk, a quiz show, where it solved logical reasoning questions. Watson could evidently prove that it may understand linguistic communication and solve questions fast. . 2012: Google launched “Google now,” which could be used as a predictor by customers. . 2014: Chatbot “Eugene Goostman” won a contest within the “Turing Test.” . 2018: The “Project Debater” from IBM had a debate on difficult topics with two ace debaters and apparently showed brilliant results. . Google launched “Duplex” which could provide assistance virtually and had taken artificer appointment on decision, and the girl on a different facet did not notice that she was conversing with a non-living machine (JavaTpoint 2017). In today’s era, AI has developed to an important place in lives of people. The constructs of Deep learning, Big Data, and Knowledge Science are on a boom. Today corporations like Google, Facebook, IBM, and Amazon are optimally using AI and make wonderful changes to the world.

3 Artificial Intelligence Applications Artificial Intelligence has become a part of our daily lives, but has been used in certain areas from a prolonged time. Some of the applications of AI are enlisted below:

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. Speech Recognition: Popularly known as speech to text (STT), speech recognition is a technology which converts words to text in digitized form. Voice Recognition is the plug-in that it is used by laptop dictation software system, TV voice remotes, text electronic communication and GPS with voice, and voice-driven phone responsive restaurant menus. . Natural Language Process (NLP): NLP is an application used for interpretation of human text. NLP is the technology used in Siri or chatbots, and other textbased voice apps. A few natural language processors also benefit from sentiment analysis to judge the mood, opinion, or other semantics in language. . Image Recognition: It establishes and classifies things, humans, handwriting, and even actions among fixed or not fixed pictures. Generally driven by deep neural networks, image recognition is an integral part of fingerprint ID systems, Mobile Banking apps, Image analysis, etc. . Real-time Suggestions: Retail sites use structural networks to suggest extra purchases to charm a client supported by the customer’s surfing history, the surfing activity of other customers, and other independent factors, as well as point of time and climate. It has been inferred that online suggestions result in increased sales. . Virus and Junk Safeguarding: The technology based on structural knowledgeable systems, in the modern era virus and junk safeguarding system uses in-depth structural networks which will be effective in detecting new sorts of virus and cybercrimes and frauds. . Taxi or Car Services: Uber, Ola, and alternative taxi services use AI to allot passengers to drivers to calculate queuing times, offer reliable ETAs, and even intimate the surged prices. . Household Robots: Robots use AI to analyze space, avoid obstacles, and learn the best way for vacuuming floor. Same technology is also used in robotic field mowers and pool cleaners. . Autopilot Technology: AI is an integral part of flying business and military craft for many years. Autopilot uses mixture of sensors, GPS technology, image recognition, and collision rejection technology, and robotics, associate degree language process to guide a craft safely and update the human pilots.

3.1 Artificial Intelligence in e-Commerce AI is beginning to enter the overall arenas of our lives. Several e-commerce sites use different kinds of AI to analyze the client demand and attitude and attain better customer satisfaction. AI is employed in numerous fields of e-commerce with totally different applications and uses like period of time, Product chase, and Visual Search. The Applications of AI in e-commerce are enlisted below: (1)

Real-time product targeting: Online Retail websites provide an improved experience in online mode, by appealing client and providing that straightforward interface as client will notice interested product simply. Machine learning

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algorithmic rule aids e-commerce trade by providing totally diverse methods for merchandise commendations, markdowns, and numerous bargains. Visual search: Image recognition is range of AI wherever in e-commerce it supports clients for looking any merchandise by victimization picture, rather than getting into manuscript to contest the applicable merchandise. Client will find merchandise simply through the appropriate picture. Pinterest is an example extensively using this technology. Image recognition software package equals client request and displays like things. AI-centered Recruitment Procedures: HR department’s work will reduce; using AI in many means for illustration, categorization of CV, screening CVs, filtering CVs apt according to job description, and arrangement of personal interview are performed automatically through AI. This eradicates the extra efforts of departments, and hence, AI helps in choosing the right candidate. Voice Search: Speech recognition is primarily voice-based search and surrogates the traditional word-centered exploration in online searching. Voice recognition precision is refining everyday. A few instances of speech-measured personal assistants are Apple’s HomePod power driven by Siri and Amazon’s Echo power driven by Alexa (Das et al. 2015). Assortment Intelligence Tool: Dheeraj Kapoor in his research stated that Assortment or Collection planning helps the retailers to provide a better combination to the customers enhancing customer satisfaction. The demands and purchase patterns of customers are dynamic. Proper planning enables retailers to understand continuation or dropping of products. The system enables the retailers to retain customers and find pressure points of customers for retention. Assortment Planning system also helps retailers to keep a check on their competitors in real time. The systems are based on Artificial Intelligence, Sentiment Analysis, Image Recognition, etc. (Dheeraj Kapoor 2016) Offer Human Touch with Chatbots: A colossal change in technological methods modified customer’s needs, and today, E-business is additionally focused on evolving the methods that cater to the desires of each individual. The analysis is done whether the client wants to make the purchase in single session or not. The E-retail websites develop an easy user interface to attract client and create a human contact with the client. In this era, E-business currently develops a convergence of graphic demonstration, speech acknowledgment and recognition, and prognosticative skills. Efficient utilization of AI in E-retail website or apps “chatbots” is one of the excellent features that AI enables that take spoken language in this upcoming era of relaxed business. Virtual Personal Shoppers: Computer-generated distinct customer will help in selection making process and for this Flipkart introduced Ping. Ping helps the customers to notice the items they are looking for. In addition to this, Amazon also has Alexa serving as virtual shopper assistant. It enables customers by using their voice to place requests for orders. Another such assistant is Anglesea. Anglesea absorbs the design shoppers are appealed to and then presents the best matching products.

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AI Faux Reviews Detection: Client review is a very important part of building trust and loyalty in other customers while making a purchase. Positive feedback on products increases the chance for purchase of product. Nevertheless, there can also be probabilities of false or unreal feedback which affects the purchase of product adversely. AI can be effectively used to filter out the faux reviews and also filter out the authentic customer reviews to enable an increase in sales of products. (9) AI-based Sales Process: AI works in sync with other processes like CRM and SCM to keep a track of sales in e-commerce Industry. The blends of these software with AI help in increasing sales and also tap on new options that can be tapped upon by the sales force. The websites will observe and provide right product for the right customer avoiding the unwanted products during online shopping. (10) Localize the Customer Experience: The world believes in the motto of Go Vocal for Local and similarly AI uses local interests of the customers in consideration while giving suggestions. For example, an app named WayBlazer, a tourism-based application, uses AI to connect B2B companies to various hotels, and other travel requirements who want to expand their business and generate more revenue. Another example is Watson, developed by IBM, and also gives local suggestions. Gawali in his paper “Artificial Intelligence in E-Commerce” stated that “Personalizing the outcomes enables to delete extra information and keep only the important information to the customer. This enhances the customer experience by enabling better product selection process.” (Gawali 2019)

3.2 AI at Online Retail A cutthroat competition prevails in the Internet-based shopping industry. Every passing day, new apps are launched or new brands are added to the list everybody hoping they can carve their own niche in the overly crowded Internet industry. Even, the well-established retail stores are thriving hard to make their online presence. As a result, a lot of techniques are adopted to enhance value of customer’s experience and money.

3.3 AI at Flipkart In its report, the tech consulting giant, Redseer Consulting stated that Flipkart shares 47% in the Indian Internet commerce industry leaving behind Amazon which has a share of 33% (Consulting 2020) (Fig. 3). Flipkart is a leading e-retailer, and AI is the future for Flipkart. Flipkart has recently Walmart has acquired a stake of 77% in Flipkart by paying US$16 billion

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Fig. 3 India’s retail market share of gross merchandise value Source Redseer Consulting

which will Walmart to take advantage of AI to understand motivators behind client purchases both rational and irrational (Nausser 2020). Taking appropriate usage of AI to analyze large volumes of data will help in better understanding of tastes and preferences of customers which has been a key point for Flipkart’s success since 2007. Flipkart uses this customer information to boost its online searching expertise, together with that product it offers yet as wherever it ought to focus its innovation efforts. AI has proved to be a major asset to Flipkart in creating enriching shopping experiences. By October 2019, mobile app of Flipkart acquired a hundred million downloads on the Google Play Store, making it the first most downloaded e-commerce app. Flipkart gains major part of its traffic via app. The business giant launched AI for India in 2019, to grab the chance of creating an effective money minting business from the growing numbers of digital users and leveraging increasing mobile users in the country. By launching AI for India, Flipkart is using AI technology sharply to create a difference in providing services and better user experience and have efficient back-end processes. The factor which makes a difference in E-business industry is the players providing things cheaper, better, or quicker. Flipkart’s AI for India craves to use AI to enhance client handling and fight the local Indian problems. There are a number of enhancements the corporate has invested in because it works toward its goal of achieving a hundred million customers, one thing the home-grown Internet supermarketer is compelling to respond to its biggest competitor Amazon India. It is aforementioned that knowledge is the fodder for AI and Flipkart generates 10–15 Terabytes of information enabling economical usage of massive knowledge. Analytics managed by AI specialists are employed from high notch institutes of the planet. Flipkart has conjointly partnered with Microsoft for development of Azure, a cloud ADP system victimization machine learning, and AI systems to modify optimized commercialism and order placement making certain and optimum show of product. It conjointly uses voice search and image look for higher interface for patrons.

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With optimal use of AI and related technologies, Flipkart has been able to achieve the following outcomes: 1. Personalized Search Recommendations Flipkart makes use of AI to customize suggestion for its customers. The giant is making efficient use of Image Recognition, an advanced AI technique for recommendations, product search, and grouping of products. It has also been observed that use of the booming technology has added another level of customization to firm’s efforts for capturing customers. It has also invested in development of product search facilities. The advanced models will enhance patterns for searching products, product feature preferences, purchases made, and conversion rates. This will enhance the overall shopping experience of customers. As a result of this, AI suggestions have already shown a rise of ten times in clicking rate of Flipkart. Flipkart also uses an advanced technology Natural Language Process (NLP) which uses and understands language used by humans and automatizes the processes. NLP is extensively used in the review or help section of giant and also helps in notifying faux reviews. The major target of the business is to achieve the popularity in the non-English speaking population sets of India. For this, it is trying to develop a technology which can enable understanding in local languages for Indian population. Flipkart’s virtual associate Mira has been making use of all customer interactions and providing end-to-end solutions for customers. Flipkart dreams of fulfilling and figuring out potential buyers and queries of customers acknowledge personalization, create a unique online experience for customers, and reduce cart abandonment and returns. Mira has increased the levels of customer satisfaction, increasing cart addition by 12%. Utkarsh, another feather in cap of Flipkart, using Utkarsh, recently controlled computing to enhance the quality of products sold by its huge number of sellers. Spokesperson from the company specially visited the sellers and acquired appropriate information to make the process more seamless. The data was thoroughly analyzed, and then, the inferences were drawn to increase product quality and reduce returns. An enhanced network of AI has helped Flipkart to establish high levels of customer need satisfaction and customization. The advanced technology has also helped in reducing returns and attained good reviews about products. This appropriate and extensive use of technology has put a step forward for Flipkart giving it a chance to carve a niche in the booming e-commerce industry. 2. Use of AI to Recognize Challenges and Opportunities The major issue with Indian topography is to find the exact location of delivery. With use of AI, the retailer has nailed the accuracy of location addresses to 98%, which has reduced the average delivery time by three hours at hubs. The

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technology is not only used for personal usage but has also helped Police department in targeting resellers committing frauds and crimes. Flipkart has nailed the customer satisfaction and timely delivery which is very necessary for to be successful in e-retail industry. 3. Recognizing Buyer Problems and Providing Solutions on AI-Derived Information Advanced use of technology has helped the big retailer to get deep into customer’s minds rather than using hours of manual research. The reviews and purchase behavior of buyer id thoroughly examined to create differentiated products to satisfy customer needs. This has equipped the Internet retailer to provide a huge variety of products with superior quality at cheaper prices. The Internet retailer has launched its own brands to provide products at lesser cost with superior quality. This power of Flipkart over has enabled the giant to directly hit the customer needs and become their first choice. The e-commerce site has set up homegrown own brands in all fields ranging from apparel to technology products. One of the brands is Billion which is a brand launched on the basis of the AI-generated information. For instance, Billion launched phones on the basis of customer reviews and provided enhanced features like better battery life, camera quality, and better storage. The techie also launched a brand named Moda Rapido under Myntra which is India’s first brand developed solely on the basis of customer insights and specifications. AI information has also helped the styling and innovation department at Myntra and has reduced the timing from six to one month. AI has deliberately been really helpful in judging the likeable colors and patterns. Another milestone on basis of AI information and analytics is launch of three more brands namely Metronaut, Anmi, and Divastri by the e-retailer. The website has efficiently used the data and is analyzed to answer the questions related to customer choices and demographics. The queries technology will answer which will be as extensive as “What are the demographics of an individual WHO wears a mandarin collar?”, to “What color works that demographic?”, and even, “What materials see the foremost returns?”. The advanced technology has supported the big retailer and has also helped the sellers registered. It has become easier to find a product and also calculate demand on basis of customer clicks and calculate Revenue Per Impression (RPI).

3.4 AI at Amazon Amazon is one of the leading e-commerce websites in the world with its operations pan world. The business giant knows how to use AI to its benefit in increasing sales. The brilliant projects like Alexa and Amazon shopping apps have in definitely helped customers to become more user-friendly with the app.

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Amazon has been able to increase its overall efficiency, maximize profits, and provide customer-centric solutions. Amazon has seen extensive growth. In the yesteryears, the yearly revenue of Amazon India in the year 2020 was INR 7593 crores (Bhalla 2020). Chatbots are popularly used by e-commerce websites, and Amazon has developed Amazon Lex to cater to this technology. Chatbots effectively analyze human voice and develop interactions. Chatbots are also popularly used in client servicing and engagement. Amazon Lex is the chatbot developed by Amazon to connect customer to client servicing. It uses voice recognition and digital text conversion to effectively answer customer queries and create an enriching customer experience. This application adds a new paradigm to better customer interaction. In his prolonged thesis on use of AI in E-Commerce: Case Amazon, Anh Tran revealed that “Lex is utilized in completely different cases like connect with enterprise applications to receive promoting information, or client will scan customer’s banking data, or career Amazon contact center. Once victimization Amazon Lex, the client will set up appointments, modification name or countersign, and requesting getting history from Amazon account. These chatbots will acknowledge client’s speech and interpret customers. Additionally, it facilitates daily individual activities, for instance, booking building rooms or doctor appointments, and order books or personal stuff from users’ mobile phones, net browsers.” The following picture shows the use of Amazon Lex for calling center bots (Tran 2019) (Fig. 4). Amazon also launched Amazon Personalize which is basically a type of suggestion portal which can be extensively used for enhancing suggestions while a customer is placing orders supported by customer’s online insights. As stated on the Aws Amazon website, “In Amazon Personalize, customers will offer associate degree activity stream from their performances like getting data, views, and also product the company need to recommend to the others like books, music, cosmetics, or videos. Besides, consumers can even give a lot of data like age, gender, and region. The system can establish customers’ information and choose correct algorithms. Finally,

Fig. 4 Amazon personalize statement Source Aws Amazon Lex

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it will optimize a personalization guide that is custom-made for customers’ information, and it will lead the shoppers to an area wherever they will see the suggestions by things giving, ranking of things and that product are counseled.” (Personalize 2019). This app increased the level of personalization and also gave in the cart suggestions that could be useful with the already existing products in the cart. Amazon is leading in the field of warehouse automation and has plenty of fully automated robots to work in its work fields. Amazon has also very recently declared delivery of products also by using robotics. Nick Wingfield in his article, “As Amazon Pushes Forward with Robots, Workers Find New Roles” expressed that “In 2014, Amazon started Robots in its distribution centers created by Kiva Systems, a corporation Amazon purchased for $775 million 2 years sooner and renamed Amazon Artificial Intelligence. Amazon presently has concerning 100,000 robots in the world. Machine-driven robots will gambol with vertical racks jam-choked with stock advisement up to 2000 kg on their backs. All of them work autonomously within an enormous place, following each other but not impacting.” (Wingfield 2017). Another astonishing AI usage of Amazon is Amazon Echo which is a virtual shopping assistant tool as known as Alexa. Alexa is a popular name in all households of India today. It not only has enhanced the overall shopping experience but has also been successful to identify needs and tastes of consumers. According to Statistic Portal, “customers are very satisfied by using Alexa and the skills of Alexa have developed from only 130 skills to upon over 80,000 skills from 2016 to the end of 2018.” (Statista 2018). Another shopping associate app of Amazon is Mona which was an app developed by former Amazon workers. A perfect blend of human intelligence, bigdata, and AI was used in Mona making it super-efficient. Mona was flexible and reliable. The app had the ability to understand the mindsets of a customer by using data from purchase types, brands preferred, and the feedback given by customers. An extensive use of Mona ensured better customer satisfaction. It has been evident that AI has become an integral part of customer’s life as well as e-commerce industry. With optimum use of AI data, the big retailers have gathered the insights and data required to capture the right customer, tap the potential customer, and provide maximum customer satisfaction.

4 Comparative Analysis Between Flipkart and Amazon . Using AI to Predict Sales In February 2020, Flipkart tied up with Redmond Big to develop cloud computing software with the name “Azure.” Microsoft also invested a whopping $200 million to develop the technology. Vinay YS, VP engineering at Flipkart confirmed that “the corporate was searching for ways in which to optimize commerce and supply placement management using AI and Cloud Computing.” It was also confirmed that Flipkart is looking at developing an advanced AI-based system which will

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help consumers in making better choices while ordering and delivery. This will also help the retailer to scale up prices and provide better quality. Further adding to this, principal mortal Krishnendu Chaudhury told daily, “the corporate is building technology to predict sales, or what percentage units of a particular product can sell.” A patent has not been filed by the company regarding such a Sales Prediction Engine. On the contrary, Amazon has a well-developed SPE which helps the e-retailer right from the beginning of purchase process. A proper patent regarding Amazon’s SPE has been filed in 2012. The technology used in SPE enhances address accuracy, inventory management, price management, and shipping partners. The prediction model uses the data stored on website like time lapsed on website, products clicked, order details, and matches with the real-time client data to develop a proper Decision Support System for the preferred products. . Voice Commerce Amazon has entered the voice recognition industry years with back with its popular Amazon Alexa. Alexa has become a huge waive in India as Amazon has leveraged upon using the local languages for understanding the human language signals. Parag Gupta, Head of Product Management for Amazon devices in India, expressed “We wished our devices to speak, walk and feel Indian. Alexa isn’t a visiting Yankee, she includes a terribly Indian temperament,” indicating the localization of product. Amazon has been pioneer for introducing voice-enabled devices in India and has enjoyed the first mover advantage. It is indeed a step ahead in the voice recognition industry which will be very beneficial for bridging the gap between customer expectations and product sales. Whereas, Flipkart has not yet entered the field of voice assistance and announced the launch of Mira in the year 2017. Flipkart is looking at benefits like customer preferences, cart abandonment, and accurate deliveries with help of Mira. Mira will be a blend of modern voice technology and human intelligence. Ram Papatla, VP, Product at Flipkart, shared this to money daily, “This February we have a tendency to launch the primary version of our colloquial search expertise. Now, our users with broad intent (searching for, say, shoes or bed sheets) are guided by relevant queries, colloquial filters, looking ideas, offers and trending collections.” . Product Recommendations Amazon has been using Collaborative Filtering approach which is based on itemto-item optimization. It is different from the traditional filtering as it is independent of the number of consumers vis-à-vis the number of products available. Amazon on the contrary uses real-time recommendations based on algorithms run by website using available data and extensive knowledge sets. Amazon also believes that product suggestions are a major targeting tool for capturing customers. On the other hand, Flipkart has laid more emphasis on visual display suggestions. It has developed a technology in which a customer can look for similar products simply by uploading the reference image in the search button of the website.

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Table 1 Basis

Flipkart

Amazon

AI to predict sales

For proper inventory management, it has developed Azure, cloud computing software in collaboration with Microsoft

Amazon has filed a patent for Sales Prediction Engine which not only provides inventory management but also captures information on shipping-related information based on prediction model

Voice commerce

It will launch Project Mira to enable product orders and deliveries. Project Mira will additionally attempt to unravel cart abandonment and frequent returns

It has its own digital voice-assistant Alexa which is very popular with the customer and uses stimulations according to customer’s voice for performing tasks

Product recommendation

It has developed a technology in which a customer can look for similar products simply by uploading the reference image in the search button of the website. The algorithm then shows results by matching the image with the available product catalog and gives appropriate suggestions for the product

It has Collaborative Filtering approach. Amazon uses real-time recommendations based on algorithms run by website using available data and extensive knowledge sets. Amazon also believes that product suggestions are a major targeting tool for capturing customers

Source Compiled by Author

The algorithm then shows results by matching the image with the available product catalog and gives appropriate suggestions for the product. This visual search technology is very popular in Fashion section of the E-retailer. To further enhance the system, the giant has also collaborated with IIT, Kharagpur, for development of our commender that helps in upselling of products and places better products in the minds of consumers (Table 1).

5 Conclusion It can be concluded that Flipkart and Amazon both are using AI and related aspects efficiently and effectively to create better customer experiences. They are both making the optimum use of technology with different targets and methods to collaborate and make the search and experience more comfortable for the users and create a customized local belonging feeling among the customers. Talking of the similarities, both companies have a clear vision of developing better customer satisfaction. Whereas, if the differences are looked upon, the way of targeting is different as Flipkart focuses on better search and less cart abandonment and Amazon focuses

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upon Product varieties and recommendations. It is also clear from the chapter that Amazon is slightly ahead in the field of Voice Recognition. Also, the inventory management systems of both sites are profound but both use a different approach. It can be concluded that both the companies have their own strength and weaknesses and they are excelling in the fields.

References Bhalla K (2020, Dec 25) https://inc42.com/. Retrieved April 23, 2021, from https://inc42.com/buzz/ amazon-india-deeper-in-the-red-in-fy20-as-flipkart-reduces-losses/#:~:text=The%20online% 20marketplace%20unit%20of,in%20the%20same%20time%20period Consulting R (2020, Nov 27) https://www.businesstoday.in/. Retrieved April 20, 2021, from https://www.businesstoday.in/current/corporate/flipkart-did-better-than-amazon-in-festive-saleredseer/story/420083.html#:~:text=According%20to%20a%20report%20by,from%20%242.7% 20billion%20last%20year.&text=As%20anticipated%20tier%202%20and,consumption%20r Copeland BJ (2020, Aug 11) Artificial intelligence. Retrieved April 23, 2021 from https://www.bri tannica.com/technology/artificial-intelligence Das S, Day A et al (2015) Applications of artificial intelligence in machine learning: review and prospect. Int J Comp Appl:31–41 Dheeraj Kapoor RG (2016) Software cost estimation using artificial intelligence technique. Int J Res Dev Appl Sci Eng Gawali SN (2019) Artificial intelligence in e-commerce. Int J Manage Econ:15–17 JavaTpoint (2017, Jan 1) https://www.javatpoint.com/history-of-artificial-intelligence. Retrieved April 24, 2021 from https://www.javatpoint.com/history-of-artificial-intelligence#:~:text=Mat uration%20of%20Artificial%20Intelligence%20(1943%2D1952)&text=They%20proposed% 20a%20model%20of%20artificial%20neurons.&text=Alan%20Turing%20publishes%20%22C omputing%20Machinery,intel Nausser S (2020, July 23) https://www.wsj.com/. Retrieved April 23, 2021 from https://www.wsj. com/articles/walmart-sells-its-indian-stores-to-flipkart-11595484002#:~:text=In%202018% 20Walmart%20bought%20a,Flipkart’s%20valuation%20to%20%2424.9%20billion Personalize AA (2019) https://aws.amazon.com/. Retrieved April 20, 2021 from https://aws.ama zon.com/personalize/ Statista (2018, Jan 1) https://www.statista.com/. Retrieved April 20, 2021 https://www.statista.com/ topics/846/amazon/ Tran A (2019, May 1) Artificial intelligence in e-commerce. Case Amazon. Glasgow. Centria University of Business Management, Glasgow, Scotland Wingfield N (2017, Sept 10) https://www.nytimes.com/. Retrieved April 23, 2021, from https:// www.nytimes.com/2017/09/10/technology/amazon-robots-workers.html

International Production and Digital Economy Namita Rajput, Vikas Garg, Jyotsna, and Shivani G. Varmani

1 Introduction 1.1 International Production The manufacture of goods and services in international locations and markets is referred to as international production. It entails a management process that must take into account the local manufacturing demand (labor and capital) as well as the needs of foreign customers. International manufacturing involves vertical production chains that cover several countries in the region, as well as multinational distribution networks. Corporate firms in the machinery industries. General machinery, electrical machinery, transportation equipment, and precision machinery are the examples of such industries and are the main factors, though some firms in other industries, such as textiles and garments, also contribute to the network (Czinkota/Ronkainen 2013). Multinational development improves global productivity and welfare by enabling innovations to be used where they are most suitable and allowing efficient countries’ technologies to displace less technologically capable countries technologies. Global production network is a significant organizational change in the global production N. Rajput (B) Sri Aurobindo College, University of Delhi, New Delhi, India e-mail: [email protected] V. Garg Amity University, Greater Noida, Uttar Pradesh, India Jyotsna Jagan Institute of Management Studies Sector 5 Rohini, GGSIPU University, Dwarka, New Delhi, India e-mail: [email protected] S. G. Varmani Bhaskarachara College of Applied Sciences, University of Delhi, Dwarka, New Delhi, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_11

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system. They have created growth opportunities for the countries and businesses involved, and they will have a greater effect on the politics, economy, and culture of these countries as a result of globalization. Ernst et al., for example, focused on the scale of development, power asymmetry, and technology diffusion in GPNs, as well as local supplier capability upgrades and developing country industrial upgrading (Morschett, Schramm-Klein, Zentes 2015).

1.2 International Product Strategies A foreign product strategy encompasses all decisions pertaining to the firm’s product and service offerings in the global market. It also requires decisions on the goods (or product lines) will be marketed in which countries, as well as standardization and customization of products (and product lines) and new product production. The cornerstone of the international marketing mix approach is also known as the international product strategy. Customers’ needs must eventually be fulfilled by the product and its core benefits; brand defects are seldom compensated for by the other elements of the marketing mix. The product strategy is often the starting point for marketing mix decisions. The decision to standardize or customize a communication strategy, for example, is often informed by the product’s standardized or locally adapted design. A wide range of tangible and intangible components go into the construction of a product. They include not only the primary physical properties, but also packaging, branding, and other augmented features including support services. There are many forms of foreign product strategy to consider. Companies have four choices for addressing foreign markets, depending on their overall marketing strategy. . Extending the home-grown product approach to foreign markets and marketing the same commodity globally. . Modifying goods for each local market in accordance with local needs. . A method of innovation that entails developing fresh products for the international market. . Combining all variations into a single versatile product design and launching a standardized commodity have four choices for addressing foreign markets, depending on their overall marketing strategy. The main question in this context is which commodity functionality should be adapted to business circumstances. In an international context, the probabilities and burden for standardizing commodity elements vary, with enhanced product features requiring the most adaptation and standardization of the core commodity (i.e., operable highlight, attainment) being the most straightforward. Companies may use commodity development schemes to reduce the price of customization by allowing them to change commodity to meet provincial specifications with minimal running costs. Modular design methods, for example, allow the company to produce unique products for each country’s market, based on a collection of globally standardized product components (Cui Fengru and Liu Guitang 2019).

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The development of a largely universal core product or framework to which local market-specific attachments can be added is the starting point for frequent platform advancement. The term “built-in versatility” refers to a policy that enables a standardized product to be marketed in each national market despite unique local requirements. All local variations are incorporated into one product, which adapts to local circumstances with aplomb (e.g., cellular phones that adapt to differences in voltage or different web work frequencies). Companies must also define their foreign commodity selection policy since most MNCs do not sell a single commodity but rather a line of commodities. It is important to decide on the width of the commodity lines, or the number of commodity ranges to be presented, as well as the depth of the commodity line, or the number of commodity or commodity varieties to be presented per commodity line, for each country market. In this sense, choices must be made between standardization and adapting the product selection to local needs (Cui Fengru and Liu Guitang 2019).

1.3 International Product Decisions A commodity is a visible or invisible good, service, concept, person, or location that individuals or organizations regard as so important, useful, or satisfying that they are willing to exchange capital, patronage, or another valuable product to obtain it. The term “product decision” refers to the features of a product as well as the different stages of its life cycle. Customer goals and culture views should be taken into account when making product decisions. India is a more cultural market, so an anti-culture product would have a negative impact on the company’s reputation. As a consequence, when making product choices, we must respect India’s truthful problems (Cui Fengru and Liu Guitang 2019). In international marketing management, essential product decisions are made. They are: . . . .

Market section decision Product combination decision Product features Positioning and communication decision.

A. Market Section Decision—Since all product blend decisions, product technical specifications, setting and communications decisions are dependent on the prospective market, the marketplace segment decision is the first product decision to be made. B. Product Combination Decision—The type of products and product combinations to be sold to the target market is decided by the product blend decision.

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C. Product Features—This includes specifications for each product item in the product mix. This includes aspects such as styling, shape, scale, and other characteristics, as well as aspects such as presentation and marking. D. Positioning and Communication Decision—The picture projected for the merchandise is known as positioning. Burgers may be categorized as veg burgers, non-veg burgers, cream burgers, or egg burgers, for example. The advertising idea for the product is defined through contact. Obviously, both the environment and the marketing contact are inextricably linked. When it comes to the same product, the positioning and communication techniques will differ between the markets. Physical goods, services, people, locations, organizations, and ideas are all examples of products that can be desired to sell for attention, purchase, use, or ingestion to satisfy a want or need (Aithal 2019).

1.4 Advantages of International Production Here are the seven benefits of international production: 1. Opportunity for additional sales. You gain access to a much wider customer base by expanding your company internationally. 2. The ability to assist a larger number of people. 3. Improved talent availability. 4. Getting to know a new world. 5. Foreign investment opportunities exposure. 6. Enhancing the image of your company. 7. Broadening the company’s market.

1.5 Product Life Cycle in International Market The international product life cycle (IPL) is a conceptual model that describes how a business grows over time and international border. This thesis depicts the growth of an enterprise’s marketing policies on both domestic and international platforms. Product life cycle marketing and international product life cycle provide lucrative concepts and degrees such as market growth and retrenchment, as well as product life process marketing and international commodity life process. The international product life cycle theory has four main elements: . . . .

A diagram of the product’s demand Producing the commodity Rivalry in foreign business Marketing plan.

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A company’s merchandising plan is in charge of origination or transformation every new commodity or concept. These components are categorized according to where the product is in the standard product life cycle. Introduction, development, full growth, overload, and decline are the phases.

1.6 Stages of a Product Life Cycle A commodity life cycle is determined by its sales volume, release, and development. These are constants of foreign business marketing, and they include the impact of outsourcing and global output. The various stages of a commodity’s life cycle in the international market are described below. Stage 1 (Inception) A new commodity is introduced in this stage in a target merchandise where the targeted buyers are unaware of its existence. Buyers who are aware of the commodity’s existence may be willing to pay a more price to obtain superior products or assistance. Because of the constant shift in manufacturing methods, production is entirely dependent on skilled laborers (Aithal 2019). Stage 2 (Growth) During the launch stage of the international commodity life process, there is no foreign competition. During the growth stage, competition arises as emerging markets begin to clone the product and sell it on the local market. These rivals may also move from foreign buyer to shipper in the same nation where the commodity was first launched. Stage 3 (Maturity) The level of product demand and sales volumes rise steadily at this point of the product life cycle. Duplicate goods have been identified in international markets, suggesting a decrease in export sales. The initial exporter cuts prices in place to retain market sales and dealing. Profit margins are declining, but the company remains appealing as revenue levels soar. Stage 4 (Congestion) At this point, the commodity’s sales have reached their peak and there is no way to raise them anymore. Congestion of sales characterizes this point (at first, sales seem to be steady, but then they begin to decline.) Sales will continue until replacements are available. Marketers must try to come up with new and different ways to use their commodities. Stage 5 (Diminish) The product life cycle comes to a close at this stage. At this point, market volumes are decreasing, and many of these items are being phased out or no longer used.

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Other countries’ economies that have produced goods that are close to or better than the very first trader’s export their products to the original trader’s local market. This has a bad effect on the initial product’s revenue and pricing structure. The very first trader will perform safely by vending the rest of the goods at the same rates as the discontinued ones.

1.7 International Product Branding Using uniform global ads and global marketing campaigns is referred to as global branding. It is basically a process of creating consistent international advertising and marketing strategies in order to create a commodity or assistance that is embraced internationally, regardless of the country, continent, or region in which it is sold. International brands are commodities or assistance that is well-known in the world. Enterprises use international trademark use the same, or at least a very similar, promoting strategy to promote the brand in every country or area where it is available (Aithal 2019). This aids businesses in ensuring that the ideals are a consistently across all markets.

1.8 International Branding Adapting on the Spot Reaching out globally and implementing an international trademark and advertisement plan can be intimidating for a small but rising enterprise. It does not have to be that way, though. Enterprises like the ones mentioned below have started out small but have benefited greatly from international trade marking. . . . .

Apple Starbucks Coca-Cola Ikea.

For example, Apple, Starbucks, and Coca-Cola have founded themselves as international trademark in several nations around the world. They have done so by employing international branding while tailoring or tweaking their message to suit the needs and desires of consumers all over the world. The international brands’ appearance and feel do not differ from one country to other country (Aithal 2019). Around the world, a Starbucks or Coca-Cola beverage looks, feels, and tastes the similar. However, these and other businesses are able to deliver the similar product, an international trademark, while tailoring the experience to the needs of their consumers in each nation and area. Challenges that company face while getting global: . The physical separation. . Cultures you have never heard about…

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Mastering the art of marketing. Communication inside the organization. Tariffs and export fees are two of the most important factors to consider. Human resource management. Selecting the right nations. Accepting the documents and matter to the culture properly.

1.9 Digital Economy Although we are increasingly seeing this as doing business across internet and World Wide Web markets, the term “digital economy” refers to an economy focused on digital computing technological advancements. The digital economy is also known as the internet economy, modern economy, or web economy. It is difficult to distinguish between the modern and traditional economies because they are so intertwined. It is the product of billions of daily online interactions between individuals, companies, computers, data, and processes. It is based on the internet, cellular phone technology, and the Internet of Things’ inter-connectedness of individuals, organizations, and machines (Aithal 2019). Extend of Information and Communication Technologies (ICT) through all industry section underpins the digital economy’s productivity. Traditional ideas about how companies are organized, how customers access services, information, and products, and how states must respond to these new regulatory challenges are being challenged by the digital alteration of the providence. The New Economy is another name for the digital economy. It is a form of economy in which economic activities are carried out using digital computing technologies. During Japan’s 1990s recession, a Japanese academician and investigation business analyst coined the word “digital economy.”

1.9.1

Structure for International Electronic Commerce

The structure for International Electronic Commerce promotes five principles that will direct the US government’s activities in electronic commerce in order to keep the digital economy’s development probable strong. The private sector’s leadership, the government’s avoidance of unnecessary limitation on e-commerce, restricted administration participation, the administration’s appreciation of the internet’s special qualities, and global e-collaboration are among the five principles (Mesenbourg 2001).

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2 Key Features 2.1 Company Roles Include Versatility The cost of planning and managing complex tasks over time has been greatly reduced thanks to developments in information and communication technology. Long businesses are increasingly able to run their global operations from a central location that is geographically separated from both the operations and the suppliers or clients.

2.2 Network Effect The “network impact” underpins this modern economic paradigm. When the value of a commodity or assistance to a customer increases exponentially in proportion to the number of other customers who use the commodity or assistance, this is called exponential growth. WhatsApp, for example, is a free networking network for personal contacts and other contacts.

2.3 Multi-sided Market The digital market is a market that can be described as “multi-sided.” This feature explains why these pages, which appeal to both customers and software developers or marketers, are able to offer their content for free. Each group’s activities has a positive or negative externality on the outcome of the other group in a market where multiple groups of people interact across networks as intermediaries. As end-users spend their hours on a website or click on links, the advertiser who places a banner there profits. Digital Multinational Enterprises (MNEs) raise money from advertisers rather than consumers by selling online advertising (Mesenbourg 2001).

2.4 Cashless Society A cashless society is one in which transactions are performed without the use of actual money (such as banknotes and coins). Dealings that might have been done with cash in the past are now more often done online. Since the world is increasingly using digital or virtual currency for transactions across electronic networks, this has progressively become a hot topic in today’s society. This is a crucial aspect of the digital economy.

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2.5 Recent Challenges One of the EU’s top precedence is to ensure equal competition. However, the rivalry in the digital market seems to be skewed. To prevent this digital ecosystem from absorbing all of the economy, the EU intends to classify it as either an “abuse of dominant position” or a “cartel,” both of which are anti-competitive in the one market. Digital companies like the GAFA thrive because of the many free services they provide to customers, which seem to benefit consumers but make it more difficult for other businesses to compete fairly. In the same manner that the GAFA offers employment and assistances all over the world, it seems that authorities will find it difficult to approve them.

2.6 The Effect of Emerging Technology on International Production Technology has always influenced trade, but the rapid growth of digital technologies in recent years has the potential to radically change international trade in the years ahead. One of the most important impacts of emerging technologies, according to the study, is the degree to which they can reduce trade costs. Furthermore, digital innovations can change the composition of trade by raising the services aspect, promoting trade in specific goods such as time-sensitive commodities, modifying competitive advantage trends, and effecting the complexity and time taken of global supply chains. Future technological changes are expected to boost trade development, especially in services trade, and developing countries are likely to gain a larger share of global trade. While the expansion of digital trade is likely to bring significant benefits, international cooperation is needed to assist policymakers in ensuring that digital trade remains a driver of inclusive economic growth (Mesenbourg 2001).

2.7 Technological Advancements in International Trade International trade has recently dominated the news around the world. These debates are important, but they ignore a more positive aspect of international trade innovation. The good information is that we might be on the verge of something important. When different technological advancements from various stages of the technology implementation life process are merged, they have the ability to radically alter how resources are distributed and foreign trade is conducted. To remain ahead of the curve, governments and companies must consider current trends.

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3 Characteristics of Digital Economy The way people and companies communicate has changed significantly over the last decade. Businesses have created their own business networks to link suppliers, consumers, and internal processes, based on the success of social networks. To successfully adapt, one must first comprehend the digital economy’s key characteristics: Tracked and digitized: Analog artifacts produce digital signals in a digital economy, which can be calculated, monitored, and analyzed for better decision-making. Companies might, for example, link multiple oilfields to boost forecast accuracy and profitability at the well level. We are connected: Wireless communications link properties, vendors, staff, and stakeholders, allowing people to make data-driven decisions and increase safety, performance, and visibility across the enterprise. It has been shared: The digital economy is based on the idea of sharing. Companies will soon buy just what they require and pay as they go. Buying only what is needed decreases inventory costs, while purchasing use as a service allows businesses to pay only for the time and value earned. Individualized: Customer personalization is another function of the digital economy. Customers get personalized items and experiences from their favorite brands when and where they want them, thanks to personalization. Straightforward: Oil and gas companies can also use the digital economy to cut out the middleman, removing unwanted intermediaries or networks and establishing a more direct partnership between buyer and seller. A streamlined ecosystem has less uncertainty and reduces the barrier to entry for new entrants in the value chain. A good example of more direct operations is remote service control. Remote intelligence is used to track, control, handle, record, and address asset problems during the service life cycle, removing the need for full-time, on-site staff (Mesenbourg 2001). Knowledge: If property, houses, labor, and money are important factors of production in classical economics, information or knowledge is the most important form of resource that an enterprise can own in the digital economy. Given the information inherent in the human brain, the intelligence element of the company’s human resources is what determines the organization’s success or failure in achieving its goals. The importance of the organization in the process of producing goods and services is collective awareness. Furthermore, technical developments have allowed the development of a number of artificial intelligence (artificial intelligence) products that are capable of assisting the company’s management and staff in improving intelligence (knowledge leveraging). Decision support systems and expert systems are two examples of software and hardware that can be used to aid in decision-making. In this period, the idea of knowledge management will be critical to a business’s success.

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Digitization: This has increased the company’s productivity by decreasing costs associated with the production process, transportation, and exchange media. Not the most advanced technology has been able to convert analog video and audio to digital formats. The advancement of telecommunications technology, which enables people to share information quickly via email to people all over the world, is making the distribution process and exchanging all forms of digitized information much easier. In other words, if the company’s goods and services can be portrayed digitally, the company can easily and affordably sell products and services all over the world. A variety of goods and services can be provided on the internet, including electronic publishing, virtual book stores, internet banking, and telemedicine Fournier, Laurent (2014). Virtualization: In comparison to running a business in the real world, where physical assets such as buildings and means of production are needed, in the virtual world, known as virtualization, a person can start a business with a simple computer and reach all potential customers worldwide. A customer engaging with an internet platform as an organization (business to consumer) in the virtual world, as well as the partnership between different companies who want to collaborate (business to business). The sharing of data and information virtually, without the physical presence of the parties or persons performing transactions, is a mechanism that exists in this relationship. In other words, the company can be conducted online and in real time at any time and from any location for as long as 24 h a day, seven days a week. Interworking: There is no organization that can work independently in the virtual world without partnering with others, which is one of the conditions for success. The related organization should decide its core activities (core activity) based on the business model chosen and work with other organizations to help implement the processes supporting it (supporting activities). Technology distributors, content partners, retailers, manufacturers (suppliers), and others are all examples of general partners. In the digital economy, a business model that wanted to manage its own capital from upstream to downstream would not last long. Convergence: The content industry, which is a form of service or services provided by a business to market in cyberspace, has real competition. Three of the above are absolute requirements that must be owned and managed by the consumer in order to operate a profitable company. Innovation: The internet operates 24 h a day, rather than the 8 h that businesses do in the real world. Competitive advantage (competitive advantage) is incredibly difficult to retain in light of how quickly an individual or business can be imitated on the internet. As a consequence, rapid innovation is required to ensure a company’s survival. The management firm should be able to find a way to ensure that the organization’s main players (management and staff) are still able to innovate, similar to Silicon Valley firms. The definition of a learning organization is one that should be thought about and applied in the workplace (Fournier, Laurent 2014)).

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Disintermediation: Another distinguishing characteristic of the digital economy is the continued lack of mediators (brokers) to serve as a go-between for vendors and consumers. Wholesalers, manufacturers, broadcasters, record labels, and other economic activity mediators are examples. Companies that rely on conventional media as a means of communication are being pushed out of business by the internet. Individual transactions may take place in a free market without the involvement of third parties. Presumption: The once-clear lines between consumers and producers are being increasingly blurred in the digital economy. Almost all information technology users can quickly turn into producers who are ready to sell their goods and services to the general public and business community. An individual who must pay $5 to gain access to a mailing list system is an example. Concerned then establishes a group mailing list for which each member must pay him one dollar. Small companies have benefited from that issue in the short time it has been around. In this case, the individual in question is classified as a prosumer. Immediacy: In the virtual world, customers are confronted with a plethora of businesses that sell similar goods or services. They only used three key criteria to choose a business. In theory, they would do business with companies that deliver goods or services that are less costly, better, or quicker than their rivals. Given how easy and inexpensive it is to turn over to the internet. The consumer will then continue to search out companies that will help him the most. As a result, the organization must always be mindful of the diverse needs of consumers that need a specific level of service satisfaction. 3-D Resolution: The effect of 3-D resolution on international trade is still up in the air. According to some reports, once high-speed 3-D bioprinting becomes widely adopted and affordable, international trade could drop by as much as 25%, as 3-D resolution requires less workforce and eliminates the need for imports. Others contend that such viewpoints are too positive and ignore the complexities and realities of mass production. Nevertheless of the positions taken, 3-D resolution has a significant effect on international trade, particularly when faster and less-expensive methods of 3-D printing become possible.

4 Creating New Value and Shaping the Future of the Digital Economy Transitioning to a new standard when handling market disruptions: The Forum on Digital Economy and New Value Creation enables companies to use technological advancements to become more flexible in the face of change and to develop new digitally enabled business models for a new normal—one that is post-COVID-19, purpose-driven, longer period, and inclusive.

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COVID-19’s unparalleled disruption is heightening the need for quickness, flexibility, and modification. Industry systems and business models are being challenged, and the economy’s digitalization is accelerating at a breakneck rate. Over the next decade, digitally powered network business models are expected to generate 70% of new worth in the economy. However, 47% of the world’s population is still without access to the internet (Delices, Patrick 2010). This site uses its vast network of more than 500 senior leaders and breadth of digital modification experience to help businesses adapt to today’s challenges and follow into tomorrow’s economy. The ongoing economic and policy debate has made digitalization a key theme. Large digital and technology multinational enterprises (MNEs) are playing an increasingly important role in the international economy. Furthermore, the widespread acquisition of digital technological advancement is radically altering manufacturing processes in all industries. Both of these (related) events have far-reaching consequences for economic systems, jobs, inequality, and growth and industrialization opportunities. Many previously unimaginable services, such as online grocery home delivery and dating apps, have been made possible by the digital economy and produce important data that can be used to gain new insights. The mass processing of data will assist governments and charities in better understanding what is going on in the economy Delices, Patrick (2010). The digital economy has gotten a lot of coverage lately, with stories ranging from dystopian to breathtakingly thrilling scenarios. Some fear job losses as a result of automation, while others marvel at the capabilities of digital technology. Then, there is the issue of whether this can translate into helping those who need it the most. Firms may use emerging technology to do things better, as well as more reliably and cost-effectively. They also open up a slew of new options. In the same way that mobile apps offer real-time, traffic-aware navigation, no group of people could ever provide it.

4.1 MNCs in Digital Economy Modern digital services are largely provided by multinational corporations of unprecedented size and scope. This, however, has not always been the case. Users used to rely on local businesses for the majority of their information just a few decades ago. Historically, software has been associated with low entry barriers and the rapid growth of startups and small businesses.

4.2 Scope of Digitalization in MNCs Every business has been impacted by the digital revolution. For some, improved technology necessitates reworking supply chains and adjusting supply chains in order

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to increase efficiency. Others will face new competitors as a result of new technologies. New technology effectively reworks an entire business in certain sectors that must now operate digitally. As digital technologies pervade MNCs, their effects are beginning to resemble those of domestic firms in many ways. The fundamental benefits of digital technologies for most of these businesses are better data collection and processing, as well as a greater ability to find patterns and insights in that data. Large businesses, on the other hand, benefit greatly from these capabilities. Large companies, for example, must typically allocate inventory across multiple and farflung facilities, necessitating the collection of data that cannot be seen from a single location. One might imagine allocating inventory using a paper-based process, as companies did decades ago, but digital tools provide massive efficiencies in terms of speed and accuracy, as well as analysis to help businesses make better decisions (Delices, Patrick 2010). Large companies, on the other hand, must track customer purchases in order to forecast demand and ensure adequate supply. Here, too, digital solutions provide significant benefits, such as the ability to track more data, more quickly, at a lower cost, and with more opportunities for analysis and insight. Meanwhile, large corporations oversee workforces dispersed across multiple locations, and digital methods streamline both assignments (how many employees will be needed at a given location on a given day and time) and operations. Finally, the breadth, accountability, and control provided by effective digital tools are a perfect match for the size and scope of a large firm. Because MNCs are so large, they tend to reap all of these benefits in spades. It is quick to dismiss global corporations’ digital operations as routine and unremarkable. Companies, on the other hand, benefit significantly from quicker or better digital technology implementations. Airlines’ early embrace of technology is exemplified by a number of notable examples.

5 Digital Economy Success Factors Factors that determine success in digital economy are:

5.1 Promoting Customer Engagement The three factors that drive a customer’s life are mobility, social ties, and preference. In a digital economy, providing instant fulfillment through the mobile genie is critical to success. Instead of concentrating on sales, businesses should change their marketing strategies to keep their “customer.” The aim of your organization should be to improve customer loyalty and make the customer’s life easier.

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5.2 Developing the Right Infrastructure Without infrastructure, there can be no economy, digital, or otherwise. The growth of internet and mobile penetration has put unprecedented strain on network providers’ current networks. As a result, the scope of digital benefits has been restricted to global locations. It is critical to improve network capacity, extend coverage, build interconnected smart cities, and, most significantly, facilitate and encourage the use of digital tools.

5.3 Adapting to New Technology Unless emerging innovations are introduced and, more importantly, adapted on a regular basis, the digital economy will grind to a halt. Technologies that are driven by powerful computation and intelligent algorithms break down barriers to produce immediate results, or in business words, instant gratification for consumers. Your customers would be excited about you if your workers are enthusiastic about using modern technologies like digital CRM. Positive reinforcement that stresses improved efficiency and value can help to dispel inhibitions.

5.4 Amplifying Partnerships Collaboration yields positive results. It will be difficult to conquer the digital waters alone, no matter how brave you are. This is due to the fact that no single organization can claim to have a full understanding of all emerging technologies and tools available. Set the right goals from the start when selecting a partner. Having a partner provides you with a sense of security when confronting new challenges. With the aid of personalized solutions like CRM in insurance and banking CRM in banking, managing partners becomes a breeze in every domain, be it insurance, financial services, or other (Newburger, Lauren Hirsch, Emma (2019-06-03)).

5.5 Shifting from Control Strategy to Influence Strategy with Regards for Technology Most large companies tend to centralize their IT operations. However, being nimble in terms of integrating appropriate technologies at the correct site and at the correct time is needed in the digital economy. As a result, an influencer-based strategy is needed, one that recognizes the benefits a company can achieve by using digital technology in various scenarios. In the end, how you handle the herculean task of

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satisfying consumer demands while retaining their fickle loyalty will decide whether your company succeeds or fails in the web economy.

5.6 India Set to Play a Vital Role in Web Economy In the years ahead, the Indian technology industry’s talent machine, combined with fully distributed global distribution models, is prone to play a vital role in the global digital economy’s transformation journey. India will be one of the world’s far-reaching and ever-growing technology markets by 2020. In India, digital and technology acquisition has been steadily growing in recent years, and the current COVID-19 widespread has accelerated the pace of adoption across industries, including in high-involvement services like education and healthcare. In terms of customer behavior, there is a trend toward using digital as the primary medium, including for high-volume daily transactions. To help India’s fast-growing digital economy, domestic and international investors are actively investing in the construction of digital infrastructure, such as communication networks, data centers and cloud services, and electronics manufacturing (Newburger, Lauren Hirsch, Emma (2019-06-03)). In particular, the year 2020 has been a landmark moment for the electronics manufacturing industry. Under the aegis of “Atmanirbhar Bharat,” government incentives such as Production Linked Incentives (PLI), Scheme for Promotion of Manufacturing of Electronic Components and Semiconductors (SPECS), and Updated Electronics Manufacturing Clusters Scheme (EMC 2.0) piqued global investors’ interest in setting up manufacturing and supply chains in India. The government approved the PLI applications of 16 electronics firms in October, and the scheme is now being expanded to ten additional industries, including telecom and networking components. Scientific and industrial research are complemented by a powerful manufacturing ecosystem, and developments in the electronics manufacturing industry in 2020 are expected to improve overall technology manufacturing in India in the years ahead. This will create a self-sustaining ecosystem for advanced technology research and development, leveraging India’s low-cost science and engineering expertise. India’s tier-1 technology services companies have shown resilience in the export markets, not only in terms of sales but also in terms of margin performance, and have increased hiring activity throughout the year. Tier-1 and tier-2 technology services firms have also expressed an interest in forming strategic alliances with their MNC clients to manage their captive technology and business operations, including the purchase and transition of such assets. Exiting sub-scale captive operations through strategic sale and business transfer enables MNCs to unlock value while preserving business continuity. Such agreements aim to enhance customer relationships and provide revenue stability in the medium term, as well as qualified personnel and skills for service providers. This year saw a few strategic transactions of this sort, and this pattern is likely to continue in the future as multinational companies streamline

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their global product creation and service delivery strategies in the post-COVID-19 environment. On the demand side, as businesses invest in cloud-based technology to digitize their customer networks and business processes, digital transformation deals are gaining traction. Artificial intelligence and edge computing technologies are gaining popularity in the development of next-generation cloud-to-edge architecture and services. The year saw major advancements in workforce change in a work-fromanywhere world, as well as a paradigm shift in the way global delivery models are implemented. In the technologically enabled world of work, global delivery models in the technology services industry will experience major changes in the future. Client project delivery will move away from mobilizing resources and toward mobilizing expertise in a fully dispersed workforce spread across various geographies, working seamlessly on client projects delivered in cloud-based environments (Fakhriddin Abdikarimov 2020). COVID-19 has resulted in dramatic changes in technology consumption for businesses, governments, and customers, with 2020 serving as a turning point in the transition. When we look to the future, we can see that mass digitization is a reality across industries and around the world, and that a variety of enterprise and consumer technology—from 5G to the cloud to virtual reality and edge computing—will continue to provide opportunities for global businesses. There is greater demand opportunity, shorter adoption times, and potentially lower costs for next-generation tools and technology, and it is important for organizations to re-imagine customer engagement and business processes for a digital first world. Across sectors, workforce change has proven to be a major trend. What began as a requirement in 2020 is projected to hit a new equilibrium in 2021, as companies re-imagine their employees and workplaces on a more fundamental basis, keeping long-term market transformations in mind. Organizations that are able to reinvent their approach to workforce management, attracting, employing, and maintaining talent in a technologically powered world of work will be successful. The technology industry’s workforce transformation lessons, which were among the first to respond to this phenomenon, will be relevant and resonant in the wider information industries (Fakhriddin Abdikarimov 2020). In the years ahead, the Indian technology industry’s talent machine, combined with fully distributed global distribution models, is likely to play a key role in the global digital economy’s transformation journey. India is lagging behind the rest of the world in terms of digitalization. In today’s fast-paced environment, data processing tasks must be completed in the blink of an eye. The traditional method of data storage and retrieval is more difficult and time-consuming. Once all administrative data has been digitized, quicker retrieval, easier access, and reliable data management can be assured, improving the organization’s ability to adapt to the fast-changing environment.

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References Bitcoin energy consumption index—digiconomist. Digiconomist. Retrieved 8 June 2018 Czinkota MR, Ronkainen IA (2013) International marketing. Available at: https://ebrary.net/21430/ management/international_marketing Digital economy report “value creation and capture: implications for developing countries” (PDF). United Nations Conference on Trade and Development, New York (2019) Economie numérique et fiscalité www.strategie.gouv.fr (in French). Retrieved 20 April 2020 https://www.civilserviceindia.com/subject/Management/notes/international-production http://crmsolutions.crmnext.com/2017/01/crm-tips-5-success-factors-for-digital.html https://www.sciencedirect.com/topics/economics-econometrics-and-finance/international-produc tion https://www.tutorialspoint.com/international_marketing/international_marketing_product_life cycle.html Nirmala R. Council post: how to harness the power of network effects. Forbes. Retrieved 20 April 2020 Some precepts of the digital economy. Productivity, Innovation and Technology eJournal. Social Science Research Network (SSRN). Accessed 27 Jan 2020

Changing Structure of Consumer Buying Behaviour and Expectation in the Digital Era Sunanda Vincent Jaiwant

1 Introduction The digital era has altered consumer behaviour dramatically, exponentially and permanently. Shopping through online modes and medium is not the only digital activity of the shoppers today; rather it has gone and grown much beyond. Digital marketing era has changed what the consumers purchase and from where they purchase and even how they purchase. Customers purchase on and through various devices namely mobiles, laptop, tab, etc., through varied social media platforms like Twitter, Facebook, Instagram, WhatsApp or Snapchat. Marketers have also adapted to this change and constantly reporting new apps or digital trends. These novel technologies have echoed on the relations between the customer–marketer relationships and impacted in formation of new business models. Corporate strategy has begun focussing on customer experience which is considered a critical success factor in this new digitalization ecosystem. Businesses are turning to social media to engage with their customers. The intrusion of digital era has impacted the customers in more than many ways, and the consumer’s mentality and behaviour has been affected and changed drastically which has reflected in his buying habits and buying patterns. The traditional consumer behaviour model is developed for the today’s tech savvy consumers. The companies are investing hugely to strengthen the social relationship with their customers to influence their buying preferences and decisions. The consumer is now more informed than ever when it comes to shopping. Consumers’ expectations are higher now in this digital era that the online shopping has increased and physical buying looks on a downward slope. The brands keeping in mind the digitally literate and well-informed and technically equipped customers should focus on rebuilding, rephrasing and repositioning their strategic plans and objectives to be more sustainable and profitable in this digital period. The brands ought to learn to S. Vincent Jaiwant (B) School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_12

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deploy the new brand communications, channels and platforms which to be able to reach faster and easily their consumers and give them an enhanced customer experience. This might change the earlier targeting and positioning strategies of the brand to give a broader reach. The marketers need to design and deploy new technology tools and strategy statements that will unlock new opportunities and prospects for the brands.

2 Research Methodology This chapter analysed related published research papers and surveys. There were some interactions and interviews also done with some marketing experts and executives. An unstructured interview was also conducted with several customers. This chapter has examined the transformations that took place in the buying behaviour and buying preference and pattern of the customers which are impacted by the evolution in the digital technology. The study investigated the digital marketing evolution making an impact on the consumer behaviour. Academic research work was studied to understand the various variations that have occurred the buying behaviour in and decision-making course in the digital era.

2.1 Objectives of the Study This chapter intends to study the following. . The new concepts of consumer behaviour in the digital era . The new model of consumer behaviour in the digital era.

3 Literature Review Consumer decision making in digital era is influenced by many factors. Bettman et al. (1998) This is paper presented that consumer decision is an integral component of purchase behaviour, and many research work has been done over the past years by many researchers and scholars. Researchers, scholars and marketers have always found the concept and process of consumer decision making very interesting. Loudon et al. (1993) Early studies aimed to focus more on the decision making and the purchase activities. Engel et al., Much after 1950s, the researchers and scholars studied and presented contemporary theories of marketing and incorporated the marketing concepts in school of consumer decision making and included a broader array of shoppers’ behaviour and buying-related activities. The modern researches revealed the fact that there are more activities involved in the shoppers’

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shopping behaviour than the final purchase itself. There are a number of determinants that drive the consumer decision making. Shree and Nagabhushanam (2018) The study had the objective to discover the traditional models in consumer behaviour as well as the numerous technological interventions. The study gave the conclusion that consumer behaviour has evolved in past and advance technology has been instrumental in bringing significant changes in the consumer. The researchers got to understand that e-consumer or consumer in the Internet age could not be understood properly because of lack of any complete theory or study about them. A focus group discussion opined that it is required to study consumers in the Indian context, markets and environment and accordingly construct a model of consumer behavioural, especially while studying the consumer behaviour in Indian context. Consumer opinion which was derived through a questionnaire revealed the impact of technology in facilitating enhanced decision making and buying behaviour. Ashman et al. (2015) has reported that there are insightful changes in consumer behaviour that is the result of online ‘participatory culture’. The traditional threshold to participation has been lowered which has led to the participatory culture. The consumers can now easily convey or share their analysis or judgement on various digital platforms and add their information about different brands and products globally over various Internet-enabled devices and platforms and specially through social media interactions. Digital technology has enabled everything available virtually and anyone from anywhere everything can be gives their views and comments. This participatory culture has resulted in democratization of consumer culture. Participatory culture has shifted the power from companies to customers. Marketers are now communicating with their consumers and presenting and promoting their offerings across different types of digital media. Akayleh (2021) The study aimed to examine the influence of e-marketing over consumer behaviour. The study was conducted Riyadh City, Saudi Arabia. The researcher used quantitative research methodology and used simple random sampling for collecting data. The dependent variable was consumer buying decision and independent variable was social media advertising. Demographic variables like income level, education status, gender and age group were the moderating variables. The study reveals that consumer buying decision is extensively driven by social media advertising. Miklošík (2018) This research paper examined the transformation that happened in the user buying course of action due to the digital revolution. The study identifies the changes that are occurred in buying course of action due to Internet and digital technology. Consumer has changed his actions before, during and after the purchase activity. Internet, media, multiple devices and multiple screens have made consumer equipped with knowledge and information through various sources.

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3.1 Consumer Behaviour Consumer behaviour is purchasers’ behaviour concerning what products as well as services the consumers purchase, how they purchase products and services and how they use them, how they dispose them and why they purchase them. Consumer behaviour also includes their emotional, mental and behavioural responses, reactions and activities. Consumer behaviour is an amalgamation of many streams of studies including psychology, biology, chemistry, and economics Marketers conduct various way to study their consumer study of consumer behaviour reveals them as to what their consumers think and how they feel about their brands and products. They also come to know what influences consumers to select between various brands. The study also explains how their consumers get influenced by a number of external environment stimuli. Initially, economic theory assumed that customers select and buy products or services by rational thinking, and this theory became the basis for succeeding the consumer behaviour studies. The theory asserts that theory of utility is active in the consumers whenever he plans to purchase a product looking at the use of the product. A cost benefit analysis is conducted by the customer to evaluate the product benefit and then the buying decision takes place. Subsequently, a cognitive approach was adopted in the study of consumer behaviour. Cognitive theory states that customer seeks information first and then does an evaluation and analysis on the gathered information to arrive at a conclusion to buy or not to buy (Jeff). Consumer behaviour involves the people, their buying decisions and buying activities for the purchase of goods and services for private use (Engel et al.). Consumer buying behaviour is learning about buyers and consumers and how they act and react when the need a product or service and also how they make their mind to procure or purchase whichever merchandise they prefer that they believe would gratify their requirements. CB is an analysis of the demeanour and conduct of the users that compel them to procure and utilize some particular brand and their offerings.

3.2 Consumer Behaviour During Digital Age The COVID-19 pandemic and the unparalleled loss and damage to the entire world have caused certain phenomenal behavioural changes in consumers all over the world. Pandemic during pandemic has led to closures of innumerable businesses. Countless men and women across the globe have lost their steady earnings and jobs. Many had to sit in their homes jobless. Many had their earnings reduced drastically. People were forced to limit their purchases to only essential items. Lockdowns added to the stress all the more with markets remaining closed or opening only for a short duration. People were confined to their homes. Hence, there is a visible and drastic change in the behaviour of the consumers as to how and when and what they shop. Even the preferences of the consumers have seen dramatic changes. Consumers no

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longer take the pleasure of leisure shopping to market places. They hesitate to visit malls and crowded trade zones. Shopping has ceased to become an entertainment for the people during pandemic. Digital era has compelled all retailers, wholesalers and marketers rework their approaches and strategies. The change in the consumer behaviour has impacted all forms of businesses of all magnitude and scale. Today, consumer buying decisions is not identical to the traditional process of decision making. Consumer is more in the participatory form in the new digital marketing era. Today’s digital consumer is more powerful and informed than it was in the past, and this enablement has been fuelled due to the plethora of easily accessible information and innovation in technological field. The new digital marketing era has the intrusion of technology throughout the customer choice-building course. Consumer behaviour is impacted by many factors in this digital era. The digital marketers take efforts to identify and understand the consumer characters, features, preferences and also purchasing objectives done on virtual platforms in addition to users’ online purchasing behaviour. The purposes and patterns of the online buying of the young people are very different form their elderly counterparts. These youngsters are digitally ware and more exposed to digital tools and technology and therefore are more inclined towards utilizing modern devices, gadgets and digital technology as studied by many authors and researchers. It is also found that the technology influenced the consumers in all the other factors; psychological, economic, social, cultural and personal factors. Customers today expect and desire a seamless buying occurrence every times they shop irrespective of what channel or platform they are using to purchase. A buyer want to explore the brands and its various options available on multiple devices and platforms and also want buy it using any device or through any platform at any point of time. Basically, today’s digital customer wants a timeless, borderless and sometime cashless and virtual shopping experience. Modern marketers need to be become proficient in attracting and engaging their prospective and current customers and also selling their offerings using a multichannel marketing strategy. They ought to focus on the customer instead of the channel of communication and selling. Digital marketing provides a more personalized and enhanced customer experience. Digital tools of marketing facilitate reaching the right segment of buyer at the right timer using the right digital platform and device with the right combination of content resulting in higher conversion rate. Today, digital technologies give the ability to the marketers to design their marketing communication and also enable them to pursue and trace their audiences over multiple devices, and also assess the outcome of all the touch points in the consumer purchasing decision process. In this digital era, the marketers have varied solutions to measure the effectiveness of their marketing content and advertisements and also measure their manipulation over purchasers and users.

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3.3 Model of Consumer Decision-Making Process in the Digital Era Consumers undergo a series of stages when they choose to purchase any brand’s offering. This process of identifying the need and selecting from hordes of alternatives available in the market is sometimes very small for daily need and convenience goods, and many times, it is a very complex and time consuming process for shopping and speciality goods. An ordinary shopper begins his journey of shopping with the identification of wants followed by information search. Then comes evaluation of all the available alternatives of products, brands, stores, payment modes payment, etc. Finally, the final decision of purchase takes place, and sometimes, there is not any buying. The after-buying assessment follows a purchase. Marketers put in their efforts to comprehend these five segments of the user purchasing course of action and try to design and establish their marketing strategy that would address each stages of the consumer buying process.

The model of consumer decision-making process in the digital era in the above figure has many online activities of the consumers at every stage of the decision process. In the first step of exploration, the users are looking for merchandize or brand-related blogs, reports, etc. At the 2nd stage of search for information, they will look for reviews or customer comments. Digital marketing facilitates comparison of different companies and their brands and the wide variety of choices that they offer. The e-retailers make themselves visible on many portals and platforms and present their products to the viewers with many offerings. The companies make their corporate websites and corporate blogs another arena of displaying their brand and a stage of promotion. During the purchasing stage, consumer will decided to buy from the company website or from the online retailer. Online purchasing gives huge importance to the post-purchase conduct because the actions of the buyers can

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be tracked very easily. Consumers usually give reviews and feedback about their experience with the product or brand the brand which in turn will become source of information for other consumers. Consumer behaviour in the digital era is different from the traditional behaviour. Dennis et al. (2009) “There are significant gaps in our understanding of e-consumer behaviour”. The online consumers need a new study because they behave very differently from the traditional consumers who purchase their products from the old and conventional outlets. Marketers require a new model of customer behaviour that would increase their knowledge of the customers purchasing online that will enable them to understand the behaviours of the online shoppers. These new models reveal a varied array of determinants that drive consumer buying trends and patters in the digital era. There are factors like external stimuli like marketing and external factors; and internal stimuli like the psychological elements of the consumer and personal characteristics of the consumers. Steps in the Consumer Decision-Making Process in the Digital Era 1. Need identification . Internal stimuli includes two components—consumer psychology and consumer characteristics . External stimuli includes marketing communications and environmental factors . Online stimulation includes online advertisements, online blogs, articles, articles emails from marketers, online brand promotions and campaign through social media and others. 2. Search for information The consumer engages in searching for information about the products, services or brands through online surveys and reports, reviews and feedback, emails from marketers, etc. 3. Evaluation of alternatives After the information is gathered, the customers evaluate the available alternatives for satisfying his needs. The consumer in this digital age evaluates the alternatives through online comparisons, website visit, online communities, etc. 4. Final Decision The buyer purchases the product or service online through company website, online retailers like Amazon, Alibaba, Flipkart, Snapdeal, or buy using voiceenabled speaker (e.g. via Alexa, Amazon Echo, Google Home). 5. Post-Purchase The buyer or user carries out the post-purchase activity of sharing his views on the product or brand on the online platform by means of reviews and feedback, emails to marketers, being influencers on social media. The new consumer and sentiments and habits in the digital age:

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. Digital customer has been empowered more so he knows more and expresses more through the use of Internet, social media, smart phones and tabs, etc. . Consumer demands have grown leaps and bound in terms of quality, features, efficiency and value-addition of products and services. . Consumer is expecting now a smooth, hassle free and enhanced experience while communicating and engaging with the brand and buying the brand offerings. . Consumer wants a delightful and rich experience with the brand and not just being satisfied with the brand. They want to take pleasure of the personalized offers and services and desire a personalized and customized treatment from the company . Customer on this digital ecosystem requires and expects a constant and relevant interaction with the brand. . Today consumer aspires to take smarter decisions and not be the victim of cognitive dissonance after the final purchase. . Today’s consumer is concerned about the sustainable and ethical practices of the company and feel more responsible towards the environment and the society in general by advocating and getting connecting to a more responsible company.

3.4 Findings The current study reveals many new facts about the changed consumer behaviour in the digital era. The digital era has totally brought a turnaround among the consumers. Today’s consumers are digitally oriented and digitally literate. There has been an evolution the digital space due to digital era which has brought copious variations in the actions and conduct of this digital era consumers. The digitally enabled consumers are totally different from the yesteryears shoppers. Shopping has become timeless and borderless and even cashless at times. Marketers are fining varied means to engage with this hyper sensitive and super active customer. The consumers are found to be frequenting social media platforms and websites and e-retailers than the brick-and-mortar stores. The consumers use Web2.0 to interact and engage with their brands. The consumers have become powerful in dictating the online platform for the bringing more traffic to the brands, companies and the marketers. Their reviews and their feedbacks have assumed significant importance on the online platform. The marketers to load the consumers with heavy and overflowing data and information and now the consumers are more aware than before. The consumers’ preferences and intensions have changed due all this online revolution. The consumers are now more engaged with their influencers and bloggers and have more information about the brands that help them in their decision-making journey.

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4 Conclusion New digital era significantly persuades and manipulates the conduct and inclinations of shoppers and users. User behaviour has changed; furthermore, their decisionmaking process is significantly impacted by the digital technology and revolution. Intensified and a comprehensive factual data about the brands and numerous reviews are available in the Internet for the consumers before they make their final purchase decision. Internet has become accessible to everyone; therefore the shopper today has become online or digital shopper. The network connections are dominating the business world and the market. It has assumed the role of a commanding and universal supply of relevant facts and figures of the companies and their brands to the shoppers in addition to acquiring the position of significant place for companies to present and promote their offerings. They have brought in the virtual store to cater to their digitally driven purchasers and to retain them as loyal consumers. The digital era has blotted the difference between the brick-and-mortar store and the online buying activities. The digital era has inadvertently and richly impacted customer buying pattern and activities by empowering the customer to shop at his comfort from his home or office and even while he is mobile and also choose the payment mode and compare and evaluate the brands and give his reviews post-purchase. Buyers can buy not only during the usual shop working hours but at any time and all the time. The digital era has taken the ability to research and shop online to the next level because shoppers can use the various devices at any point during the sales cycle. The evolution of the shoppers’ behaviour has fuelled further growth in the new strategies of the marketers. The marketers resort to various means and mediums to attract their customers, keep them engaged on numerous online platforms and also strategies to retain their loyal consumers.

References Akayleh FA (2021) The influence of social media advertising on consumer behaviour. Middle East J Manage 8(4) Ashman R, Solomon MR, Wolny J (2015) An old model for a new age: consumer decision making in participatory digital culture. J Cust Behav 14(2):127–146. https://en.wikipedia.org/wiki/COVID19_pandemic Bettman JR, Luce MF, Payne JW (1998) Constructive consumer choice processes. J Consum Res Dennis C, Merrilees B, Jayawardhena C, Wright LT (2009) E-consumer behaviour. Eur J Mark 43(9) Engel JF, Blackwell RD, Miniard PW, Consumer behavior. Harcourt Publishers Group (Australia) Pty. Ltd. Loudon DL, Delia Bitta AJ (1993) Consumer behavior: concepts and applications. McGraw Hill Miklošík A (2018) Changes in purchasing decision-making process of consumers in the digital era. Eur J Sci Theol 11(6):167–176 Shree K, Nagabhushanam M (2018) Consumer behaviour in new digital era: a paradigm shift. Int J Manage Stud 3(7)

A Software Based on Modelling Solution Using Weibull Distribution and Depreciation, Applicable in MSM e-Business and e-Commerce Industry Pooja Tiwari, Shradha Goyal, Rudresh Pandey, and Esra Sipahi

1 Introduction The pedagogical importance of operation field of mathematics is to face and resolve decision related to optimization in any industry, irrespective of the industry type and nature for this pollution; the problem is first restated as an algorithm based on which a model is designed and then analysed. Further using different mathematical methods this model can be analytically solved for real-world applications and to find solutions to day-to-day life decision. This paper is based on an inventory model using concepts of operation research and other mathematical concepts of education. Inventory models with fixed demand have been widely studied in literature review since long time. Donaldson initially theory with linear demand in positive direction. Within and wager also discussed an exclusive version on the same concept. Meal and silver developed an exclusive algorithm and named it as ‘Silver Meal Heuristic’ to find a pattern of demand when demand is dependent on time. Mitra et al. further extended the study to fill the gaps and consider both positive and negative direction in linear demand. Chavdhari and Deb, Dave revised ‘Silver Meal Heuristic’ to un corporate shortages. Many theories have been worked on till now, with depreciation and demand dependent on time. Scientists like Patel and Dave, Sachan, Hariga, Chaudhari and Goswami, Bahari and Kashani, etc., have given their contributions to this study. While resolving issue of P. Tiwari (B) School of Business Studies, Sharda University, Greater Noida, Uttar Pradesh, India e-mail: [email protected] S. Goyal JIMS, Kalkaji, New Delhi, India R. Pandey Institute of Management Studies, Ghaziabad, Uttar Pradesh, India E. Sipahi Social Sciences University of Ankara, Ankara, Turkey © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_13

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fitting the empirical data in various distributions for mathematical analysis, Berrotoni felt that depreciation in practical cases like failure due to leakage in dry cells or expiration of medicines and chemicals can be expressed through Weibull distribution. In above examples, the rate of depreciation. Hence, Covert and Philip got motivation from Berrotoni to developed model variable rate of depreciation. There is a bag full of inventory theories for demand dependent on time contrary to very few works done considering demand dependent on price even through it is well known that selling price widely effects the demand of the product. In this regard, Richard and Kunreuther discussed the policy for ordering and pricing jointly for off-season stock. Whereas, Schrage extended this to study of on-season stock. Cohen then developed a model representing the policy for pricing and ordering jointly considering the depreciation of a stock at fixed rate. Cheng then developed a model representing the policy for pricing and ordering jointly considering the depreciation of a stock at fixed rate. Cheng also developed a similar theory and model but for a kind of stock does not depreciate but have lesser space for storage and limited funds for inventory investments. This model was then reused by Chen and Min. Models discussed till now are based on linear function for rate of demand dependent on price. Then Hwang and Shinn further discussed a nonlinear function for rate of demand dependent on price and also assumed constant depreciation. In this paper, reconsideration of model given by Cohen about pattern of demand dependent on price is done in the form of power law and Weibull two-parameter distribution. Here, function represents distribution of depreciation to time. From the revised review of literature of various models in inventory, it is understood that depreciation is a very common process in models since evaluation of inventory theories various categories of stock items go through depreciation in their own ways. For example, aircrafts, hardware, routine fashion products, etc., become old fashioned and out of demand as soon as they are upgraded with new technology in the market by industry. Stocked units like food products, chemicals, etc., depreciate continuously and quickly over a small time period. Hence, looking at the practical implication of depreciation in real life, it is important to consider it into the development of inventory models. Many researchers have been made to categorize different types of depreciation for different nature of products. Within (1957), Ghare and Schrader, Aggarwal (1978), Jaiswal and Shah and many others have studied inventory models taking into consideration steady and constant depreciation and demand along with real-time replenishments. Patel and Dane studied a model of inventory by studying demand proportional to time zero stock cuts and real-time refill and replacements. Later again Dave elaborated his own work to includes variable stock outs. Kashani-Bahari presented an algorithm for demand proportional to time. Chaudhuri and Roy Chowdhury discussed an inventory model with level of order under shortages and finite level of replenishments. Many researchers have also started working on models of inventory such that rate of depreciation is dependent on time. Modelling algorithms developed by Mishra

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Philip, Deb and Chaudhuri (1986), etc., are based on above concept. A better generalized model was discussed by Goswami and Chaudhari (1992), which also considered rate of depreciation as proportional to time. Also, the rate of production is finite and is dependent on rate of demand along with stock outs as possibility. For example, Berrotoni (1962) specifically studied the depreciation in case of failure of dry batteries due to leakage and expectancy of life of ethical drug and expressed it in function of Weibull distribution. In his study, Berrotoni (1962) considered case where, the time for which the unused stock is kept is directly proportional to rate of depreciation. Carrying this study forward Covert and Philip (1973) to build up an inventory model in two-parameter Weibull distribution taking time and depreciation as parameters. The function for instantaneous rate for two parameters is Z (t) = αβt β−1

(1)

where α > 0 is shape, and β > 0 is scale parameter. Also, t > 0 is depreciation time. This distribution is applicable specifically for items with decreasing depreciation rate and can be used only if the rate of depreciation initially is very large and for stock which has increasing depreciation rate, the distribution is with zero initial rate of depreciation. To overcome the above constraints, Philip (1974) developed a generalized model for EOQ considering a three-parameter Weibull distribution with r (≤ t) the location parameter in addition to the ones discussed for two-parameter distribution. The function for instantaneous rate can be expressed as Z (t) = αβ(t − γ )β−1

(2)

This revised three-parameter distribution is more suitable for any stock with and initial rate of depreciation and there after depreciating after a certain time period. This work was further extended by many researchers like Chaudhari and Giri developed its extension taking linear time function and stock outs. Chaudhari et al. (1998) also extended the work in his own way. It is very common to find the review of literature for demand dependent on time, but only few models are studied and developed for demand dependent on price. In this context, Kunreuther and Richard (1971) discussed policy for joint ordering and pricing for off-season stock, and further, Schrage and Kunrenther extended this for on-seasonal stock. Also, Cohen (1977) discussed the policy for joint ordering and pricing for stock depreciating at fixed rate. Min and Chen revised work of Cheng (1990) in which they discussed about non depreciating items having constraint of space and investment for inventory. Mostly, models were developed taking linear function of demand dependent on price; however Shinn and Hwaug devised a similar model with nonlinear function. Often in study of inventory modelling the depreciation effect is taken into special consideration. Depreciation or deterioration is the decay in stored products which makes them unfit for future use and hence leading to loss of money invested on

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the spoiled stock. The category of products more prone to decay are food items, medicines, chemicals, electronics, radioactive substances, etc. Since they depreciate during their normal time of storage also, thus, considering this loss in calculating the results of the model becomes a priority. A model based on EOQ technique for analysing a stock, showing depreciation in an exponential function, fixed rate of depreciation w.r.t time. The model based on the variation parameter of the available stock and its rate of depreciation was studied by Ghare and Schrader, Covert and Phillip, Misra, etc. They too the product demand of market to be constant, in their work. But with progressing time, many researchers considered rate of demand to be dependent on time for depreciating stock. To name a few people who worked with this assumption were Donald Son, Silver, Goel and Aggarwal, Ritchie, Datta and Pal. The recently done studies by Wu, Lin, Tan and Lec, Mandal and Pal, Hwang, Giyi et al., Kishan and Mishra, Chung and Ting, Datta and Pal are worth a mention. An instantaneous restocking policy was discussed by Sahu and Mishra for depreciating goods with demand dependent on price. They used Weibull distribution for three variables to prove dependency on the rate of depreciation of stock on time. Alternate research study was done by Begum, Sahu and Sahoo with previous study as the base but assuming no stock outs and considering demands to be linearly dependent on price. Covert and Phillip studied an inventory model in which two-parameter Weibull distribution is used to discuss the depreciation trend. Philip gave a general picture of model given by Singh and Sahoo by assuming no shortages, fixed demand and variation in fixed rate of demand for depreciating stock. Chakrabarty, Giri and Chaudhary proposed a model using three-parameter Weibull distribution and assuming depreciation, stock outs and rate of demand as linear function and concluded an infinite series for level of inventory at t = 0 and function representing average of total cost. Sahu, Meher and Panda gave an order policy for inventory with three-parameter Weibull distribution and depreciation of stock and stock outs as assumptions along with demand and price as a quadratic function. Ghosh and Chaudhary combined the above concepts and discussed an inventory model with two-parameter Weibull distribution of depreciating stocks with shortages and quadratic rate of demand as other assumptions. They also represented inventory level at t = 0 and average total cost equation in the form of an infinite series. Sahini developed a three-parameter Weibull distribution model of depreciation assuming shortages and rate of demand as a quadratic function. Samanta and Bhowmick considered a two-parameter Weibull distribution to discuss depreciation w.r.t time and allowing stock outs in the warehouse in following two cases. Firstly, when inventory has stock outs at t = 0 and secondly, when inventory has no stock outs. They derived EOQ results for both cases. Among other researchers to study and discuss two-parameter Weibull depreciation in an inventory are Meher, panda and Sahu, Singh and Sahu; Dash; Misra, Sahu, Bhalua, and Raju are some famous names. Sahu and Panda gave an EPQ using Weibull depreciation in stock using credit trade policy. Sahu and Panda discussed inventory model for level of order using Weibull depreciation for stock with fixed rate of demand. Hollier and Mak initially proposed demand as an exponentially decreasing function and concluded with a policy with an optimized outcome for replenishment

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under constant or variable time intervals. Wee discussed model with deterministic stock size, specifically for depreciating goods where exponential decline in demand was studied in constant time interval. In this paper, a generalized model is studied with a production policy for inventory having one-parameter Weibull distribution for depreciating stock taken on a time interval of planning. The demand curve is exponential, rate of production is finite, and shortages can occur. Objective is to find the optimized number of cycles, required to get minimum average cost of production system. The model is further illustrated using a numerical example and then carry out the sensitivity analysis of the optimized solution obtained. In large parts of the study, much attention has been paid to the models of goods with structured requirements. Donaldson first proposed a straightforward policy to replace the type of stock that is in demand growing in a consistent manner over a limited period of time. Following this many such as Silver and Meal, Ritchie, Goyal et al., Silver. They proposed simplified models to achieve results that are equally costly in exchange policies. Deb and Chaudhary re-read and classified the deficit in the model given to Silver. The study limit on the models mentioned above was to consider the depreciation of stocks. Dave and Patel discussed an innovative model for the decline in the number of items and items with time-dependent demands. Barari and Kashani provided a method of calculating the quantity of a stock order with a constant decrease in the rate and rate based on the demand period. To further this, Goswami and Chaudhary have learned the concept of time-consuming planning, constant depletion, moderate level of demand, and total deficit costs. Hariga studied the model for final adjustment and provided the corresponding correction. Recently, Lin, Tan and Lee, Chakraborty and Chaudhuri, Chang and Dye also discussed EOQ types in deficits and demands based on the downturn in unit units. In another category of inventory models, researchers often discuss demand and time in excessive variation. Hariga and Benkherouf used this pattern to provide a customized model of stock downtime. Kishan and Misra also developed a model with a constant decrease and decrease, using the same demand pattern. Considering the literature review, we find that researchers have so far encountered only two variations in demand-time variables that mean direct and indirect differences. The line variance reflects a constant change in the demand rate for each unit of product time, which is a realistic and unambiguous assumption in any real industry. For example, the demand for the latest technology, chips, computers, etc., is growing rapidly against the technology used and gadgets. Some researchers also refer to this variation in the classification class as an increase or decrease in function in relation to a time unit. From the researcher’s point of view the level of diversity is very high and finding satisfaction is actually a demand in the real market. Therefore, a realistic approach that is consistent with the research ideas and market conditions itself is not equal and does not reflect but quadratic variations in demand and time indications of growth in both the direction and direction of demand. One of the biggest challenges for an inventory manager is the maintenance of perishable goods in today’s industry structure. Since depreciation is an obvious process with all types of goods with respect to time, and its effects on inventory physical conditions

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cannot be ignored. Any kind of spoilage, damage, or change in physical attributes is referred as depreciation. The rate of depreciation for different goods is at different speed with respect to time. For example, items like steel, glassware, plastic, etc., depreciate slowly, hardly affective the size of EOQ, whereas items like food products, chemical, medicines, radioactive, and volatile substance has quick or fast rate of depreciation, so much so the EOQ cannot be calculated without its consideration. Therefore to develop an important factor of consideration in inventory mathematical models. Initially, a fixed rate of depreciation was considered for inventory research modelling. Many researchers namely Aggarwal, Jaiswal and Shah, Ghara, Whitin and more assumed real-time replenishment, fixed demand and fixed rate of depreciation, while developing inventory models. Also, Dave (1986) discussed modelling for demand replenishment. Roy Chowdhury and Chaudhuri discussed modelling with further addition of shortages in assumptions along with the condition for refill. Dave also used shortage as assumption of work of Patel and Dave (1986). A heuristic inventory model considering demand proportional to time was considered in their work by Bahari-Kashani. In all the above discussed cases, a fixed rate of depreciation was assumed. Now, further a next level of models was developed with rate of depreciation to be dependent on time instead of fixed. In the work of Cohen and Philip depreciation under Weibull two-parameter distribution was considered. This work was extended by Philip by considering Weibull three-parameter distribution. Mishra used Weibull two-parameter distribution in his work along rate of replacement being finite. Whereas Deb and Chaudhari fixed the rate of production and took depreciation dependent on time. All the above discussed models had a common assumption of uniform rate of demand with respect to time. The third type of assumption on which inventory modelling has succeed in constant rate of depreciation and rate of demand varies with time under a linear curve. Few examples of work done on this criteria are by Chung and Ting, Hariga, Goswami and Chaudhari, Gorin et al. and many more. Also, model of Covert and Philip was extended by Jalan, Chaudhari, Giri to include these assumptions, and model of Philip was also similar extended by Chakrabarti et al. (1998). The modelling algorithm with finite rate of depreciation and exponential variation in demand with respect to time in various researchers like Jalan and Chaudhari Wee, Hariga, and Benkherouf. In addition to this, policy for lot size based on increasing or decreasing function of demand having log—concave variations with respect to time and assumption of fixed rate of depreciation was studied in Hariga. The study on rate of demand dependent on price is rare as compared to study on rate of demand dependent on time. In this area, Kunreuther and Richard studied the decision based on joint price policy for off-season stock. This study was further expanded by Scharge and Kunreuther for on-season stock. Cohen also discussed the policy based on same assumptions but for stock which depreciates at a fixed rate over time, whereas Cheng (1990) studied for stock which is non-depreciating but has limited space for storage and limited capital for investment. In a revised model

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of Cheng (1990), given by Chen and Min, it was suggested that linear dependence of demand on price was considered. The case of non—linear dependence was assumed by Hwang and Shinn along with the assumption of fixed rate of depreciation. As per a recent study by Abad, discussion on fact related to fixing of price and lot size of a stock which a varying depreciation rate, the discussion also allowed shortages and backlogged stock at times. Although in this, a theory was developed to generalize variation in rate of depreciation with time and dependency of rate of demand on price, the numerical illustration of this theory was not general and could elaborate only few special cases. The reason for this mismatch is not clearly known. Hence, noted till now, the function developed by Hwang and Shinn is nearest in representing demand dependent on price.

2 Objective In this paper, the model of Cohen (1977) in extended to Weibull three-parameter distribution representing depreciation and time distribution and take rate of demand dependent on price. Notations and Assumptions: The model is developed with the following notations and assumptions. (i) (ii) (iii) (iv) (v) (vi)

‘c’ fixed cost of purchasing per unit K: Cost of ordering for one cycle h: Cost of holding one unit per unit time p: Price to sell one item d(p): Rate of demand dependent on price Z(t) = αβ(t − γ )β−1 is the Weibull distribution in three parameters to denote depreciation with respect to time. (vii) T: time of one cycle (viii) No shortages in assumed. Let at any instant ‘t’, the level of inventory is denoted by I(t). The inventory reduces with demand and depreciation parallelly. Hence, the level of inventory I(t) at any time ‘t’ is given by differential equation d I (t) = −Z (t)I (t) − d( p) dt

0≤t ≤T

(3)

Using boundary condition I (t) = 0 and Z(t) = αβ(t − γ )β−1 (3) Can be solved and written as

(4)

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I (t) = I (0) = e

αβ (−γ )β−1−α (t−γ )β

− d( p) e

−α (t−γ )β

{t +

β

eα(t−γ ) dt

(5)

0

where I(0) is the level of inventory at initial stage substituting (4) in (5), we get, I (0) = d( p) e

−α(−γ ) β

{t

β

eα(t−γ ) dt

(6)

0

Putting (6) in (5), it gives I (t) = d( p) e

−α(t−γ ) β

{t

β

eα(t−γ ) dt, 0 ≤ t ≤ T

(7)

0

Which is solution of Eq. (3) when subjected to its boundary condition in (4). If there is no depreciation, then level of inventory at any instant of time ‘t’ is given by d I1 (t) = −d( p), 0 ≤ t ≤ T dt

(8)

and its boundary condition is I 1 (t) = 0. Equation (8) can be elaborated as I 1 (t) = −td(p) + I 1 (0), or I1 (0) = I1 (t) + td( p)

(9)

where I 1 (0) represents the level of stock at initial stage when no depreciation has taken place. At this initial stage since I 1 (t) = 0, therefore, we can say (9) becomes I1 (0) = T d( p) Also therefore, solution of (8) becomes I1 (t) = (T − t)d( p), z 0 ≤ t ≤ T

(10)

Therefore, considering depreciation in stock, we get I(0) and I(t) becomes levels of inventory and initial stage (t = 0) and at any instant (T = t), respectively. Also, the quantity reduction of inventory due to demand and depreciation in given by I(0) − I(t). The quantity reduction of inventory due to only demand and assuming no depreciation is given by I 1 (0) − I 1 (t). Above statement explains that the quantity reduction due to depreciation only can be calculated by (at any time ‘t’) is

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S(t) = [I (0) − I (t)] − [I1 (0) − I1 (t)] = [I (0) − I1 (0)] − [I (t) − I1 (t)]

= d( p)e

−α(−γ )β

{t e

α(t−γ )β

dt − T d( p) − d( p) e

−α(t−γ )β

{T

(11)

β

eα(t−γ ) dt + (T − t)d( p)

t

0

(12) = d( p) e

−α(−γ )β

{t e

α(t−γ )β

0

dt − e

−α(t−γ )β

{T

β

eα(t−γ ) dt · · · − t

(13)

t

Equations (12) and (13) can be solved using a numerical illustration through any viable computer based numerical method by prescribing the values of α, β, γ , and p parameters as shown in illustration below: Numerical Illustration Assuming α = 0.0001, β = 0.37, γ = −0.005 in suitable units. Using these values, Eqs. (12) and (13) are simultaneously solved to conclude the value of T * which represent the length of cycle. Also p* is calculated to represent optimized selling price. The result found are T * = 0.1738 and p* = 30.1471.

3 Notations The model use following rotations: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

λ (t) = ∝ βt is instant rate of depreciation ∝: Scale parameter β: Shape parameter d(p): rate of demand p: per unit selling price ‘c’: per unit purchase cost ‘K’: per cycle ordering cost ‘h’: per unit holding cost of stock per unit time T: per cycle duration I 1 (t): level of inventory at any instant t. λ (t) follows a Weibull two-parameter distribution with t ≥ 0, ∝ > 0, β > 0 d(p) is dependent on price ‘c’ is constant No shortages I 1 (t) = 0.

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In this paper, model is proposed and is analytically developed and illustrated for solution through a numerical example. The procedure of solution is carried out and shown in tabular representation with values obtained from sensitivity analysis. Hence, the computational procedures of important results are calculated. Let I 1 (t) denote level of inventory at any instant of time ‘t’. Then the corresponding instantaneous rate of inventory I 1 (t) is given by differential equation. d I1 (t) = −λ(t) I1 (t) − d( p), Costs T dt

(14)

I1 (t) = I0 and I1 (t) = 0

(15)

having conditions,

where I 0 is the initial quantity order at initial stage. There can be two factors for gradual depletion of inventory; these are depreciation and demand. λ I 1 (t) represents depletion of inventory due to depreciation per unit time and d(p) represents depletion due to demand. Also, negative sign for each term represents depletion (decrease) over time. Taking λ (t) = t β−1 , Then Eq. (14) can be solved as I1 (t) = I0 e

−αβ

− d( p)e

−xt β

{t

β

eαt dt

(16)

0

Equations (15) and (16) simultaneously gives, {T I1 (0) = I0 = d( p)

β

e∝T dt

(17)

0

Putting I 1 (0) from (17) in (16), it gives, I1 (t) = e

−∝T β

{T e

∝T β

dt − d( p)e

0

= d( p)e−∝T

−∝T β

{T

β

e∝T dt

0 β

{T

β

e∝T dt

(18)

0

Let Z(t) represent the loss in stock due to deterioration between time interval [OL t].

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Therefore, we get {T Z (t) = d( p)

e

∝T β

dt − d( p)e

−∝T β

0

{T

β

e∝T dt − td( p).

(19)

0

Therefore, knowing that depletion is only due to depreciation and demand, we can make the following conclusion for order quantity per cycle. Q T = Z (T ) + d( p) T {T = d( p)

β

e∝T dt

(20)

0

Also, we can know through calculations that total cost of one cycle is {T C(T , p) = k +c Q T + h

I1 (t)dt 0

{T = k + ed( p)

β

e∝T dt + hd( p)

0

{T 0

⎡ ⎣e∝T

β

{T

⎤ e∝T du ⎦dt β

t

[ 2 [ ] ] T ∝ T β+1 ∝ βT β+2 + hd( p) + = k + ed( p) t + β +1 2 (β + 1)(β + 2) Therefore, for average cost of system, we have C A (T, p) =

(21)

C(T , p) T

[ ] [ ] ∝ Tβ ∝ βT β+1 K − hd( p) + = pd( p) − + ed( p) 1 − T β +1 (β + 1)(β + 2)

(22)

Also, the rate of profit can be described as a function of price and duration of cycle, formulated as, π (T, p) = pd( p) − C A (T, p) = pd( p) −

[ ] [ ] ∝ Tβ T ∝ βT β+1 K + ed( p) 1 + − hd( p) + T β +1 2 (β + 1)(β + 2) (23)

The objective of the model and algorithm is to compute optimized values of π (T, p) and CA (T, p) for which values of T and p needs to be determined first. This objective is now elaborated using a numerical illustration and further is tested using sensitivity analysis.

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4 Numerical Illustration Assuming C = 15, h = 0.7, k = 175, ∝ = 0.2, β = 0.7 in suitable units. Equations (9) and (10) can be solved with these values to get T ∗ = 0.201, p∗ = 23.280, C A ∗ (T , p) = 7882.42, π ∗ (T , p) = 3112.81 These results are now tested for analysis using sensitive analysis. The obtained values are shown in Table 1 followed by the findings. Table 1 Table of sensitivity analysis

Parameter A

B

[

H

K

B

% Change in parameter

T*

p*

−25

0.1742

30.1466

−10

0.1740

30.1469

+10

0.1738

30.1472

+25

0.1737

30.1475

−25

01,740

30.1476

−10

0.1739

30.1478

+10

0.1740

30.1468

+25

0.1740

30.1466

−25

0.1739

30.1471

−10

0.1739

30.1471

+10

0.1739

30.1470

+25

0.1739

30.1470

−25

0.2447

30.0895

−10

0.1941

30.1263

+10

0.1540

30.1659

+25

0.1425

30.1915

−25

0.1226

30.0890

−10

0.1554

30.1261

+10

0.1957

30.1660

+25

0.2135

30.1918

−25

0.0132

58.6339

−10

0.0590

34.2810

+10

0.5303

28.2102

+25

3.5141

29.0887

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Table 2 Values of independent variable Change in %

T*

p*

π*

e*

C

−25 −10 +10 +25

0.1094 0.1650 0.2381 0.2937

11.3757 18.4392 28.2447 35.9532

34,311.71 12,683.60 5330.94 3288.111

15,158.84 5257.21 1996.226 1126.116

H

−25 −10 +10 +25

0.1999 0.2009 0.2022 0.2032

23.1537 23.2294 23.3320 23.4105

7972.09 7918.64 7846.93 7792.55

3150.40 3127.867 3097.80 3075.215

K

−25 −10 +10 +25

0.02695 0.8535 2.6760 64.177

∝

−25 −10 +10 +25

0.26395 0.21974 0.18795 0.17261

23.12197 23.21937 23.33876 23.41959

7887.89 7888.19 7875.19 7863.07

3266.687 3168.348 3062.90 2995.895

B

−25 −10 +10 +25

0.18467 0.18984 0.21469 0.23419

24.7575 23.621 23.1780 22.9027

7019.78 7685.84 7994.12 8082.70

2643.399 2979.429 3205.03 3297.279

42.4148 25.5255 68.5647 16,755.52

1,083,176.00 62,976.45 72.0604 1.3634

1,960,280.22 40,828.95 −18.22441 −103,634

5 Sensitivity Analysis The extent of effect of a model value and its changes on the results is very accurately analysed using sensitivity analysis. In this paper it is estimated the sensitivity changes in parameters T * and p*, i.e. the effect of cycle time and selling price with respect to variation in independent variables of the model. The analysed values and results are hence recorded for representation in Table 1. From the table, following findings are concluded. Sensitivity analysis is used to analyse the level of change or effect in the optimal solution obtained from the model due to variation in independent variables values. Here, different values are allotted to f , h, k, ∝, β to analyse the corresponding effect on T *, p*, C A *, and π * (Table 2).

6 Findings (1) (2) (3) (4)

The model shows steady sensitivity towards variations in ‘c’. The model shows very less sensitivity towards variations in ∝ and β. The model shows negligible sensitivity towards variations in ‘h’. The model shows high sensitivity towards variations in K, i.e. values of T *, C*, π *, and p* shows abused values in inversely proportional direction to variations

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of K should be carefully selected during its applications in industry or case studies. (1) Model shows no variation due to changes in α, β, γ . (2) Model shows an average sensitivity to other parameters like a, h, k described in the beginning. (3) Model is mostly affected by the changes in values of only one parameter, i.e. ‘b’ explained before.

7 Conclusion From numerical illustrations and findings of the sensitivity analysis, it can be concluded that for real-world application of this model, the utmost case should be taken of parameter ‘b’ for attaining optimum results of cycle time and selling price using Weibull distribution. As already mentioned, this model gives an extension to the work of Cohen (1977), whose unrealistic assumptions of constant depreciation and a linear dependency between price and demand were reconsidered with today’s fickle market and using Weibull distribution with three parameters and distribution of time. Also, the nonlinear function of demand and price gives a more realistic and general outlook of the work done by Shink and Hwaug (1997). In the long past history of inventory management, traditional assumption of no shortage, steady pattern of demand and function in square root was studied. Then, after four decades Donaldson theory was then improved later by Silver, Ritchie, Mitra et al. Till now, depreciation was not considered anywhere in assumptions of models developed, when depreciation is a sure process undergoing in inventory. Dane and Patel, then proposed a model linear pattern with fixed rate of depreciation. But real market analysis and its application through illustration and sensitivity analysis show that instead of linear rate of demand in quadratic function is closer to reality. In this paper, a model is formulated by taking into consideration a quadratic function for demand and fixed rate of depreciation. In this paper, the invention model of the order level is discussed where the demand rate is based on time. The estimated demand ratio is calculated by quadratic performance variation. Model resolved to deficit. The result is obtained by solving two odd variables in the Newton–Raphson method. Also, the cost of a large system is proven to allow for the operating process. Cultural or explicit differences in demands over time were studied by investigators. The direct function of the demand ratio with time is D(t) = a + bt, b /= 0, a ≥ 0, indicating a slow and constant change in demand. Similarly, the descriptive function of the demand ratio over time by D(t) = aebt, b /= 0, a > 0, indicates an excessive suspension of demand. Descriptive change is a numerical height that does not match the desired person in the real life market of any product. The change in demand has also been in the nature and nature of the product. Therefore, to prove the reallife market pattern, it is suggested that quadratic activity provides results that do not always be as active or extremely high as the indicator. Therefore, the quadratic function of the demand level in relation to the time studied id D(t) = a + bt + ct2

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is very true. And using the full maxima concept, it can be proved that D(t) has high values in t = −b/2c. This also concludes that the demand rate is gradually increasing and the beginning is declining. In this paper, stock with depreciation with respect to one-parameter Weibull distribution is discussed with, finite time phrase; exponentially dependent demand; rate of production is finite; allowed backlogs and shortages. The optimized cycles of production at minimum cost of average are discussed. In this model, the shortage in the inventory is allowed and is backlogged through the cycle only. It is assumed that at initial of every cycle of production, the inventory is zero. As the cycle proceeds, the stock is collected, after meeting market utilization and excluding depreciated stock. This collected inventory is utilized for meeting the demand during no production time. Due to some exceptions, at times, as soon as the complete stock is exhausted during the course of cycle, the production may not get started instantly again for further cycle but this delay may lead to shortages. And hence working on the bottlenecks and restriction in production initiation, the demand and shortages are all met and cleared till the production reaches end of cycle. Hence, it is shown that the production cycle ends with no shortage or backlogs or unused accumulated stock for the next cycle. Hence, this is taken as a different point from the classical theory of carry forwarding the shortages to next cycle. The increasing and decreasing demands are also considered with other parameters. The production and no production time durations are also determined during the study of optimized results. The total time duration of production is separated into cycle of production of equal time intervals.

8 Future Scope In future, the actual application areas can be studied for examples and for development of computerized software based on the protocol of this algorithm for more convenient and faster usage in various industries dealing with stock. In future, this model has a scope to be further developed as a computer software for practical industry application in cosmetics, woollen, computer machine aviation industry, etc., with b > 0, c > 0, for which this model can be further studied in future.

References Aggarwal SP (1978) A note on an order-level inventory model for a system with constant rate of deterioration. J Oper Res Soc 15:184–187 Berrotoni JN (1962) Practical applications of Weibull distribution. ASQCTech Conf Trans 303–323 Chakrabarti T, Giri BC, Chaudhuri KS (1998) An EOQ model for items with Weibull distribution deterioration, shortages and trended demand: an extension of Philip’s model. Comput Oper Res 25(7/8):649–657 Cheng TCE (1990) An EOQ model with pricing consideration. Comput Ind Eng 18(4):529–534

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Cohen MA (1977) Joint pricing and ordering policy for exponentially decaying inventory with known demand. Naval Res Logist Q 24:257–268 Covert RP, Philip GC (1973) An EOQ model for items with Weibull distribution deterioration. Aim 71-Cmsactions 5:121–l25 Dave U (1986) An order level inventory model for deteriorating items with variable instantaneous demand and discrete opportunities for replenishment. Opsearch 23:244–249 Deb M, Chaudhuri KS (1986) An EOQ model Cor items with !initc rate of production and variable rate of deterioration. Opsearch 23:175–181 Goswami A, Chaudhuri KS (1992) Variations of order-level inventory models for deteriorating items. Int J Prod Econ 27:111–117 Hwang H, Shinn SW (1997) Retailer’s pricing and lot sizing policy for exponentially deteriorating products under the condition of permissible delay in payments. Comput Oper Res 24(6):539–547 Kunreuther H, Richard JF (1971) Optimal PNCMG and inventory decisions for retail stores. Econometrica 39:173–175 Philip GC (1974) A generalised EOQ model for items with Weibul! distribution deterioration. A/IE Transactions Whitin TM (1957) Theory of inventory management. Princeton University Press

House Price Prediction: A Case Study for Istanbul Semra Erpolat Ta¸sabat

and Mert Ersen

1 Introduction Residences are places where individuals live. In addition, it is a durable consumption good and an investment tool that provides economic and social benefits to the people living in it. For many people, their homes are the most valuable tangible assets in their portfolio. Housing market, housing with supply and demand mechanism, it is defined as a place where its services are allocated. One of the features of the housing market that differs from the goods and services markets is the inelastic housing supply. Housing services are one of the most expensive household spending. Changing housing prices have been a source of concern for both individuals and governments, affecting socio-economic conditions and having an additional impact on national income conditions. The effect has been a source of concern. Capital gains expectations from housing investments housing prices will increase the demand for housing, which will lead to high volatility in housing prices. Housing market is one of the macroeconomic variables; it can be affected by spatial differences, structural features of society and environmental features (Kim and Park 2005). Housing spending is an important investment decision as it is among the priority needs of people. The housing market shows changes in comparison to other investment markets since it is considered as both an investment instrument and a property. The differences between the housing market and other investment instruments can be listed as: having high cost of housing supply, the housing market being a permanent investment instrument and being heterogeneous, its effect on growth of secondary markets and being capability to be shown as collateral for financial transactions. In S. E. Ta¸sabat (B) Prof., Mimar Sinan Fine Arts University, Istanbul, Turkey e-mail: [email protected] M. Ersen Yıldız Technical University, Istanbul, Turkey e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_14

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Turkey, many investors prefer residential investment rather than government bonds, treasury bills, or gold because of features listed above. Price of house may vary according to many reasons such as floor area and the size of house (number of rooms and bathrooms), total number of floors, the floor of the house, heating systems, quality of the components, age, physical wear, ease of transportation, distance of business centers, landscape, and car park. However, as the imbalance between the supply and demand in the housing market varies in different districts of Istanbul, it is seen that housing prices differ according to the district where they are located. Although some houses have the same characteristics, it is observed that they do not have the same price because they located in different districts or even neighborhoods. For this reason, even the name of the neighborhood where the house is located adds an added value to the price of the house. The methods used in house price prediction problems are traditional and advanced; it can be divided into two methods. As the hedonic model is the traditional method, artificial neural networks are included in the advanced methods category. Hedonic price model has been used effectively as a traditional method for estimating the market prices of houses. The price of a house is evaluated according to quantitative variables such as the number of rooms, age of the building, and the number of floors, as well as pricing differences in terms of environmental quality such as the district and location. Hedonic regression model enables the estimation of house prices to be modeled with a standard approach method. The most used price component is created with the help of dummy variables. Although the relationship between house prices and house properties has been studied extensively in the literature with the hedonic method, this approach is subjected to same criticism in determining the supply and demand, market balance, selection of independent variables, determination of the functional form of the hedonic equation (Fan et al. 2006; Malpezzi 2003). In such cases, ANN can be used as an alternative method for determining the house price. ANN is a flexible regression approach. This method is fundamentally different from the standard methods. In this model, there is no correct functional relationship between input and output values (Kaukot 2003). This model includes three basic components: input data layer, hidden layer, and output layer. The hidden layer also has two components. The first is the weighted sum, and the second is the transfer function. Both functions form a link from input values to output values. ANN are programs designed to simulate the operation of the simple biological nervous system. They contain simulated nerve cells (neurons), and these neurons connect to each other in various ways to form a network. These networks have the capacity to learn, memorize, and reveal the relationship between data. In other words, ANNs provide solutions to problems that normally require a person’s natural abilities to think and observe. The main reason why a person can produce solutions to problems that require thinking and observing skills is the ability of the human brain, and therefore the human being, to learn by living or experimenting (Yurto˘glu 2005). In this study, it is aimed to analyze the factors affecting the housing prices in Istanbul, regarding the difference of neighborhood, by using HPM and ANN methods and to compare the performances of these two methods. The following sections of

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this study are as follows: In the second section, previous studies on this subject are examined, and in the third section, information about HPM and ANN methods which are methods used are given. In the fourth section, the data and methods used in the model are discussed, and the predictive performances of the methods used are compared. In the last section, the obtained information is summarized, and the results are evaluated.

2 Literature Summary Ridker and Henning (1967) are responsible for analyzing of application of hedonic prize theories of house market to effects of air pollution to house prizes. Ridker and Henning hedonic prize theory can be considered as one of the first work about air pollutions effect on house prize. In this work, he investigated of developing of quality of environment’s (raise of air pollution) effects on house market. Kain and Quigley (1970) found that 1184 total observations, 854 restricted observations, and semi-logarithmic and linear models of housing services affect the housing prices rather than objective characteristics (such as number of rooms, number of bathrooms and land area). The continuation of these works was Straszheim (1974), Goodman (1978), Palmquist (1984) tried to explain the sale price of the house, which is the dependent variable with hedonic price approach, with different independent variables. Do and Grudnitski (1992), when using a test sample of 105 households, stated that an artificial neural network model performs better than the multiple regression model to estimate the housing price. The authors reported absolute errors of 6.9% and 11.3% as evidence. Worzala et al. (1995) analyzed the housing price in the state of Colarado with artificial neural networks. The parameters they use building age, number of rooms, number of bathrooms, total area, garage, fireplace, land area, and area. They have reached 82% accuracy with 270 datasets. Cechin et al. (2000) analyzed the building data for sale and rent in Porto Alegre, Brazil with linear regression and artificial neural networks. The parameters they used are the size of the residence, the district, the geographical location, the environment, the number of rooms, the construction date of the building, and the total area of use. At the end of the study, the artificial neural network method was more useful than linear regression. They reached an average of US $ 11 with artificial neural networks and an average of 33 US dollars in linear regression. Analysis of the rental results was more successful than the analysis of the sales results. Üçdo˘gruk (2001) has searched the factors that affect house prize in ˙Izmir City which is about 2718 houses. In this work, lots of independent variables are used, and mostly, houses heating system, being houses on the avenue and being houses at the Cigli district (in negative way) are the important variables that affect houses prizes. This work’s analyzes method is multi-regression.

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Özus and Dökmeci (2006), in their studies, determine the physical and functional factors and their degree of influence in the historical residential areas of Beyo˘glu, where the reflections of the transformation process experienced in Istanbul are intensely observed, by using hedonic price analysis. As a result of the study, it has the most impact on the price of housing. Other variables according to the sea view width and degree of influence; the building structure type, the number of vacant flats in the building, the distance to the industrial facilities, the number of floors, the use of the garden and the presence of heat insulation. According to the results of the study, the widening of the sea view angle of the house increases the sale price of the house. In addition, if the building containing the house for sale is detached, the sales price of the house is higher than if the house is located in an apartment-type building. In the study, it is concluded that the number of vacant flats in the building positively affects the house prices, while the presence of an industrial facility around the house decreases the house prices. In addition, according to the results of the study, the increase in the number of floors in the region positively affects the house sales prices. Kördi¸s et al. (2014) are to analyze the factors affecting housing prices in Antalya by hedonic pricing method. According to the results of the study, the important factors affecting housing prices in Antalya are the width of the house, being in a high-income area, having a sea view, having a closed car park, being an apartment, being close to the sea, having a heating system and an elevator. In the study, it is seen that house prices in regions close to the sea are much higher than the average in far regions. Similarly, the sea view has been found to have a positive effect on house prices. In the study, there is a positive relationship between the width of the house and the number of rooms and the house prices; it is stated that the prices of the houses that are not on the south side are well below the general housing price average in Antalya. According to the results of the study, the presence of the parking garage and the doorman positively affects the prices of the houses. Similarly, the fact that the house is within the site also affects the housing prices positively. The fact that the house has a swimming pool is also one of the factors affecting housing prices. In addition, the high floor of the house, the high number of toilets/bathrooms, and the multi-story building have a positive effect on the price of the house. In the model, it is found that the prices of flat-type houses are higher than duplex houses. In the study, the age variable has a significant and negative effect on house prices. Ecer (2014) in his work compared the hedonic regression method and artificial neural network to estimate house prizes in Turkey. In this work, number of 610 houses data in ˙Izmir in Kar¸sıyaka district which have been sold at between the months of January and July in 2013 is used to estimate house prizes. The variables that have been used in this dataset are the number of 83 properties that houses have. Variables affecting the housing price in the artificial neural network model: Swimming pool, being by the sea, close to the city center, having a burglar alarm, having a built-in closet, age, being close to the train station, having security on the site, being close to the sea bus, being close to the mosque, university, etc. close to the health center, on the street, built-in kitchen, sound insulation and heated glass, cable TV, hydrophore and steel door, and a terrace. While two model’s estimation of accuracy is compared,

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it is concluded that the artificial neural network is more useful at making predictions rather than hedonic model. Çiçek and Hatırlı (2015) analyzed house prices with hedonic analysis method in their study in Isparta Province. In the study involving nearly 50 neighborhoods, the neighborhoods were gathered in 3 groups against the possibility of using each neighborhood as a separate dummy variable to increase the margin of error of the model. Groups: It was determined according to the level of development, taking into account features such as income level, education level, and being close to the city center. According to the results of the study, the most important factors affecting the price of the house; distance to the city center, air pollution, the surroundings of the house, the age of the house, the size of the house, the number of rooms, having a central heating, having a car park and being on the south side. Among these variables, the proximity of the house to the city center, the size of the house, the number of rooms, its being on the south side, having a car park positively affect the price of the house, while the presence of air pollution and the increase in the age of the house reduce the price of the house. In addition, according to the results of the study, among the neighborhoods divided into 3 according to their development levels, housing prices were also higher in the neighborhood with the highest level of development. Yılmazel and Af¸sar (2018) have used YSA method to estimate house prizes in Eskisehir. In this work, house’s size, room numbers, availability of house whether on the first floor or not, total number of floors in building where the house is available, availability of central heating, number of bathrooms, availability of elevator, car park, built-in kitchen, fiber Internet connection, etc., are set with distance of house to its neighborhood and distance to tram parameters and set with artificial neural network models. At the developed artificial neural network, hidden layer neuron numbers are differentiated, and number of 19 models is gained. Then, these models’ performance comparison has been done, and the most suitable hidden layer neuron numbers is provided. As a conclusion, it is clearly understood that the artificial neural networks are very efficient tool at the estimation of housing prize. According to works that YSA models have been used and which is used for estimation housing prizes are mostly show that YSA models exhibit more performance rather than other models at the estimation housing prizes.

3 Material Method The most used house price prediction methods are HPM and ANN. In this study, these methods are used for predicting housing price. The details of the methods are given below.

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3.1 The Hedonic Price Model The HPM was first created in 1939 by American automobile industry expert Andrew T. Court. In the housing market, Ridker and Henning (1967) were the first use the linear functional form to determine the effect of air pollution on the prices of residential houses. They made a study based on the 1960s census of the Lousis district (Ridker and Henning 1967). Housing markets have a significant share of the country’s economies. Because the housing market is related to many sectors, accurate estimation of housing prices is extremely important in terms of control of the economic market. The HPM, which is one of the methods developed for this purpose, is a method used in examining the effect of a product feature on price (Yazgan et al. 2017). HPM is based on the idea that products have a heterogeneous structure. In this price model, products differ in terms of their characteristics. The characteristics of these differentiated product markets and the price relations between these products form the basis of the HPM. In this model, it is believed that each of these features that the model holds has a different effect in determining the price. In the HPM, an environment is provided for determining the marginal cost that the consumers are willing to pay to purchase a product and for determining each of these features effecting the price. It is used in differentiated product market. Differentiation of consumer preferences is very crucial for the housing market as it forms the demand in the housing market. For instance, although additional features of house such as gym, swimming pool, sauna, and private security are not priced out separately, the price of these houses including these features can be calculated via hedonic model. This allows consumers to easily see which features they care about most when buying a house and what qualities convince them to pay the price. Contractors engaged in the construction of new houses also take these qualities into consideration and construct new houses according to consumers’ demands (Üçdo˘gruk 2001; Goodman 1978). As the HPM is a regression-based approach, it is aimed to investigate the effects of these qualities on the price by helping establish a relationship between the qualities and prices of a product. When we exclude one of the features that make up the model, a change in the price, which is the dependent variable of the model, will occur. For this reason, the HPM is an important method in the housing market due to fact that it reveals the qualities that consumers’ demand, and it also identifies which features constitute the housing prices (Af¸sar et al. 2017). In determining a housing price using the HPM, it is necessary to determine whether all the properties that are thought to have an effect on the estimation of the price of the house have a significant share in the price estimation of the house. In addition, if these properties have a significant impact on the price of the house, a hedonic price function should be established to determine the impact strength and direction of this property on the price of the house, and the hedonic price function should be applied to regression analysis. In hedonic price function, the dependent variable is the price of the house, while the independent variables are the properties that affect the price of the house. Considering the variables affecting the price of the house are classified as

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the structural characteristics of the house, the location locational features, the other variables in the hedonic price function are the location of the house and locational features (Straszheim 1974). As the HPM does not provide guidance on which pattern should be chosen to correctly determine the functional pattern, researchers using this model need to determine the functional pattern that best describes the relationship between the price and the characteristics of the house. If the functional pattern is selected incorrectly, deviations and misinterpretations will occur in the model. Therefore, it is very important to choose the right functional pattern (Kaya 2012). There is no definitive criterion for hedonic price function when performing housing analyses. Four different functional patterns are evaluated in the analysis of hedonic price function. These are as follows: . . . .

Linear Model, Full Logarithmic Model, Linear Logarithmic Model (Lin-Log), Logarithmic Linear Model (Log-Lin).

In the following sub-sections, the variable definitions used in all given formulas are as follows: P: Price of the house, X n : Property features (independent variables), α: Constant term, β n : Hedonic price of each feature, εt : Error term, Y: Dependent variable, D: Dummy variable. Linear Model It refers to the hedonic price function pattern that will be used if there is a full linear relationship between the price of the dependent variable home and the characteristics of the housing expressed as independent variables. The linear model is given in (1). P = α + β1 X 1 + β2 X 2 + β3 X 3 + . . . βn X n + εt

(1)

The absolute increases and decreases in the properties of the dwelling indicate that if the price of the hedonic price function is linear, the price of housing will cause absolute increases and decreases (Kaya 2012). Full Logarithmic Model It refers to the hedonic price function pattern that will be used if there is no linear relationship between the price of the dependent variable and the characteristics of the housing expressed as independent variables. Each of the dependent and independent variables is a logarithmic model in the hedonic price function to be used. The formula of this function is given in (2).

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In P = α + β1 In X 1 + β2 In X 2 + . . . βn In X n + εt

(2)

In this formula, βs are defined as the parameters of houses properties at the full logarithmic model, and this represents these properties’ flexibility value. In other words, βs express the percent changes that occur on dependent variable (price of house) by the independent variable (properties of house’s percent change). It can be interpreted as “this model can cause at the independent variable X 1 %1 changes and at the dependent variable as β 1 %1 changes” (Kaya 2012). Linear Logarithmic Model (Lin-Log) Linear logarithmic model refers to the hedonic price function pattern where house’s properties (as independent variables) are in logarithmic form while the price of house (as a dependent variable) is in a linear form. It was given in (3). P = α + β1 InX 1 + β2 InX 2 + . . . βn InX n + εt

(3)

The %1 change that happens at properties of houses (as independent variables) causes some changes on price of houses (as a dependent variable), and this absolute change is defined with this model. It can be interpreted as “the linear logarithmic model, the %1 changes the independent variable X 1 can cause changes on dependent variable P as β 1 ” (Kaya 2012). Logarithmic Linear Model (Log-Lin) Logarithmic linear model refers to the hedonic price function pattern where house’s properties (as independent variables) are in logarithmic form while the price of house (as a dependent variable) is in a linear form. This model is given in (4). In P = α + β1 X 1 + β2 X 2 + β3 X 3 + . . . βn X n + εt

(4)

The absolute changes that happen at properties of houses (as independent variables) cause some changes on price of houses (as a dependent variable), and percent changes are defined with this model. It can be interpreted as, in the logarithmic linear model, one unit change on X 1 (independent variable) can cause changes as β 1 at the P (dependent variable). In this study, logarithmic linear model pattern was utilized because of the fact that the most preferred pattern in the studies related to HPM in logistic analysis was the logarithmic linear model, and no problems were encountered in the addition of dummy variables in this model. The reason why there is no problem in adding dummy variables like the other models used in this model is that the change in dummy variables (for example, having a dwelling pool) is only expressed by the percentage changes. Since some variables considered to have an effect on the price estimation of the house cannot be measured, their assets can only be related to whether they exist or not. For example, having a pool to be determined as one of the properties of a dwelling can be added to the model by dummy variable and if the dwelling has a

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pool, the dummy variable is considered to be 1; otherwise, it is considered to be 0. The logarithmic linear model that dummies variables include is given in (5) (Kaya 2012). In Y = α +

∑

βi X i +

i

∑

βi Di

(5)

j

3.2 Artificial Neural Network (ANN) The ANN approach is an artificial intelligence research field inspired by the working principle of the human brain. It has been developed with the aim of developing new knowledge through learning which is a characteristic of the human brain and at the same time realizing the capabilities automatically without the need of any help. The first studies on this subject started with the modeling of neurons that make up the human brain and their application in computer systems, and in later stages, it has become a method that can be used in many fields with the developments in the computer system (Worzala et al. 1995; Cechin et al. 2000). Computer systems developed with this method are trained with the examples shown to them and thus have the ability to decide on similar issues. In order to make an estimation with ANN, input data and training stage and test phase should be completed first. Estimation data are obtained after these operations are performed (Öztürk and Ergin 2018; Do 1992). Estimation of housing prices is very difficult because of the redundancy of parameters. With the development of technology, ANN method was added to the methods used in the development of technology. The biggest advantage of the ANN method as opposed to the traditional methods is that, in cases where it is very difficult to solve the problem, the dataset is not given in a linear way; there are missing or incorrect data, and it is multidimensional; this method can give effective results (Karahan 2011). Moreover, this method is more advantageous than the statistical methods because it does not make any assumptions regarding data characteristics and distributions (Yılmazel et al. 2018). In this study, multilayer perceptron (MLP) method which is one of ANN models was used. The MLP model is a feed-in network and is a method used in consultation. The backpropagation algorithm is used to educate these networks, and this algorithm aims to bring back the error to the minimum level. This method is thought to resemble to a black box because a relationship between the input and output parameters cannot be established in the ANN method. The reason why this method is likened to a black is that the knowledge of what is inside is not known. After entering the data, only, the results are taken into consideration. In other words, this method has no ability to explain how the results occurred. Although such situations lessen the reliability of this method, the studies carried out in this area in recent years have increased the interest in this method. In this study, the properties of a house were used as the input

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Fig. 1 Architecture of a single layer perceptron

parameter, while the price of the house is used as the output parameter (Öztemel 2006). The Artificial Neural Network Models The models that developed for ANN can be lined in four main groups: single layer perceptron (SLP), multilayer perceptron (MLP), forward feed ANN, backfeed ANN.

3.2.1

The Single Layer Perceptron

Single layer ANNs consist of only input and output layers. For SLP, the output function is a linear function and takes 1 or −1 values. If the output is 1, the first grade −1 is accepted to the second grade. Figure 1 shows architecture of a single layer perceptron. The architecture consists of a layer on input neurons fully connected to a single layer of output neurons.

3.2.2

The Multilayer Perceptron

In the case of being failure of single layer perceptron at nonlinear problems, this MLP is developed. This perceptron consists of input layer which is the information entrance is done, one or more interval perceptron, and it consists of one output layer. In this perceptron type, the passages which is called inter-layer forward and backward spread are available. At the phase of forward spread, the output of network and value of error is being calculated. And at the phase of backward spread, to minimize the calculated value of errors, inter-layer linked weighted values are being updated. Figure 2 symbolizes this structure. In this example, the network includes 3 layers: input, hidden, and output layer. Each connection between two neurons is given by a certain weight.

3.2.3

The Forward Feed Artificial Neural Networks

In this type, neurons are lined up as regular layers from input to output. There is only a link exists from a layer to next layers. The knowledge that come to entrance of artificial neural network is sent to middle point (hidden layer) without changing.

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Fig. 2 Structure of a multilayer perceptron neural network

Later than, respectively, it is passed from the output layer with being processed and sent to external environment. There is a flow opposite to the arrows in Fig. 2 in the forward feed ANN.

3.2.4

The Back Feed Artificial Neural Networks

The back feed artificial neural network is different from the forward feed artificial neural network at the point of where the output of a neuron is not being accepted as input to the next neuron layer. It can be linked to neurons where the previous layer or its own layer. With this structure, the back feed artificial neural networks show nonlinear (dynamic) attitude. According to type of links that which is gained the specification of back feed, with the same artificial neural network (Do˘gan 2016), it can be evaluated different behavioral and different structured artificial neural networks (Fig. 3). In this work, the MLP method from the artificial neural methods is being used. In this study, the MLP method, which is one of the Artificial Neural Network models, was used. The MLP model is a feed-forward network and is a method used in supervised learning. Back propagation algorithm is used to train these networks and it is aimed to bring the error backwards to a minimum level with this algorithm. In the ANN method, this method is likened to a black box, since there is no definite relationship between the input and output parameters. The reason why it is called a black box to this method is the content inside is not known by us. After the knowledge is entered, the conclusions that gained are concern at the moment. If it is explained in another words, there is not an ability exist of how we explain this method’s conclusion. Although the situations which is previously mentioned harm to this method, especially at the last years, the research that has been made takes attentions on this method. In this work, as an input parameters, house’s features and as an output parameter house’s price algorithm has been used.

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Fig. 3 Architecture of a multilayer perceptron neural network with backpropagation

4 The Research Findings and Discussion In this study, districts of Istanbul were determined to be the fields of study. There are various options as residence types online such as villas, detached houses, and flats; hence, only, flat advertisements are taken into consideration. A total of 900 data were selected by random sampling method between September 2017 and April 2019 through a computer program. The district where the flat is located, the square meter of the house, whether it is on the lower floor or the upper floor, the number of rooms, the floor where the apartment is located, the total number of floors in the building, whether there is an en-suite bathroom or not, and the proximity to the city center is determined as the properties of the flats. When the data used in this study are examined in terms of room numbers, the results are as follows: one-room 4 (0.05%), 2-room 62 (8.3%), 3-room 377 (50.6%), 4-room 192 (25.8%), 5-room 73 (9.8%), 6-room 17 (2.3%), 7-rooms 10 (1.3%) 8roomed 2(0.03%), 9-room 4 (0.05%), 10-room 4 (0.05%). The number of apartments with an en-suite bathroom is 255 (28.3%). It is seen that the highest number of flats for sale belongs to Esenyurt with 154 advertisements, while Gaziosmanpa¸sa, Çatalca, and Silivri hold the lowest numbers. The reason for the high number of houses for sale in Esenyurt district is that it is one of the districts with high-rise buildings. When we have a look at the number of the

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flats for sale regarding the number of rooms, Esenyurt and Ba¸sak¸sehir have flats with fewer rooms compared to Kartal and Maltepe, where 3 + 1 flats and flats with more rooms are available. When the housing prices are compared with the square meter unit prices, it is seen that the cheapest houses are located in Esenyurt, while the most expensive houses are located in Be¸sikta¸s. In terms of the date of sales advertisement, the longest time interval seems to be in Kartal. As a result of the analyses conducted while forming the HPM, the number of floors and the number of rooms and the district where the house is located are decided to be removed from the model since they are accepted to have no statistical significance. In the model implementation of the study, statistically significant features are continued to be used. These features are duration of the advertisement, the age of the building, the total number of floors in the building, whether the apartment was on the lower floor or in the upper floor, the square meter of the apartment, whether it had an en-suite bathroom or not and its proximity to the city center. In the first phase of this study, HPM was developed by using multiple regression technique. The logarithm of the house price was found to be strongly correlated with statistically significant independent variables. Besides, the values of variance inflation factor (VIF) values are found to be below 10, and the tolerance statistical value is found to be above 0.2. Therefore, it was seen that there was no problem with multiple linear connection because of low tolerance and high VIF values. The variables included in the model explain 42% of the change in the housing pricedependent variable. As a result of the ANOVA test, the F value was found to be 38,089, and the significance value was found 0,000. Therefore, it was concluded that the model was statistically significant (F value 38,089 and sig 0.000 < 0.05). It should also be examined if there is autocorrelation. According to the results obtained in the model, Durbin Watson value was found as 1.717. The Durbin Watson value being between 1.5 and 2.5 indicates that there is no autocorrelation problem in the model. Since the value found in the model was between these two values, there was no autocorrelation (Af¸sar et al. 2017). In this study, logarithmic linear model pattern of hedonic price function was chosen. The reason for this is that it does not create any problems in the addition of dummy variables and is the most preferred model in the studies. This model is given in (6). In P = 2229 + β1 X 1 + β2 X 2 + β3 X 3 + β4 X 4 + β5 X 5 + β6 X 6 + β7 X 7 The descriptions of the variables used in this model is as follow: X 1 : Created date, X 2 : Building age, X 3 : Total floor, X 4 : Lower floor and upper floor, X 5 : Log square meters, X 6 : Parent bedroom, X 7 : Proximity city center.

(6)

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Table 1 Results of multiple regression analysis Variable

β

Standard deviation

t

Significant

Constant

2.229

0.296

7.537

0.000

Created date

0.008

0.003

2.270

0.024

Building age

0.010

0.003

3.998

0.000

Total floor

0.015

0.003

4.547

0.000

−0.128

0.041

−3.165

0.002

Log square meter

1.426

0.143

9.957

0.000

Parent bedroom

0.156

0.051

3.078

0.002

Proximity to city center

0.307

0.038

8.134

0.000

Lower floor and upper floor

The result of the model is given in Table 1. From the results, it can be said that whether the flat is located on a lower or an upper floor of the building has a negative effect on the housing price. In the second part of the study, ANN method was used. Nowadays, many ANN models have been developed for specific purposes and in different fields. Among these models, multilayer perceptron model is the most widely used (Kaynar et al. 2011). In the study, MLP model which is one of the ANN models was preferred. The dependent and independent variables used in the MLP model are the same as those used in the hedonic model for a healthy comparison. The network structure of the model is as in Fig. 4. This model was developed by using IBM SPSS modeler. For HPM (Fig. 5a), the most effective physical variables on the housing price are found to be the age of the building and the square meter of the house, respectively. Whether the flat is located on a lower or an upper floor of the building has a negative effect on the housing price. For ANN model (Fig. 5b), the most effective physical variables on the housing price are the square meter of the house and the total number of floors in the building, respectively. The mean absolute error (MAE) performance criteria were calculated to compare the prediction results obtained from the models constructed with the HPM and ANN. If these calculated values are close to zero, it can be said that the model’s prediction performance is near perfect (Ecer 2014). When the MAE values were compared according to Table 2, smaller results were obtained in ANN model. The smaller the MAE values in the ANN model, the better the performance of this model and the more accurate the housing price. The graphical comparison of the two methods for training and testing datasets (Fig. 6: 1_Training and 2_Testing) is also shown that the ANN model gives better results. When the previous studies between the properties of the house and the price of the house are examined, it is seen that there is a nonlinear relationship. Therefore, in order to estimate the housing price, the ANN model, which is a safer method rather than linear approaches, was developed as an alternative to hedonic price method.

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Fig. 4 Network structure of model

5 Results In this study, 900 houses which were sold between September 2015 and April 2019 in Istanbul were chosen by means of a random sampling method. In the prediction of housing price, ANN model was used with HPM. According to the HPM, the most effective physical variables on the housing price were the building age and the square meter, respectively, whereas the most significant variables were the square meter and total coefficient in the building, respectively. Compared to the prediction performance of the two models, it was found that the ANN model gave better results than the hedonic model. In addition, the results obtained from this study supported the results of many previous studies and confirmed that the ANN method gives better results than the HPM. The scope of the study can be further elaborated by adding the exchange rates and interest rate variables from the economic factors that are thought to have an impact on the housing price.

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Fig. 5 Variable importance for a HPM and b ANN Table 2 Comparison of HPM and ANN

Performance measure

HPM

ANN

MAE

Training = 0.319

Training = 0.228

MAE

Testing = 0.341

Testing = 0.302

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Fig. 6 Comparison of models

References Af¸sar A, Yılmazel A, Yılmazel S (2017) Konut Fiyatlarını Etki-leyen Faktörlerin Hedonik Model ˙Ile Belirlenmesi: Eski¸sehir Örne˘gi, Selçuk University Social ScienceInstitute Journal, Business Administration/Research,pp 195–205 Cechin A, Souto A, Gonzalez MA (2000) Real estate value At Porto alegre city using Ann. In: Proceedings 6th Brazilian symposium on neural networks Çiçek U, Hatırlı SA (2015) Isparta ˙Ilinde Konut Fiyatlarını Etkileyen Faktörlerin Hedonik Fiyat Modeli ile Analizi, Mehmet Akif Ersoy Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 7(13):98– 114 Do AQ (1992) A neural network approach to residential property appraisal. The Real Estate Appraiser 58:38–45 Do Q, Grudnitski G (1992) A neural network approach to residential property appraisal, The Real Estate Appraiser, 58:38–45 Do˘gan O (2016) Yapay Sinir A˘gları Ecer F (2014) Türkiye’deki Konut Fiyatlarının Tahmininde Hedonik Regresyon Yöntemi ile Yapay Sinir A˘glarının Kar¸sıla¸stırılması. In: International conference on Eurasian economist, pp 1–10 Fan G, Ong ZSE, Koh HC (2006) Determinants of house price: a decision tree approach. Urban Studies 43(12):2301–2315 Goodman AC (1978) Hedonic prices, price indices and housing markets. J Urban Econ 5:471–484 Kain JF, Quigley JM (1970) Measuring the value of housing quality. J Am Stat Assoc 65(330):532– 548 Karahan M (2011) ˙Istatistiksel Tahminleme Yöntemleri: Yapay Sinir A˘gları Metodu ˙Ile Ürün Talep Tahminlemesi. Konya Selçuk University Social Sciences Institute Kaukot T (2003) On current neural network applications involving spatial modelling of property prices. J Housing Built Environ 18:159–181 Kaya A (2012) Türkiye’de Konut Fiyatlarını Etkileyen Faktörlerin Hedonik Fiyat Modeli ˙Ile Belirlenmesi, Central Bank of Turkish Re- public, General Directorate of Statistics, Specialty Proficiency Thesis, Ankara

250

S. E. Ta¸sabat and M. Ersen

Kaynar O, Ta¸stan S, Demir KF (2011) Yapay Sinir A˘gları ˙Ile Do˘galgaz Tüketim Tahmini, Atatürk University Business Administration Journal, 10. Econometrics and Statistics Symposium Special Issue Kim K, Park J (2005) Segmentation of the housing market and its determinants: Seoul and its neighboring new towns in Korea. Aust Geogr 36(2):221–232 Kördi¸s G, I¸sık S, Mert M (2014) Antalya’da Konut Fiyatlarını Etkileyen Faktörlerin Hedonik Fiyat Modeli ile Tahmin Edilmesi. Akdeniz ˙I.˙I.B.F. Dergisi 28:103–132 Malpezzi S (2003) Hedonic pricing models: a selective and applied review. In: O’Sullivan T, Gibb K (eds) Housing economics and public policy. Blackwell Science, Malden, MA, pp 67–89 Öztemel E (2006) Yapay Sinir A˘gları. Papatya Publishing, Istanbul Öztürk K, Ergin SF ¸ (2018) Yapay Sinir A˘gları ve Yapay Zekâ’ya Genel Bir Bakı¸s. Recep Tayyip Erdo˘gan University, Eng Fac 6(2):25–36 Özus E, Dökmeci V (2006) Dönü¸süm ya¸sanan tarihi alanlarda konut fiyatlarında etkili faktörlerin analizi, ˙ITÜ Dergisi/a Mimarlık, Planlama, Tasarım 5(2):177–186 Palmquist RB (1984) Estimating the demand for the characteristics of housing. Rev Econ Stat 66(3):394–404 Ridker R, Henning J (1967) The determinants of residential property values with special reference to air pollution. Rev Econ Stat 49(2):246–257 Straszheim MR (1974) Hedonic estimation of housing market prices: a further comment. Rev Econ Stat 56(3):404–406 Üçdo˘gruk S (2001) ˙Izmir ˙Ilinde Emlak Fiyatlarına Etki Eden Fak- törler - Hedonik Yaklasım. Dokuz Eylül Üniversity, Econ Adm J 16(2):149–161 Worzala E, Lenk M, Silva A (1995) An exploration of neural networks and its application to real estate valuation. J Real Estate Res 10(2):185–200 Yazgan AE, Koçyi˘git N, Telli ÜY, Cici KEN (2017) Konut Fiyatlarının Tahmininde Hedonik Model ile Yapay Sinir A˘glarının Kar¸sıla¸stırılması: TR 52 Bölgesinde Amprik Bir Çalı¸sma. Acad Soc Res J 5(59):465–478 Yılmazel Ö, Af¸sar A, Yılmazel S (2018) Konut Fiyat Tahmin- inde Yapay Sinir A˘gları Yönteminin Kullanılması. Int J Econ Adm Stud 286–290 Yılmazel Ö, Af¸sar A, Yılmazel S (2018) Konut Fiyat Tahmininde Yapay Sinir A˘gları Yönteminin Kullanılması. Uluslararası ˙Iktisadi ve ˙Idari ˙Incelemeler Dergisi, (20):285–300 Yurto˘glu H (2005) Yapay Sinir A˘gları Metodolojisi ile Öngörü Modellemesi: Bazı Makroekonomik De˘gi¸skenler için Türkiye Örne˘gi, Devlet Planlama Te¸skilatı, Ekonomik Modeller ve Stratejik Ara¸stırmalar Genel Müdürlü˘gü, Uzmanlık Tezi, No: 2683

Government Implications of Infrastructural Development and CSR in Industry 4.0 Teena Saharan and Anchal Pathak

Abbreviations ADP AIM AIA AMT BIRAC CAGR CEFC DISHA DHI DST DRDO DPIIT FDI FICCI FAME GAGAN GOI IBEF ICAR IoT IIT IIM

Automatic Data Processing Atal Innovation Mission Automation Industry Association Advanced Manufacturing Technology Biotechnology Industry Research Assistance Council Compound Annual Growth Rate Common Engineering Facility Center Digital Saksharta Abhiyan Department of Heavy Industries Department of Science and Technology Defense Research and Development Organization Department of Promotion and Internal Trade Foreign Direct Investment Federation of Indian Chambers of Commerce and Industry Faster Adoption and Manufacturing of Hybrid and Electric Vehicles GPS Aided Geo Augmented Navigation Framework Government of India India Brand Equity Foundation Indian Council of Agricultural research Internet of Things Indian Institute of Technology Indian Institute of Management

T. Saharan (B) MGM Group, Aurangabad, India e-mail: [email protected] A. Pathak Bule Hora University, Bule Hora, Ethiopia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_15

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The Indian Institute of Science National Electric Mobility Mission Plan National Automotive Testing and R&D Infrastructure Project The National Institution for Transforming India Ministry of Electronics and Information Technology Ministry of Micro, Small and Medium Enterprises Smart Manufacturing Demo and Development Cell Smart Advanced Manufacturing and Rapid Transformation Hub Ude Desh ka Aam Nagrik United Nations Industrial Development Organization

1 Industry 4.0 This 4th Industrial Revolution (I4.0) has changed the market and gained exponential momentum to the advancement of many techniques such as artificial intelligence, augmented reality or the Internet of Things (IoT). More in-depth information is expected in the year 2021 across industries due to an unimaginary advancement in robotics, artificial intelligence, 5G Networks and augmented reality (AR). The latest trends have transformed the operational processes and procedures of industries. It has been witnessed by the companies using artificial intelligence that the organizational operational efficiencies and customer experience took a high ride with the offered power solutions for industrial automation. The increasing use of collaborative robots has started providing many benefits to industries such as the safety of workers during risky operations and handling strenuous activities. The assembly lines with more risks and intricacies could be automated using robots. The revolution of cobots (collaborative robots) created a dimension of work culture where men and machines can work together. Cobots can detect humans and are able to change paths or reduce speed to avoid accidents. The humans in organizations can focus on more strategic and critical business activities, whereas routine and strenuous tasks can easily be handled by these cobots (GOI 2018a, b). Now, the introduction of 5G networking has opened new doors of possibilities. It will provide the users with more reliable or low latency networks which would eventually make it easy and flexible for organizations to reconfigure the existing layouts and alter factory setups. Another golden feather has been added in Industry 4.0 with the emergence of augmented reality (AR). It has bought a significant revolution in operational efficiency by providing the option of seeing an overlay in virtual form. The adoption of augmented reality has improved efficiency and enabled organizations to work faster.

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1.1 Industry 4.0 in India India became the only developed economy that made its position in the second group for new innovations in ADP (Automatic Data Processing) Technologies according to the ‘Industrial Development Report on Industrialisation in Digital Age’ released by UNIDO. India shared this position with many leading economies like Australia, Canada, Spain and Italy in this field of ADP Technologies. It presented that Indian companies are progressing with innovation in ADP technologies and providing support to many developed countries such as USA, European Union, Japan and many more leading markets. Indian developers are embedding these technologies in smart machines and new capital goods to increase the export (Van Berkel 2020). In India, the adoption and widespread implementation of I4.0 still are at its beginning stage. Inadequate knowledge, lack of adequate cyber norms and infrastructure and need for higher investments are the major challenges. India also understands the benefits of acceptance of I4.0 in the manufacturing and assembly sector such as reduced production cost, faster speed, higher production and safe production environment which is important for competitive position in the global world. The government is trying hard to adopt Industry 4.0 and has launched few programs and policies such as ‘Make in India’ and ‘National Policy for Advancement in Manufacturing’. Industry 4.0 can accelerate the growth of the manufacturing sector of India and can increase its GDP share from 17% in 2018 to 25% by 2022 (KPMG Industry 4.0 report 2018). By 2023, the experts projected that the market of Industry 4.0 can reach $2.214 billion at global level. Germany is way too ahead and advanced in terms of adoption of Industry 4.0. It adopted the automation of manufacturing process in 2010 and established itself as the leader in providing advanced manufacturing solutions. Many more countries such as the USA, UK, Japan, China and many other European Union countries follow Germany in its footsteps and adopted Industry 4.0. Although at the global level India lay behind in the adoption and implementation of Industry 4.0 in comparison with its peer countries, however, it also offers attractive opportunities to Indian manufacturing sectors. Given its strong focus on the ‘Make in India’ program and is the sixth-largest manufacturing country, India has started giving a strong focus on the adoption of Industry 4.0 technologies. It has launched many policy reforms such as liberalized FDI policies in many sectors and implementation of GST for smooth operational flow. There are more than 50 million manufacturing companies in MSME sector. To unlock the true potential of I4.0, it is important that the new technology is accessible to the small companies and transcends the large manufacturing companies. The transformation of MSMEs in India can increase the visibility and acceptability of their products whether finished or semi-finished goods. At the global level right now, 45% of the total manufacturing output is produced by these MSMEs out of which 40% is exported to other countries. Due to the high cost of modern technology, MSMEs have very little access to it (AIMA and KPMG 2018). India is progressing into technologies—first, in IoT and second, Big Data Analytics. India has set its targets high and expected to gain 20% of the US $3 billion global IoT market. 65% of the current IoT market caters to the manufacturing sector

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in India (Government of India 2018). Similarly, the Analytics industry such as Big Data is also expected to grow at a 26% CAGR. By 2025, it is expected to reach about the US $1.6 billion (Nishimura 2018).

1.2 Sector Wise I4.0 Espousal in India I4.0 has revolutionized the world by providing innovative and advanced technologies specifically in the field of manufacturing sector by equipping them with high intensity, advancement, new degrees of capacities and ceaseless improvement in machines. This article talks about the Indian government implications toward infrastructural development for I4.0 to create global markets, featuring Indian manufacturers. The development in the field of automation and mechanization has provided India with a new platform, competitive to other countries and better association with multinational companies around the globe. However, many challenges are associated with adoption and implementation of technologies associated with I4.0; some are more specific and limited to India only. The manufacturers and firms that are ready to take risk and keen to address and find solution of these issues keenly and fortuitously will change themselves in top-notch producers of quality products (Bhat 2020). The adoption of I4.0 is presented in the four growing sectors of India, namely automobile, IT, banking and hospitality.

1.2.1

Automobile Sector

In India, the automotive sector is the fourth-biggest sector in the world and is growing at a pace of 9.5% each year. Government-supported activities like ‘Make in India’ have additionally added new degrees of development, wherein the point is to present India as a worldwide assembling place. Vehicle industry intends to make 44% of its plants technologically smarter in the following five years. Interest in this area is set to be expanded by 60% in the following three years, bringing profitability gains of up to $167 billion. The arrangements, specifically, being made by the auto manufacturers to make their manufacturing plants more intelligent incorporate Distributed Computing, 5G innovations, Progressed Robotization, virtual meeting innovations, self-ruling ground vehicles, driverless cars, metal 3D printing community, shared robots and cobots and so on that are empowering the change of old industrial facilities to the much beneficial more up to date ones. Around 30% of the auto manufacturing plants have received Industry 4.0 arrangements over the most recent two years. For instance, German car parts maker Bosch has put around 31 million Euros in its Indian plant to create Industry 4.0 arrangements. With assistance from innovation departments, the rise of electric vehicles is prevailing upon the world as they are people as well as climate-friendly. Simulated intelligence and ML (Machine Learning) will assume an imperative part in developing the association between the client and the vehicle.

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IT Sector

As indicated in the 2019 Nasscom report, the earnings of Indian IT sector have expanded by 2.3% in comparison with previous year, making it a $194 billion market by end of FY 20–21. The government and private players’ complete focus in 2020 was on profounding new tech companies making it 14%, up from 11% in 2019. Further, 87% of all major tech speculations were in new businesses related to AI/ML in 2020. With addition of more than 1600 new tech businesses and a record number of 12 extra unicorns included 2020—the most elevated at any point included a solitary schedule year, the Indian tech fire up base is seeing a consistent development at a size of 8–10% year-on-year development. Areas like EdTech, BFSI, AgriTech, Gaming and so on are seeing a consistent growth in seed funding and angel investments, up from 29% in 2019 to 42% in 2020, earning a 14% development in the investments. Nasscom gauges that this sector is extending at a 5-Year CAGR of 41%, faster than the growth rate of any other sector. Blockchain, artificial intelligence, Big Data Analytics, AR/VR, IoT, augmented reality and 3D printing are some of the innovations on which the research and development of different companies are focusing upon. Companies like Fintech and Wellbeing, operating in the tech businesses, noticed a rush in the interest for their programs like computerized contactless installments and telemedicine. Trendy computerized abilities are need for ability in enormous IT firms just as developing new businesses, particularly in the territories of blockchain, AR/VR, artificial intelligence, security systems and online competition examination. Nasscom has predicted a multifold demand of computerized machineries and automated facilities by FY24.

1.2.3

Healthcare Sector

Medical service area in India is developing at a quick speed and is additionally going through various technological innovations and progresses. As per IBEF, the emergency clinic industry is relied upon to ascend from Rupees 4 trillion in FY17 to Rupees 8.6 trillion by FY 2022, growing at a compound annual growth rate of 16–17%. As of now, the rising rates of lifestyle infections and developing interest for reasonable medical care are pressurizing the government to innovate in space of the medical field with help of the latest technologies such as artificial intelligence. AI/ML and advanced mechanics are the significant driving forces in the Indian medical care industry. Today, telemedicine, AI, information examination and cloud-based programming, software as a service (SaaS) are being utilized to improve medical care foundation, self-administration and patient experience. Between years 2019– 24, the Indian advanced healthcare market is estimated to grow at a CAGR of 19.7%. It is expected to reach INR 26.01 billion by 2024 in comparison with INR 7.02 billion in 2017. The reception of mechanical technology in careful intercession has given tremendous opportunities to the Indian medical services industry. Medical care offices in Indian urban cities like Pune, Mumbai, Gurugram, Delhi, Bangalore and Hyderabad

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are offering robot-driven health check-ups and administrations. India has encountered an expanded rate of complex routine conditions like muscular diseases, cardiovascular diseases, neurological issues and malignancy that need high expertise and careful medication. The huge development in the Indian hospital tourism industry has motivated investors to bring technological advancements in the sector to provide uncompromised world-class services. The number of medical travelers has developed at a rate of 16% in the year 2018. India has accepted medically advanced technologies at a much more slow speed than other developed nations; the restrictive expense of establishment and slow processing were the main hindrances of the market infiltration. The significant expenses of procurement, expendable stock and yearly upkeep of careful robots take about as huge cost input for the appropriation. Besides, the robot-helped medical procedures are not covered by the Indian medical insurance companies, which increase the burden on patients’ pockets. Notwithstanding, positive clinical results and the headway of innovations like 3D representation, single-port frameworks, completely wristed instruments, haptic criticism and computerized reasoning are projected to set out worthwhile market open doors (Laura Wood 2020).

1.2.4

Banking Sector

The Indian financial industry is going through a huge change, technological advancements versus changing clients’ needs. The new companies such as FinTech have reformed this change with imaginative items and administrations to suit the different client base. In turn, it has attracted huge investments from banking and non-banking financial institutions for bringing the latest technological arrangements to modify the loan and repayment processes. The big private banks in India have just adopted Robotic Process Automation (RPA) to improve their effectiveness and efficiency. ICICI Bank, one of India’s driving private area banks, is among the first in the nation to adopt RPA for an enormous scope. It has incorporated advanced mechanics to mechanize manual and dull tasks, such as IT uphold, client email revert and compactness of records. They have planted 750 robots to encourage the handling of more than 20 lakh exchanges each day. In addition to it, redressal of ATM money disbursal complaints has come down to 4 h as against 12 h, with 100% accuracy. Many banks like HDFC Bank and Axis Bank are in the league of adopting automation. Machine Learning (ML) and computer-based intelligence have allowed banks to computerize their central financial administrations facilitating better output and the improved client relationship. Banks are currently bringing incredible innovation, for example, blockchain to build up effective and accurate record maintenance and adequate record exchange management systems as per monetary policies. The FinTech advancements, for example, e-wallets, installment passages, UPI, shared loaning and so forth have extended financial administrations to a more extensive client base and empowered a consistent financial experience. The idea of anywhere work culture has been presented in the financial business as of late; however, it will

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continue even in the post-covid world also. Banks are attempting to embrace better and updated business progression models to plan for unforeseen circumstances like the current emergency. This incorporates a blend of computerized workspaces, cloud adaptability, inborn security and upgraded network capacities.

2 Indian Government Implications of Infrastructural Development for Industry 4.0 Many of the small and medium enterprises in India are working in I3.0 or I2.0 environment. The reason behind this slow adoption of technology is restricted IT frameworks which are able to perform just a few routine activities, and it is not possible to bring creativity and innovation in every work. Moreover, India still is lagging behind in adoption of I4.0 and the shift of industries toward I4.0 has just started and it will take time to bring the momentum. In the course of the last 15– 20 years, the country’s impressive development is coming to an end. 2019, Q3 GDP eased back to a six-year low of 4.5%. India’s GDP in 2020 was 4.2% which was the least in the previous 11 years. Development in India is dragging despite worldwide disputes and the big Indian conglomerates and MNCs are worried about looking at the development facilities and the after-effects of the 2020 slowdown (ET Bureau 2020). The firms that are engaged in continuous improvement of technologies and processes are not going to slow down; however, their advancement decisions depend upon the governmental policies and legal system of the country which largely influence their advancement prospects. The GDP of India is not growing which is not a good indicator for investors and growth bearers in the adoption of I4.0. Even due to the pandemic, it is expected that the automation plans that were supposed to take three-to-five years will now take a slow gear and might change to five- to sevenyear approach. The expansion of IT-OT centers, modernization and mechanization of plants and automation of processes is going to be more nomadic. Considering the dropping economic growth and slower progress, Indian CEOs are worried about the speed of bringing innovative changes. Even at present, advanced frameworks and supportive environments are deficient. Manufacturing plants of spare parts, automobiles, advanced machinery for different sectors, and their associated firms will require a widespread, empowered and creative environment. The insufficient availability of techniques and average organizational production are due to imperfect advanced frameworks and communication systems (PwC 2020). The Indian government has announced many policies and projects for the improvement in the field of advanced technologies of I4.0. The public authorities have announced projects and strategies such as an Internet of Things Policy in year 2015, and in 2018, a critical Cyber-Physical System for advancement in computerization, mechanical technology and AI applications in assembling. Yet, it will take a long time, all things considered, to develop a structure for producers to flourish and upgrade world-level

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quality, in addition to the burden of lower ROI and risks associated with failure of new advancements and innovations (Ahaskar 2019). Until infrastructural and ecological systems’ availability is improved, India’s producers have to compromise, stay off guard to their worldwide rivals and require more monetary support to purchase and implement the I4.0 capacities. It is more important to focus upon the expectations of Asian firms for designing and implementation of I4.0, profiting by pacesetter countries such as European, Middle East and Africa (EMEA) or US learning, synchronous with relatively latest neighborhood options in territories like automation and information technology-operational technology integration (Mearley 2018). India is growing at a fast pace, and it is becoming one of the fastest growing economies in the world. It is about to cross the economy of UK and is ready to take the world’s fifth-biggest economy. However, India still lags far behind than China where the yearly profitability per worker is $63,400 in comparison with $6000 in India. The adoption of I4.0 can address this challenge and might limit the growth and profit difference. The advancement in technologies presents a guaranteed growth in coming 15 years. It is expected to reach $957 billion where 33% of GDP contribution will be made only by AI applications alone in India (India Skill Report, GOI 2019). India should be ready to face huge challenges to assure businesses who want to increase their manufacturing and assembly capacities. The adoption of I4.0 can provide due assurance, drive the strength to bring globally accepted quality standards and improve the overall trading conditions. The unexpected changes and growth in technological advancements have created a distress among Indian manufacturers where government initiatives might reenergize their initiatives and commitments and can drive technological advancement.

2.1 SAMARTH Udyog Bharat 4.0 SAMARTH Udyog Bharat is an initiative of DHI under the guidance of Ministry of Heavy Industries and Public Enterprises, Government of India. It is an initiative to promote I4.0 which stands for Smart Advanced Manufacturing and Rapid Transformation Hub. The objective of DHI is to bring I4.0 revolution in India manufacturing and assembly industry with the assistance to focus on revolution to make 25% growth in GDP by 2025. The main features of SAMARTH Udyog Bharat 4.0 are creating awareness through campaigns, training of master/expert trainers, incubators facilities for the start-ups, guidance and supporting small and medium size enterprises to execute the adopt and execute the I4.0 processes. However, this is possible with the help of expert consultants. It further focuses on collaborating with neighborhood institutes and universities to provide internships and training programs to students. The project features involve the adoption of SPV model for sustainability and regular participation in government provided platforms for I4.0 on common agenda. The further motive of this project is

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to involve as many clusters of capital gods as possible and make adequate provisions for e-waste management (Javaid 2021). The five facility centers are identified and developed to focus on I4.0. These centers are well-known names in the field of technology and are sanctioned for spreading awareness and creating a brand for SAMARTH Udyog. The main focus of SAMARTH Udyog is to target manufacturers, assemblers, vendors and clients as the major stakeholders. These five centers are highly experienced and technology hubs, elected to spread awareness among Indian manufacturing sector for the acceptance and growth of I4.0. The centers are focused to achieve targets by experiential learning and demonstrating the benefits of updated technologies of I4.0. The Government of India has emphasized that the utilization of the available resources should be maximized by providing common platforms to these five centers so that they are better able to network with each other and share the available resources with each other (SAMARTH Udyog Bharat 4.0 2019–20). The five common engineering facility center projects are as follows: . . . . .

C4i4 Lab Pune (Center for I4.0) IITD-AIA Foundation for Smart Manufacturing IISc Factory for I4.0 SMDDC (Smart Manufacturing Demo and Development Cell) at CMTI I4.0 projects at DHI CoE in AMT (Advanced Manufacturing Technology), IIT Kharagpur.

2.1.1

C4i4 Lab Pune

Digital actual frameworks are driving the assembling business into the fourth modern revolution famously known as Industry 4.0. It can address numerous difficulties looked by the Indian business that block its worldwide intensity like the impression of bad quality, hardened rivalry on expense from different countries, low degrees of advancement and restricted spryness to meet quickly changing client needs. Center Lab for I4.0 is a very special lab setup to bring technological advancement in Indian manufacturing and assembly industry. C4i4 Lab has put India on the rundown of nations that have taken up devoted activities for the advancement and selection of I4.0. The projects of C4i4 Lab will help firms in fabricating as well as help to build up a supportable ecological system that sustains and drives advancement and development. C4i4 Lab is planning to change the layout and setup of small manufacturing units to present the benefits of I4.0 to the industries. It gives admittance to innovation and resources to help Industry 4.0 pilot projects in organizations. C4i4 Lab partners with driving organizations to use their resources, machines and capacities to show innovations in the experienced environment. The Vision of C4i4 Lab Pune is to be considered and admired as a center of innovation promotion and technological adoption at world level to enhance the competitive advantage of Indian manufacturing industries. The aspirations of C4i4 Lab Pune are associated with improving the experience of companies with the immersion of I4.0, to provide experts and trainers to train

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the executives to bring desirable growth in I4.0, motivating companies to implement pilot projects, providing fixed hours of lab demonstration to practically convince manufacturers to adopt I4.0 and providing incubation support to start-ups. Solutions and Services offered by C4i4 Lab Pune: This center has been established to experiment and conduct various activities centering toward exclusive designs for the industries to achieve India’s vision of being globally competitive in manufacturing. (a) I4.0 Enablement Learning C4i4 Lab Pune focuses on two major events to enable learning environment and help organizations to adopt initiatives of Industry 4.0, i.e., ‘Are you Ready’ Workshops and ‘Digital Champions Program’. C4i4 Lab-created Industry 4.0 mindfulness workshops under the arrangement ‘Are You Ready’ for digital transformation. These workshops are led for senior/mid-level chiefs of SME/MSME/Large organizations. The workshop covers various advances and needs of the usage completely created while considering Indian shop floor. This workshop is joined by contextual analysis conversations and exhibits. These workshops and projects are so designed to suit the need of the members—for instance for foundry proprietors, the program examines open doors in the foundry. It helps in demystifying Industry 4.0. More than 1000 companies have partaken in this program since its inception in 2018. Intending to create inner experts inside an association who can successfully characterize, focus on and actualize the association’s advanced vision, C4i4 built up a 16-week hands-on program for mid- and senior-level supervisors. This program begins with fundamental Industry 4.0 advertence and closures with effective execution of pilot projects by the members. This program covers subjects, for example, Industry 4.0 fundamentals; defining computerized vision; Industry 4.0 Maturity appraisal; Technology Immersion; identification and prioritization of pilot projects; and defining extension for advanced tasks lastly usage of pilot projects. One of the significant highlights of C4i4 Lab is live show for different advancements. It helps in understanding the benefits of different technological advancements. These shows are created with select accomplices, and a portion of the units incorporate Energy Monitoring and Management, productivity per man and move, Quality 4.0 and a portion of the high-level applications like augmented reality. To assist associations with understanding their development and preparation regarding the digitalization of their current plants, C4i4 Lab built up an Industry 4.0 Maturity and Readiness evaluation instrument explicit for Indian assembling organizations. The essential goal of this device is to help organizations to: . Understand where organizations are standing in terms of digitalization. . Identify the gaps which need to be plugged in for creating a successful digital transformation roadmap. . Understand organizational readiness and maturity across all three elements— people, process and technology. (b) I4.0 Implementation Advisory

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C4i4 Lab believes that the implementation of pilot projects will build confidence among the organizations and inspire others to invest their resources in taking the first step. C4i4 Lab Pune Industry 4.0 Implementation advisory services help organizations to prepare an actionable and measurable strategic plan to implement Industry 4.0 solutions and develop simple solution architectures which can be horizontally and vertically deployed inside and across the organization. I4.0 motive is to bring upgraded technological and functional automation and linkage between the manufacturing processes. However, the technology is changing so fast that the market is unable to fulfill the skill demand gap with appropriate workforce. To develop a favorable ecosystem for this demand, C4i4 Lab has initiated the ‘Academia Facilitation Programme’ to develop a system where the technical graduates can acquire the knowledge and skills expected for the adoption and implementation of I4.0 initiatives with the industry-academia collaboration. The motive of this program is to update the curriculum in universities as per the requirement of upcoming technologies and focusing on advanced manufacturing.

2.1.2

IITD-AIA Foundation for Smart Manufacturing

IIT Delhi being a pioneer institute of innovation has a dream to add to India and the world through greatness in logical and specialized instruction and examination; to fill in as an important asset for industry and society; and stay a wellspring of pride for all Indians. AIA is resolved to be a dynamic discussion for all robotization organizations in India spreading information and developing consciousness levels that have an essential effect on the worldwide acceptance of the Indian industry. IITD and AIA propose to set up a completely incorporated Smart Manufacturing and Learning Facility for discrete and half processed manufacturing sections like automotive, consumer durables, processed foods and so on. These sections are quickly developing and rival worldwide brands on innovation, quality and customer delivery. A demo cum experience office in North India, upheld by broad ability building, creative infrastructure, MSME consultancy, multi-scholarly social development organizations and exploration, will give a tremendous impetus to the seriousness of Indian manufacturing. The undertaking will infuse innovations from Europe, Japan, the USA and India. For smart manufacturing research, the Government of India affirmed CEFC to be set up mutually by IIT Delhi and AIA to set up a Cyber-Physical Lab at IIT Delhi, Hauz Khas, and an undeniable Cyber-Physical Facility at IITD Sonepat Campus. The objective of the initiative is to educate manufacturers by providing demonstration facilities, training and up-skilling of workforce, copyrights and integrated facilitation center for promoting smart technology enabled manufacturing. A brief layout of the facility is available at https://www.samarthudyog-i40.in/project. The proposed floor zone for setting up the smart manufacturing research and Cyber-Physical Lab at IIT Delhi, Hauz Khas, is 1200 ft2 , whereas the proposed floor size is 30,000 ft2 for smart and advanced Cyber-Physical Facility at IITD Sonepat.

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The selected areas of advancements by these facilities are related to cobots (collaborative robots), I4.0 compliance sensors, augmented reality, fast and unhampered telecommunication facilities, advanced cyber systems, simulations and digital growth, remote manufacturing, cyber security, etc. Many AIA experts have collaborated to contribute in upcoming technological innovation and their implementation. CEFC will stretch out after administrations to advance development and selection of Industry 4.0 arrangements to make Indian businesses internationally acceptable specifically in the field of capital goods sector. The focus of this foundation is to create awareness among MSMEs, along with specialized paid consulting facilities and site integration facilities. The CEFC focuses on providing training and education facilities by collaborating with more institutes and universities to create an environment of advanced learning, providing skill certification to improve employability and job work skills. The body has setup research centers for continuous improvements and innovations in the field of manufacturing technologies.

2.1.3

IISc Factory for I4.0

Industry 4.0 has been a significant activity worldwide by every significant economy. Industry 4.0 activities right now center on process computerization and also centered around incorporation and strengthening of human skill and efficiency. This might help organization in two ways: reducing insignificant human work and producing zero defect products with undeniable degrees of technical innovation and robotization and the other on making customized and heavy machineries for industries through brilliant innovations and instruments. Industrialization in India is at a very different stage, and IISc is trying to provide R&D platforms to companies who can come up with technological innovations which are easy to accommodate and execute and low in implementation cost. Indian MSMEs are the spine for work creation in assembling industry. Their quality shifts from world norm to Industry 1.0. They are the most noteworthy occupation makers, yet have a low portion of economy (in contrast to those in cutting edge economies). The innovation and reception of ‘keen’ are moderately less and, however, are basic for the MSMEs to climb the value chain. In general, these industries, especially MSMEs, are having many drawbacks such as: Indigenous R&D capability for adoption of I4.0 is very little, smart factory setups are not present in general for research, development and innovation, unawareness and lack of hands-on experience to develop understanding of such facilities, limited training programs to generate awareness, tradition education system, limited industry-academia liasoning, lack of applicable protocols, standards for integrating innovative devices of I4.0, government focus on automation instead of labor empowerment and very limited support for entrepreneurship opportunities supporting I4.0. The CEFC at IISc, called the I4.0 for India@IISc, is to help reduce these gaps. CEFC provides many facilities such as two contrasting platforms for supporting demonstration, exploration and experience of Industry 4.0 technologies and capabilities, i.e., what networked automation can offer and the other centered on smart

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solutions to empower labor. It provides smart tools for legacy integrated into the platforms; provides smart, affordable point solutions for MSMEs; gives demo of trade-offs and benchmarking of these platforms on selected KPIs; provides training to industry leaders, R&D personnel and advanced students; gives indigenous research base to support industry in Industry 4.0; supports development of indigenous Industry 4.0 Standards, Protocols and Middleware; organizes international I4.0 conferences and awareness workshops; provides incubator’s facilities to support for Industry 4.0 start-ups; and acts as policy advisor for industry and government.

2.1.4

SMDDC (Smart Manufacturing Demo and Development Cell) at CMTI

The Demo and Development Cell for Smart Manufacturing Demo at CMTI is conceptualized in the plan proposed underneath. The total framework is conceived to work with least human obstruction, receiving most recent sensors, actuators innovation in different types of products and equipments. The mind of the framework is correspondence and movement of data between components of the framework with the expert regulator having more significant level of PCs and oversaw by extremely versatile PLC and related programming. Make a stage at CMTI for Indian assembling enterprises incorporating machinery OEMs, sub-system designers, users, component producers, solution engineers, new companies, etc., to investigate, insight, test, assess and embrace Smart Manufacturing/I4.0 advancements with master help from CMTI. Mini, Small and Medium Enterprises (MSMEs), specifically, will be profited by the CEFC administrations to prepare for full scale I4.0-based creation and improve their worldwide acceptance. There are many initiatives taken by CMTI such as Development of Advanced Technologies for Hi-Tech Shuttleless Looms. The cost of the project is Rs. 20 Cr, and consortium of 5 SME units is the industry partners in this project. The second project is ‘Modernization of Precision Metrology Laboratory of CMTI (MOPML)’. CMTI Bangalore is the implementing unit of the project. The third project under CMTI is ‘Nano Manufacturing Technology Centre—Continuation of Building Infrastructure works’. The estimated cost of the project is Rs. 25.06 Cr. The fourth project is development of ‘Sensor Technology Development Facility at CMTI’, and the overall project cost is Rs. 52.60 Cr. The major objectives of setting up of developmental cell at CMTI are to establish a Smart Manufacturing Demo cum Development Centre as a pilot implementation of Smart Manufacturing at cell level in INDIA. Its motive is to showcase the tools and techniques, related capabilities and advantages and limitations for Industry 4.0, explore limits of automated smart production systems, benchmark I4.0 elements and evaluate system security aspects. Its other objective is to enable localization and customization of tryout and evaluation facility for solution developers and developing expertise on smart implementations. The goal of the body is to support industry for rolling out smart production systems in form of consultation for providing customized solutions related to technology transfer and handholding.

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I4.0 Projects at DHI CoE in AMT, IIT Kharagpur

IIT Kharagpur has become the hub for experiments in areas of new technological advancements after the setup of Center of Excellence in Advanced Manufacturing Technology. The center has been set up by the DHI, Ministry of Heavy Industries and Public Enterprises, GOI. The consortium of six manufacturing and technologically advanced conglomerates has joined hands with DHI to bring worldclass R&D facilities. These six industries include BHEL (Bharat Heavy Electricals Limited), Tata Motor, Tata Steels, HEC (Heavy Engineering Corporation Limited), Tata Consultancy Services and Tata Sons. The facility means to invigorate the advancement to make brilliant machines in the product manufacturing area. This facility offers a special stage for community, consortium driven imbuement of cutting edge innovations in the assembling sector, which is aligned with the Government of India’s initiative named as ‘Make in India’. The facility will start creative and top-quality exploration adjusted to the enterprises on specialty materials, design and robotization, additive assembling and digital assembling and Industrial Internet of Things (IoT). The facility will help invent high-level assembling area by empowering an environment among institutes of higher caliber, hefty ventures and furthermore the MSMEs and new businesses. The facility searches for dynamic interest in this ecological system for a collective examination in the proposed areas. The facility likewise provides an Innovation Lab to encourage the way of life of advancement and open designing. The Innovation Lab welcomes MSMEs and the start-ups to get chances of getting a start to finish uphold from the specialists including assistance from starting the project to its copyright. The facility likewise invites brilliant and skilled researchers with high worth doctoral partnership to help its exercises. In a mechanical joint effort with Tata Consultancy Services, IIT Kharagpur has created novel Industry 4.0 innovation for distantly controlled manufacturing plant activities and continuous quality rectification during modern creation. The advantages of controlled activities have a greater effect particularly with regard to Atma Nirbhar Bharat in conveying quality yield at low expenses. The current advancement redesigned the mechanical cycle of contact mix welding to a multi-tangible arrangement of Industry 4.0. It has not just set the course for distantly controlled tasks in the Indian mechanical area; however, it has empowered ongoing quality check and solution during the production outbreaks. This will make it workable for modern houses to accomplish targeted quality objectives all through the manufacturing cycle and lessen wastage subsequently bringing down the expense of production. In an activity attempted by the Center of Excellence in Advanced Manufacturing Technology at IIT Kharagpur, scientists are set for making AI and ML applications reasonable for India’s modern fields including MSMEs. They have built up an imaginative and innovative framework comprising of a virtual imaging gadget and an AI-empowered programming for ongoing metrological investigation. The created framework can be used in the production line to check the production changes much in advance. The precision check and practicality of the arrangement have been

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ensured by testing it on various sorts of occupations. Specialists are working further to decrease the time.

3 ‘Make in India’ Initiative To cultivate advancement, encourage innovation, upgrade the skill of workforce and manufacture world-class frameworks within the country, Government of India launched an important program for public and that is ‘Make in India’. The motive of this initiative is to bring in the latest knowledge and innovation across the countries and improve the manufacturing and assembly industry of India at the extent of global acceptance. Under the flagship of Government of India, the initiative was driven by DPIIT headed by Ministry of Commerce and Industry. ‘Make in India’ is very important program for the economic development of country as well as creating more employment opportunities by up-skilling the available workforce ready to change the face of manufacturing by engaging them into different vocational programs and associated areas. The second objective of this initiative is to provide an environment to small, medium and large enterprises to do business with ease by removing duplicity of formalities, complicated legal compliances, simpler administrative procedures and making the processes more transparent, straightforward and up to the point (KPMG and FICCI 2018). There are many areas where the major focus of ‘Make in India’ initiative is, and these sectors include: 1. Automobiles and components

2. Aviation

3. Biotechnology

4. Chemicals

5. Construction

6. Leather

7. Defense manufacturing machinery

8. Electronic systems

9. Food processing

10. IT & Bpm

11. Mining

12. Oil and gas

13. Pharmaceuticals

14. Ports and shipping

15. Roads and highways

16. Railways

17. Renewable energy

18. Space

19. Thermal power

20. Textile and garments

21. Tourism and

22. Hospitality and wellness

23. Media and entertainment

24. Biotechnology

India is the biggest maker of automobile sector in all sections—two-wheelers, three-wheelers and transportation vehicles at global level. Due to high manpower supply at low price, India has a cost advantage over its competitor countries. India has announced numerous activities to foster this area like FAME and NEMMP 2020 which has been introduced to bring advancement in the segment of electric vehicles. The 100% FDI (Foreign Direct Investment) and NATRIP are focused to bring technological innovations in this sector.

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The aeronautics area is relied upon to take a leap and is before long expected to arrive at the skies, and India as of now possesses 9th position worldwide in this field. The major activity focus in this area was UDAN to make air travel possible for every common man by providing required infrastructure and more local airports. To make the airline industry more competitive, helping private airlines with augmented navigation systems, to improve safety and security and to reduce the fuel consumption, the program called GAGAN was launched. The biotechnology industry in India has flourished a lot and created a gap with other countries with a wide margin. The improved research and development facilities and continuous support of governmentaided programs have blessed the businesses dealing in the areas of biotechnology. To promote the growth in this sector, the Government of India changed the trade policy and opened 100% FDI investment. BIRAC, a biotechnology assistance council, was set up to help the entrepreneurs and established businesses by financing their initiatives, skill training and coaching, consultancy and framework support (NITI Ayog 2018). In the electrical manufacturing sector and electronics sector, the Indian producers are at their pinnacle of seriousness in the areas of item configuration, producing and testing centers. Alongside 100% FDI in this area, a major piece of speculations is made in innovative work which will assist India with quickening its assembling. Around 38 portable assembling units have been set up which have provided to skill to many talented people, and under the Government Initiative DISHA, digital education initiative has been taken to prepare and develop approximately 10 million applicants with necessary skills and employment opportunities. Clinical Tourism is moving at a fast pace as India has become a hub and an attractive option for foreigners. The medical expenses are very less in India, almost half of the expenses of USA and other European countries. After the announcement of new policy, the drug business has seen an upswing from $ 21.44 billion in 2013– 14 to $24.02 billion in 2014–15 to $27.65 in 2015–16. The Pharmaceutical and Drug Industry in India has brought the mass manufacturing of innovative medical equipments and medicines in the field of medicines and medical equipments in the field of cardiology, oncology and neurological diseases (Laura Wood 2020). India has also strengthened its position in the field of railways, metro and longest railway and metro tracks. India has a rail network of 66.30 km, and the option of 100% FDI has opened new horizons for bringing revolution and building high speed metro and bullet trains. Programmed Ticket Vending Machines and electronic traveler reservation frameworks focus on traveler comfort. The Government of India has collaborated with GE Global Sourcing India Pvt. Ltd to set up an electric train manufacturing plant at Madhepura, India. The government has also given contract to M/s Alstom Manufacturing India to produce high speed diesel trains with a composite budget of $5.43 billion. A lot more initiatives have been taken, and countless opportunities have been announced by the Government of India in fields of oil and gas, energy and solar power, manufacturing, the travel industry, hospitalization and wellbeing.

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4 Corporate Social Responsibility Initiatives India has renovated itself and now presenting itself as a hotbed for businesses with liberal and firm friendly policies and many initiatives to promote entrepreneurship in different sectors and spaces (Tracxn 2019). In 2018 alone, India has put its resources—financial, physical and expertise in 1800 new companies (Tracxn 2019). This number might seem very small; however, this presents a pace of development in the Indian ecological and industrial system which is moving at a sustainable pace. Florida and Hathaway conducted a survey in 2018 and found that the businesses from Delhi and Bangaluru attracted and pulled most of the funding between year 2015 and 2017 in comparison with other 20 metro cities of India. A big leap has been noticed in the economic environment in the previous thirty years which motivated the start-ups to develop their businesses. The GOI has initiated many policies to create an ecosystem that can give a significant push to the start-ups and bring a significant change into the ecological system (Niti Ayog 2018). India has gained the third position worldwide on providing number of incubation centers to the new venture capitalists after USA and China (Sharma 2017). More than 60% of the incubators are situated in the academic institutes and universities to motivate youngsters to start their own small business, and approximately 40% of them are used for established business purpose on chargeable basis. Some examples are ICICI and Coir Board who has tied-up with quality education providers, and others such as FICCI, Wadhwani Foundation and Deshpande Foundation are the centers set up for industrial establishments. Some business parks have also been developed by government initiatives for different services such as IT parks, Trade Centers and BioTech Business parks. The South Indian regions have allured most of the incubators by being the most energetic and promising region of the decade. As per the report of Department of Higher Education 2017–18, Tamil Nadu and Karnataka alone have 75 incubators out of 130 total incubators in the region with the introduction of advancement in quality education sector. Thirty percent of the incubators (approximately 85) are established in the regions with high potential and growth prospects. For telecommunication and data analytics—38% and for agribusiness—19% incubators have been established (Sharma and Vohra 2020). Practically, all incubators notice their actual foundation as one of the basic contributions for the new businesses. Numerous incubators feature the accessibility of specific labs, hardware and framework. Most incubators additionally notice offering some benefit added administrations like tutoring, help with different IPR measures, legitimate, bookkeeping and other business administrations. About 60% incubators likewise make a particular notice of giving admittance to capital. Given that more than 90% of incubators are upheld under an administration scheme, the best four government bodies supporting incubators are DST under the guidance of Ministry of Science and Technology, AIM under the flagship of NITI Aayog, MEITY and MSME, all operating broadly under the guidance of Government of India (Sharma and Vohra 2020).

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There are some common linkages between DST’s and MSME’s plan, i.e., NIDHITBI and ASPIRE, both target commercialization of business and provide added administration facilities. The targets of NIDHI TBIs additionally stretch out to advancement of ‘innovation and information’ in new companies. DST upheld new companies to work in niche areas so that acceptability is high and risk is low, whereas MSME’s emphasis is on agribusiness. Point’s arrangement exhibits affectability to the subtleties of the brooding cycles. This approach makes reference to how incubators could create environments by directing projects, organizations and occasions. Point additionally accentuates on the production of significant worth added administrations by incubators, especially around the destinations and objectives of tutoring and making organizations (Narayanan and Shin 2019). There are many CSR projects launched by private players in tandem with Central Government of India in 2019–20. Few of them are presented below: a. Bajaj Finance Limited: The company is installing technology incubators and developed Rahul Bajaj Technology Innovation Centre (RBTIC) with an investment of INR 12.5 Cr in 2019–20. The project sector is technology incubation aligned with the initiatives of Central Government of India, and the implementing partner of the project is IIT Mumbai. The location of the project is Mumbai, Maharashtra, and the motive is to contribute toward installing technology incubators. b. Vodafone Idea Limited: The objective of the project is to establish technology incubators along with central government initiatives, and the name of the project is ‘Connecting for Good’. The project was launched in 2019–20, and the implementing partner is Vodafone India Foundation. The allocated budget of the project is INR 2.00 Cr, and the location is PAN India. The main objective of the project is to promote an ecosystem to empower NGOs in terms of using technology for addressing various social and political challenges, bringing product innovation, improving interventions and disseminating the procured knowledge with needy groups. The project wants to create greater impact with two major applications, i.e., solutions for good and social app hub. The ‘social application hub’ has more than 800 apps to disseminate knowledge and create social awareness. Similarly, ‘solution for good’ motivates designing of new technological innovations which can provide solution to social issues and can be replicated easily at large scale. c. Info Edge (India) Limited: The project has been launched in the sector of technology incubation with Central Government of India. The implementing partner in this project is Reimagining Higher Education Foundation. The budget of the project is INR 2.00 Cr, and the project location is Mohali-Punjab. The motive of this project is to support Plaksha University, Mohali, in achievement of its dream of imparting technological education to students to meet the changing demands of twenty-first century. This CSR initiative is to support and establish research labs and centers in the university.

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5 The Salient Role of the Government The public authorities and the top-notch academic institutions have been among the main supporter of development of start-up incubators in India. The information validates that the public authority’s incubating exercises have been completed predominantly in organization with advanced education foundations. Some of the well-known organizations such as IIT Delhi, IIM Ahmedabad and IISc are to name a few who have started working in area of technological and workforce advancement, established innovation centers, opened up R&D labs and supported newly setup ventures by providing them required facilities, support and consultation (Narayanan and Shin 2019). At the point when the strategies of the public authority were friendly, similar organizations turned into the first recipients of the monetary help for incubation. These organizations accepted that the government-academia collaboration is going to be a win–win with two profitable perspectives—the places for business ventures and advancements, and got monetary help and acquired permission for their businesses, while the government authorities discovered places to conduct their experiments. The examination likewise shows that best, notable and exceptionally respected incubators, housed inside instructive foundations in India, created their system in accordance with the nearby environment and qualities of the incubator (Sharma and Vohra 2020). Banding together with the scholarly community as opposed to making its own incubating framework likewise shows up more productive in light of the fact that it would encourage a better utilization of available facilities to help new businesses instead of spending unnecessary on making their own incubation facilities. Adding to innovation incubators situated inside selected premises limited stretching out any guide to different incubators. Government has also made CSR investment mandatory for organizations where 2% of the annual profit should be spent on listed CSR activities. The organizations are engaged with various ministries and departments (such as various IITs, ICAR, national laboratories and public funded universities, DRDO, Ministry of Electronics and Information Technology, etc.) to make best use of their CSR investments, for bringing innovations in areas like technology, communication, medicine and agriculture (Narayanan and Shin 2019; Kalra 2019).

6 Conclusion The Government of India has launched multiple initiatives to promote adoption of I4.0 in all kind of industries. Indian companies are progressing with innovation in ADP technologies and providing support to many developed countries such as USA, European Union, Japan and many more leading markets. Indian developers are embedding these technologies in smart machines and new capital goods to increase the export. The Indian government has announced many policies and projects for the improvement in the field of advanced technologies of I4.0. The public authorities

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have announced projects and strategies such as an Internet of Things Policy in year 2015, and in 2018, a critical Cyber-Physical System for advancement in computerization, mechanical technology and AI applications in assembling. SAMARTH Udyog Bharat is an initiative of DHI with an objective to bring I4.0 revolution in Indian manufacturing and assembly industry with the assistance to focus on revolution. The five innovative facility center projects were launched under these initiatives which are C4i4 Lab Pune, IITD-AIA Foundation, IISc Factory for I4.0, SMDDC at CMTI and DHI CoE in AMT at IIT Kharagpur. To cultivate advancement, encourage innovation, upgrade the skill of workforce and manufacture world-class frameworks within the country, Government of India launched an important program for public and that is ‘Make in India’. It is very important program for the economic development of country as well as for creating more employment opportunities by up-skilling the available workforce and to provide an environment to small, medium and large enterprises to do business with ease. Government has also made CSR investment mandatory for organizations who are actively engaged with various ministries and departments to make best use of their CSR investments. Many more initiatives have been launched by the Government of India to make I4.0 adoption in all sectors a reality.

References Ahaskar A (2019) Robots are gaining ground in India stead ily. Retrieved on March 15, 2021 from https://www.live-int.com/technology/tech-news/robots-are-gaining-ground-in-indiasteadily-1552837348297.html AIMA and KPMG (2018) Industry 4.0: Indian INC. Gearing up for Change, All India Manufacturing Association (AIMA), March, New Delhi. Retrieved on March 14, 2021 from http://re-sources. aima.in/presentations/AIMA-KPMG-industry-0-report.pdf Bhat TP (2020) India and Industry 4.0. A paper prepared as part of the research programme industrial, trade and investment policies: pathways to industrialization theme: I structure and growth performance sub-theme: large Indian corporate sector and market competition. http://isid.org.in/ wp-content/uploads/2020/07/WP218.pdf ET Bureau (2020) MF cuts India’s FY20 growth forecast to 4.8%. Retrieved on March 15, 2021 from https://economictimes.indiatimes.com/news/economy/indicators/imf-cuts-indiasfy20-gdp-growth-forecast-to-4-8/articleshow/73435183.cms GOI (2018a) Report of the artificial intelligence task force, Ministry of Commerce and Industry, Government of India, New Delhi. Available at https://dipp.gov.in/sites/default/files/Report_of_ Task_Force_on_ArtificialIntelligence_20March2018_2.pdf GOI (2018b) Internet of Things (IoT), IoT India Magazine, Delhi India skills report (2019) All India Council for Technical Education, Government of India, 2019. Retrieved on March 15, 2021 from https://www.aicte-india.org/content/india-skill-report-2019 Javaid A (2021) Industry 4.0: all you need to know about SAMARTH Udyog Bharat 4.0 Kalra A (2019) Corporate social responsibility: funding incubators. Startup India, Government of India. https://www.startupindia.gov.in/content/sih/en/reources/startup_india_notes/regulations_ and_policies/corporate_social_responsibil-ity_funding_incubators.html KPMG (2018) Industry 4.0 report. Retrieved on March 14, 2021 from https://home.kpmg/xx/en/ home/campaigns/2018/11/industry-4-0.html KPMG and FICCI (2018) Skilling India: a look back at the progress, challenges and the way forward

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Laura Wood (2020) Surgical robotics in India 2019: comprehensive market insights and projections to 2024. Retrieved on March 16, 2021 from https://www.globenewswire.com/fr/news-re-lease/ 2020/02/19/1987189/0/en/Surgical-Robotics-in-India-2019-Comprehensive-Market-Insightsand-Projections-to-2024.html Mearley R (2018) Asia Pacific manufacturing companies champion digital transformation; gaps with America and EMEA set to widen. Retrieved on March 15, 2021 from https://www.strategyand.pwc.com/gx/en/about/media/press-releases/champion-digital-transformation.html Narayanan VK, Shin JN (2019) The institutional context of incubation: the case of academic incubators in India. Manag Organ Rev 15(3):563–593 Nishimura T (2018) Big data analytics market—future scope in India. Silicon India, September, 12. Retrieved on March 14, 2021 from http://isid.org.in/wp-content/uploads/2020/07/WP218.pdf NITI Ayog (2018) National strategy for artificial intelligence. Government of India, Discussion Paper PwC 23rd Annual CEO Survey 2020: 51% of Indian CEOs believe ‘uncertain economic growth’ is a threat. Retrieved on March 15, 2021 from https://www.pwc.com/gx/en/ceo-agenda/ceosurvey/2021.html#cs23DataExplorer SAMARTH Udyog Bharat 4.0 (2019–20) A Industry 4.0 initiative of DHI, Ministry of HI & PE, Government of India. Retrieved from https://www.samarthudyog-i40.in/ Sharma S, Vohra N (2020) Incubation in India—a multilevel analysis. W. P. No. 2020–03–01, Research and Publication, IIMA (Indian Institute of Management Ahmedabad) Sharma D (2017) India Now Ranks Third Globally In Number Of Incubators, Accelerators: Report. Retrieved from: https://www.vccircle.com/india-now-ranks-third-globally-in-number-of-incuba tors-accelerators-report Tracxn (2019) India’s most exciting start-ups of 2019. Retrieved from https://tracxn.com/explore/ India’s-Most-Exciting-Startups-of-2019 Van Berkel (2020). India well-poised for digital transformation of manufacturing. ET Contributors. https://econom-ictimes.indiatimes.com/small-biz/sme-sector/india-well-poised-for-digitaltransformation-of-manufacturing/arti-cleshow/77428990.cms?from=mdr

The Post-pandemic Perspective of Rejigging the Gig Economy in India and the Issues of Returnees to Homeland Rabinarayan Patnaik and Sukanta Kumar Baral

1 Introduction In a fine evening during the month of March 2020, while addressing the nation, the Prime Minister of India suddenly announced complete lockdown in the country in the fight against the spread of COVID-19. Considered to be one of the most daring and challenging initiatives taken by any government across the globe, this step by the Indian government forced the working class (who generally work miles away from their homeland) of Indian economy to simply start moving towards their respective areas which they had left years ago (Verma 2020). In normal situations, going back to the homeland is considered to be really joyful and encouraging. But in this condition, there were reports of deaths came to forefront because of non-availability or rarely available transportation means like trains, buses, etc. (due to stringent lockdown guidelines). Most of these working class people were from states like Uttar Pradesh, Bihar, Rajasthan, etc. (Table 1). They didn’t have any option but to move back to their rural bases without any proper facility of transportation. With the lack of sufficient money in hand, many of them started going to their far away destinations by walking. In this process, most of them became either physically ill or mentally imbalanced. In various news channels, both national and international, there were reports of these mishaps to the migrant labourers and even there were legal suits and complaints put in front of judicial bodies related to the human crisis and damages (Sinha 2020). In addition to that, the problems faced by migrants who returned their home states are due to (a) lack of local jobs opportunities, (b) job scheme benefits not accessible, (c)

R. Patnaik IBCS, SOA University, Bhubaneswar, Odisha, India S. K. Baral (B) Department of Commerce, Faculty of Commerce and Management, Indira Gandhi National Tribal University (A Central University), Amarkantak, Madhya Pradesh, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_16

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274 Table 1 States in India with highest reverse migrants and number of returnees

R. Patnaik and S. K. Baral Sl

States

Number of returnee migrants

1

Uttar Pradesh

3,249,638

2

Bihar

1,500,612

3

West Bengal

1,384,693

Source Compiled by authors

expensive transportation option to return to cities, (d) no income and lack of capacity to pay back rent for lockdown period (Jha 2020). In order to overcome this challenge and making the migration convenient for the people, Government of India arranged a special train under the name called Shramic Special. In addition, there was distribution of free food and water to the passengers as well (Tiwari 2020). It was observed that the unemployment caused because of this lockdown and all increased the requirement of jobs and employment under the MGNREGA (Mahatma Gandhi National Rural Employment Guarantee Act). The migration of workers from urban to rural bases led to the overutilization of MGNREGA scheme to address close to 39% of increase in the necessity of occupations. This really did wonders with more than eight crore people got benefited with some kind of employment or other. In addition to the area of job creation under this scheme, there were many adjustments done by the government by adopting other related initiatives, e.g. merging the then existing 29 labour laws in four coded classes and so on (Charjee 2020). The silver lining is that due to the efforts of government, there seems to be a steep rise in the household employment moving up by 39% by the end of financial year 2020-21. However, looking at the volume of migrant workers and returnees, it is really doubtful whether MGNREGA and other similar schemes can really accommodate the required amount of livelihood means. Adding to the fact that a World Bank study in April 2020 suggested that nearly 40 million internal migrants have been impacted by their livelihoods. The Centre for Monitoring the Indian Economy (CMIE) also announced that in July 2020 alone, five million wage earners became unemployed and jobless leading to enormous challenge to the government. The government may initiate alternative skill development programmes in sectors like nursing, beautician courses, textile, food processing and the like, under the Pradhan Mantri Kaushal Vikas Yojna (PMKVY), and COVID19 has been a major disruption. It has affected lives and made many new women and girls vulnerable to trafficking. It’s only logical to believe that trafficking may increase post-pandemic making the condition more horrific. In its attempt to create employment and rehabilitation of affected workers, there will be a huge requirement of funds to the tunes of INR 3 lakh crores by the end of 2021. This will also be requiring alternative as well as complimentary income generation sources through agro-production covered under MGNREGA (Yogima 2020).

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2 Objectives of the Study The current study makes its way with the following objectives: . To study the migration trends of returnees. . To study the scenario of employment status of migrant workers and different employment opportunities provided by the government. . To study the significant of government financial support announcements during lockdown.

3 Analysis and Observation Various reports on unemployment in India caused by pandemic have shown certain figures which are really alarming, e.g. the figures from PLFS, i.e. Periodic Labour Force Survey, a Government of India organizational process on its report have concluded on the unemployment rate to be 5.8% covering each age group. In addition to that, economies around the globe, including India, have been impacted by the global spread of the coronavirus following the lockdowns. A significant number of migrant workers have returned to their native locations as result of COVID-19. To mitigate this kind of situation and to prevent it from further worsening, there are various programmes initiated by Government of India in the form of Aatmanirbhar Bharat and so on. There was another unwanted dimension added to the results of unemployment, i.e. the case on improper nutrition and in most cases malnutrition becoming a consequence of lockdown. It was found that inadequacy in feeding the children below two years has caused the untimely casualty of those infants, e.g. NFHS (National Family Health Survey) reported the damage of infants and children being below the expected weight to the tune of 37%. The situation became more aggravated because of Anganwadis (the centres opened by government catering to the needs of rural women and children, typically food and education free of cost) across India being shut down. Thus, the unemployment leading to insufficient food and improper care drastically downgraded the situations in the workers’ community. Then comes the unhygienic conditions of living. One of such instances can be the slums in Mumbai like Dharavi, with a population density of 277,136 people/km2 , and others like Worli Kolivada, Deonar, etc., have shared water supply, toilets, bathing facilities and laundry sites and improper sewerage systems. In such scenarios, these high-density and poorly ventilated informal settlements not only pose the highest risk of the spread of the infection (Bhargav and Reema 2020). Among all these adversaries, among 174 countries across the globe, India ranked 116th in the Human Capital Index as per the data released by World Bank and has improved its score to 0.49 by the year 2018 from the previous score of 0.44. It has been observed that the post-pandemic situations on health and education of children show slow but a steady growth due to various initiatives taken by government in the

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form of Jan hai to Jahan hai and so on to prevent the crisis during different phases of lockdown (i.e. four different phases between 25 March 2020 and 31 May 2020) and keep a track of consistent livelihood levels.

3.1 Status of Migrant Workers’ Deaths Owing to the lockdown and social distancing, many casual, normal and self-employed workers have been unable to work and have had to risk their livelihoods. Reports by various media houses have communicated about the seriousness of this issue. For example, as per India Today, out of a compiled database, out of around 238 workers who have migrated and died because of COVID and other economic factors, the identity of only 173 could be traced. The real numbers could have been more but because of inaccessibility to their locations, the fact remained partly opened (Chougule 2020). This still makes a very sensitive information. Another report obtained under the Rights to Information Act by The Wire, another independent news agency, opened up about the death of migrant workers close to 80 in numbers while travelling under the Shramik trains specially provided by Government of India for the COVID period. To make the situations more worsening, there was a mismatch between the number of deaths (due to travel of migrant workers, road accidents and for other reasons) as provided by the government departments and the numbers collected by one independent agency called LIFE Foundation. As per the reports by this Foundation, there were more than 970 deaths caused due to non-COVID reasons differing from a lesser number as cited by the government reports.

3.2 Role of States for Migrant Workers Among all these panicking situations, Government of India had made many endeavours to create an encouraging environment in the form of providing employment, occupation and livelihood to different classes of people who have become jobless and made a return to their homeland (Charjee, subharda). For example, Rozgar Abhiyan initiated by the government was focusing on enhancing the migrant workers’ skill level and equipping them with some kind of income generating capabilities. These kind of processes have started in a war footing manner covering as many regions as possible (like covering 116 districts in six states across India within a span of 125 days). At a whooping budget of INR 50,000 crores, another state-level initiative planned by Government of India was Garib Kalyan Rozgar Abhiyan (GKRA) aimed at creating employment for a time period of around four months for the jobless migrant workers. Ironically, as per government sources, by the end of three months only INR 28,138 crore was spent. Thus, the role of states becomes really important to monitor and ensure the utilization of these initiatives in appropriate manner (Puri 2020). They need to ensure the funds generated under various schemes like

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MGNREGS, should not be underutilized as once not utilized the funds are likely to return to the respective Government of India department and less likely to be coming back even at the worst situations of similar scope. In a bid to enhance the quality of life and livelihood, different departments like Indian Railways have come to the support of government initiatives at national as well as state level. For example, in different states where there were maximum number of returnees, it has supported local governments to construct houses typically in rural belts, creating jobs by deploying people in various project works related to harvesting, conservation of water, etc. It was also noted that under the banner of Bharat Grid, fibre optical cables were laid down generating jobs and employment for migrant community and engaging them during their home coming days. One gigantic steps taken by the Indian Government was that of constructing housing facilities under the scheme called Pradhan Mantri Awas Yojana-Gramin (PMAY-G). Under this scheme, a target has been set up to provide houses worth INR 2.44 crore to the rural people mostly comprising migrant workers and other affected by pandemic. Though a very meagre percent of this fund has been utilized due to this lockdown period and all, it is expected that it will pick up during the unlock and post-pandemic periods. It can be observed that the utilization of this PMAY-G scheme by different states has been different (Table 2). As can be seen among all the states, Madhya Pradesh as well as Odisha, two of the leading states in terms of being affected by migrant workers and their returns to the home villages, are very slow in utilizing the scheme of creating housing facilities in the rural bases. There are various other initiatives to counter this crisis and reviving the economy heading towards post-pandemic days. For example, different states have started a provision of constructing job portals and encouraging the migrant community to empanel themselves in the appropriate places. The Jharkhand government is preparing more plans for providing employment opportunities to people. The government provided 15 lakhs more people ration cards to take the benefits attached with. A programme, Sarkar Apke Dwar, had been organized, in rural and urban areas; the government is preparing an action plan so that every person can get jobs. Under the MNREGA system, planting work has begun, construction of the playground has begun, and control dam work is going on. Apart from this, an action plan is being prepared for individuals of every group, He said that Mukhyamantri Pashudhan Yojana has benefited many farmers. Livestock is the bank balance of people in rural areas. With their cooperation, their happiness furthers their life in times of sorrow. Urban Shramik Yojana for urban areas was started by the government, in which the work of registration of people is being done. Under this scheme, the employment opportunities are created. In the state of Uttarakhand, the government’s top priority is to create opportunities for job and resource development. A major instrument for achieving this is the Mukhyamantri Swarozgar Yojana (MSY). For this reason, industry, agriculture, cooperatives, animal husbandry, tourism, forestry, energy and other departments should set goals and do what is required. The government also stressed the preparation under the Management and Planning Authority of the Compensatory Afforestation Fund (CAMPA) of an integrated work plan to optimize job generation opportunities.

278 Table 2 State-wise status of PMAY-G scheme

R. Patnaik and S. K. Baral States

Sanctioned

Completed

34,042

1553

881,833

317,507

Bihar

3,285,574

1,220,596

Chhattisgarh

1,588,202

744,899

1707

73

Arunachal Pradesh Assam

Goa Gujarat

466,678

238,229

Haryana

21,502

20,400

Himachal Pradesh

14,863

7371

165,801

24,736

1,281,857

687,294

42,431

16,996

Madhya Pradesh

3,010,329

1,701,740

Maharashtra

1,209,398

500,439

34,482

9070 17,374

Jammu & Kashmir Jharkhand Kerala

Manipur Meghalaya

67,881

Mizoram

19,681

3317

Nagaland

24,383

4237

Odisha

2,423,012

1,283,013

Punjab

24,000

14,150

1,571,213

927,075

Rajasthan Sikkim Tamil Nadu Tripura Uttar Pradesh

1079

1055

527,552

255,599

53,827

37,498

1,461,516

1,428,691

Uttarakhand

12,666

12,362

West Bengal

3,404,467

1,881,967

Andaman & Nicobar

2125

354

Dadra & Nagar Haveli

5718

424

Daman & Diu

15

13

Lakshadweep

57

33

Puducherry

0

0

Andhra Pradesh

123,112

46,723 85,625

Karnataka

383,064

Telangana

0

0

Ladakh

0

1205

22,144,067

11,491,618

Total Source Compiled by authors

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Table 3 State-wise welfare schemes by the respective governments State

No. of registered BOCW

Cash

Other items like food/ration/shelter

Bihar

13.4 lakh

NIL

NIL

Chhattisgarh

18.9 lakh

NIL

Food packets only

Uttar Pradesh

19.2 lakh

1000/head

NIL

Odisha

20.8 lakh

1500/head

NIL

Punjab

3 lakh

6000/head

NIL

Karnataka

21.8 lakh

5000/head

Food packets also

Source Compiled by authors

An integrated district plan should be prepared for this reason, and the governing body of CAMPA should meet once every two months. He said the use of human resources in watershed projects, the production of fruit belts and women’s nurseries, along with the conservation of wild animals, could provide thousands of people with employment opportunities. It also directed that successful plan for optimizing job opportunities under MSME and MNREGA should be made. For smaller projects, with the provision of Mudra loans and subsidies, small entrepreneurs can also benefit from MNREGA and MSME. Emphasis should also be laid on 50 days of additional job creation in rural areas under MNREGA, he emphasized. In addition, under the Jal Jeevan Mission, as many local young people as possible should be given job opportunities. This will allow the development of jobs while helping to grow agriculture and horticulture as well. Coming to the welfare of people across the states and regions, the respective states need to have a mechanism while running various schemes, e.g. the initiatives under the Building and Other Construction Workers Welfare Board (Table 3). It can be seen Karnataka and Odisha tops the list of registered cases of empanelment under this board. In certain untraditional sectors (being generated due to this gig economy), the attrition of jobs as well losses are maximum as per the reports from International Labour Organization (ILO), assuming the causal and temporary nature of work in services and industrial sectors due to frequent and strict guidelines during lockdowns. In 2019–20, such workers were projected at 86.1 million, which declined to 67.2 million by July. For most individuals, these are favoured modes of employment as they provide better conditions of employment and wages. White-collar professionals, which included 5.9 million workers between May and August, accounted for the largest job loss among salaried workers. This group includes developers, software engineers, doctors, journalists, accountants, analysts, teachers and mostly highly trained people who have been working in some of them (Balwant and Arju 2020). For example, in case of the state of affairs in Odisha, the contractual employees are having a comparatively less share to that of regular employees (Table 4). It has become really difficult for the employers to retain the contractual employees during the lockdown period. To understand the initiatives taken by the government in

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Table 4 Employee status of Odisha industries as regards to regular and contractual during 8 April 2015 to 27 August 2020 Sl

1

Industries

Tata Steel

2015

2020

2015

2020

(Regular employees)

(Regular employees)

(Contractual employees)

(Contractual employees)

2602

3475

36,108

11,817

2

Visa Steel

1130

689

2350

1205

3

Mesco Steel

498

417

578

36 2866

4

Nilachal Ispat

1587

1478

1459

5

Adani

190

179

248

256

6

Rohit Ferotez

268

223

744

703

7

BRPL

125

119

349

429

8

Jindal stainless steel

1661

1556

6468

4958 699

9

Maithan Ispat

260

254

699

10

J.K.Ispat

71

60

74

11

JSW Cement

–

64

290

60

12

Nunon Tubes

–

13

144

13

Saigar enterprise

–

101

8

14

Emami Cements

–

105

316

15

Jindal United Steel

–

286

888

16

Jindal Coco Limited

–

116

472

Total

8392

9135

49,077

25,147

Source Compiled by authors

creating a healing impact on the damages caused by the gig economy and rebuilding the same, the major points of those can be mention worthy.

3.3 Important Areas of PMGKY (Pradhan Mantri Garib Kalyan Yojana) Scheme (i)

It covers various health-related issues like treatment for COVID in different health centres and hospitals mostly run by government and providing a special insurance package to the tune of INR 50 lakhs. It aims to create beneficiaries belonging to working class (almost more than 21 lakhs).

The Post-pandemic Perspective of Rejigging the Gig Economy in India … Table 5 Migrant workers under free food grain scheme

States

Original estimate

Indicated states/UTs

Uttarakhand

6.2 lakh

15,000

UP

1.4 cr

4 cr

MP

54.6 lakh

2 lakh

Gujarat

38.3 lakh

1.5 lakh

Odisha

32.4 lakh

5 lakh

Bihar

86.5 lakh

15 lakh

West Bengal

60.2 lakh

35 lakh

MH

70 lakh

15 lakh

281

Source Compiled by authors

(ii) Basic and necessary food items like rice, wheat, pulses, etc. can be mixed in different proportions to be provided to the needy people at different quantities at least for a month, and it can cover almost 80 crore Indians living different rural and suburban areas. (iii) Another most important beneficiaries will be the farmers who can get INR 2000 starting from April 2020 credited to their respective bank accounts. (iv) The Regulations of the Workers Provident Fund shall be updated to include a pandemic as the justification for authorizing a non-refundable advance from their accounts and can be benefiting the migrant workers as well (Table 5). (v) At the same time, the respective state governments can use the allocated fund meant for the workers under the BOCW Act, 1996 which acts as a safeguard to these groups of people during exigencies and turbulent economy. At the same time, there are various financial supports from the government during the lockdown to keep the morale of workforce in right order (Table 6). For example, floating EPFO for workers, increasing the margin of financial support to MGNREGA, small and medium enterprises (SMEs) and so on.

3.4 New Government Initiatives in Regard to the Migrant Labourers in India (i)

As per the census records 2011, child labourer in India stands at 1 crore and it has decreased from 2001 numbers (1.25 crores). At this rate, it is going touch around 70 lakhs by the end of 2021 which still is a big number to control and manage. Adding to the fact that job losses of parents and senior members of households might increase the number in the years to come (Panda 2020). Therefore, the government has made provisions looking at the crisis created due to migrations. On the lines with Article 39(e) of Child Prohibition and Regulation Act, 1986, the conditions of putting children into dangerous and risky working environment have been revised made more stringent. There won’t

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Table 6 Government financial support announcements during lockdown Sl

Measures

1

SMEs (credit guarantee trust)

2

MSME (fund of funds)

10,000

3

NBFCs, HFCs (liquidity and credit guarantee)

39,000

4

Workers EPFO

2500

5

Food grain subsidy

3500

6

MUDRA SHISHU LOAN

1500

7

CAMPA Funds for employment generation

6000

8

Fisheries spending

9

Animal husbandry funding

2500

10

Herbal cultivation

3300

11

Bee-keeping initiative

500

12

Micro food enterprises

9500

13

Viability gap funding (social infrastructure)

8100

14

MGNREGA

Total fiscal impact

Amount (Cr.) 4000

20,000

40,000 150,400

Source Ministry of Finance, RBI, Barclays Research

be any compulsion or coercion to make the child labourer engaged in the workplace. (ii) There has been a major amendment brought in the Industrial Relations Code. There will be strict vigilance on the companies with number of employees less than 300. These companies cannot go for recruitment and expansion of workforce without obtaining the permission from the concerned ministry and department of government. At the same time, there are changes in the previous bye laws related to laying off the employees and industrial workers (Ananchal 2020). The professional set ups with less than 300 manpower cannot issue the retrenchment or laying off at its will, rather it has to be put forward to the concerned authority and after proper notification, this has to be taken forward. However, along with all these stringent conditions posed for the industries, there are certain flexibilities created for companies. For example, in the conditions of strikes and lockouts, there will be government interventions making the companies working with more agility and flexibility. (iii) Another provision has been related to the health, safety and the working conditions. The introduction of OSHWC (Occupational Safety, Health and Working Condition) Code Bill during 2020 has made the safety and health issues suitable and more favourable for the working groups in industries. Special provisions have been made for temporary and freelance employees who wish to work beyond their home states. However, till this time it covers only the part timers and over period of time there might be changes related to full timers and permanent employees as well. What is expected from the state governments to see and

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monitor the contractors operating in multiple cities and states and to prevent them from exploiting the workforce. There must be constant monitoring of benefits like insurance, provident fund, etc. going to the exact beneficiaries. The organizations will now have to ensure the arrangements of providing accommodations to the migrant workers from place to place wherever the later gets engaged. The flagship programme of Government of India under MGNREGA has been in the forefront of reconfiguring the gig economy and focusing on creating a better livelihood for the displaced and returnees. The scheme, which saw a sharp increase in its budget in 2020–21 because of increased demand, continues to see strong interest, through there has been a decline in work demand since lockdown was eased and farming activity picked up in villages. In its effort to encourage the industries and their interests in rebuilding process, the government is focusing on bringing medium-sized companies under the umbrella of Aatmanirbhar Bharat (Bhatia 2020). The changing policies of government reflect the evolving nature of the economy thereby creating a growth path of gig elements and transforming the migrant labourers to make a change in their traditional mind set of working and performing. The special provisions make ways for the simplification of legislation and the implementation of welfare initiatives for 50 crore employees in India, covering organized and unorganized industries. Last year, India jumped 14 places to 63rd place in the Easy to Do Business (EODB) rankings and 79 places. With structural modifications in development, consumption and work habits, the environment after COVID-19 will be different.

4 Practical Implication of the Study Right from saving on real estate costs by reducing office space to making employees work from home on a remote virtual basis for a long time and into the future, there have been across the board multiple changes to the way companies run their businesses. These uncertain times have made employers realize the worth of a few key business skills that they would like their employees to possess to enable the companies to survive and flourish. Businesses today work in multiple technologies and different platforms. Employees with solid digital skills especially in the emerging areas like artificial intelligence, machine learning and the ability to manage large sets of data would be a cut above the rest. Thus, the policymakers can get real insights of gaps in understanding the plights of migrant workers, the changing environment of working places and accommodating the gig workers in the changing world order of development of human civilization at large.

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5 Conclusion As the world is entering into the Industry 4.0 largely defined by technology-based business and economic processes due to the pandemic, India has been in the forefront of working in synchronous with the new global order. In the post-pandemic scenario of economy, high-end and most-efficient work environments will be fitting into the new framework of standard operating procedures. Businesses and economic activities both technological and non-technological will start depending on more of digitally skilled and efficient workforce. The time spent with the organization may not be the yardstick of performance, rather the more sophisticated usage of technology by the workforce in producing the results will be of paramount importance. Thus, most of the workforce might be engaged in contractual or part-time or consulting based processes. In this new scenario emerging out of post-pandemic situations, India as an economy needs to rethink to configure the workforce in a technology and digitalized skilful environment (Puri 2020). As far as implantation is concerned, there are three set of rules. One is central, state, and there are rules to be framed by appropriate government. The rules to be framed by the appropriate governments are common in nature but it varies depending upon which sector is to be covered. Once the central government framed out those, the states are free to adopt. In the Code on Social Security, there are only 11 rules under the state domain and 22 with appropriate government, out of total 82 rules. In the Occupational Safety Health and Welfare Code, out of 108 rules, only 26 are with the state, 68 with the appropriate government and rest 18 with the Centre. In the Industrial Relation Code, there are 57 rules and mostly they are with the central government, except we will not be framing rules for the trade unions. In the Wages Code, all the rules are with appropriate government for implementation as concerned.

References Ananchal M (2020). In labour codes, what changes for workers, hirers. The New Indian Express, 22nd September 2020, p 22 Balwant SM, Arju K (2020) White collar blues. The Pioneer, 1st October 2020, p 9 Bhargav R, Reema B (2020) A dignified period in an unprecedented era. The Guardian, New Delhi, p4 Bhatia G (2020) Devise a new labour law regime for gig economy workers. The Hindustan Times, New Delhi Edition, 23rd September 2020, p 8 Charjee S (2020) Unused rural funds hint migrant s may be back at work in cities. The Hindustan Times, 28th September 2020, p 1 Chougule A (2020) The case of missing data on migrant workers deaths: the free. Press, 22nd September 2020, Indore Edition, p 6 Jha S (2020) 6 months on. Migrants caught between hope and despair. Business Standard, 28th September 2020, p 1 Panda B (2020) Child labour in India. Around Odisha, 22nd September 2020, p 4 Puri L (2020) The future of work. The Indian Express, 22nd September 2020, p 7

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Sinha S (2020) Govt clueless on number of jobs lost during pandemic. The Business Line, 17th September 2020, p 1 Tiwari R (2020) States told to pace up distribution of free grains to migrants. The Economic Times, 6th June 2020, p 7 Verma S (2020) PM Modi’s game-changing labour reforms to boost growth. The Guardian, 29th September 2020, p 5 Yogima SS (2020) Demand for work under MGNRGEA up by 40 percent. The Pioneer, Lucknow, p7

Work-Life Balance and Its Socio-cultural Inclination from Industry 1.0 to Industry 4.0 Joshin Joseph

1 Introduction According to Department for Trade and Industry, U.K, work-life balance is not only about childcare and families nor it is about working less. Rather, it is about working smart. It is about being fresh enough both at work and at home, without sacrificing one another. And the work-life balance is very essential for everyone, irrespective of the life stage (as cited in Houston 2005). Whatever the definition is, work-life balance is necessary for everyone, and having right balance between work and non-work activities enhances the happiness and life satisfaction. WLB is a concept that encompasses each and every life sphere of which are relevant to an employee. Because of the interdisciplinary nature of the WLB concept, considering WLB as a human resource management concept only can result in the development of a handicapped view about the WLB concept. That is, WLB is a concept which is rooted upon multidimensional framework structured upon behavioural science as a whole. Therefore, WLB is a concept which conceives its ideology equally from management, psychology, sociology, and other related fields. Effective and efficient balancing of time in between work and social life results in the fulfilment of personal needs which in turn result in the employee well-being (Gröpel and Kuhl 2011). The proper prioritisation of resources between personal and professional life in accordance with the personal objective is the essence of WLB. Appropriate distribution of time and energy between work and personal life pose a challenge to many working people, and unfortunately, many professionally active people face work-life imbalance in their life (Andysz et al. 2014). With an objective to crack down the work-life imbalance, WLB policies were introduced in organisations. The impact of WLB policies on work-life imbalance was limited as the there is a gap in between WLB initiatives and WLB policy usage by the employees. The success of WLB policy is J. Joseph (B) KMML (A Govt. of Kerala Undertaking), Kollam, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_17

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depended upon the integration between the individual initiative and organisational initiative (Andysz et al. 2014). The magnitude of integration between the individual initiative and organisational initiative depends upon the extend of commonly shared views with regard to the socio-cultural environment. WLB is a socially devised as well as socially driven concept based on the interaction between personal psychology and perception.

2 Etymology of Work-Life Balance During the early days of the evolution of WLB concept, WLB is often defined as the absence work-life conflict (Staines and O’Connor 1980). Later on, researchers found that interaction between life domains not only has the potential to produce a negative outcome but also has the potential to produce positive outcome and started focusing on the positive aspect of work to non-work interaction such as compensation, enhancement, and enrichment. Compensation occurs when the negative turmoil from one domain is setoff against the positive outcome from the other domain; that is, bad performance at work is setoff against good performance at family (Guest 2002). Work-life enhancement occurs when the efficiency acquired as a result of multiple responsibilities at work facilitate improved performance in the life as a whole, and the work-life balance is estimated based on the level of work-life enhancement (Wiesea et al. 2010). Similarly, in the enrichment-based model of WLB, WLB is defined as the improvement in the non-work life because of the influence of work life and vice versa, and the level of WLB will be depended upon the level of work-life enrichment (Greenhaus and Powell 2006). Higher the level of work-life enrichment, higher will be WLB, whereas lower the level of work-life enrichment, lower will be the WLB. The theory underlying the positive approach (enrichment, compensation, and enhancement) of WLB is that balance between work and non-work leads to positive at work and non-work domain such as life satisfaction, work satisfaction, employee engagement, reduced employee turnover, increased morale, enhanced job performance, and marital satisfaction (Brough et al. 2014; Carlson et al. 2009; Valcour 2007; Voydanoff 2005). Later in 2003, Fisher-McAuley, Jeffrey M Stanton, Jeffrey A. Jolton, and James Gavin proposed that both the conflict and enrichment occur at the same time, and therefore, WLB is the total effect of both work-life conflict and work-life enrichment. According to Fisher-McAuley, Jeffrey M Stanton, Jeffrey A. Jolton, and James Gavin, WLB is a situation at which where there is low level of work-life conflict and high level of work-life enrichment. And this conflict plus enrichment model of hypothesis supported WLB researchers like Jeremy Hayman, Szener, Grzankowski, Eng, Odunsi, Frederick, etc. They argued that studying WLB either using conflict (negative) or using enrichment (positive) approach can reveal only half truth; it is just like predicting the outcome of a coin just by considering its one side. Therefore, in order to have a complete view about WLB and its implications, it is essential to integrate

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the effect of both conflict and enrichment (Szener et al. 2016; Hayman 2005; FisherMcAuley et al. 2003). Another major turning point in the WLB was the hypothesis put forward by the Thomas Kalliath and Paula Brough in 2008, that the balance is more than just the absence of conflict or presence of enrichment. According to Kalliath and Brough, balance is a construct which is distinct from both conflict and enrichment; hence, measuring WLB based on conflict and or enrichment is as same as measuring balance. Carlson et al. (2009) empirically validated the claim of Thomas Kalliath and Paula Braugh that balance is a construct which is distinct from conflict and/or enrichment. The work of Kalliath and Brough enlightens the WLB research, and researchers started to adopt assessing WLB directly rather than the traditionally followed indirect method of assessing WLB through conflict and/or enrichment, enhancement, and compensation. WLB can explain large variance in employee satisfaction, happiness, life satisfaction, employee turnover, and employee morale than work-life enrichment and work-life conflict can explain, and there exists discriminant validity between WLB and work-life enrichment and/or work-life conflict (Brough et al. 2014). Though the discriminant validity between WLB and work-life enrichment and/or work-life conflict has been established, researchers often defined WLB differently because of its strong bond with contextual environment such as socio-cultural factors, psychological factors, and personal perception. According to Jack Welsh, former CEO of General Electric’s, WLB, ‘There is no so-called thing called WLB, rather there are work-life choices, and you make them, and they have consequences too’ as cited in (UK Essays 2013). Welsh here exposed the individualistic characteristics of the WLB concept. Because of the extreme bliss between the socio-cultural environment and WLB, having a common conscience over WLB is awkward. Researchers (Joseph and Sebastian 2017; Szener et al. 2016) often acknowledged the absence of a common definition over WLB. The absence of a universally accepted definition together with the perpetual coalition of WLB together with socio-cultural environment smouldered the WLB research. Casper et al. (2017) identified that WLB research is often prone to and/or driven by jingle-jangle fallacy. Because of the jingle-jangle fallacy, the content depth and width of the WLB is still a matter of debate across the researchers and academicians.

3 Industrial Revolution and Work-Life Balance Industrialisation initiated from the Europe during the beginning of seventeenth century revolutionised the work environment. Industrialisation resulted in the emergence of a product-oriented concept. Maximum production was the sole moto of the industrialised economy. The industrialisation has four stages, viz., family-oriented production, handicraft system, cottage system, and factory system (Jain 2017). During the initial phase of industrialisation, the orientation is on the mechanisation of the production function. The mechanisation of the production increases the productivity without any significant change in work environment. That is, during

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the early stage of industrialisation self-reliance was the major outcome. Agriculture was the prime focus during this phase. Industrialisation resulted in the introduction of innovative methods of farming, high productive crops; pave way for more food production, healthy lifestyle, increased population growth, and larger workforce (Sharman 2017).

4 Industry 1.0 and Work-Life Balance Gradually with the widespread of industrialisation, production was shifted from home to factory. That is, production not only becomes mechanical but also extracted out of the family and society. Factory system resulted in the isolation of work and segregated it from the society, and hence, the workers need to move out of the family for work. Thus, it resulted in the development of new work culture. The segregation of work and family widens the gender role divide. The factory work becomes masculine entity, and the house work becomes feminine. The factory system makes it impossible for women to participate in the paid work as they have to bear the burden of care responsibility and family. That is, the factory system initiated as a consequence of industrialisation resulted in the widening of gender role divide in the society. However, even during the factory system the focus was on the production and the role of employees was ignored. Enhancement of the productivity was the major focus, and hence, the workers needs were often ignored because of the undue focus on the production. During the first quarter of the nineteenth century, Europe becomes industrialised in terms of mechanisation of the production process. And as a next step to enhance the productivity, the entrepreneurs started to focus upon the human resource. During the mid of 1800s, human resource becomes the prime factor of entrepreneurial focus. Focus upon the management of human resource as a mean to enhance productivity resulted in the development of various management theories and concepts which necessitated the improvement in the work environment (ERIH 2018). Robert Owen was one of the primates who initiated employee friendly work reforms in the Europe during the mid of 1800s. He refused to employee children under the age of 10 in his factory and argued against the practice of long work hours followed. However, the first noticeable improvement in the working condition happened in the year 1842 when the Great Britain restricts the child labour and employment of women in factory by law (ERIH 2018). Furthermore, in the nineteenth century management gurus such as Charles Babbage, Andrew Ure, Charles Dupin, and Henry Robinson Towne popularised the various innovative management philosophies such as division of work, specialisation, cap on long work hours, and scientific study of work. Division of work and specialisation were the major work-related reforms happened during the nineteenth century that revolutionised the management philosophy (History 2017).

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5 Industry 2.0 and Work-Life Balance The twentieth century management philanthropy was put forward by Frederick W. Taylor, Peter Drucker, Lillian Gilbreth, and Henry L. Gantt was rather employer friendly than employee friendly. The management philanthropy of the twentieth century focused on the enhancement of the labour productivity and often ignored the human aspect. They believed in the productivity enhancement through specialisation and output-based pay. The management philanthropy of the twentieth century was cornered on the belief that money is the most influential motive for an employee. Thus, it overlooked the welfare aspect and resulted in the over tuning of the labour force. Similarly, division of labour and specialisation makes the work environment mechanical rather humane. Employers often concentrated in the development of a work environment which is highly formal and segregated from the family as well as society. The over tuning of the work environment makes the employee exasperated socially and gives rise of argument in favour for the social integration of work environment. Furthermore, automation and mechanisation of the work environment reduce the physical strain involved in the work, which in turn attracted more women into the workforce. Thus, at the initial stage the factory system resulted in the antifeminisation of the labour force, whereas at the later stage industrialisation (i.e. mechanisation and automation) facilitates the feminisation of the labour force. It has become essential for the employers to adapt the work environment in such a way to accommodate the women, which in turn resulted in the welfare-oriented management concepts such as quality of work-life, employee engagement, and WLB. In addition, it should be noted that the Europe as well as the North America become industrialised (in terms of production process automation) in twentieth century, whereas the Asia and Africa are still on its road heading towards industrialisation. In concurrence with the rate of industrialisation, WLB policies have been intuitionalised in the Europe, North America, and Ocarina by the last quarter of the twentieth century (Oláh and Fahlén 2013; Lutz et al. 2013; Lingard et al. 2009), whereas in Asia as well as in Africa, WLB is not yet become the part of corporate philanthropy (Suresh and Kodikal 2017; Tambe 2017; Morganson et al. 2014; Dale 2005).

6 Socio-cultural Enlightenment, Industrialisation, and Work-Life Balance Renaissance movements started in the Europe during the fourteenth century are the forerunner of socio-cultural enlightenment in the twentieth century. French enlightenment gives birth to a modern human and social science based of equality and liberty (Osborne 1998). The enlightenment movement of the eighteenth century focus is to improve the human existence by making the society safer and stable (idea conceived by Hobbes’s), more tolerant (idea conceived by Bayle’s), improving health by reducing disasters (idea conceived by Descartes), and making the individuals more

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accepting and dynamic (Israel 2010). That is, the eighteenth century enlightenment concentrated on the enlightenment of the society as a whole form it decaying unscientific methodology dominating in the society during that time. Social awakening of the society as a whole was very crucial to restore the social ethics during that time. However, till the end of nineteenth century employee welfare was out of card as the concept of multiculturalism, global citizenship, civil society, and personal liberty was in its evolutionary stage. The enlightenment philosophers and thinkers of the seventeenth and eighteenth century faced strong opposition from the country men, as they were against the prevailing social structure. The modish multiculturalism infused with postmodernism that swept Western universities and local government in the 1980s and 1990s has got wider acceptance in the society (Israel 2010). Many of the western intellectuals and the policy makers adopted a positive attitude towards application of the principles of multiculturalism in governance and policy implementation. The widespread acceptance of multiculturalism assisted the process of dismantling the social hierarchy prevailed in the society, and working class becomes more powerful. During this period, society becomes more aware about the humanitarian values and employers were forced to adopt labour welfare policies in organisations. The postcolonial enlightenment thoughts such as universalised concepts with regard to citizenship, human rights, the public sphere, civil society, democracy, and popular sovereignty are constitutive of political modernity and remain indispensable to social science concerned with issues of social justice (Carey and Trakulhun, Universalism, Diversity, and the Postcolonial Enlightenment 2009). During the postcolonial enlightenment era, Europe and North America adapted cosmopolitan attitude in its social engineering. As a result, organisations started practising humanitarian values and transformational principles in its operations. The concept of corporate citizenship started to evolve. The societal modernisation diluted the power distance and reduced the gender gap. The paradigm shifts in the sociocultural views and the acceptance of metabolism supported the democratic and participative forms of management and governance. Though contentious, western nations started to frame labour welfare laws and practices by the twentieth century. The principle such as equality, democracy, and the quest for perpetual peace which is indeed clandestine for employees during nineteenth century became the basic apparent of employee in the twentieth century. Employees as well as the entrepreneurs were treated at par as stakeholders, and employee welfare has become one of the strategic objective of the human resource management. WLB is one of such labour welfare activity aimed at enhancing the well-being in terms of their physical and mental health. Studies (e.g. Sonnenschein et al. 2013; Carey and Festa, Postcolonial Enlightenment 2009; Lewis et al. 2007) have often identified WLB as an employee welfare terminology evolved as a result of parading shift in the socio-cultural attitude of the society. The conspicuous critique in contrast to radical enlightenment and postcolonial enlightenment is that the light of enlightenment curbed within Europe and North American. Till the twenty-first century, Asian as well as African nations miscarried the principles of radical enlightenment as democracy. Therefore, the benefits

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inclined with the radical enlightenment such as sexual equality, individual liberty of lifestyle, freedom of thought, religious transparency, separation of state from religion, and secularism were trampled in most of the southeast nations. Irreligion, libertinism, and subversiveness were still seemed as colossal disapproval typically across Asia and Africa. Because of the fabian approach towards the socio-cultural redefining, labour welfare still emancipated with the socio-cultural wall. It was only in the twenty-first century Asian and African nations started to inculcate the principles of radical enlightenment in the corporate philanthropy. It is because of this fabian approach towards socio-cultural refinement management philosophies such as employee participation in management, quality of work life, employee engagement measures, corporate citizenship, and WLB measures which are still considered as innovative management philanthropy across Asia and Africa.

7 Industry 3.0 Work-Life Balance The prominent characteristics of the 3rd generation industry are the automation of the work environment. Traditionally, gender role divide was very eminent in the society. Even during the period of hunters and gathers, the gender role divide was explicitly evident. In hunter and gather societies, the hunting—the work that required larger physical effort—was the duty of males and the duty of gathering lives, seeds, and fruits was entrusted upon females (Woodburn 1982). That is, the gender role divide based on the ‘capability’ has historical and physical underpinnings, whereas the gender role divide based on ‘discrimination’ has only socio-cultural underpinnings rather than physical underpinning. During the preindustrial era, the societies were male oriented and women were marginalised from the mainstream, and the gradual emergence of industrialisation together with family-factory divide strengthens the existing patriarchal system prevailed (Gambles et al. 2006). The factory system and segregation of work out of family were the immediate consequence of the industrialisation. When the economies become industrialised gradually, it overturned work environment companionable for women. Particularly, the 3rd and 4th generation industrialisation which resulted in the automation of the production process together with remote work options welcomed the women and the marginalised into the labour market. Work-life balance is often conceived as a concept emerged as a consequence of the feminisation of the work environment. Industrialisation resulted in the automation of the production process which in turn thins the physical strain involved in the factories, that encourage the women participation in the labour-intensive factories. Similarly, the widespread acceptance of the postcolonial enlightenment principles such as equality, multiculturism, civil society, public space, and humanitarian values redefined the power distance as well as the gender role divide prevailed and invigorated women into the labour market. According to Greenberg and Avigdor (2009), WLB is a concept which is feminine in nature. When the women joined into the workforce as a result of the socio-cultural and work-process reforms, the employers

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become compiled to draft work schedule and policies in such a way to inculcate the ‘women’. The feminisation of the work environment resulted in the argument in favour of work schedule flexibility and facility for work-family integration which necessitated the employers to adopt WLB policies at workplace so that the ‘women’ were able to run across between their work and personal responsibilities (Bhardwaj 2017; Joseph and Sebastian 2017; Weinstein 2009). Thus, the need of balancing various life roles becomes necessary because of the entrance of the women into the paid work. The ‘women’ only life wake cannot be either shifted or transferred to one another; hence, the only possible option available before the employer is to make adjustments to the work environments in such a way women can balance their so-called personal (family) responsibilities along with the responsibilities at work. The configuration of the workforce structure changed has changed drastically since 1950s; to be specific, the number of people who integrate the work and family responsibilities has risen (Francis et al. 2009; Booth and Frank 2005; Dale 2005). Raising the literacy rate of women, declining fertility, and increasing desire for personal fulfilment were major underlying forces behind the increased women work participation rate since 1950 (Francis et al. 2009). It was the automation of the work environment which drastically reduced the manual effort involved in the manufacturing processes. Human intervention is only needed for the operational and control process of machines and equipments. Dilution of the physical efforts involved in the manufacturing processes enables the physically weaker sections into the manufacturing industries. That is, it was the technological advancement and office automation that actually pave way for the paradigm shift in work demographics, which in turn result in the feminisation of work environment. The socio-cultural paradigm was also adapted in accordance with the redistribution of the power distance and gender role divide. When the women entered into the labour force, primarily for young moms who have the caregiving responsibility it necessitated the employers to provide flexible work options available in order to keep their employees loyal and committed towards the organisation. Thus, as a counter move watered down the difficulty in running across the work and personal life responsibility the organisations initiated policies to remove the imbalance against work and personal life. Therefore, feminisation of work environment is a factor that fertilised the WLB.

8 Hours of Work and Work-Life Balance Hours of work is the another important indicator of work-life balance. Studies (e.g. Kumari 2013; Shree 2013; Malaviya 2012; Mehtha 2012) have often identified that there is inverse relationship between WLB and hours of work. Table 1 illustrates the change in the annual statistics of hours of work over the last forty-seven years (only selected years are shown). As shown in Table 1, the annual hours of work have decreased constantly over the period considered. As per the statistics illustrated in Table 1, during the year 1970 employees worked 1980 h on an average, and the hours of work have declined to

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Table 1 Table showing change in annual hours of work from 1970 to 2016 Yea r

1970

1975

1980

1985

1990

1995

2000

2005

2010

2015

2016

HoWa

1980

1936

1912

1899

1879

1863

1841

1806

1775

1767

1765

= Hours of work Source OCED statistics a

2000

Yearely Hours of Work

Fig. 1 Graphical distribution of average yearly hours of work around the globe from 1970 to 2017

Yearely Hours of Work Vs Years

1950 1900 1850 1800 1750 1700 1650 1600 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2016 2017

Years

1765 in the year 2016. Yearly hours of work have declined significantly over the year considered. Similarly, during the period from 1970 to 2000, the hours of work have declined significantly. It was during the period from 1970 to 2000, the concept of WLB and labour welfare started to evolve. And the implementation of WLB policy in organisations can be considered as one of the factors responsible for the steep decline in the yearly hours of work level. Furthermore, the constant decrease in annual rate of hours of work over the past decade is one of the tangible outcomes of WLB intervention (OCED 2015). Cap over hours of work is one of the major binding rule every nations WLB bill (Eurofound 2017). Therefore, the annual hours of work statistics illustrated in Table 1 validate that the labour welfare initiatives particularly WLB programmes are effective in curtailing the culture of long hours of work persist in the golden age of capitalism. Figure 1 illustrates the graphical illustration of the change in the annual statistics of hours of work over the past forty-seven years.

9 Women Work Participation Rate-A Matter of Concern for Indian Women Work participation rate is the percent of people in the age group of 16–65 in the economy, out of which who are either employed or actively seeking for a job (OECD 2018). Table 2 illustrates the women work participation rate of women of Europe, North America, Oceania, and India over selected period from 1960 to 2015. As shown in Table 2, the women work participation rate increased constantly over the period considered. That is, during the past 50 years the women work participation rate has been increased significantly among nations across Europe, North America,

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Table 2 Women work participation rate Year

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

Europe NAa

42.0

40.0

43.0

45.2

47.2

50.2

52.4

54.9

56.5

58.4

60.7

63.2

44.0

49.3

53.4

59.7

64.0

67.9

62.7

63.6

63.1

63.0

62.2

52.6

49.6

51.2

52.5

56.0

57.4

58.4

60.2

61.8

65.0

39.2

30.3

27.4

Oceania India

Data not available

36.0

Source OCED data base a N.A = North America

and Oceania. With regard to Europe, North America, and Oceania, over the past 50 years the women work participation rate has increased significantly. It is an indication that the developed nations across the world have better working environment and work-family balance options available. The higher women work participation rate is the indication of better WLB and quality of work-life (OCED 2014), which means the women who belong to developed nations (Europe, North America, and Oceania) were capable of integrating their work and personal responsibilities successfully, where in the case of India, a rapidly developing nation still has a very pathetic women work participation rate. That is, the women in India were still unable to enter into the labour market because either of the socio-cultural restrictions and/or work-related hindrances. Even during the period of 1960s, OCED nations had a superior women work participation rate than that of India during 2000. The statistics further questions the effectiveness employee welfare reforms and women friendly work legislations formalised in India during the past decade. The statistics illustrated in Table 2 indicates that over the years labour market in India remains padlocked towards women. Even in comparison with south Asian nations, India’s women work participation rate is relatively low, during the year 2017; according to International Labour Organisation (2018) statistics, the women work participation rate was as follows: India (27%), Bangladesh (33%), China (61%), Nepal (83%), Pakistan (25%), and Sri Lanka (35%). As per ILO rank 2013, India’s women work participation rank was 121 out of 131 nations across the world (Prabhu 2017). Therefore, it is essential to frame legislations and redefine the socio-cultural as well as work environment prevailing in India in order to make it attractive for women. WLB legislation can be a significant foot ahead with regard to this. Figure 2 is the graphical representation of work participation rate of women of Europe, North America, Oceania, and India over selected period from 1960 to 2015.

10 Dual Carrier Culture Re-defining the Work-Family Culture Rapoport and Rapoport (1969) define a dual carrier family as a family in which both partners peruse a professional career. Traditionally, non-paid (household) work was

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Fig. 2 Graphical Illustration of women work participation rate from 1960 to 2015 Rate

50

Years Europe

N.A*

Oceania

India

considered as feminine and paid work as masculine. The emergence of dual carrier family is one of the structural refinement occurred in the twenty-first century. Developed economies have almost adapted to the family structure refinement by adjusting the socio-cultural and work environment. The dual carrier familyship (DCF) resulted in the gender role and power restructuring within the family. When the women entered into the paid career apart from the household work, it not only enhances the burden of the women alone, rather it also enhances the burden of men too. That is, when a wife started to concentrate more on paid carrier along with the household work, the household work overlooked by her need to be assumed by someone else in the family, preferably her spouse. Thus, the DCF not only enhances the responsibility of women but also it resulted in the men’s household responsibility enhancement. The feminisation of the work environment initiated negotiations both at organisational level and at family level. Certain household chaos such as cooking, housekeeping, and caretaking of kids traditionally earmarked as ‘women only’ were re-stamped as gender neutral. The doctrine of egalitarianism becomes the operating force in the society as well as in the family. This restructuring of the family culture further enhances the workfamily friction and necessitated the balancing in between work and personal life. The doctrine of egalitarianism dismantled the traditionally followed gender role divide. And as a result, either men cannot be considered as sole breadwinners or women as housekeeper. In DCF, both couples are highly educated and have a high career orientation and full-time work commitment (Abele and Volmer 2011). DCF is the characteristic of a post-industrial era, where both the men and the women have the free will to choose the role they want to play in the society. The DCF dilutes the gender-based power distance, reduced the spouse dependence, enhances the partner’s autonomy, and provides opportunity for recognition and acceptance both at family and at society. DCF is often identified as a new family arrangement evolved as a consequence of socio-cultural enlightenment, high women labour force participation rate, and increased professional competence acquired by the women through education in the past few decade (Abele and Volmer 2011). The DCF culture is gaining its ground rapidly nowadays typically in the case of developed economies. According to Modern Fatherhood Project (2016), the proportion of DCF was raising steadily 26.4% in 2001 to 30.8% in 2013 across 17 European

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Table 3 Table showing gender-wise distribution of time spent for household work from 1990 to 2010 Years Male

1990 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 3.7

3.7

3.7

5.8

7.6

9.2

Female 50.4

49.1

47.4

45.9

43.7

42.7

11

12

14.4

15.3

16.9

19.3

42.4

39.1

32.5

30.4

30.9

29.1

Source Our world in data

countries (as cited in Barrett 2018). The statistics of U.S. is also similar, in the year 2017; among married couples, 48.3% have adopted DCF culture (Bureau of Labor Statistics 2018), whereas in Canada two third of the married couples have adopted DCF culture (Wittenberg-Cox 2018). Even in the case of conservative economies like Japan where there is very high level of power difference, the rate of DCF is on raise, which is an indication of the structural refinement happening in family culture across the globe. One of the major catalysts for the growth of DCF culture is the tendency of assortative mating; that is, the people with similar educational qualification and work status marry each other. According to Prof. Petriglieri, a human resource management expert the trend of assortative mating has increased nearly by 25% in the past few decades (as cited in Barrett 2018). The culture of assortative mating is the replication of widespread acceptance of egalitarianism in the society. Among dual carrier couples, particularly in the case of assertive couples the success of the DCF depends upon the magnitude of integration of mutual support and vicarious ambition. The optimum equilibrium can only be attained through the equitable apportionment of the family responsibilities between the couples. Adopting a ‘you versus me’ can only enhance the level of friction in between. Table 3 illustrates the time spent by men as well as women over the age of 25 for household work on a weekly basis during the past century from 1990 to 2015. As shown Table 3, over the past century, the men’s participation in household work increased steadily, whereas the women participation in household work declined steeply. As per the statistics illustrated in the table, men spend around 3.7 h per week for household chaos, whereas women spend around 50.4 h per week for household chaos during 1990. The time apportionment statistics between gender turned around during the twenty-first century. As per Table 3, in 2010 the apportionment of household work between men and women was compactable in nature; men spend around 19.3 h on a weekly basis, whereas women spend around 19.3 h on a weekly basis. Table 3 further illustrates that the decline in women’s homework participation was steeper after 1950s. It is because during the 1950s and 1960s, the concept of egalitarianism, multiculturalism, pluralism, and women empowerment started to evolve, which in turn pave way for development of work-life (family) balance concept during 1970s. Figure 3 is the graphical illustration of house work arrangement among men and women during the past century from 1990 to 2010.

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60

Fig. 3 Weekly house work arrangement among men and women during the past century Hours of Work

50 40 30 20 10

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Years

Men

Women

11 Work-Life Balance and the Legal Environment Regulatory framework is very essential for the successful implementation of any policy. Laws and policies are very essential part of shaping balance between work and personal life (Lingard et al. 2009). Some countries, particularly the Nordic nations, have taken considerable effort to structure the work environment employee friendly. Flexible working hours, paid maternity leave, child care facilities, paid parental leave, career break, part-time work arrangements, and equal pay were the most commonly identified ‘WLB’ policies. Industrialised nations which operate upon the sociodemocratic (Denmark, Norway, Sweden, etc.,) doctrine have successfully framed laws with regard to WLB, whereas the nations which operate upon the doctrine of classical liberalism (U.S., Italy, Japan, etc.,) yet have a fabian approach towards legalisation of full-fledged WLB policy. The magnitude of post-industrial enlightenment and the extend egalitarianism prevailing in the nation were often identified as the catalyst agent that drive the government in framing WLB policy (Eurofound 2015; Holter 2007). WLB policy is a set of laws with regard to employment, intended to assist the employees to achieve a sustainable quality of work life (OECD 2016). The legal framework of WLB often reflects the socio-cultural attitude of the society. In UK, working time and work-home arrangements have traditionally been identified as individual responsibility, and therefore, work-home balancing is a private responsibility rather than a ‘public’ matter upon which either the employer or government to address with (Lingard et al. 2009). Because of this cultural deadlock, UK was very passive towards the implementation of WLB policies and most of the so-called worklife balance policies were implemented as a member of European Union (Eurofound 2015).

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Because of the widespread recognition inevitability of the WLB and consequence of the work-life imbalance to employees, international organisations such as European Union, European Trade Union Federation, and International Labour Organisation (ILO) have issued various directive principles with regard to WLB. Some of the important WLB directives proposed by ILO were: forty-hour week, prohibition of discrimination on employment, part-time work arrangement, caregiving arrangements, paid maternity leave, equal remuneration, social security, equality of treatment at organisation with regard to promotion and upgradation, occupational health service, etc. However, because of the directive nature of the policy the member nations were not binding with regard to the policy implementation, though many governments are opened up with regard to the implementation of WLB policies to enhance the WLB level of the employees. Major hindrance faced by the regulators with regard to the implementation of the WLB policy is the dynamic as well as individualistic nature of the concept. Because of its strong blend with socio-cultural environment and personal-family underpinning, resulting the policy multi-layered and complex. From the organisational point of view, one of the major deterrents in the development and implementation of WLB policy is the multi-faced structure of the WLB concept, that is the interlink of the WLB concept with other factors outside the work environment such as child care, gender equality, economic development, stage of industrialisation, and socio-cultural attitudes. Hence, the integration of multi-faced structure remains as a challenge for organisations and governments in an effective WLB policy. In industry 3.0, the human takes the role of controller. That is, the work is executed through machines and equipments and the human intervention is only needed when there is a change in the level of activity.

12 Industry 4.0 and Work-Life Balance—The Road Ahead The essential characteristics of industry 4.0 are that the work environment becomes cyber-physical and work can be scheduled, monitored, and executed anywhere around the globe with the help of Integrated Telecommunication Services (ITS). The Work From Home (WFH) successfully employed by the service industry during the period of COVID-19 pandemic is one of the best example for the use of ITS at work. Similarly, in the case of manufacturing sector work can be executed from a remote location with the help of robotics controlled and directed over ITS. When it comes to industry 4.0, the role of human at factory has changed from the controller to facilitator. If the twentieth century WLB is about the industry 3.0, gender equality, feminisation of the labour force, and the refinement of the power distance, the twentyfirst century WLB is about the practice of principles of radical enlightenment in the corporate philanthropy and industry 4.0. It is not just about the gender equality, rather it is about equality of ethnic minorities, disabled, and older people in front of the economy and employment with the help of ITS implementation factories. That is, the work environment needs to be redefined with the incorporation of cyber-physical

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systems at factory. The introduction of cyber-physical systems at factory not only facilitates the remote access over the manufacturing activities but also provides a way to accommodate the ‘social minorities such as moms, disabled and old aged’ into the environment of work. Even after the implementation of the equal pay legislation and WLB across the world in the case of developed nations, women still earn only 82% of male wage, and the highest percent of women workers 48% have dependent children; furthermore, 55% of the women with children under five are at work, and because of the premium tagged nursery provisions, they make the part-time work which was the only viable option for young mom (Kelly 2006). That is, in the twentieth century the Europe and North American have achieved the status of WLB formally in terms of labour legislations, but still the work environment remains imbalanced. The situation of developing and underdeveloped nations with regard to gender equality and work provisions is even worse and questions the quality and effectiveness of employed WLB policies. The middle-class people of the developing and underdeveloped nations in the Asia and in the Africa is facing a kind of sexual hypocrisy during the Victorian era. When the family were segregated because of expatriate work culture, family cohesion has dismantled, and while defining the WLB policies, the need of expatriate needs to be inculcated. The piety of an expatriate towards his family cannot be exploited. Studies suggest that due to unique stressors, workers from the marginalised group specifically the disabled people have a more difficult time and lower expectations when it comes to attaining and sustaining a sense of balance than that of other workers (WLB & D 2018). The WLB has rarely focused on the need of achievement and WLB of disabled people (WLB & D 2018). Balancing work, life, and disability is even more sensitive than balancing work and life. Finding balance between work and life is not easy, and having a disability can make it even more challenging (Ability Magazine 2018). The WLB of the disabled is a subject which is often ignored by the academicians and the researchers due to the lack of social sense of ‘equality’. Therefore, it is very essential to consider the WLB need of ‘marginal’. The WLB policies such as flexitime, leisure and rest, compressed week, remote working, and part-time work can enormously enhance the capability of disabled at work. The industry 4.0 has levelled the ground of work environment across the gender dimensions and minorities. The industry 4.0 opened up an opportunity to the employee to integrate the work into the personal life of the employee with minimal interference to his personal life.

13 Concluding Remarks This chapter examines the socio-cultural underpinnings of the WLB concept along with the various stages of industrial revolutions. The meaning and content of WLB emerged and evolved in congruence paradigm shift in the work environment as a consequence of industrialisation. During the post-industrial era, the concept of egalitarianism, multiculturism, and women empowerment becomes very popular across

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the developed societies. Even the developing nations such as India, Brazil, and South Africa have initiated WLB policies upholding the doctrine of egalitarianism and multiculturism. The evolvement of the transformative paradigm helps in identifying and mitigating the disparities of imbalance in the work and personal life. In the past 50 years, there is a steady growth with regard to women work participation rate. Similarly, power distance, women’s home responsibility, and hours of work show a declining trend since 1950, all indicating the advancement in WLB and empowerment of the employee. The WLB policies often failed to inculcate the needs of marginalised especially the needs of disabled people, old aged generation, and the ethnic minorities. The undue focus of WLB research upon ‘women’ overlooked the balancing need of disabled, old aged, and ethnic minorities. Furthermore, the WLB provisions are not yet recognised as a necessity, rather it is still identified as a luxury for the employee mostly in developing and underdeveloped economies. The cybernetics and virtual office have proved that it is possible to celebrate work at the convince of the employee. The successful implementation of the WLB policy is only possible, if the socio-cultural environment of the policy regime extends the benefits of industry 4.0 and meagre it with the values of multiculturism, egalitarianism, and pluralism in such a way to embrace the marginal sections of the workforce who were excluded because of their physical inability and presence at factory.

References Abele AE, Volmer J (2011) Dual-career couples: specific challenges for work-life integration. In: Kaiser S, Ringlstetter MJ, Eikhof DR, Cunha MP (eds) Creating balance? Springer, Heidelberg, pp 173–192 Ability Magazine (2018) Managing work, life, and disability. Retrieved from Ability Magazine: https://abilitymagazine.com/Balancing-disability.html Andysz A, Najder A, Merecz-Kot D (2014) Organizational and individual determinants of using initiatives conducive to successful work-life balance. MED-PR 119–129 Barrett H (2018) Employers baffled by dual-career couples with joint ambitions. Financial Times Bhardwaj R (2017) Beyond flexibility: How to make workplaces women friendly. Retrieved from People Matters: https://www.peoplematters.in/blog/diversity/beyond-flexibility-how-to-makeworkplaces-women-friendly-15434?utm_source=peoplematters&utm_medium=interstitial& utm_campaign=learnings-of-the-day Booth AL, Frank J (2005) Glender and work-life flexibility in the labour market. In: Houston DM (ed) Work-life balance in the 21st century. Palgrave Macmillan, New York, pp 11–28 Brough P, Timmsb C, O’Driscollc MP, Kalliathd T, Siue OL, Sitf C, Log D (2014) Work–life balance: a longitudinal evaluation of a new measure across Australia and New Zealand workers. Int J Human Resour Manag 25(19):2724–2744. https://doi.org/10.1080/09585192.2014.899262 Bureau of Labor Statistics (2018) Employment characteristics of families summary. Bureau of Labor Statistics Carey D, Festa L (2009) Postcolonial enlightenment. Oxford University Press Inc., New York Carey D, Trakulhun S (2009) Universalism, diversity, and the postcolonial enlightenment. In: Carey D, Festa L (eds) Postcolonial enlightenment. Oxford University Press, Oxford, pp 243–277 Carlson DS, Grzywacz JG, Zivnuska S (2009) Is work–family balance more than conflict and enrichment? Nat Inst Health 62(10):1–20. https://doi.org/10.1177/0018726709336500

Work-Life Balance and Its Socio-cultural Inclination from Industry 1.0 …

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Casper WJ, Vaziri H, Wayne JH, DeHauw S, Greenhaus J (2017) The jingle-jangle of work-nonwork balance: a comprehensive and meta-analytic review of its meaning and measurement. J Appl Psychol. https://doi.org/10.1037/apl0000259 Dale A (2005) Combining family and employment: evidence from Pakistani and Bangladeshi women. In: Houston DM (ed) Work-life balance in the 21st century. Palgrave Macmillan, New York, pp 230–245 ERIH (2018) The Industrial Revolution in Europe. Retrieved from Europian Route of Industrial Heritage: https://www.erih.net/how-it-started/the-industrial-revolution-in-europe/ Eurofound (2015) Policies to improve work–life balance. Retrieved from Eurofound: https://www. eurofound.europa.eu/publications/report/2015/eu-member-states/policies-to-improve-worklife-balance Eurofound (2017) Working time and work-life balance. Retrieved from Eurofound: https://www.eur ofound.europa.eu/observatories/eurwork/about-eurwork/working-time-and-work-life-balance Fisher-McAuley G, Stanton JM, Jolton JA, Gavin J (2003) Modeling the relationship between work/life balance and organizational outcomes, pp 1–30. Retrieved August 8, 2016, from https:// www.researchgate.net/publication/260516221 Francis V, Fulu E, Lingard H (2009) Is it a problem? In: Lingard H, Francis V (eds) Managing work-life balance in construction. Spon Press, Oxon, pp 1–38 Gambles R, Lewis S, Rapoport R (2006) The Myth of work–life balance. John Wiley & Sons Ltd., West Sussex Greenberg CL, Avigdor BS (2009) What happy working mothers know: How new findings in positive psychology can lead to a healthy and happy work/life balance. John Wiley & Sons Greenhaus JH, Powell GN (2006) When the work and family are allies: a theory of work-family enrichment. Acad Manag Rev 31(1):72–92 Gröpel P, Kuhl J (2011) Work–life balance and subjective well-being: the mediating role of need fulfilment. British J Psychol 365–375. https://doi.org/10.1348/000712608X337797 Guest DE (2002) Perspectives on the study of work-life balance. Soc Sci Inf 42(2):255–279. https:// doi.org/10.1177/0539018402041002005 Hayman J (2005) Psychometric assessment of an instrument designed to measure work life balance. Res Pract Hum Resour Manag 13(1):85–91 History (2017) Industrial revolution. Retrieved from History.com: https://www.history.com/topics/ industrial-revolution Holter ØG (2007) Men’s work and family reconciliation in Europe. Men and Masculinities 425–456 Houston DM (2005) Work-life balance in the 21st century. In: Houston DM (eds) Work-life balance in the 21st century. Palgrave Macmillan, pp 1–10 Israel J (2010) A revolution of the mind. Princeton University Press, Woodstock Jain M (2017) 4 main stages of industrial revolution. Retrieved from Your Article Library: http:// www.yourarticlelibrary.com/industrial-engineering-2/4-main-stages-of-industrial-revolution/ 90115 Joseph J, Sebastian DJ (2017) Work-life balance a conceptual review. Mirror Kelly J (2006) Women thirty-five years on: still unequal after all this time. In: Cole M (ed) Education, equality and human rights. Routledge, Oxfordshire, pp 7–21 Kumari S (2013) Work-life balance and its impact on performance of women executives in IT companies. PhD Thesis, Himachal Pradesh University, Shimla Lewis S, Gambles R, Rapoport R (2007) The constraints of a ‘work–life balance’ approach: an international perspective. Int J Human Resour 360–373 Lingard H, Francis V, Turner M (2009) Social policy and legal frameworks. In: Lingard H, Francis V (eds) Managing work-life balance in construction. Spon Press, Oxon, pp 38–76 Lutz K, Boehnke M, Huinink J, Tophoven S (2013) Female employment, reconciliation policies and childbearing intentions in East and West Germany. In: Oláh LS, Fratczak E (eds) Childbearing, women’s employment and work—life balance policies in contemporary Europe. Palgrave Macmillan, New York, pp 97–134

304

J. Joseph

Malaviya V (2012) Determinants of work life imbalance among faculty members of higher educational institutes in Delhi. Bhagwant University Ajmer, Department of Management, Ajmer Mehtha MR (2012) A study of work life balance (WLB) among women employees in the service sector with special reference to Pune City. PhD Thesis, Tilak Maharashtra Vidyapeeth, Pune Morganson VJ, Litano ML, O’Neill SK (2014) Promoting work-family balance through positive psychology: a practical review of the literature. Psychol Manag J 17(4):221–244. https://doi.org/ 10.1037/mgr0000023 OECD (2014) Germany: OECD OCED (2015) How’s life in New Zealand. OCED OECD (2016) France: OECD Publishing OECD (2018) Labour market statistics. OECD, Paris Oláh LS, Fahlén S (2013) Introduction: aspirations and uncertainties. Childbearing choices and work–life realities in Europe. In Oláh LS, Fratczak E (eds) Childbearing, women’s employment and work–life balance policies in contemporary Europe. Palgrave Macmillan, London, pp 1–27 Osborne T (1998) Aspects of enlightenment. UCL Press, London Prabhu N (2017) Labour participation rate of women in India visibly low, says World Bank study. The Hindu Rapoport R, Rapoport RN (1969) The dual career family. Human Relations 22(1) 3–30. https://doi. org/10.1177/001872676902200101 Sharman J (2017) Four phases of industrial revolution: phase one. Retrieved from Thenbs: https:// www.thenbs.com/knowledge/four-phases-of-industrial-revolution-phase-one Shree RM (2013) A study on worklife balance and life satisfaction of critical care nurses at Coimbatore district. Bharathiar University, Coimbatore Sonnenschein C, Lee D, Nguyen J, Soto AM (2013) Unanticipated trends stemming from initial events in the history of cell culture: vitalism in 2013? In: Normandin S, Wolfe CT (eds) Vitalism and the scientific image in post-enlightenment life science, 1800–2010. Springer, New York, pp 291–311 Staines GL, O’Connor P (1980) Conflicts among work, leisure, and family roles. Monthly Labor Rev 103(8):35–39. Retrieved from http://www.jstor.org/stable/41841305 Suresh S, Kodikal R (2017) SEM approach to explore work life balance: a study among nurses of multispecialty hospitals. Sahyadri J Manage 1–16 Szener JB, Grzankowski KS, Eng KH, Odunsi K, Frederick PJ (2016) Evaluation of satisfaction with work-life balance among U.S gynecologic oncology fellows: a cross-sectional study. Gynecol Oncol Rep 17–20. Retrieved from https://doi.org/10.1016/j.gore.2016.03.001 Tambe S (2017) Work-life balance and gender bias: a contrarian view. Int J Bus Manage 14–16 UK Essays (2013) The concept of work life balance. Retrieved from UKESSAYS: https://www.uke ssays.com/essays/social-work/the-concept-of-work-life-balance-social-work-essay.php Valcour M (2007) Work-based resources as moderators of the relationship between work hours and satisfaction with work-family balance. J Appl Psychol 92(6):1512–1523. https://doi.org/10.1037/ 0021-9010.92.6.1512 Voydanoff P (2005) Toward a conceptualization of perceived work-family fit and balance: a demands and resources approach. J Marriage Family 822–836 Weinstein SM (2009) Workplace balance. In: Weinstein SM (ed) B is for balance: a nurse’s guide for enjoying life at work and at home. Renee Wilmeth, pp 67–80 Wiesea BS, Seigera CP, Schmidb CM, Freund AM (2010) Beyond conflict: functional facets of the work—family interplay. J Vocat Behav 104–117 Wittenberg-Cox A (2018) Being a two-career couple requires a long-term plan. Retrieved from Harvard Business Review: https://hbr.org/2018/02/being-a-two-career-couple-requires-a-longterm-plan WLB & D (2018) Living with a disability. Retrieved from Work-Life Balance and Disability: http:// work-life-disability.org/#wlbd Woodburn J (1982) Egalitarian societies. Man 17(3):431–451. Retrieved from http://www.jstor.org

The Impact of Emotional Contagion on Managerial Efficiency: IIOT as a Moderator Tilottama Singh, Rajesh Upadhyay, and Abdullah Akhtar

1 Introduction There has been a considerable development in the area of IT with the incrementing pace of IT development globally. The Indian industries are also matching the pace of this development in the arena of Industry 4.0 which bases itself on industrial Internet of things (IIOT) which is an effective system of enhancing the effective utilization of cyber system, smart devices and IT with the objective of making intelligent decisions (Aggarwal et al. 2019). With the change of economies to circular economy aiming to base itself on sustainability and reuse of existing resources, it has created a path toward IIOT, cloud computing and more of human–machine interaction for effective working (Chang et al. 2010). The cognitive theory is the essential idea affecting character and feelings of individuals across the globe. The concept called emotional contagion or the extent of copying and experiencing the emotional identities and involvements of others in social organizations is much more than just being influenced by the inner influence of the people who participate in these interactions. An audit paper Hatfield co-composed in 2014 explained that numerous investigations had demonstrated that individuals every now and again get each other’s feelings. Extraordinary negative feelings that are communicated are more infectious. During this time of pandemic when individuals were accustomed to various ways of life and work routine because of lockdown, it is difficult to protect yourself from emotional contagion. A large portion of the people T. Singh (B) Associate Professor, Uttaranchal Institute of Management, Uttaranchal University, Dehradun, India e-mail: [email protected]; [email protected] R. Upadhyay Graphic Era University, Dehradun, Uttarakhand, India A. Akhtar Mazoon University, Muscat, Oman © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 G. Singh et al. (eds.), Industry 4.0 and the Digital Transformation of International Business, https://doi.org/10.1007/978-981-19-7880-7_18

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do not know about emotional contagion and how it has an important influence on their day to day routine. The post-COVID-19 world will see increasing value fluctuation, virtualization, and internationalization of capital (Sułkowski 2020). Emotional disorders have been defined as a process that is often determined, which involves the automatic processing of mixed emotions and the handing out of information that is more conscious of others’ emotions and behaviors. So far, most research has focused on the first aspect of mood disorders, mentioned to as automatic imitation: Unknowingly, we tend to imitate and align our non-verbal and non-verbal expressions of other people (Zuckerman et al., 1981). So, we smile, get dressed, walk, cry, sit, or stand in the same way as others, without ever realizing how we act. The physical response from this imitation will change our subjective feelings accordingly. In other words, we are not just smiling, or giggling, but our smile or fondness makes us feel happy with these unkind shows. Various studies have provided support for automated simulation. For example, people show more happy and sad faces by responding to movie characters or just pictures showing similar expressions; they begin to smile or laugh when they see others drinking or laughing; people even imitate others by tapping their feet, swallowing, or showing pain. It is not clear, however, how people feel about similar situations as a consequence of this imitation. Facial mimicry, which is the propensity to imitate other’s facial expressions, is described as reflex mechanism which leads to certain behavior (Bourgeious and Hess 2008). Figure 1 model framework suggesting the transmission of emotional contagion from one person to a large group. Further to this additional default behavior, individuals may attempt to showcase or identify with another person on a more perceptive level, leading to similar feelings and emotions. Understanding how emotional contagion leads to increase in your awareness of the negative version of it—and is a way to prevent in its own right, as research on the benefits of recognizing unconscious process has shown. Similar studies like Morris and Feldman (1997) have examined the role of social factors on emotional contagion which plays a significant role on effecting the EC levels. There are numerous factors that can facilitate the transmission of emotions. The first thing concerns the behavior of human relations, that is, empathy (Neuman and Strack, 2000). Intimate relationships are more noticeable by emotional displacement than relationships between professionals or between strangers. Indeed, it has been revealed that college roommates who stay with them emotionally for more than a year. This effect of mood disorders has been active in positive and negative emotions in events and cannot be explained by increasing the similarities of personality differences (Wang et al., 2020). In addition, the amount of empathy one can feel for another person also reflects each difference: Some people are simply more empathetic than others. In the end, empathy can come from even less relationships. Here, empathy may depend on whether or not a person shares goal. For example, the prospect of collaborating with another person leads to more empathy. Emotions may be a stronger predictor of success than IQ, within the midst of the present crisis which may so easily trigger a tension in human mind, the emotion we are spreading is a matter of concern and these emotions are by default effected through technology and its effective usage (Oliver et al., 2020). That is why we must

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Fig. 1 Source Based on the emotional contagion scale, a model for emotional contagion has been developed. João Bispo Ana Paiva UTL/IST Av. Rovisco Pais, 1, 1049–001 Lisboa

be even more conscientious about managing our own emotions—particularly with regard to others who have the ability to catch them (Wrobel and Imbir, 2019). Due to the influence of various research on emotions, marketing, and consumer behavior, the topic of emotions and information technology in the workplace has received more attention in human resource literature (Lin and Liang 2011). An investigation on how people react to emotional exchanges in the workplace by Rafaeli and Sutton (1989) sheds light on wider contextual aspects that influence interpersonal interactions. Recent developments in psychological and organizational literature have given light on emotional language, emotional labor (Scott and Barnes 2011; Liu et al. 2011), and emotional competence. The EC research shows it is more effective at influencing

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senior management than operational people. Marketing and customer transaction activities in firms rely heavily on effective customer service and empathy. As a result, research in this field has focused on emotional contagion. Employee affect is a key component in detecting the source of emotional contagion in on-the-job service transactions. The customer’s attributions of service quality and impressions of the organization are influenced by employee emotion, according to (Heskett 2002). Similar study by Hennig et al. (2012) inspects the impact of display of optimistic emotions by the service providers on customer retainment. Emotions are crucial part of everyday life. Psychologists illustrates that the process of emotions are completed with emotional contagion. No organization can ignore the impact of emotional contagion on their work styles, productivity and daily operations; therefore, the importance of this concept has been gaining tremendous visibility after the studies on emotional quotients (Omdahal and Donnel, 1999). A lot of companies might not pay much importance to how their employees may be feeling but emotions are the basis of building a strong organization culture. This deals in reshaping the cognitive culture which is demonstrated through values, ethics, organization environment and interactions among employees within and outside the organization (Larsen et al., 1992). The culture affects the emotional quotient which further impacts the emotional contagion of professionals (Burns et al., 2017). Seeing the economic perspective, the IIOT facilities enhances the connectivity of business, reduce costs, and creates better quality of service and goods (Oesterreich and Teuteberg 2016) and altogether these leads to increased customer satisfaction (Stock and Seliger 2016). However, like any other technological implementation, even efficacious implementation of IIOT requires certain preconditions generation like foremost requirement of huge capital, good mental health, and positivity (Laudien and Daxbock 2016) The study carried during the time of pandemic COVID which brought plethora of emotions among masses. Though a lot of research has been conducted in the field of industry 4.0 and emotion independently, a substantial gap exists in examining this field together where the real utilization of technology and modern tool rest on the emotional and psychological level of employees which make them collaborate with IIOT for managing efficiently. The diaphragm of the study is of professionals working in finance domain as the epidemic has brought current and future economic transition in global economy and during this lockdown the companies are aiming for survival over and above the goals of maximizing profits in such digitalized world. The study undertook Delphi method and survey in which financial experts were interviewed. By conducting a video conferencing with finance professionals and finance experts, various themes have come up after analyzing the transcripts through grounded theory themes like lack of emotional culture, insensitivity, emotion intolerance, job security issues, and disturbing work life balance during pandemic were emerged. Drawing conclusion from the above the present study addresses certain key issues. Firstly, it aims to examine the emotional contagion with reference to efficiency of finance professionals. Secondly, it examines the moderating effect of IIOT over the two variables. After examining the current literature and formulating the research problem based on the gaps observed, the paper highlights the essentials for studying and examining the

The Impact of Emotional Contagion on Managerial Efficiency: IIOT … Fig. 2 Emotional contagion model with efficiency and IIOT acting as mediator

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EC levels for incrementing efficiency of the tech employees. The study is divided into the introductory part, followed by literature. Further it brings forward the procedure of the research followed by the outcome and discussions (Fig. 2).

2 Objectives 1. To identify the factors effecting EC levels of finance professionals 2. To measure the impact of EC on efficiency of finance employees 3. To study the moderating effect of IIOT in the relationship between EC and efficiency.

3 Hypothesis Formulation Hypothesis 1 Positive emotional contagion will be positively related to efficiency at workplace. Hypothesis 2 The use of IIOT will moderate the relationship between emotional contagion and efficiency at workplace. Further based on the respondents, the study also takes gender as one of the demographic variables and studies the comparative EC level between male and females. Hence formulating the third hypothesis. Hypothesis 3 Gender has no role on effecting the EC levels of finance professionals.

4 Research Methodology The study involved conducting the research probing the impact of positive emotional contagion (EC) on efficiency at workplace and moderating effects IIOT on the relationship between EC and effeciency. IT industry was selected for the study where professionals in finance domain were chosen, who had been working past more than a year on virtual teams. They communicated through various e platforms on mails, telephone, voice mails and instant messaging, reporting the CEO. The measures

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adopted for the study are the PANAS scale and EC Scale. The “Positive and Negative Affect Schedule” (PANAS) scale and the “emotional contagion” (EC) scale (Watson et al. 1988). Prior to the gathering of data by survey method, interviews and discussion with financial experts through video conferencing have provided proof check to questionnaire and added to the analysis.

5 Factors Affecting Emotional Contagion The change to overcome the threats of varying commercial in techno economy is inexplicable and all the corporate houses aimed at surviving the phase in year 2020 where the query of profit and losses is vague. The world stands united to fight against the pandemic and India came out with various plans at different phases. Numerous variables can lead to how people understand and respond to emotional contagion and its impact. Coenen and Broekens (2012) classified these components into three broad categories: distinctiveness, interpersonal gaps, and other variables. Gender and work both have a significant impact on emotional contagion. A lot of studies have tried worked on enumerating the factors responsible for effecting emotional contagion levels; however, quite a few have worked on the interrelation between these factors with reference to varied dimensions. Another relevant study examining the factors was done by Hancock et al. (2008) to watch emotions in estimator mediated communication. Psychological studies examining the mood contagion and emotions have been conducted (Kupers and Weibler 2008). Organizations have relatively given the importance to emotions in organizations, thereby emphasizing on varied employee engagement activities promoting employee engagement and affiliation in the organization. The initiation on emotional studies in organization is gaining more relevance with changing challenging times where the examination of emotional levels shows effect on employee productivity, belongingness, and team behavior in organization as emotions tend to be contagious in organization (Ashkanasy 2002). Based on an extended literature study and reviewed papers in the field of emotional contagion the following factors have been explored, as depicted in the Fig. 3. The concept of emotions is subjective and rests on varied domains like psychological, intellect, role, behavior and perception of oneself. Understanding the extension of emotions touching lives of individual both personally and professionally, the neglection of this phenomenon can be dangerous for the growth of employees and organizations. The increasing interest in emotions has paved the opportunities for wider discussion on this aspect in organizations (Lindebaum et al. 2017). Figure 4 illustrates how the contagion level can shape up for the working professionals if not monitored on times with preventive techniques. Thus, the emotional climate pervades all human interaction and carries contagion aspect. It mainly has an influence on organization climate and can have significant effect on innovation and success of or ganizations (Cox and Bachkirova 2020).

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Fig. 3 Factors effecting emotional contagion Personal Differences comprising of attitude amongst individuals working in teams

Individual Stimulus comprising of emotions and temperament

Structural Factors dealing with type of work, work dynamics, environmental factors

Fig. 4 Model framework depicting the responce pattern to Disaster. Source (When disaster strikes, Beverly Raphael, 1986)

6 Result and Analysis The sample included financial analyst working in Delhi NCR with MNC’s. Total questionnaire circulated were 200 out of which 148 were received. After eliminating the incomplete questionnaire, the sample consisted of 50 males and 98 females. The EC rating and PANAS values were established after collecting all assessments. The EC Scale has a maximum potential score of sixty and a minimum possible value of fifteen. The mean score for this examination was 40.10 (SD = 5.90), ranging from 60 to 24. The maximum possible score is 50, while the minimum possible score is ten. The mean PA rating was 29.64 (SD = 6.86), ranging from 44 to 9, whereas the mean NA rating was 13.58 (SD = 4.29), ranging from 28 to 10. The link between emotional contagion and efficiency was examined using Pearson bivariate collaboration. This investigation revealed a strong connection between EC (M = 40.11, SD = 4.92) and proficiency scores (M = 46.22, SD = 7.72), r = 0.23, p

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= 0.008. Similarly, connections were found between temperament scores and PA manifestations, as well as between mind-set scores and NA side effects. Positive associations of r = 0.23, p = 0.010 were observed between mind-set problems (M = 42.11, SD = 5.92) and PA scores (M = 32.64, SD = 7.86). A non-significant positive association (r = 0.10, p = 0.149) was observed between disposition problems (M = 42.11, SD = 4.92) and NA scores (M = 13.58, SD = 4.29). These data suggest that the degree of positive EC has a substantial influence on the efficiency of these enzymes. The link between sex, a predisposition for passionate behavior, and enthusiastic compassion was examined using a free sample test. A free t-test assessment of tests comparing males and females’ propensity for eager aggravation indicated that females’ proclivity for enthusiastic aggravation was considerably larger than males’ proclivity for bipolar disorder (M = 37.49, SD = 4.30), t(93) = 3.79, p.001. A ttest, examination of the instances investigating enthusiastic immersion in males and females indicated that females’ passionate immersion (M = 47.16, SD = 9.61) was not significantly larger than males’ passionate articulation (M = 48.18, SD = 9.66), t(95) = −0.01, p = 0.497. Females appear to be more vulnerable to delicate contaminations than men. The picture below depicts the regression research that was done to investigate the mediating effects of IIOT on the relationship between emotional contagion and managerial efficiency. As the beta weight demonstrates, there is a connection between EC and efficiency. When EC was isolated, it had a beta weight of −0.25. The beta weight decreased to −0.07 when IIOT was introduced.

IIOT .26

.63

Efficiency

Emotional Contagion .25(.07)

7 Discussion The results are in consistent with the expectations, as the findings showed that IIOT techniques mediate the relationship between emotional contagion and efficiency levels. The mediation which is use of information technology, indicates as more IIOT techniques are adopted by professionals and better they are equipped with their usage better is the EC level and better the efficiency. Enormous studies have been conducted in EC and efficiency levels of individuals but rare have examined the mediating effects of IIOT.

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Few limitations are there in the work. The sample size could have been more. Also, having finance professionals working in Delhi NCR can be a limitation as the study could have covered other metro cities as well bringing a broader picture. The study is a base which can be applied in other situation and sectors in broader perspective.

8 Future Research The research gives as a basis for future research to be conducted in numerous organizations as emotional contagion is advancing momentum. The study is an effort to examine the emotional contagion relation with efficiency, where IIOT acting as a mediator, taking the sample of finance professionals. The results can serve as a base to conduct like studies in other industry or different context. The aware ness and acceptance of EC with technology by individuals and organizations would serve as an important aspect helping management to stimulate activities and group dynamics building effective teams in organizations. It is imperative to understand others emotion to control the flow of emotions (Kupers 2013). Declaration of Potential Conflicts of Interest The researchers disclosed that they had no possible conflicts of interest with the investigation, authorship, or publishing of this article. Funding The authors got no financial assistance for conducting the study, writing the article, or publishing it.

References Aggarwal A, Mittal R, Gupta S, Mittal A (2019) Internet of things driven perceived value cocreation in smart cities of the future: a PLS-SEM based predictive model. J Comput Theor Nanosci 16(9):4053–4058 Ashkanasy NM (2002) Studies of cognition and emotion in organisations: attribution, affective events, emotional intelligence and perception of emotion. Aust J Manage 27(1_suppl):11–20 Bourgeois P, Hess U (2008) The impact of social context on mimicry. Biol Psychol 77:343–352 Burns MD, Monteithl PJ, Parker LR (2017) Training away bias: the differential effects of counter stereotype training and self-regulation on stereotype activation and application. J Exp Soc Psychol73:97–110 Chang C, Tran VH, Wang J, Fuh YK, Lin L (2010) Direct-write piezoelectric polymeric nanogenerator with high energy conversion efficiency. Nano Lett 10(2):726–731 Coenen R, Broekens J (2012) Modeling emotional contagion based on experimental evidence for moderating factors. In: Conitzer, Winikoff, Padgham, van der Heck (eds) Proceedings of the 11th international conference on autonomous agents and multiagent systems. International Foundation for Autonomous Agents and Multiagent Systems, Valencia, Spain

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T. Singh et al.

Cox E, Bachkirova T (2020) Coaching with emotion: how coaches deal with difficult emotional situations. Coaching Researched: A Coaching Psychology Reader, pp 167–181 Hancock JT, Gee K, Ciaccio K, Lin JMH (2008) I’m sad you’re sad: emotional contagion in CMC. In: Proceedings of the 2008 ACM conference on computer supported cooperative work, pp 295–298 Hennig-Thurau T, Marchand A, Hiller B (2012) The relationship between reviewer judgments and motion picture success: reanalysis and extension. J Cult Econ 36(3):249–283 Heskett JL (2002) Beyond customer loyalty. Managing Serv Qual Int J Kupers W, Weibler JR (2008) Emotions in organisation: an integral perspective. Int J Work Organ Emot 2(3):256–287 Küpers W (2013) A phenomenology of embodied senses: the ‘making’of sense in organisational culture. Int J Work Organ Emot 7, 5(4), 325–341 Larsen RJ, Kasimatis M, Frey K (1992) Facilitating the furrowed brow: an unobtrusive test of the facial feedback hypothesis applied to unpleasant affect. Cogn Emot 6:321–338. https://doi.org/ 10.1080/02699939208409689 Laudien SM, Daxböck B (2016) The influence of the industrial internet of things on business model design: a qualitative empirical analysis. Int J Innov Manag 20(08):1640014 Lin JSC, Liang HY (2011) The influence of service environments on customer emotion and service outcomes. Managing Serv Quality Int J Lindebaum D, Geddes D, Gabriel Y (2017) Moral emotions and ethics in organisations: introduction to the special issue. J Bus Ethics 141(4):645–656 Morris JA, Feldman DC (1997) Managing emotions in the workplace. J Manag Issues 257–274 Neumann R, Strack F (2000) “Mood contagion”: the automatic transfer of mood between persons. J Pers Soc Psychol 79:211–223 Oesterreich TD, Teuteberg F (2016) Understanding the implications of digitisation and automation in the context of Industry 4.0: a triangulation approach and elements of a research agenda for the construction industry. Comput Ind 83:121–139 Oliver A, McCarthy PJ, Burns L (2020) Using a “Think Aloud” protocol to understand metaattention in club-level golfers. Int J Sport Exerc Psychol 1–14 Omdahl BL, O’Donnell C (1999) Emotional contagion, empathic concern and communicative responsiveness as variables affecting nurses’ stress and occupational commitment. J Adv Nurs 29(6):1351–1359 QinW, Beck LH, Zeng C, Chen Z, Li S, Zuo K, Liu Z et al. (2011) Anti-phospholipase A2 receptor antibody in membranous nephropathy. J Am Soc Nephrol 22(6):1137–1143 Rafaeli A, Sutton RI (1989) The expression of emotion in organizational life. Res Organ Behav 11(1):1–42 Scott BA, Barnes CM (2011) A multilevel field investigation of emotional labor, affect, work withdrawal, and gender. Acad Manage J 54(1):116–136 Stock T, Seliger G (2016) Opportunities of sustainable manufacturing in industry 4.0. Procedia Cirp 40:536–541 Sułkowski Ł (2020) Covid-19 pandemic; recession, virtual revolution leading to de-globalization? J Intercultural Manage 12(1):1–11 Wang M, Cao R, Zhang L et al (2020) Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro. Cell Res 30(3):269e271 Watson D, Clark LA, Tellegen A (1988) Development and validation of brief measures of positive and negative affect: the PANAS scales. J Pers Soc Psychol 54:1063–1070 Wrobel M, Imbir KK (2019) Perspectives on psychological science broadening the perspective on emotional contagion and emotional mimicry: the correction hypothesis Young ZQ (2019) Reviewof the mechanism of emotional contagion. PPRS 4:263–274 Zuckerman M, Klorman R, Larrance DT, Speigel NH (1981) Facial, autonomic, and subjective components of emotion: the facial feedback hypothesis versus the externalizer–internalizer distinction. J Pers Soc Psychol 41:929–944