Fostering Sustainable Development in the Age of Technologies 1837530610, 9781837530618

Table of contents :
Table of Contents
List of Contributors
Foreword • Hokey Min
Preface
Acknowledgements
1 The Role of Digital Technology in Achieving Sustainable Development Goals (SDGs): A Systematic Literature Review, Bibliometric Analysis and Content Analysis • Arushi Bathla, Priyanka Aggarwal and Kumar Manaswi
2 Digital Technologies, Sustainable Development Goals and the Grand Societal Challenges in the Context of Slum Dwellers of Kolkata, India • Atiba Batul, Keya Das Ghosh and Swapnamoyee Priyabhasini Palit
3 Blockchain and Artificial Intelligence Technology in Professional Services • Chandan Kumar Jha and Amit Sachan
4 Confrontation Strategy for Evolution of Future Employment • Donghun Yoon
5 Framing the Digital Transformation Journey for Sustainability Based on the Lenses of Integrated Skills and Competencies for Future Work • Joseph Odhiambo Onyango
6 Role of Social Networking Technologies in Developing Public Services Supply Chain During COVID-19 • Kali Charan Sabat and Som Sekhar Bhattacharyya
7 Adopting Technology for Sustainable Development: Reflections on Innovative Ecosystem • Jasmandeep Kaur, Kirandeep Kaur and Ramanjeet Singh
8 Exploring the Relationship Between Digital Initiatives, Dynamic Capabilities and Market Performance: A Conceptual Framework • Lan Phuong Ho Dang
9 Reverse Logistics: Rebuilding Smart and Sustainable Transformation Based on Industry 4.0 • Leena Wanganoo and Rajesh Tripathi
10 Reflections on Sustainable Development, Sustainability and Business Practice: Lessons From Measurement, Scalability and Bias in Artificial Intelligence (AI) • Luisa F. Melo
11 Digital Healthcare and Patient Transformation: Review Research and Future Agenda • Nimesh P. Bhojak, Suresh N. Patel and Mohammadali K. Momin
12 A Comparative Framework Analysis of the Strategies, Challenges and Opportunities for Sustainable Smart Cities • Oluwagbemiga Paul Agboola and Meryem Muzeyyen Findikgil
13 Leveraging Blockchain Technology in Adopting Digital Tokenization of Green Bonds • Pulak Chugh
14 Digital Technologies and Education for Sustainable Development • Renji George Amballoor and Shankar B. Naik
15 Safety Management in the Era of Emerging Industrial Revolution: The Conceptualisation of Safety 4.0 • Shatrudhan Pandey, Kirtika Kiran, Shreyanshu Parhi, Abhishek Kumar Singh and Sanjay Kumar Jha
16 Spiritual Approach Among Techies: An Approach for Achieving Sustainable Development • Snehal G. Mhatre and Nikhil K. Mehta
17 The Evolution of Manufacturing: A Comprehensive Analysis of Industry 4.0 and Its Frameworks • Somayya Madakam, Rajeev Kumar Revulagadda, Vinaytosh Mishra and Kaustav Kundu
18 Application of Industry 4.0 Technologies in Climate-Smart Agricultural Practices • Soumya Sucharita Panda, Sudatta Banerjee and Swati Alok
19 The Digital Revolution – Implications of Digital Technologies on Women’s Workforce Participation • Tanaji Pavani Prabha, Swati Alok, Rishi Kumar and Swati Singh
20 Building Resilience Against Ongoing and Future Pandemics: Blockchain Technology to the Rescue • Taab Ahmad Samad and Yusra Qamar
21 Impact of Awareness on the Adoption of Electric Vehicles: A Systematic Literature Review • Divya Singh and Ujjwal Kanti Paul
Index

Citation preview

Fostering Sustainable Development in the Age of Technologies

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Fostering Sustainable Development in the Age of Technologies EDITED BY ROHIT SHARMA University of Wollongong in Dubai, UAE

ANJALI SHISHODIA University of Wollongong in Dubai, UAE

AND ASHISH GUPTA Indian Institute of Foreign Trade, India

United Kingdom – North America – Japan – India – Malaysia – China

Emerald Publishing Limited Emerald Publishing, Floor 5, Northspring, 21-23 Wellington Street, Leeds LS1 4DL First edition 2024 Editorial matter and selection © 2024 Rohit Sharma, Anjali Shishodia and Ashish Gupta. Individual chapters © 2024 The authors. Published under exclusive licence by Emerald Publishing Limited. Reprints and permissions service Contact: www.copyright.com No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center. Any opinions expressed in the chapters are those of the authors. Whilst Emerald makes every effort to ensure the quality and accuracy of its content, Emerald makes no representation implied or otherwise, as to the chapters’ suitability and application and disclaims any warranties, express or implied, to their use. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-83753-061-8 (Print) ISBN: 978-1-83753-060-1 (Online) ISBN: 978-1-83753-062-5 (Epub)

Table of Contents

List of Contributors

ix

Foreword

xi

Preface

xiii

Acknowledgements

xvii

Chapter 1 The Role of Digital Technology in Achieving Sustainable Development Goals (SDGs): A Systematic Literature Review, Bibliometric Analysis and Content Analysis Arushi Bathla, Priyanka Aggarwal and Kumar Manaswi Chapter 2 Digital Technologies, Sustainable Development Goals and the Grand Societal Challenges in the Context of Slum Dwellers of Kolkata, India Atiba Batul, Keya Das Ghosh and Swapnamoyee Priyabhasini Palit

1

23

Chapter 3 Blockchain and Artificial Intelligence Technology in Professional Services Chandan Kumar Jha and Amit Sachan

43

Chapter 4 Confrontation Strategy for Evolution of Future Employment Donghun Yoon

51

Chapter 5 Framing the Digital Transformation Journey for Sustainability Based on the Lenses of Integrated Skills and Competencies for Future Work Joseph Odhiambo Onyango

63

vi

Table of Contents

Chapter 6 Role of Social Networking Technologies in Developing Public Services Supply Chain During COVID-19 Kali Charan Sabat and Som Sekhar Bhattacharyya

79

Chapter 7 Adopting Technology for Sustainable Development: Reflections on Innovative Ecosystem Jasmandeep Kaur, Kirandeep Kaur and Ramanjeet Singh

93

Chapter 8 Exploring the Relationship Between Digital Initiatives, Dynamic Capabilities and Market Performance: A Conceptual Framework Lan Phuong Ho Dang Chapter 9 Reverse Logistics: Rebuilding Smart and Sustainable Transformation Based on Industry 4.0 Leena Wanganoo and Rajesh Tripathi

113

129

Chapter 10 Reflections on Sustainable Development, Sustainability and Business Practice: Lessons From Measurement, Scalability and Bias in Artificial Intelligence (AI) 145 Luisa F. Melo Chapter 11 Digital Healthcare and Patient Transformation: Review Research and Future Agenda 163 Nimesh P. Bhojak, Suresh N. Patel and Mohammadali K. Momin Chapter 12 A Comparative Framework Analysis of the Strategies, Challenges and Opportunities for Sustainable Smart Cities Oluwagbemiga Paul Agboola and Meryem Muzeyyen Findikgil

187

Chapter 13 Leveraging Blockchain Technology in Adopting Digital Tokenization of Green Bonds 213 Pulak Chugh Chapter 14 Digital Technologies and Education for Sustainable Development Renji George Amballoor and Shankar B. Naik

225

Table of Contents

Chapter 15 Safety Management in the Era of Emerging Industrial Revolution: The Conceptualisation of Safety 4.0 Shatrudhan Pandey, Kirtika Kiran, Shreyanshu Parhi, Abhishek Kumar Singh and Sanjay Kumar Jha Chapter 16 Spiritual Approach Among Techies: An Approach for Achieving Sustainable Development Snehal G. Mhatre and Nikhil K. Mehta

vii

239

257

Chapter 17 The Evolution of Manufacturing: A Comprehensive Analysis of Industry 4.0 and Its Frameworks 269 Somayya Madakam, Rajeev Kumar Revulagadda, Vinaytosh Mishra and Kaustav Kundu Chapter 18 Application of Industry 4.0 Technologies in Climate-Smart Agricultural Practices Soumya Sucharita Panda, Sudatta Banerjee and Swati Alok

289

Chapter 19 The Digital Revolution – Implications of Digital Technologies on Women’s Workforce Participation Tanaji Pavani Prabha, Swati Alok, Rishi Kumar and Swati Singh

303

Chapter 20 Building Resilience Against Ongoing and Future Pandemics: Blockchain Technology to the Rescue Taab Ahmad Samad and Yusra Qamar

319

Chapter 21 Impact of Awareness on the Adoption of Electric Vehicles: A Systematic Literature Review Divya Singh and Ujjwal Kanti Paul

331

Index

359

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List of Contributors

Priyanka Aggarwal Swati Alok Renji George Amballoor Sudatta Banerjee Arushi Bathla Atiba Batul Som Sekhar Bhattacharyya Nimesh P. Bhojak Pulak Chugh Keya Das Ghosh Lan Phuong Ho Dang Chandan Kumar Jha Sanjay Kumar Jha Jasmandeep Kaur Kirandeep Kaur Kirtika Kiran Rishi Kumar Kaustav Kundu Somayya Madakam Kumar Manaswi Nikhil K. Mehta Luisa F. Melo

Delhi Technological University, India Bits Pilani, India Directorate of Higher Education, India BITS Pilani, India Indian Institute of Foreign Trade, India Amity University, India Indian Institute of Management, Nagpur, India Hemchandracharya North Gujarat University, India National University of Study and Research in Law, India Amity University, India The University of Bedfordshire, UK Indian Institute of Management (IIM) Ranchi, India Birla Institute of Technology, India Ideal Institute of Management & Technology, India Chandigarh University, India Birla Institute of Technology, India Bits Pilani, India Indian Statistical Institute, India Atlas SkillTech University, India Delhi Technological University, India National Institute of Industrial Engineering, India Alvernia University, USA

x

List of Contributors

Snehal G. Mhatre

National Institute of Industrial Engineering, India Vinaytosh Mishra Gulf Medical University, United Arab Emirates Mohammadali K. Momin Veer Narmad South Gujarat University, India Meryem Muzeyyen Findikgil Istanbul Gelisim University, Turkey Shankar B. Naik Directorate of Higher Education, India Joseph Odhiambo Onyango Strathmore University, Kenya Swapnamoyee Priyabhasini Palit KIIT University, India Soumya Sucharita Panda BITS Pilani, India Shatrudhan Pandey Birla Institute of Technology, India Shreyanshu Parhi International Management Institute (IMI), India Suresh N. Patel Hemchandracharya North Gujarat University, India Oluwagbemiga Paul Agboola Istanbul Gelisim University, Turkey Ujjwal Kanti Paul National Institute of Technology, India Tanaji Pavani Prabha Bits Pilani, India Yusra Qamar O P Jindal Global University, India Rajeev Kumar Revulagadda National Institute of Industrial Engineering (NITIE), India Kali Charan Sabat RV University, India Amit Sachan Indian Institute of Management (IIM) Ranchi, India Taab Ahmad Samad University of Birmingham Dubai, UAE Abhishek Kumar Singh Birla Institute of Technology, India Divya Singh National Institute of Technology, India Ramanjeet Singh Assam Down Town University, India Swati Singh IBS, IFHE, India Rajesh Tripathi University of Petroleum and Energy Studies, India Leena Wanganoo Murdoch University, UAE Donghun Yoon Kyonggi University, South Korea

Foreword

In the wake of the COVID-19 pandemic, many supply chain professionals have faced unprecedented challenges in dealing with endless supply chain disruptions and geopolitical tensions. One of the best ways to handle such challenges is by adapting various digital technologies designed to harmonise supply chain ecosystems. Drs Rohit Sharma, Anjali Shishodia and Ashish Gupta collected beautiful pieces of research articles that can be trendsetters for enriching the body of literature in the fast-emerging fields of supply chain technologies in the digital era. I have no doubt that their edited book will be an invaluable source of building knowledge bases and inspiring future research efforts for those who pursue academic careers in sustainability and technology areas. Warmest regards Dr Hokey Min James R. Good Chair in Global Supply Chain Strategy Distinguished Research Professor Department of Management, Maurer Center 312 Schmidthorst College of Business Bowling Green State University Bowling Green, OH 43404

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Preface

This book is a collection of pioneering research and insights from experts across various fields, all focused on exploring the intricate relationship between digital technologies and holistic, sustainable development. In an era defined by rapid technological advancements, it is paramount to understand how these innovations can be harnessed to address pressing global challenges and shape a more sustainable future for all. Chapter 1, ‘The Role of Digital Technology in Achieving Sustainable Development Goals (SDGs): A Systematic Literature Review, Bibliometric Analysis and Content Analysis’ by Arushi Bathla, Priyanka Aggarwal and Kumar Manaswi, sets the foundation for our exploration. Through meticulous analysis, the authors comprehensively understand the role digital technology plays in achieving the United Nations’ SDGs. Moving forward, Chapter 2, ‘Digital Technologies, Sustainable Development Goals and The Grand Societal Challenges in the Context of Slum Dwellers of Kolkata, India’ by Atiba Batul, Keya Das Ghosh and Swapnamoyee Priyabhasini Palit, delves into the context of slum dwellers in Kolkata, India. The authors examine how digital technologies can be harnessed to address the grand societal challenges faced by these communities and achieve sustainable development goals. Chapter 3, ‘Applications of Disruptive Technologies in Professional Services’ by Chandan Kumar Jha and Amit Sachan, explores the transformative potential of disruptive technologies in various professional service industries. The authors shed light on how artificial intelligence (AI), blockchain and automation can enhance sustainability and drive innovation. In Chapter 4, ‘Confrontation Strategy for Evolution of Future Employment’ by Donghun Yoon, the impact of technological advancements on the future of employment is examined. Yoon offers a confrontational strategy to navigate the evolving employment landscape and ensure sustainable employment practices. Chapter 5, ‘Framing the Digital Transformation Journey for Sustainability Based on the Lenses of Integrated Skills and Competencies for Future Work’ by Joseph Odhiambo Onyango, focuses on the skills and competencies needed to leverage digital technologies for sustainable development effectively. This chapter provides valuable insights into integrating skills and competencies into the digital transformation journey. Chapter 6, ‘Role of Social Networking Technologies in Developing Public Services Supply Chain During COVID-19’ by Kali Charan Sabat and Som Sekhar Bhattacharyya, highlights the role of social networking technologies in developing resilient public service supply chains during the COVID-19 pandemic. The authors explore the transformative potential of

xiv

Preface

technology in crisis response and service delivery. Jasmandeep Kaur, Kirandeep Kaur and Ramanjeet Singh, in Chapter 7, ‘Adopting Technology for Sustainable Development: Reflections on Innovative Ecosystem’, reflect on adopting technology for sustainable development. This chapter offers insights into the innovation ecosystem that drives transformative change in various sectors. Chapter 8, ‘Exploring the Relationship Between Digital Initiatives, Dynamic Capabilities and Market Performance: A Conceptual Framework’ by Lan Phuong Ho Dang, presents a conceptual framework for understanding the relationship between digital initiatives, dynamic capabilities and market performance. This chapter guides organisations in leveraging digital technologies to enhance market performance and sustainability. In Chapter 9, ‘Reverse Logistics: Rebuilding Smart and Sustainable Transformation Based on Industry 4.0’, by Leena Wanganoo and Rajesh Tripathi, the authors delve into reverse logistics. They discuss how Industry 4.0 technologies can rebuild intelligent and sustainable transformation, optimising resource utilization and reducing environmental impact. Chapter 10, ‘Reflections on Sustainable Development, Sustainability and Business Practice: Lessons From Measurement, Scalability and Bias in Artificial Intelligence (AI)’ by Luisa F. Melo, offers critical reflections on sustainable development, sustainability and business practices. This chapter examines the challenges and opportunities of applying AI in sustainable development, focusing on measurement, scalability and bias. Chapter 11, ‘Digital Healthcare and Patient Transformation: Review Research and Future Agenda’ by Nimesh P. Bhojak, Suresh N. Patel and Mohammadali K. Momin, provides a comprehensive review of research on digital healthcare and its impact on patient transformation. This chapter explores the current state of digital healthcare, identifies future research directions and envisions the potential for improved patient outcomes through technology-enabled solutions. In Chapter 12, ‘A Comparative Framework Analysis of the Strategies, Challenges and Opportunities for Sustainable Smart Cities’ by Oluwagbemiga Paul Agboola and Meryem Muzeyyen Findikgil, the authors present a comparative framework analysis of strategies, challenges and opportunities for sustainable smart cities. This chapter offers a holistic perspective on integrating technology into urban environments to create more sustainable and livable cities. Chapter 13, ‘Leveraging Blockchain Technology in Adopting Digital Tokenisation of Green Bonds’ by Pulak Chugh, explores the potential of blockchain technology in adopting the digital tokenisation of green bonds. This chapter highlights how blockchain can enhance transparency, efficiency and accountability in sustainable finance, facilitating the transition towards a greener economy. ‘Digital Technologies and Education for Sustainable Development’ by Renji George Amballoor and Shankar B. Naik, in Chapter 14, sheds light on the transformative power of digital technologies in education for sustainable development. This chapter examines innovative educational approaches and technologies that can empower learners and foster sustainability-conscious mindsets and behaviours. Chapter 15, ‘Safety Management in the Era of Emerging Industrial Revolution: The Conceptualisation of Safety 4.0’ by Shatrudhan Pandey, Kirtika Kiran, Shreyanshu Parhi, Abhishek Kumar Singh and Sanjay Kumar Jha, focuses on safety

Preface

xv

management in the context of the emerging industrial revolution. The authors conceptualise Safety 4.0, emphasising integrating digital technologies and advanced safety practices to ensure a safe and resilient working environment. ‘Spiritual Approach Among Techies: An Approach for Achieving Sustainable Development’ by Snehal G. Mhatre and Nikhil K. Mehta, in Chapter 16, offers a unique perspective on sustainable development by exploring the role of spirituality among technologists. This chapter emphasises the importance of ethical values, mindfulness and compassion in harnessing technology for sustainable outcomes. Chapter 17, ‘The Evolution of Manufacturing: A Comprehensive Analysis of Industry 4.0 and Its Frameworks’, by Somayya Madakam, Rajeev Kumar Revulagadda, Vinaytosh Mishra and Kaustav Kundu, delves into the realm of Industry 4.0. The authors present frameworks that guide organisations to adopt and implement Industry 4.0 technologies to enhance productivity, sustainability and competitiveness. In Chapter 18, ‘Application of Industry 4.0 Technologies in Climate-Smart Agricultural Practices’ by Soumya Sucharita Panda, Sudatta Banerjee and Swati Alok, the focus shifts to the agricultural sector. This chapter explores how Industry 4.0 technologies can be applied in climate-smart agricultural practices, enabling sustainable food production, resource optimization and environmental conservation. Chapter 19, ‘The Digital Revolution – Implications of Digital Technologies on Women’s Workforce Participation’ by Tanaji Pavani Prabha, Swati Alok, Rishi Kumar and Swati Singh, examines the implications of the digital revolution on women’s workforce participation. The authors explore the opportunities and challenges that arise as digital technologies shape the future of work and gender equality. ‘Building Resilience Against Ongoing and Future Pandemics: Blockchain Technology to the Rescue’ by Taab Ahmad Samad and Yusra Qamar, in Chapter 20, explores the potential of blockchain technology in building resilience against ongoing and future pandemics. This chapter highlights the role of blockchain in enhancing healthcare systems, ensuring supply chain resilience and facilitating effective crisis response. Finally, Chapter 21, ‘Impact of Awareness on the Adoption of Electric Vehicles: A Systematic Literature Review’ by Divya Singh and Ujjwal Kanti Paul, delves into the impact of awareness on adopting electric vehicles. The authors conduct a systematic literature review to understand the factors influencing consumer awareness and adoption of electric vehicles, offering valuable insights for sustainable transportation strategies. Each chapter presents unique perspectives and insights into how digital technologies can drive sustainable development across various sectors. We extend our gratitude to the authors for their invaluable contributions, and we hope that this compilation inspires readers to engage with the possibilities offered by digital technologies, fostering a more sustainable, equitable and prosperous future.

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Acknowledgements

Dr Rohit Sharma: I dedicate this book to my mother, (Late) Mrs Neelam Sharma. And my family who have been the force behind me in all my endeavours. Dr Anjali Shishodia: I dedicate this book to my family for their unwavering support and understanding. Dr Ashish Gupta: I dedicate this book to my family (Pooja Gupta, Aradhay Gupta and Ayansh Gupta) and parents (Mr Ramesh Chandra Gupta and Mrs Kamla Devi Gupta) for their constant love, support and motivation.

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Chapter 1

The Role of Digital Technology in Achieving Sustainable Development Goals (SDGs): A Systematic Literature Review, Bibliometric Analysis and Content Analysis Arushi Bathla, Priyanka Aggarwal and Kumar Manaswi

Abstract Digital technology and SDGs have gained increasing interest from the research community. This chapter aims to explore the field through a holistic review of 188 publications from 2017 to 2022. For the systematic review of 188 articles, a three-step methodology comprising of PRISMA guidelines was performed, bibliometric analysis and text analysis using VOS-Viewer and Sentiment Analysis using RStudio had been undertaken. Bibliographic coupling revealed the following clusters Digital Space (Over all SDG), Localising SDGs, Financial Systems and Growth (SDG 8), Sustainable Supply Chain (SDG 9), Education (SDG 4), Energy Management (SDG 7), Smart Cities (SDG 11 and 13), Gender, Skills, and Responsibility (SDG 5 and 12), Food Management (SDG 1, 2 and 3), Business Innovation (SDG 8 and 9) and ICT (SDG 9). Next, co-occurrence analysis highlighted the following clusters Circular Economy (SDG 8), Higher Education System (SDG 4), Digital health (SDG 3), Industry 4.0 (SDG 9) and Supply Chain Management (SDG 9). Next, text analysis traced the most relevant areas of work within the theme. Finally, sentiment analysis revealed positive sentiments of the field. The research concluded that only a few SDGs had found major focus while the others don’t have any solid ground in the literature. This chapter presents a knowledge structure by mapping the most relevant SDGs in the context of digital technology and sets directions for future research. Keywords: SLR; bibliometric analysis; digital technology; SDGs; text analysis; sustainable development

Fostering Sustainable Development in the Age of Technologies, 1–22 Copyright © 2024 Arushi Bathla, Priyanka Aggarwal and Kumar Manaswi Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231003

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Introduction Sustainability and digitalisation stand as major trends shaping the economy and society (Costanza et al., 2016; Holden et al., 2014). The nexus between both domains foreshows outstanding opportunities to foster a transformation ¨ towards sustainable development (Kohler et al., 2019; Osburg & Lohrmann, 2017; Seele, 2016). The United Nations (UN) Sustainable Development Goals (SDGs) 2030 provide a roadmap towards equity and sustainable development (Allen et al., 2016; Liu et al., 2018; United Nations, n.d.). Digitalisation is heralded to be one of the most promising transformations for sustainability (Gouvea et al., 2018) towards tackling the SDGs (Sachs et al., 2019; Seele & Lock, 2017; Walker et al., 2019). Modern digital technologies like artificial intelligence (AI) and machine learning (ML) have grown exponentially, predicted to add 14% to the global economy by 2030 (George et al., 2020). Despite the potential of the SDGs and digitalisation to work in tandem to advance sustainable development, there has been limited research into their connection (Fukuda-Parr & McNeill, 2019; Kostoska & Kocarev, 2019; Vinuesa et al., 2020). This means that many of the opportunities to leverage the power of digitalisation to promote sustainable development remain untapped and unexplored. To further research in this area, there is a need for greater collaboration between scholars, the private sector, governments and civil society. This chapter reviews sustainability and digitalisation literature to see if digitalisation support SDGs. The authors claim that this study is the first to combine SLR, bibliometrics and text analysis.

Methodology As the SDGs and digital technology research field is just emerging, we chose a qualitative three-step methodology to examine the underlying field. The authors first conducted an SLR using PRISMA (Moher et al., 2015) guidelines. The authors sourced the articles from the Web of Science (WoS) (Falagas et al., 2007; Kullenberg & Kasperowski, 2016). The search string used was: ‘Sustainable Development Goals’ or ‘SDG’ and ‘digital*’ and ‘technology*’ or ‘artificial intelligence’ or ‘blockchain’ or ‘AI’. The search process generated 193 academic papers from 2016 to 2022. We thoroughly read and reviewed all full-text publications. Finally, 188 papers were selected for the final review. Please refer Fig. 1.1 for data curation process. Secondly, bibliometric analysis assisted in the development of the thematic structure of the underlying research field (Ellegaard & Wallin, 2015; Valtakoski, 2019). Finally, content analysis was performed by analysing the themes emerging out of bibliographic coupling, followed by text and sentimental analysis of the future research scope of the latest articles.

Identification

The Role of Digital Technology in Achieving SDGs

Records identified through database searching (N=193)

3

Additional records identified through other sources (N= 0)

Screening

Records after duplicates removed (N=193)

Eligibility

Records screened (N=193)

Full-text articles assessed for eligibility (N=193)

Excluded (N=0) (Articles not relating to underlying topic removed)

Full-text articles excluded, with reasons (N=5)

Included

Studies included in systematic review (N=188)

Fig. 1.1.

PRISMA. Source: Authors Compilation (Adapted from Moher et al., 2009).

Findings Publications Trend Fig. 1.2 displays SDGs and digital technologies research articles by year. The topic is novel, as the first traceable article was published in 2017.

Contributing Countries To gain insights into the most productive countries, we analysed the countries that had minimum of three documents with minimum of three citations (Chakma et al., 2022) in the domain of SDGs and digital technologies; out of 77 countries, 36 have fulfiled this criterion. The most impactful country was China with 30

4

Arushi Bathla et al. Number of Publications 120 100

Publications

80

70

65

60 40

30

20 4

6

2017

2018

13

0 2019

2020

2021

2022

-20

Year

Fig. 1.2.

Authors Compilation. Source: Data used from Web of Science.

documents and 482 citations. Subsequent productive countries were Australia, England, Spain, the United States and Germany with a large number of citations (see Table 1.1).

Keyword Co-occurrence Analysis The keyword co-occurrence analysis is used for mapping the thematic development of the SDGs and digital technologies field because keywords are great pointers for the central focus or content of an article (Castriotta et al., 2018;

Table 1.1. Contributing Countries. S. No.

1 2 3 4 5 6 7 8 9 10

Country

Documents

Citations

Peoples R China Australia England Spain The United States Germany France Brazil Sweden India

30 22 32 26 25 13 9 6 10 18

482 318 299 253 218 215 186 133 126 123

Source: Authors Compilation (Data used from Web of Science).

The Role of Digital Technology in Achieving SDGs

Fig. 1.3.

5

Keyword Co-Occurrence Analysis. Source: VOS-Viewer.

Strozzi et al., 2017). Fig. 1.3 shows the clusters of keywords with at least five occurrences. Of the 1,287 keywords, 61 met the threshold. Table 1.2 shows the name and items in these clusters.

Bibliographic Coupling of Documents In simple words, it relates to the crossover in the reference list (Donthu et al., 2021). The study undertook a threshold of default five citations for a document ´ (Mart´ınez-Lopez et al., 2018; van Eck & Waltman, 2014) and got 86 documents out of which only 76 consisted of the largest set of connected items. We finally got 11 clusters as shown in Fig. 1.4. An established academic practice of analysing the top 10 cited articles of each cluster (as shown in Table 1.3) to describe the dominant theme of the cluster has been undertaken (Bhandari, 2022; Fahimnia et al., 2015) as shown in Table 1.4.

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Table 1.2. Clusters. Colour

Items

Red

Circular Economy, Consumption, Energy, ICT, Integration, Performance, Development Green Developing Countries, Digital divide, Governance, Grand Challenges, Higher Education, Security Blue COVID-19, Digital Health, Information Technology, Knowledge, Management, Systems, Transformation Yellow AI, Big Data, Blockchain, Digital Twin, Digitalisation, Industry 4.0, IoT, Renewable Energy, Sustainability Purple AI, Augmented Reality, Blockchain Industry 4.0, Innovation, Supply Chain

Name

Application of Digital Technologies for Sustainable Development and Circular Economy Application of Digital Technologies for Improving Higher Education System Application of Digital Technologies for Digital Health

Role of Industry 4.0 for Sustainability

Role of Industry 4.0 for Supply Chain Management

Source: VOS-Viewer.

Fig. 1.4.

Network Visualisation. Source: VOS-Viewer.

Table 1.3. Top 10 Articles of Each Cluster. 1

2

Adarkwah (2021)

Arner et al. (2020)

Leng et al. (2020) Ockwell et al. (2019) Tsolakis et al. (2021) Lagna & Khanfar et al. Ravishankar (2022) (2021)

B˘arbulescu et al. (2021) ¨ Gossling (2021) D’Amico et al. Frimpong Boamah (2021) & Murshid (2019) Ajwani-Ramchandani Palomares et al. Moro-Visconti et al. et al. (2021) (2021) (2020) Tham & Sigala (2020) Al-Htaybat Treude (2021) et al. (2019) Hoosain et al. (2020) Gupta et al. Goel et al. (2021) (2020) Nativi et al. (2021) Radovanovi´c et al. (2020)

4

Parmentola et al. (2022) Vafadarnikjoo et al. (2021) Quayson et al. (2021) Nurgazina et al. (2021) Chivilgina et al. (2020)

5

Shahzad et al. (2022) Bhatti et al. (2021) Fernandez-Luque & Imran (2018) Abad-Segura et al. (2020) He et al. (2021) Popkova et al. (2022)

6

Ghobakhloo et al. (2021) Nayal, Raut, et al. (2022) Ali & Govindan (2021) Nayal, Kumar, et al. (2022) Giraldo et al. (2021) Costa et al. (2022)

Zahid et al. (2021) Carayannis & Morawska-Jancelewicz (2022)

Singh et al. (2021) Cioac˘a et al. (2020)

The Role of Digital Technology in Achieving SDGs

França et al. (2020) Portillo et al. (2020) (del R´ıo Castro et al., 2021) Asi & Williams (2018) ElMassah & Mohieldin (2020) Lembani et al. (2020) Guo et al. (2018)

3

7 (Continued)

8

Table 1.3. (Continued) 8

Pan & Zhang (2020)

Baena-Morales et al. (2020) Allam & Jones (2021) Liritzis & Korka (2019) Dwivedi et al. (2022) Tim et al. (2021) Pournaras (2020) Gunnlaugsson et al. (2020)

Source: VOS-Viewer.

Garc´ıa et al. (2020) Oftedal et al. (2019) Kerras et al. (2020) Parth et al. (2021)

9

Reˇzek Jambrak et al. (2021) Fuster Morell et al. (2020)

10

Bican & Brem (2020) Grijalvo Mart´ın et al. (2020) Martos et al. (2021) Camodeca & Almici (2021)

11

¨ ur ¨ Broo, Lamb, Gurd et al. (2021) ¨ ur ¨ Broo, Boman, Gurd et al. (2021)

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The Role of Digital Technology in Achieving SDGs Table 1.4. Clusters. Theme

Sub-theme

No. of Articles

Digital Space (Over all SDG) Online learning, e-learning, ICT integration, distance education, circular economy, digital health, tourism, big data, Industry 4.0, digital ecosystems (DEs) model, digital inclusion, internet lite, bitcoins Localising SDGs Reflective accounting, sustainable logistics, solid waste-management, blockchain, regional sustainability, cloud manufacturing, Internet of Things-assisted manufacturing Financial Systems and FinTech, financial inclusion, Growth (SDG 8) innovation, entrepreneurial ecosystem, mobile money, smart cities, model scalability, market valuation, e-business models Sustainable Supply Chain Blockchain, sustainable (SDG 9) manufacturing, product lifecycle management, Industry 4.0, environmental sustainability, sustainable supply chains, supply network design Education (SDG 4) Sustainability, augmented reality, higher education, management, ICT, virtual technology, digital twin technology, future universities Energy Management (SDG Industry 4.0, energy transition, 7) energy trading, energy commercialisation, AI, renewable energy, hydropower projects Smart Cities (SDG 11 and 6G, digital twins, immersive realities, 13) new urban economies, climate change COP26, information management, information systems research, blockchain, augmented democracy, digital resilience

13

12

8

8

8

7

6

(Continued)

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Table 1.4. (Continued) Theme

Gender, Skills and Responsibility (SDG 5 and 12)

Sub-theme

Training teachers, skill, competence development, social networks, education, society, gender digital divide, cultural heritage, e-health, consumer responsibilities Food Management (SDG 1, Agricultural sustainability, food, 2 and 3) Industry 4.0 Business Innovation (SDG 8 Digital business model, digital and 9) entrepreneurship, new sustainable business models ICT (SDG 9) Cyber-physical systems research and education

No. of Articles

6

3 3

2

Source: VOS-Viewer.

Content Analysis This technique is employed to trace each cluster’s insights (Micheli et al., 2019). In this chapter, articles with more than 25 citations have been selected for content analysis (Bhandari, 2022; Hota et al., 2020) to ensure the high quality and robustness of an article.

Cluster 1: Digital Space (Overall SDG) This cluster has most articles from 2018 to 2021. Adarkwah (2021) proposed a conceptual framework for crisis transition to e-learning. Lembani et al. (2020) examined the digital divide between urban and rural remote students to assess how ICT availability affects higher education. Asi and Williams (2018) mentioned the significance of e-health in achieving SDG 3 in conflict-affected communities.

Cluster 2: Localising SDGs The second-largest cluster contains articles from 2018 to 2021. According to R´ıo Castro et al. (2021), SDGs research has many gaps, including design flaws and disparities; execution and leadership complexities; inappropriate indicators and evaluation techniques; and an undeveloped role for technological knowledge and innovation strategic planning. Localisation and digitalisation can help governments build grassroots sustainable development policies, according to ElMassah and Mohieldin (2020). França et al. (2020) found that reorganising and regulating solid waste management with blockchain technology could help decouple economic growth from non-renewable resources.

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Cluster 3: Financial Systems and Growth (SDG 8) This cluster has articles from 2018 to 2022. According to Arner et al. (2020), financial technology is the primary engine of financial intermediation, which in turn underpins sustainable coordinated growth, as represented in the UN SDGs. Cluster 4: Sustainable Supply Chain (SDG 9) This cluster has articles from 2018 to 2022. Tsolakis et al. (2021) and Leng et al. (2020) found that the blockchain-enabled transformation of a sustainable manufacturing paradigm is still in its early stages, but it is fast gaining acceptability. Cluster 5: Education (SDG 4) This cluster has articles from 2018 to 2022. According to Portillo et al. (2020), a low education level with poor technological proficiency is the most disadvantaged in remote education. The expansion of quality education (SDG 4) that minimises disparities (SDG 5, SDG 10) involves setting people at the centre of solutions (SDG 3, SDG 8). Cluster 6: Energy Management (SDG 7) Ghobakhloo et al. (2021) examined how Industry 4.0 might address SDGs, especially industrial production growth. Industry 4.0’s large-scale interaction and communication capabilities can inspire industrial cooperation to alleviate excessive consumption and carbon emissions. Cluster 7: Smart Cities (SDG 11 and 13) This cluster has articles from 2021 to 2022. Allam and Jones (2021) illustrate the major directions and scope of nascent dimensions inherent in 6G technology (SDG 11). Pan and Zhang (2020) proposed six SDG pandemic themes: ‘growing digital surveillance,’ ‘tackling the infodemic’, ‘orchestrating data ecosystems’, ‘adapting information behaviours’, ‘creating the digital workplace’ and ‘maintaining social separation’. Cluster 8: Gender, Skills and Responsibility (SDG 5 and 12) No articles in this cluster adhere to the criterion. This cluster has articles from 2019 to 2021. Cluster 9: Food Management (SDG 1, 2 and 3) This cluster contains 2020–2021 items. Life cycle assessment (LCA) is needed to measure the environmental, social and economic components, according to Jambrak et al. (2021). Cluster 10: Business Innovation (SDG 8 and 9) No articles in this cluster adhere to the criterion. This cluster has articles from 2020 to 2021.

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Cluster 11: ICT (SDG 9) This cluster has articles from 2021. Bican and Brem (2020) identified seven fundamental digital-related concepts: Digital, Business Model, Digital Business Model, Digital Technology, Digital Innovation, Digital Transformation and Digital Entrepreneurship.

Text Analysis of Future Scope Data cleaning and mining were performed on 62 articles from 2021 to 2022, representing 33% of the selected 188 publications, to anticipate the future of text analysis. As in Fig. 1.5, the most frequent words are smart, social, health, city, study, food, processes, etc. These call attention to the potential SDGs for future research to achieve the goals of sustainability as highlighted by themes (bibliometric coupling and co-word analysis) from the analysis. This implies that, as mentioned in the Table 1.5 indicating total presence sentiment, the (line by line) future is a very positive sentiment with quite low negative sentiment.

Fig. 1.5.

WordCloud. Source: RStudio.

Table 1.5. Presence-Sentiment. Sarcasm

Negative

Very Negative

Neutral

Positive

Very Positive

70

12

172

217

276

15 Source: RStudio.

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Discussion Studies on the use of digital technology to support the SDGs will be essential for understanding how best to use digital technology to achieve the goals. Such studies should consider the range of digital technologies, including AI and blockchain, and the potential implications for economic, social and environmental sustainability. Research should also look into how digital technologies can help to reduce inequality and poverty, while promoting economic growth and development. Finally, the analysis indicated that just a handful SDGs have received significant attention, while others had no scholarly support. The authors mapped the literature’s future research scope. Fig. 1.6 is segregated into two parts: first, motor themes and second, emerging/niche themes. As noted in ‘Bibliographic Coupling of Documents’ section, studies on digital transformation and SDGs like SDG 1, 2, 3, 4, 5, 7, 8, 9, 11, 12 and 13 are eminent and thoroughly investigated in motor topics, while in emerging themes, they are still unexplored. The question remains: (1) Can digital technologies work to reduce inequality within and between countries, communities and populations by extending access to technologies and knowledge to disadvantaged segments of society (SDG 10)?

Fig. 1.6.

Future Research Directions. Source: Author compilation.

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(2) How effectively ICTs like blockchain and AI can be used to identify, monitor and track wildlife populations (SDG 15)? (3) When and how can public–private partnerships become key to bringing ICTs to all nations, peoples and communities (SDG 17)?

Implications This chapter will help policymakers understand the potential of digitalisation to create and enable new models for sustainable development. Digitalisation can help improve the efficiency of existing policies and public services, reducing costs and enabling the delivery of better outcomes for citizens. It can also create new possibilities for interacting with citizens, allowing them to become more engaged in the policy process and better understand their own role in achieving the SDGs. At the same time, digitalisation has also created an opportunity for businesses to pursue SDGs. By leveraging digital technologies, businesses can measure, track and optimise their environmental and social impact. The study has further created new opportunities for researchers to make new discoveries in the underlying field.

Conclusion This chapter offers a comprehensive analysis of the literature on the current state of digital technology and SDGs research. This chapter will aid academics, researchers and managers in developing a comprehensive understanding of digital technologies and SDGs fields. However, the primary disadvantage of this study is that it solely utilises the Web of Science database. Future researchers can utilise other databases to strengthen the results.

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Quayson, M., Bai, C., & Sarkis, J. (2021). Technology for social good foundations: A perspective from the smallholder farmer in sustainable supply chains. IEEE Transactions on Engineering Management, 68(3), 894–898. https://doi.org/10.1109/ TEM.2020.2996003 Radovanovi´c, D., Holst, C., Belur, S. B., Srivastava, R., Houngbonon, G. V., le Quentrec, E., Miliza, J., Winkler, A. S., & Noll, J. (2020). Digital literacy key performance indicators for sustainable development. Social Inclusion, 8(2), 151–167. https://doi.org/10.17645/si.v8i2.2587 Reˇzek Jambrak, A., Nutrizio, M., Djeki´c, I., Plesli´c, S., & Chemat, F. (2021). Internet of Nonthermal Food Processing Technologies (IoNTP): Food Industry 4.0 and Sustainability. Applied Sciences, 11(2), 686. https://doi.org/10.3390/app11020686 ´ (2021). Unleashing R´ıo Castro, G., Gonz´alez Fern´andez, M. C., & Uruburu Colsa, A. the convergence amid digitalization and sustainability towards pursuing the Sustainable Development Goals (SDGs): A holistic review. Journal of Cleaner Production, 280, 122204. https://doi.org/10.1016/j.jclepro.2020.122204 Sachs, J. D., Schmidt-Traub, G., Mazzucato, M., Messner, D., Nakicenovic, N., & ¨ Rockstrom, J. (2019). Six Transformations to achieve the Sustainable Development Goals. Nature Sustainability, 9, 805–814. https://doi.org/10.1038/s41893-0190352-9 Seele, P. (2016). Envisioning the digital sustainability panopticon: A thought experiment of how big data may help advancing sustainability in the digital age. Sustainability Science, 5, 845–854. https://doi.org/10.1007/s11625-016-0381-5 Seele, P., & Lock, I. (2017). The game-changing potential of digitalization for sustainability: Possibilities, perils, and pathways. Sustainability Science, 2, 183–185. https://doi.org/10.1007/s11625-017-0426-4 Shahzad, U., Ferraz, D., Nguyen, H.-H., & Cui, L. (2022). Investigating the spill overs and connectedness between financial globalization, high-tech industries and environmental footprints: Fresh evidence in context of China. Technological Forecasting and Social Change, 174, 121205. https://doi.org/10.1016/j.techfore. 2021.121205 Singh, R., Gehlot, A., Akram, S. V., Gupta, L. R., Jena, M. K., Prakash, C., Singh, S., & Kumar, R. (2021). Cloud manufacturing, internet of things-assisted manufacturing and 3D printing technology: Reliable tools for sustainable construction. Sustainability, 13(13), 7327. https://doi.org/10.3390/su13137327 Strozzi, F., Colicchia, C., Creazza, A., & No`e, C. (2017). Literature review on the ‘Smart Factory’ concept using bibliometric tools. International Journal of Production Research, 22, 6572–6591. https://doi.org/10.1080/00207543.2017.1326643 Tham, A., & Sigala, M. (2020). Road block(chain): Bit(coin)s for tourism sustainable development goals? Journal of Hospitality and Tourism Technology, 11(2), 203–222. https://doi.org/10.1108/JHTT-05-2019-0069 Tim, Y., Cui, L., & Sheng, Z. (2021). Digital resilience: How rural communities leapfrogged into sustainable development. Information Systems Journal, 31(2), 323–345. https://doi.org/10.1111/isj.12312 Treude, M. (2021). Sustainable smart city—Opening a black box. Sustainability, 13(2), 769. https://doi.org/10.3390/su13020769 Tsolakis, N., Niedenzu, D., Simonetto, M., Dora, M., & Kumar, M. (2021). Supply network design to address United Nations Sustainable Development Goals: A case study of blockchain implementation in Thai fish industry. Journal of Business Research, 131, 495–519. https://doi.org/10.1016/j.jbusres.2020.08.003

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United Nations. (n.d). The 17 GOALS j Sustainable Development. https://sdgs.un.org/ goals. Accessed on November 27, 2022. Vafadarnikjoo, A., Badri Ahmadi, H., Liou, J. J. H., Botelho, T., & Chalvatzis, K. (2021). Analyzing blockchain adoption barriers in manufacturing supply chains by the neutrosophic analytic hierarchy process. Annals of Operations Research. https:// doi.org/10.1007/s10479-021-04048-6 Valtakoski, A. (2019). The evolution and impact of qualitative research in Journal of Services Marketing. Journal of Services Marketing, 1, 8–23. https://doi.org/10.1108/ jsm-12-2018-0359 Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Fell¨ander, A., Langhans, S. D., Tegmark, M., & Fuso Nerini, F. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature Communications, 1. https://doi.org/10.1038/s41467-019-14108-y Walker, T. W. N., Janssens, I. A., Weedon, J. T., Sigurdsson, B. D., Richter, A., Peñuelas, J., Leblans, N. I. W., Bahn, M., Bartrons, M., De Jonge, C., ´ ´ Fuchslueger, L., Gargallo-Garriga, A., Gunnarsdottir, G. E., Marañon-Jim´ enez, ´ S., Oddsdottir, E. S., Ostonen, I., Poeplau, C., Prommer, J., Radujkovi´c, D., . . . Verbruggen, E. (2019). A systemic overreaction to years versus decades of warming in a subarctic grassland ecosystem. Nature Ecology & Evolution, 1, 101–108. https:// doi.org/10.1038/s41559-019-1055-3 Zahid, A., Poulsen, J. K., Sharma, R., & Wingreen, S. C. (2021). A systematic review of emerging information technologies for sustainable data-centric health-care. International Journal of Medical Informatics, 149, 104420. https://doi.org/10.1016/j. ijmedinf.2021.104420

Chapter 2

Digital Technologies, Sustainable Development Goals and the Grand Societal Challenges in the Context of Slum Dwellers of Kolkata, India Atiba Batul, Keya Das Ghosh and Swapnamoyee Priyabhasini Palit

Abstract One major impact of demonetisation is rise of cashless or digital transactions. The extension of the transition from a cash-based to a cashless economy has expanded even more now, based on the lessons learnt from the COVID-19 pandemic. This chapter discusses the various electronic payment methods used by the people, the frequency of using these methods and also to examine the reasons of changing habits in using electronic modes of payments. This study is both theoretical and empirical in nature, based on both primary and secondary data. Digitalising rural and poor population is much in talks but earlier literature did not acknowledge the status of slums and its inhabitants. Slum dwellers are the ones to be in the margin, and therefore are subject to more societal sufferings. In the context of female population particularly, the mechanism of urbanisation and increment in urban slums are subject to unique causes and unique consequences, and still these challenges are greatly underexplored by earlier literature in this field. Thus, the aim of this chapter is to find out the schemes, achievements and challenges for the cashless transaction practised by the female slum dwellers. To be extremely explicit, the sample area consists of two biggest slums of Kolkata and 100 female respondents are inquired for this study, taking 50 from each slum. For analysing the collected data, descriptive statistics tools and percentage analysis have been used. This chapter will also analyse India’s gradual transition towards a cashless economy. Through the examination of digitalisation of slum dwellers, this study also attempts to identify whether digital modes result in empowerment of these women, of any kind. Fostering Sustainable Development in the Age of Technologies, 23–42 Copyright © 2024 Atiba Batul, Keya Das Ghosh and Swapnamoyee Priyabhasini Palit Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231004

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Atiba Batul et al. By paying a visit in the discussion of women empowerment, this chapter wants to revisit the 2030 Agenda for Sustainable Development and its 17 Sustainable Development Goals (SDGs) adopted by world leaders in 2015, that embodies a roadmap for progress which leaves no one behind. The questions impacting achievement of SDG through women empowerment may not seem of utmost concern during the current situation but is equally important and needs to be discussed on a platform of its own. Keywords: Urban slums; digital payments; cashless economy; slum economy; SDGs; women empowerment

Introduction Cashless Economy Indian economy is now gradually transiting into a no-cash economy. The introduction of cashless economy can be seen as a step in the right direction of economy growth and development. It has been conducted to unravel the challenges and opportunities of cashless economy by promoting electronic money instruments, developing electronic financial infrastructures and spreading digital transaction habits among people (Singhraul & Garwal, 2018). The government has implemented a major change in the economy by demonetising the high-valued currency notes – of Rs 500 and Rs 1,000 denomination in November 2016 (Saha, 2016). It was perceived that one of the principle objects to reform currency is that physical currency must shrink but the economy and its trade has to expand. Therefore, what shrinks has to be substituted and further expanded by the digital mode. COVID-19 also taught us that allocating highest value to economic activities such as health services, general utility services, bill payments, etc. is the starting point of a cashless economy (Kumar, 2020). The pre-requisite for cashless economy is an efficient banking system which requires more and more people to come under the banking purview. This has rippling effect because it plays a substantial role in credit creation which is a primary requirement for economic development. To gain the impact of credit creation, more and more people should undertake cashless transactions. This will bring in more money into the financial system and enable a steady growth of the economy. The success of this move lies in the hands of the citizens of the country. However, a majority of population still remains beyond the purview of the banking system which is expected to bring in a wave of customer trends towards cashless transactions (Saha, 2016).

Slum Economy The open areas with poorly built tenement on public lands or along drains and railway lines lacking electricity, latrines, sewerage, medical facilities, having taps or tube-well as their major drinking water resource and which gets badly impacted

SDGs in the Context of Slum Dwellers

25

through water lodgings can be characterised as slums. There is a good debate about the head count ratio of slum dwellers. The Census and the National Sample Survey Organization (NSSO) are two major government agencies held responsible for calculating population. In 2011, Census reported the slum population in India to be 6.5 crore, whereas in 2012, NSSO reported the same to be 4.4 crore (Varma, 2014). The difference in the two government reports is of 2.1 crore, a huge figure, which cannot be owed to any measurement discrepancy or error in calculation (Times of India, 2014). Therefore, this is clear that accurate data on slum population of India are not available. In fact, in the case of Kolkata too, the entity responsible for maintaining data on slum dwellers, i.e. Kolkata Municipal Corporation (KMC), does not have data on slum areas population wise. This leads to one of the major drawbacks in the field of research on slums. From this, one can also interpret that the policy benefits that should reach to slum dwellers is not able to travel to the person standing on the last mile (Batul & Palit, 2022). Slums are growing every day. Economic growth and sustainable development are the goals of any country that is in developing state. The phenomena of urbanisation result in inaccessibility of basic services by all the residents. Rural development receives immense amount of significance from researchers and policy initiators whereas immediate focus is required to be on urban development due to fast rising urbanisation, uncommon needs of urban residents and less earning people of urban centres, specifically slum regions (Bapat & Bhattacharyay, 2016). The focus of this chapter is to highlight the plight of this vulnerable section of the population, particularly women residing in the slums of Kolkata city. This chapter discusses the various electronic payment methods used by them, the frequency of using these methods and also to examine the reasons of changing habits in using electronic modes of payments.

Literature Review Dominic et al. (2018) examined the approach of individuals towards the cashless economy among 50 respondents comprising businessmen, government employees, students, housewives, etc. and showed that majority prefer cash transactions because of the degree of high risk associated with the digital transaction and high rate of digital illiteracy. Dhanalakshmi (2018) found that government initiatives to drive cashless payments has grown over the last couple of years, subsequent to the government’s demonetisation initiative in November 2016. Although there has been expansion in mobile payments, card-based transactions continue to be a huge driver of cashless payments. Saha (2016) found that there is considerable awareness among the rural masses as to e-transactions with all the respondents being aware of the e-banking services. However, awareness as to government utility services over the internet has the least degree of awareness where a mere 50% believe that they can achieve public services through the electronic medium.

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Bapat and Bhattacharyay (2016) found in a study from Pune, Maharashtra, that out of 202 total households, 62% of adults have a bank account whereas 38% do not. Also, there is a gap of 49% among respondents who are interested in taking loans and those who have actually taken. Tiwari (2018) found in a study from Nagpur city, that out of 75 slum dwellers, 55% were aware about the term ‘Financial Inclusion’ whereas 45% were not, and 83% had bank accounts whereas 17% did not. Also, 74% of slum dwellers had savings accounts, 15% both savings and recurring accounts and 3% had fixed deposit accounts. Bhatia and Singh (2019) surveyed 737 women slum dwellers in Ludhiana, Punjab, and found that 40% of them could fill banking forms, 35% could check their balance, 6% could do online transactions and financial literacy about insurance and pension was very low. Malik et al. (2020) examined the nature of savings among 100 slum dwellers of Lucknow in the state of Uttar Pradesh and found that 58% of respondents were aware of financial services and this is negatively related to savings. They prefer to save at home rather than at banks and 99% of them failed in their credit gap management. Karmakar et al. (2020) surveyed 631 households dwelling in slums of Dumduma, Bhubaneswar, and found that almost all the households had zero balance bank accounts under PMJDY and the Mahila Samiti helps women self-help groups (SHGs) here. There are 60 SHGs and 90% of them have accessibility of microfinance. Bag and Seth (2016) randomly selected 63 slums from 15 boroughs, out of which interviewed 808 households from Kolkata slums and found that there was no difference in the per capita incomes of households across different regions within Kolkata and female-headed households reflected lower standard of living. Households in slums of Kolkata’s Central and South-west regions appear to be statistically significantly better off non-monetarily (as in education, health wise, etc.) compared to those in its South-east region. Kumari (2017) spoke about the trend of growing income gap at national level that Kolkata follows with 80% of its population earning under Rs 5,000. The areas under study were Esplanade (Chandni chowk, Burrabazar), South Kolkata (Alipore, Khidderpore), Southern fringes (Behala, Garia), North Kolkata (Shyambazar, Bagbazar) and Northern fringes (Barrackpore, Madhyamgram) with a total of 547 sample size of households. It was found that financial exclusion was highest in South Kolkata, where 34% were totally excluded financially, whereas lowest in Southern fringes with 3.5%. Peck (2018) shown the comparison between rural and urban slum economics and found that the average income of a slum dweller in Kolkata is 32% more than the rural counterpart employed in farm activities, whereas that of slum dwellers is 32% lower than the rural counterpart in terms of non-farm activities. Seventy percent of inhabitants have lived in Kolkata for 15 years or so, whereas 41% have lived for 30 years or more. Singh et al. (2019) explored lives of some families living in three different slums of Kolkata, namely, Chingrighata, Jadavpur and Nonadanga slums. It was

SDGs in the Context of Slum Dwellers

27

observed that almost every child had proper accessibility of education. They strive hard to earn and sometimes, end up receiving inadequate and uncertain payments, which usually falls within the range of Rs 4,000–10,000. They spend more on food, especially non-veg items, than on things like clothing and other unnecessary things and save even a small amount of money for any emergency situation.

Objectives of the Study • To study the demographics of the slum dwellers of Kolkata, particularly

women. • To study about the accessibility, usage, methods and frequency of cashless

transaction practised by the female slum dwellers. • To evaluate the impact of the degree of success of digitalisation in the context

of marginalised population on the achievements of Sustainable Development Goal (SDG).

Research Methodology The study is both theoretical and empirical in nature, based on both primary and secondary data. To be extremely explicit, the sample area consists of two biggest slums of Kolkata and 100 female respondents are inquired for this study, taking 50 respondents from each slum. Therefore, the sample criteria are that the respondents should have an account in any formal financial institution, automatically setting the age criteria of sample selection to be 18 years and above, and that they have to be women. Interview survey method was used to collect data. For analysing the collected data, descriptive statistics tools and percentage analysis have been used.

Data Analysis and Findings Demography of the Respondents Geographical Location of the Sample To be very crisp, the total sample size is 100, taking 50 respondents from each of the two biggest slums of Kolkata, as per Kolkata Municipal Corporation (KMC), for primary database, namely: • ‘Shahid Smriti Colony’ (ward 109, off EM Bypass) – The ward (shown in Fig.

2.1) is served by Purba Jadavpur, Survey Park and Panchasayar Police Stations in the East Division of Kolkata Police and is a part of Jadavpur (Vidhan Sabha constituency). • ‘Mia Bagan Bustee’ (ward 35, Beliaghata) – The ward (shown in Fig. 2.2) is served by Beliaghata and Narkeldanga Police Stations of Kolkata Police and is a part of Beleghata (Vidhan Sabha constituency).

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Fig. 2.1. Interactive Map Outlining Ward No. 109. Source: © OpenStreetMap (https://www.openstreetmap.org/copyright).

Age of the Respondents In the context of age range of the respondents (Fig. 2.3), we found that among the 100 respondents, 11 females belong to the age group of 18–30 years, 4 women to 21–30 years, 39 to 31–40 years, 27 to 41–50 years, 16 to 51–60 years and 3 of them belonged to 61–70 years of age. Household Structure of the Respondents This subsection shows the type of household structure they belong to. According to the analysis, 13 respondents had nuclear family with elders living with them, 57 had nuclear family living with their children and 30 of them had joint family living with other relatives as well (Fig. 2.4). Education of the Respondents The study found that majority of female slum dwellers in Kolkata lack education. In fact, about 37 of them had only basic knowledge of their mother tongue without proper schooling or elementary education and we have clubbed them under the category of ‘upto primary’ level of education and almost 50% of them (49 respondents) had no education at all. Nine percent of women had upto

SDGs in the Context of Slum Dwellers

Fig. 2.2. Interactive Map Outlining Ward No. 35. Source: © OpenStreetMap (https://www.openstreetmap.org/copyright).

45 40 35 30 25 20 15 10 5 0

39

27 16 11 4

18-30

Fig. 2.3.

21-30

3 31-40

41-50

51-60

61-70

Age Group of the Respondents. Source: Author’s Compilation.

29

30

Atiba Batul et al.

nuclear family with elders

13

nuclear family

57

joint family

30 0

Fig. 2.4.

10

20

30

40

60

Structure of Family of the Respondents. Source: Author’s Compilation.

Up to secondary

9

Up to primary

37

Up to HS

1

no education

49

graduation & above

4 0

Fig. 2.5.

50

10

20

30

40

50

60

Educational Attainment Level of the Respondents. Source: Author’s Compilation.

secondary level of education (class X), 1% had upto Higher Secondary level (class XII) and 4% above it (Fig. 2.5).

Occupation of the Respondents With reference to the occupational pattern of the female slum dwellers, it is seen that majority of the females (55%) are wage earners with irregular income, 26% are regular labourers usually earning weekly, 7% are casual labourers usually paid on monthly basis, 3% were into government salaried job under the municipality working as cleaners and 9 of them had no earning at all since 7 of them were housewives and 2 were students (Fig. 2.6).

Digitalisation of the Slum Dwellers This subsection of data analysis shows the accessibility, awareness, usage, methods, frequency, time period, etc. of digital payments by the female inhabitants of slums in Kolkata.

SDGs in the Context of Slum Dwellers

31

55

60 50 40 26

30 20 10

7

7

3

2

0 casual labour

Fig. 2.6.

govt. salaried

housewife

regular labour

student

wage earner

Type of Occupation of the Respondents. Source: Author’s Compilation.

9 3

independently jointly with the help

88

Fig. 2.7.

Accessing of Bank Accounts by the Respondents. Source: Author’s Compilation.

Accessibility by the Respondents • In line with how do the respondents operate their accounts (Fig. 2.7), only 9%

can access their account independently and 3% operate their account jointly with their husbands. About 88% of the women operate their account with the help of others, since they cannot operate their account on their own. The help involves filling up of bank forms, withdrawal, deposit, etc. • Next, for accessibility of accounts, we also attempt to see whether the slum dwellers are able to put their signatures on their own or not. It was found that 66% knew how to put their signature (mostly in their mother tongue language). On the other hand, 34% of them did not even know how to put their signature (in any language) and usually put thumb impression, wherever required (Fig. 2.8).

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34 no yes

66

Fig. 2.8.

Number of Respondents Who Can Sign. Source: Author’s Compilation.

Pre-requisite for Online Banking For digitalisation, there are some basic requirements that needs to be fulfiled. One such pre-requisite is debit card, which is mandatory for online banking. It was found that 81% of them had ATM cards with them and 19% do not (Fig. 2.9). This reflects some good efforts that have been put in by the banking system.

Awareness of the Respondents We begin with the awareness about online banking among the marginalised population and found that about more than half of the respondents, i.e. 56% were unaware of online banking whereas only 44% were aware of it (Fig. 2.10).

100 81 80 60 40 19 20 0 no

Fig. 2.9.

yes

Number of ATM Card Holders Among the Respondents. Source: Author’s Compilation.

SDGs in the Context of Slum Dwellers

44

33

no yes

56

Fig. 2.10.

Awareness of Online Banking Among the Respondents. Source: Author’s Compilation.

Usage by the Respondents In terms of the usage of digital transaction (Fig. 2.11), it is observed that 92% of the slum dwellers affirmed that they do not use online banking. It was found that only 8% of the slum population makes use of online banking.

Methods Used by the Respondents Among the 9% of respondents who use online banking, 2 of them use the medium of Paytm, Google Pay, etc. for digital payments and 6 of them use their respective bank apps (Fig. 2.12).

8

no yes

92

Fig. 2.11.

Number of Respondents Using Online Banking. Source: Author’s Compilation.

Atiba Batul et al.

34

paytm, google pay

2

none

92

bank app

6

0

Fig. 2.12.

10

20

30

40

50

60

70

80

90

100

Medium of Online Transaction Used by Respondents. Source: Author’s Compilation.

Frequency of Usage Since the income pattern of the slum dwellers is very uncertain and irregular in nature, the information collected on the frequency of using online banking seemed to be not of significance due to the same ‘very less frequent usage’ responses made by them. Therefore, we attempted to find the time period since when they started using digital transaction mode and found that it has been more than 1 year but less than 5 years, since they began to use online banking (Fig. 2.13). An important reason can be COVID-19 pandemic that led these few people to opt for or introduced them to the online mode of transaction.

nil

92

1-5 yrs

8

0

10

Fig. 2.13.

20

30

40

50

60

70

80

90

Time Period of Using Online Banking by the Respondents. Source: Author’s Compilation.

100

SDGs in the Context of Slum Dwellers

35

SDG and Women Empowerment Although the concept of women empowerment was much in talks for a long time, it gained more significance in the 9th five-year plan in India and that year of 2001 was announced as ‘Women Empowerment Year’. The term empowerment is described by the World Bank as ‘the process of increasing the capacity of individuals or groups to make choices and to transform those choices into desired actions and outcomes’. It is the mechanism which deals with the capacities of women in taking decisions regarding their lives, in terms of choices and preferences. This can take place in various aspects of life, such as, economic, social and political. No doubt, women are successfully involved in various fields be it sports, medical, entertainment or politics but a large proportion of them are victims of many societal evils and traditional burden and lack even the basic necessities of life. They are the ones without any bank account of their own and fall under the major category of financially excluded (Maurya, 2015). As per Findex database, only 26% of female adults have a bank account in comparison with 44% of male adults in India (World Bank, 2014). From the experiences gained from most of the parts of Africa, Asia and Latin America, it is learnt that women tend to face more risk of violence, if they lack the power of economic autonomy (Capraro, 2017). Women in less developed and developing countries are somewhat found to be lower in status than that of men by various social evils and are relatively disempowered due to the acceptance of gender-specific norms. The process of guarding them against all kinds of violence is to make women empowered through access to education, employment and transformed social structure. Therefore, the phenomenon of upliftment of economic, social and political status of women in the society is known as women empowerment (Shettar, 2015). The 2030 Agenda for Sustainable Development and its 17 SDGs, adopted by world leaders in 2015, embody a roadmap for progress that leaves no one behind. Providing the same opportunities to women and men in all kinds of activities including decision-making ensures that interests of both the genders are taken into account in allocating resources. The 17 SDGs which are interdependent as action in one area will affect outcomes in others and that development must also balance social, economic and environmental sustainability. As per UNDP, through the pledge to Leave No One Behind, countries have committed to fast-track progress for those furthest behind first. That is why, the SDGs are designed to bring the world to several life-changing ‘zeros’, including zero poverty, hunger, AIDS and discrimination against women and girls (UNDP). Government along with civil societies and other shareholders has been globally endorsing gender equality through SDGs. There is a need of commitment in the proper implementation of SDGs in order to end violence against women and raise economic women empowerment (Dhar, 2018). Inequality in the accessibility of economic resources of women demonstrates inferiority in their status in any society and policies that do not consider women’s participation to its fullest incur billion dollars costs (Finnegan, 2015). In short, all the SDGs depend on the achievement of Goal 5 – gender equality, which can be framed into some targets as presented in Table 2.1.

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Table 2.1. Targets of SDG 5. Sl No.

i.

Targets

End discrimination

Description

End all forms of discrimination against women and girls everywhere ii. End violence and Eliminate all forms of violence against exploitation women and girls in the public and private spheres, including trafficking, sexual and other types of exploitation iii. End other harmful practices Eliminate all harmful practices, such as child, early and forced marriage, and female genital mutilation iv. Value unpaid care and Recognise and value unpaid care and domestic work domestic work through the provision of public services, infrastructure and social protection policies and the promotion of shared responsibility within the household as nationally appropriate v. Ensure female participation Ensure women’s full and effective participation and equal opportunities for leadership at all levels of decision-making in political, economic and public lives vi. Ensure access to Ensure universal access to sexual and reproductive health and reproductive health and rights as agreed rights in accordance with the Programme of Action of the International Conference on Population and Development and the Beijing Platform for Action and the outcome documents of their review conferences vii. Ensure women’s property Undertake reforms to give women equal rights rights to economic resources, access to ownership and control over land and other forms of property, financial services, inheritance, natural resources, etc. in accordance with national laws viii. Enhance use of technology Enhance the use of enabling technology, particularly information and communication technology, to promote women empowerment

SDGs in the Context of Slum Dwellers ix.

Enhance gender equality

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Adopt and strengthen sound policies and enforceable legislation for gender equality and empowerment of women and girls at all levels

Source: Author’s Compilation based on the excerpts taken from the United Nations (Department of Economic and Social Affairs, Sustainable Development).

If observed closely, the above stated goals look to be far away in its achievement in regards with women of slums. We present the implications of specific targets on the slum dwelling females in Table 2.2.

Conclusion Kolkata attracts population from rural regions as well as its adjacent states due to the opportunities of better livelihood. Not all these people get livelihood or housing when they migrate to the city of joy. The surplus labourers start living wherever they get vacant places irrespective of keeping a check on sanitation and hygiene (Batul & Palit, 2022). This is what increases the number of slums in the urban areas. More than half of the female slum dwellers have nuclear household structure, living with their husband and children whereas rest of them have joint family structure of household, living with elders and other relatives. Only 14% of female slum dwellers had education, reflecting 86% of them had no formal education at all. Therefore, it can be interpreted that lack of education is the major reason of their backwardness. In the absence of proper formal education, they are majorly involved in the informal sector for employment with insecure and irregular earning. Fifty-five percent of females are wage earners with irregular income, 26% are regular labourers usually earning weekly and 7% are casual labourers usually paid on monthly basis. The worst part is that, due to overcrowd of workers in urban centres, the wage rate tends to fall and probability of unemployment tends to rise as not all people who migrate into the city gets employed (Batul & Palit, 2022). On the banking front, 88% of the women operate their account with the help of others in filling up of bank forms, withdrawal, deposit, etc. and 34% do not even know how to write their names. Eighty-one percent of them had ATM cards yet more than half of the marginalised population was unaware about online banking and 92% do not use online banking. Illiteracy, irregular income or poverty and unawareness due to illiteracy are the major obstacles in the path of practising digitalisation by the slum inhabitants. These are the grand societal challenges that need to be addressed, if India aims to become cashless or fully digitalised. Huge part of the Indian population resides in the slums of the urban cities that have not received much attention by the policy initiators or researchers, in the context of digital technologies.

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Table 2.2. Implication of Targets of SDG Goal 5 for Female Slum Dwellers. Sl No.

i.

Targets

End discrimination

Implication

This just not seems to be true for slum women because the slum dwellers living in the urban areas are still excluded from the mainstream urban economy. ii. End violence and Slum inhabitants are more prone to exploitation violence and exploitation, since majority of their husbands and fathers are into alcohol and other types of addiction. iii. End other harmful practices Due to extreme poverty, slum girls are pushed in the direction of ill practices such as child, early and forced marriage, etc. iv. Value unpaid care and Slum people have more mouths to feed domestic work and fewer hands to work, because of which the recognition of unpaid care and domestic work remains abstract feeling for them. v. Ensure female participation Since most of them are daily wage earners, they do not get enough time to participate in any political and public commitments. Plus, their unawareness and illiteracy are major reasons that cannot ensure their participation in decision-making mechanism. vi. Ensure access to Slum dwellers lack basic sanitation, reproductive health and hygiene, drinking water and electricity rights facilities which have not been met for years, forget about reproductive and sexual necessities. They are more prone to air and water pollution that impact their overall health, leave alone reproductive health. vii. Ensure women’s property They are among the poorest in an urban rights centre and have been poor from the past generations, and therefore do not have any asset or wealth. In fact, their income is way less to fulfil daily requirements, and hence there is no point of making savings and accumulating wealth.

SDGs in the Context of Slum Dwellers viii. Enhance use of technology

ix.

Enhance gender equality

39

Here comes the main concept of this chapter, where we have already discussed and shown that use of technology does not reflect much success in case of slum dwellers, due to lack of education, unawareness and less income. With regards to what have been discussed earlier in this table, we conclude that gender equality and empowerment still look unachievable in terms of slum women.

Source: Author’s Study.

Recommendations and Implications Policy Implications i. Sanfeliu (2021) explains some of the following elements which can be looked upon to make the strategies more effective: • Recognising that a situation or public policy can impact different groups,

especially among vulnerable populations, in unequal ways. It is vital that every age group is considered and does not remain neutral. • There is the requirement of quality, timely, reliable and sufficiently disaggregated data. We need to engage with national and international bodies so that disaggregated data can be generated and disseminated transparently for the various vulnerable groups. • Incorporating elements of ‘evaluation thinking’ when designing or implementing a response. Incorporating this kind of thinking can help us detect and avoid potential problems in implementation, or to identify how various aspects or policies interact, compete or reinforce each other (identify synergies and trade-offs). • Help in reassessing local priorities to better reflect the most urgent needs of different populations (Sanfeliu, 2021). ii. OECD Policy Responses (2020) put forward the following concepts to deal with the issues and challenges of women empowerment: • Providing alternative public care arrangements. • Providing easier access to benefits targeted at low-income families, in

particular single parents, who are predominantly female. • Policy options to support victims of gender-based violence (OECD, 2020).

iii. UN-Women Facts & Figures (2020) has provided with a number of suggestions on ‘what government can do’, which are presented in the following points:

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Atiba Batul et al. • Scale up public awareness campaigns, particularly those targeted at men

and boys. • Increase funding to women’s organisations. • Provide cash transfers to women. Target individuals rather than households

to diminish women’s economic dependence on men. • Prioritise access to basic services. Increase the frequency of water delivery,

instal additional water storage and handwashing facilities, distribute free soap and sanitation products and suspend water and electricity shut offs in case of non-payment. • Expand and invest in universal gender-responsive social protection, including income support, as well as contributory and non-contributory social protection systems to increase women’s resilience to future shocks. • Strengthen social protection systems to cover all workers in formal and informal employment. Such protections should include paid sick and maternity leave, pensions and unemployment compensation (UN Women, 2020).

Implications for Research and Practice Works in the field of urbanisation are looked forward to be policy relevant in their queries and outcomes. There is a requirement of evaluative consideration of the methodological challenges associated with undertaking policy-relevant research and regard how newly evident methodological perspectives in sustainability can question expectations among the policy reformers about how the research in sustainability should be done. When in discussion about inclusive societal change, one should always begin with the concept of exclusion, to get a better understanding of who are excluded and how, so that efforts can be put in the right direction to make them included. This chapter analyses the usage of digital technologies and the achievement of SDG in the context of marginalised section of India, limiting its research to women from urban slums. Therefore, there is room for extended research in the context of this study, by considering all gender sample respondents. Almost every other literature that deals with digital technology or sustainability usually focuses on inclusion of the rural poor citizens. However, the population of slums has not been focused much. The mechanism of urbanisation and increment in urban slums are subject to unique causes and unique consequences, and still these challenges are greatly underexplored by earlier literature. Thus, there is a hint of direction of further research towards incorporating more slums from different states or different slums from the same state and undertaking a comparative study of state or national level. Digitalising financial services or strengthening slum dwellers technologically appears appealing when observed from upper surface but once we delve deeper, it will be seen that marginalised population still suffer from no electricity, no internet connectivity, no proper documents, etc. So, an over-dependence on technology and online initiatives to achieve targets set by the policymakers or

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service providers is impractical. Households from marginalised communities already struggle with the expense of basic and necessary facilities that are essential for human survival; it then becomes more difficult for them to be able to cope with the burdened expenses of digital add-ons. Just because we reside in urban areas that offers better infrastructure and employment opportunities compared to the rural counterparts does not essentially mean more like the statement ‘one size fits all’. This is because in the same urban area, there are existence of attractive multi-storeyed shopping complexes as well as the savagery of bastis along the drainage lines. Therefore, ignoring the socio-economic, societal and categorical divisions of urban population is an impractical concept of inclusion and empowerment. For many years, India has derived knowledge and inspiration from western models of urban planning, specifically education. Keeping an eye on the process of Indian urbanisation and urban development through the binoculars of western lens and trying to imitate western urban planning and development perspectives without realising their relevance in a country like India is no more advisable.

References Bag, S., & Seth, S. (2016). Understanding standard of living and correlates in slums: An analysis using monetary versus multidimensional approaches in three Indian cities. Working Paper No. 263. Centre for Development Economics, Delhi School of Economics. Bapat, D., & Bhattacharyay, B. N. (2016). Determinants of financial inclusion of urban poor in India: An empirical analysis. CESIFO Working Paper No. 6096 (pp. 1–31). Batul, A., & Palit, S. (2022). Environment and habitat assessment of the slum dwellers in Kolkata, India. International Journal of Advance and Innovative Research, 9(1), 97. Bhatia, S., & Singh, S. (2019). Empowering women through financial inclusion: A study of urban slum. Vikalpa: The Journal for Decision Makers, 44(4), 182–197. Capraro, C. (2017). Rights and realities: A briefing on women and the economy. Womankind Worldwide. Data from © OpenStreetMap. https://www.openstreetmap.org/copyright Dhanalakshmi, C. (2018). A conceptual study on cashless economy: Digital India. International Journal of Commerce and Management Research, 4(6), 135–136. Dhar, S. (2018). Gender and Sustainable Development Goals (SDGs). Indian Journal of Gender Studies, 25(1), 47–78. https://doi.org/10.1177/0971521517738451 Dominic, A., Saranya, K., & Rajani, G. K. (2018). A study on transformation in behaviour of individuals towards cashless economy. International Journal of Pure and Applied Mathematics, 118(18), 1365–1372. Finnegan, G. (2015). Strategies for women’s financial inclusion in the Commonwealth. Discussion Paper. Commonwealth Secretariat. Karmakar, P., Mishra, S., & Singh, R. (2020). Overall slum development through financial inclusion, livelihood and employability. Journal of Critical Reviews, 7(4). Kumar, V. (2020). The hybrid economy of the future. Academia.edu.

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Kumari, U. (2017). An empirical study of financial inclusion in urban poor of Kolkata. International Journal of Research in Economics and Social Sciences (IJRESS), 6(2), 4–30. Malik, F., Yadav, D., & Ismail, A. (2020). Purpose of savings and its determinants in case of destitute population: An empirical analysis of slum dwellers. International Journal of Social, Political and Economic Research, 7(3), 499–517. https://doi.org/ 10.46291/IJOSPERvol7iss3pp499-517 Maurya, P. (2015). Financial inclusion and women empowerment in India. ABS International Journal of Management, IV(2), 81. OECD. (2020). Women at the core of the fight against COVID-19 crisis. https://www. oecd.org/coronavirus/en/policy-responses Peck, D. (2018). An overview of the economics of Kolkata’s slums. https://doi.org/10. 13140/RG.2.2.29748.96641 Saha, A. (2016). Transition to cashless economy in North East India: A study on Kamrup (Rural) District of Assam. International Research Journal of Management Science & Technology, 7(11). Sanfeliu, M. (2021). What can think tanks do to make public policies more effective? Southern Voice. http://southernvoice.org/what-can-think-tanks-do-to-make-publicpolicies-more-effective Shettar, R. (2015). A study on issues and challenges of women empowerment in India. IOSR Journal of Business and Management, 17(4), 13–19. Singhraul, P. D., & Garwal, S. Y. (2018). Cashless economy – Challenges and opportunities in India. Pacific Business Review International, 10(9). Singh, R., Shinde, R., & Bakshi, M. (2019). Such is life: An observational case study on urban slum dwellers in Kolkata. Working Paper Series No. 825/April. Indian Institute of Management Calcutta. Tiwari, A. (2018). A study of financial inclusion of slum dwellers in the City of Nagpur, Maharashtra State. Journal of Emerging Technologies and Innovative Research (JETIR). UN-Women Facts & Figures. (2020). www.undp.org United Nations. Department of Economic and Social Affairs, Sustainable Development, Goal 5, Targets and Indicators. https://sdgs.un.org/goals/goal5 Varma, S. (2014). Census, NSSO differ on slum population figures. The Times of India. http://timesofindia.indiatimes.com/articleshow/28415537.cms?utm_ source5contentofinterest&utm_medium5text&utm_campaign5cppst

Chapter 3

Blockchain and Artificial Intelligence Technology in Professional Services Chandan Kumar Jha and Amit Sachan

Abstract In recent years, scholarly focus has shifted towards exploring the applications of disruptive technologies in professional services. These studies emphasise the need for further research in this domain. This research aims to comprehensively review the existing literature on the uses of blockchain, artificial intelligence (AI) and machine learning (ML) algorithms in professional services such as higher education, healthcare, financial securities firms and smart energy consulting. The rapid innovation and advancement in technology have led to substantial improvements in work efficiency and productivity. As industries transition towards sustainability and digitalisation, the role of energy-efficient systems becomes important in shaping smart factory designs and in further implementations. The uses of AI and other disruptive technologies for business operations not only boost production efficiency but also enhance customer satisfaction. Central to this transformation are strategies like deep learning and data/text mining, which facilitate the shift from conventional manufacturing practices to smart manufacturing. Apart from smart energy systems, the fields of higher education, healthcare and financial securities are witnessing a surge in the applications of AI, ML algorithms and blockchain technology and their contributions in emerging service economy. This study undertakes a comprehensive investigation into various factors associated with the application of disruptive technologies, evaluating their impact on the operational efficiency of professional service firms (PSFs). Through this research, we aim to identify gaps in the current literature and will suggest the directions for future research. Keywords: Artificial intelligence; blockchain; higher education; healthcare; professional services; sustainability; disruptive technologies

Fostering Sustainable Development in the Age of Technologies, 43–50 Copyright © 2024 Chandan Kumar Jha and Amit Sachan Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231005

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Introduction In recent years, the adoption of disruptive technologies such as artificial intelligence (AI), blockchain and Internet of Things (IoT) has significantly increased within businesses. Data and technology management through the cloud has emerged as a catalyst for efficiency, offering numerous advantages to organisations. These benefits include reduced data storage costs, heightened security measures and the scalability needed to address future challenges. Professional service sectors such as healthcare, higher education, hospitality, consulting, banking and insurance generate vast volumes of data encompassing business operations, client records, financial information, socio-economic data, feedback and reviews. These industries harness data analytics and visualisation techniques to glean deeper insights and predict trends and behaviours among their stakeholders. Arthur and Owen (2022) discussed the role of data and technological innovation in financial services. They conducted an exploratory, ethnographic study on small-medium sized company, which focuses on disruptive technology and analytics, to gain valuable insights from the banking sectors. Choi et al. (2022) mentioned in their research study that automation and data analytics have emerged as important forces in the digital age to increase productivity in manufacturing and services economy. AI, robotics, blockchain, IoT and augmented reality (AR) are few examples of disruptive technologies that can lead towards a dramatic shift in organisation’s growth and will provide competitive advantage. Their study extensively discussed about various types of disruptive technology and their role in upcoming Industry 5.0. Their study also highlighted the advantages and disadvantages of human–machine associations and unleashed the potential of disruptive technologies to achieve sustainable goals. Bloom et al. (2021) identified 29 disruptive technological innovations across US corporations and labour markets and discussed about their applications in multiple fields of economies and entrepreneurial domains. Pemer (2021) suggested a conceptual model which highlights the impact of disruptive technology and digitalisation on service workers, while considering the service climate and occupations as moderator. Their research findings highlighted how technology-service intelligence influences market competition and market demands. New digital technologies like automation, robots and AI make it possible to come up with new ideas that could change and disrupt the professional service sector. Their study also discussed the importance of leadership and technological innovation for the development of blended services and digital expertise in professional services (majorly discussed about only two professional service industries, i.e. auditing, and public relation/communication consulting, (Pemer, 2021) and provided the future research directions in this context (Castaldi & Giarratana, 2018; Keating et al., 2018; Pemer, 2021; Powers et al., 2022; Tomo et al., 2019). Therefore, the purpose of this research work is to address the current research gaps highlighted in the past studies. This study will discuss the impact of technological innovations/disruptive technology in various professional services (Brandon-Jones et al., 2016; Harvey et al., 2016; Singh & Rennstam, 2022; von Nordenflycht, 2010) such as healthcare, consulting, tourism, higher education, energy, etc. in further sections.

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AI/ML and Blockchain Applications in Professional Services Professional services firms (PSFs) such as accountancy, legal, advertising, banking, IT, consulting, hospitals and universities have gained a lot of attention for research in recent years and has a significant impact on the knowledge economy (Castaldi & Giarratana, 2018; Dobrzykowski et al., 2016; Khaksar et al., 2020; O’Higgins et al., 2021; von Nordenflycht, 2010). von Nordenflycht (2010) reviewed the scholarly literature and identified key characteristics of professional services which depends on skilled workforce with expertise and knowledge intensity, who focuses mainly on non-routine, creative and consulting works. Disruptive technology such as AI has automated professional services works and contributed to decision-making in critical situations, like use of AI in medical radiology (Sampson, 2021) and encourages the multidimensional nature of innovation capability in professional service firms (Hogan et al., 2011; Tomo et al., 2020). Rust and Huang (2014) mentioned the disruptive technology such as big data analytics, cloud computing and machine learning are the main drivers of the service economy’s growth. In recent years (during COVID-19 and post COVID-19), the use of disruptive technologies in healthcare industry increases significantly. Yaqoob et al. (2022) discussed about different applications of blockchain in healthcare systems such as auditable, trusted and secure database management while ensuring transparency, accessibility and traceability. Their study found that blockchain applications in healthcare can boost operational efficiency and data security. Blockchain-based healthcare data management helps improve healthcare service quality. IoT-based health devices/smart applications with end-to-end connectivity control can bridge the gap between hospital-centric medical checks into home-centric check-ups and may save lives in emergency situations (Chukwu & Garg, 2020; Mettler, 2016; Yaqoob et al., 2022). Huang and Rust (2021) briefly discussed about automatic speech emotion detection and considered it as the next generation of AI (mechanical, analytical, intuitive and empathetic analytics/AI roles in services) and has the potential to contribute to customer-centric services in healthcare, banking, security and other PSFs. Andoni et al. (2019) highlighted the role of disruptive technology in energy sector and suggested the need for ‘decarbonisation, decentralisation and digitalisation’. These are the three main global movements (decarbonisation, decentralisation and digitalisation), emerged in Industry 4.0 as uses of data and technological innovation (disruptive technology) increases gradually. The empirical research work of Arifin (2022) indicates that firms can get competitive advantages by using disruptive technologies and their utility in innovative manner. Sehnem et al. (2022) examined the role of disruptive technological innovation for managing data and business requirements under resource constraint situations, while supporting the sustainability goals. Industry 4.0 focuses majorly on system integration (end-to-end control) and disruptive technologies. As global markets become more competitive and volatile, companies must reassess and rethink on their traditional business models and way they are managing operations (Dias et al., 2022). Fragni`ere et al. (2022) studied the role of blockchain as disruptive

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technology in tourism industry. They conducted a total of 18 semi-structured interviews of managers, senior managers, directors, executive directors, entrepreneurs from various types of organisations related to tourism industry such as IT for tourism sector, hotel association, tourism digital marketing, online tourism agency, etc. Their finding highlights the adaptation of technological innovation in European tourism sector and integration with global digital value chain. Their study suggests that blockchain as a disruptive innovation can be a unique opportunity for government/policymakers to promote ecological and digital transitions in the tourism sector. Blockchain, as a disruptive technology, has lot of potential to change the tourism industry. Kwok and Koh (2019) discuss the benefits and potential obstacles associated with the implementation of blockchain technology as well as practical consequences for tourism stakeholders. As power shifted from suppliers to consumers, the emergence of online travel agencies has changed the market dynamics of the tourism industry. Rashideh (2020) conducted the semi-structured interviews with the tourism industry experts to explore the role of intermediary’s partners/channels in tourism business and future challenges for adopting the blockchain technology in tourism. The goal is to create a blockchain-based framework for the industry. Their findings suggested that disruptive technological adaptation will remove the intermediaries from the supply chain of the tourism industry. There has been a lot of scholarly debate in the literature on disruptive technological innovation in various services economy. According to Ritala et al. (2022), disruptive innovation may offer established organisations many opportunities for business development and growth opportunities in global market. During pandemic and post pandemic, technological innovation affected the client’s expectations and consulting service. The digital transformation, as well as the accessibility of data and analytical tools to clients, appeared to be threats to traditional ways of managing consulting business of PSFs. Mamedova et al. (2022) argued that there is a need to formulate more regulation and standards for consulting services business, in terms of uses of data and disruptive technology, considering the stakeholders expectations. Sun et al. (2018) investigates the uses of big data analytics to improve the business intelligence for industrial systems, products and services. Oyewo and Tran (2021) examined the impact of big data analytics on the competitiveness of PSFs. They collected the responses from 118 consulting firms and used structural equation modelling to test their hypothesis. Their finding supports the argument that the implementation of big data analytics can increase the competitiveness of consulting firms. Apart from AI, blockchain, big data analytics and cloud computing’s rapid adoption significantly impacted the business environment of IT services and consulting. Nieuwenhuis et al. (2018) conducted 15 expert interviews and identified that the data management and technological infrastructure value for consulting services can be improved further by using cloud computing as disruptive technology. Flavin (2016) discussed about the uses of disruptive technologies in higher education. Current practices in technology-based education have implications for the future of higher education. The recent pandemic period has shown the importance of digitalisation in higher education. Bucea-Manea-

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Țonis¸ et al. (2021) discussed the applications of blockchain as disruptive technology in higher education. The basic applications of blockchain in higher education include the data management for students (personal, online recordings, video lectures, feedbacks from faculty mentors, marks/assessment scores, etc.), professors (personal, research publications, courses, feedbacks, patents and project work, etc.) and file storages. It can be used for rewards as smart contracts and digital badges also. Blockchain technology will help educational institutions to have better learning platforms and sustainable business model.

Conclusion and Future Research Directions The digital transformation, use of data and technology plays an important role for professional services firms as the global economy shifts towards knowledgebased and service-oriented. The majority of knowledge management research is concerned with the acquisition, retention and reuse of explicit knowledge, which can be a source of competitive advantage (Martinsons et al., 2017). Kv˚alshaugen et al. (2015) discussed about the two dynamic capacities that drive innovation are diversifying the service portfolio and knowledge accumulation. Chang et al. (2020) mentioned that blockchain technology has the potential to enhance the efficiency and security of banking and financial industry. Several new technologies have arisen in recent years with the potential to disrupt many aspects of society. Ronzhyn et al. (2019) highlighted the need for research and training for IoT, AI, virtual reality (VR), AR and big data technology for government agencies/public sectors. Boone and Ganeshan’s (2001) and Hund et al. (2021) study supported the role of organisational experience and productivity in a professional service firm (PSFs). Their research study highlighted the research gap in the existing literature and argued the need for further study to examine the impact of organisational experience and role of data and technology for productivity improvements. The findings of their research work indicate a positive relationship between the uses of disruptive technologies and productivity if it is a part of production process, not simply used for collection of data/files, etc. In future, researchers can do further research on the role of digital technology in knowledge recombination, i.e. how disruptive digital innovation and technology are impacting the human capabilities in various phases of knowledge recombination.

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Bloom, N., Hassan, T. A., Kalyani, A., Lerner, J., & Tahoun, A. (2021). The diffusion of disruptive technologies. https://doi.org/10.3386/w28999 Boone, T., & Ganeshan, R. (2001). The effect of information technology on learning in professional service organizations. Journal of Operations Management, 19(4), 485–495. https://doi.org/10.1016/S0272-6963(00)00064-4 Brandon-Jones, A., Lewis, M., Verma, R., & Walsman, M. C. (2016). Examining the characteristics and managerial challenges of professional services: An empirical study of management consultancy in the travel, tourism, and hospitality sector. Journal of Operations Management, 42–43(1), 9–24. https://doi.org/10.1016/j.jom. 2016.03.007 Bucea-Manea-Țonis¸, R., Martins, O. M. D., Bucea-Manea-Țonis¸, R., Gheorghiț˘a, C., Kuleto, V., Ili´c, M. P., & Simion, V.-E. (2021). Blockchain technology enhances sustainable higher education. Sustainability, 13(22), 12347. https://doi.org/10.3390/ su132212347 Castaldi, C., & Giarratana, M. S. (2018). Diversification, branding, and performance of professional service firms. Journal of Service Research, 21(3), 353–364. https:// doi.org/10.1177/1094670518755315 Chang, V., Baudier, P., Zhang, H., Xu, Q., Zhang, J., & Arami, M. (2020). How Blockchain can impact financial services – The overview, challenges and recommendations from expert interviewees. Technological Forecasting and Social Change, 158, 120–166. https://doi.org/10.1016/j.techfore.2020.120166 Choi, T., Kumar, S., Yue, X., & Chan, H. (2022). Disruptive technologies and operations management in the Industry 4.0 era and beyond. Production and Operations Management, 31(1), 9–31. https://doi.org/10.1111/poms.13622 Chukwu, E., & Garg, L. (2020). A systematic review of blockchain in healthcare: Frameworks, prototypes, and implementations. IEEE Access, 8, 21196–21214. https://doi.org/10.1109/ACCESS.2020.2969881 Dias, S., Espadinha-Cruz, P., & Matos, F. (2022). Understanding how Additive Manufacturing influences organizations’ strategy in knowledge economy. Procedia Computer Science, 200, 1318–1327. https://doi.org/10.1016/j.procs.2022.01.333 Dobrzykowski, D. D., McFadden, K. L., & Vonderembse, M. A. (2016). Examining pathways to safety and financial performance in hospitals: A study of lean in professional service operations. Journal of Operations Management, 42–43, 39–51. https://doi.org/10.1016/j.jom.2016.03.001 Flavin, M. (2016). Technology-enhanced learning and higher education. Oxford Review of Economic Policy, 32(4), 632–645. https://doi.org/10.1093/oxrep/grw028 Fragni`ere, E., Sahut, J.-M., Hikkerova, L., Schegg, R., Schumacher, M., Gr`ezes, S., & Ramseyer, R. (2022). Blockchain technology in the tourism industry: New perspectives in Switzerland. Journal of Innovation Economics & Management, 37(1), 65–90. https://doi.org/10.3917/jie.pr1.0111 Harvey, J., Heineke, J., & Lewis, M. (2016). Editorial for Journal of Operations Management special issue on “Professional Service Operations Management (PSOM). Journal of Operations Management, 42–43(1), 4–8. https://doi.org/10. 1016/j.jom.2016.03.005 Hogan, S. J., Soutar, G. N., McColl-Kennedy, J. R., & Sweeney, J. C. (2011). Reconceptualizing professional service firm innovation capability: Scale development. Industrial Marketing Management, 40(8), 1264–1273. https://doi.org/10.1016/ j.indmarman.2011.10.002

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Chapter 4

Confrontation Strategy for Evolution of Future Employment Donghun Yoon

Abstract Industry 4.0 refers to an era in which human work, creative activities and professional knowledge are largely replaced by artificial intelligence (AI) and robots. Due to the current exponential rate of technological development and the infinite expansion and generalisation of technologies, it is not difficult to predict that these technologies will spread at exponential rates and will spur massive changes in the adopted production, management and governance mechanisms and in the future employment market. Especially, employment changes are inevitable with the rise in automation and the job scope and prospects are bound to vary widely. In this chapter, confrontation strategies for employment in Industry 4.0 are proposed. It is hoped that this study will be able to provide an accurate direction for future employment and will be able to contribute to the study of employment policies and Industry 4.0. Keywords: Industry 4.0; employment; confrontation strategies; future; evolution; human; smart factory; artificial intelligence

Introduction The evolution of employment in Industry 4.0 is a key issue and is everyone’s most important concern at present. On the manufacturing side, consumers want smart services, reasonable prices and faster delivery of their purchased items. Communication skills that accurately reflect customer needs and read market trends will be a key to manufacturing in Industry 4.0 (Wang, 2018). There will be a new business model that combines machinery, electronics, telecommunications, natural sciences, humanities, social sciences, art, media and policies resulting in new types of jobs (Xu et al., 2018). Examples of such jobs include cloud service provider, software developer, engineering maintenance service provider, Fostering Sustainable Development in the Age of Technologies, 51–62 Copyright © 2024 Donghun Yoon Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231006

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single-person company, corporate external social worker, home office worker and platform provider. The emergence of AlphaGo, however, a computer program that plays the board game ‘Go’, and its success in beating a handicap-free human professional Go player on a full-sized board, has caused widespread job apprehension. That is, people have come to fear that their jobs will soon be taken over by artificial intelligence (AI) and robots. Indeed, simple, repetitive tasks in the workplace can be handled by robots, and humans need to find new and better jobs (Liu & Xu, 2017). Rather than simply recognising robots as employment rivals, however, ways of living harmoniously with them should be sought. Discussed in this chapter are the proposed confrontation strategies for employment in Industry 4.0. The changes in the industrial structure and global trend in Industry 4.0 will first be presented and discussed, and then the impact of Industry 4.0 on future employment will be examined. Also, confrontation strategies for employment in Industry 4.0 will be proposed.

Literature Review In Germany, the smart manufacturing has been called ‘Industry 4.0’, whereas comparable initiatives outside Europe are called ‘Advanced Manufacturing Partnerships’ for the United States or ‘Made in China 2025’ for China (Dujin et al., 2014; Kagermann et al., 2013). Smart manufacturing is a key element in Industry 4.0 (Jiang et al., 2020). Industry 4.0 is increasingly being promoted as the key to improving productivity, promoting economic growth and ensuring the sustainability of manufacturing companies (Rosin et al., 2020). Emerging technological developments are likely to bring widespread automation and irreversible shifts in the structure of jobs, raising major challenges on labour markets and for policymakers responsible (Kergroach, 2017). Advances in machine learning (ML), robotics and AI will inevitably prompt automation, changing labour demand and driving job movement (Brynjolfsson & McAfee, 2011). Although the occupational structure has already evolved in many countries, job creation polarising high-skilled and low-skilled occupation groups and job losses concentrated in middle-skilled routine occupations (Autor & Dorn, 2013; Goos et al., 2009). The way we work will be one of the most affected changes in Industry 4.0 (Gebhardt et al., 2015). Industry 4.0 will not only affect technology and production, but also the way we will work in all its dimensions (BAS, 2015). This transformation of the work environment will change the job profiles and therefore requires employees to be outfitted with a wide range of competency ¨ Materialfluss und Logistik, 2016; Kagermann (Acatech, Fraunhofer Institut fur et al., 2013; Smit et al., 2016). Research is still evolving towards the development of frameworks linking Industry’s 4.0 enabling technologies to specific goals and to their impact on the manufacturers’ businesses (Calabrese et al., 2022). Industry 4.0 strategy does not only revolutionise the manufacturing system and processes but also lead to the formation of the intelligent supply chain (Xie et al., 2020). Industry 4.0 involves interconnecting the virtual–digital and physical world, as well as ML in production. This includes machines, products, information and

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communication systems and humans. This goes hand in hand with discussions about the future of labour under these circumstances (Autor, 2015; Frey & Osborne, 2013; Weber, 2016).

Changes in the Industrial Structure and Global Trend Through Industry 4.0 The United States is building a manufacturing ecosystem using the industrial Internet of Things (IoT). Germany is pushing for policies that emphasise practicality, such as expanding the smart factories for medium and small businesses. Japan has utilised the economic issues and manufacturing innovation opportunities presented by Industry 4.0. China is focusing on R&D and product/service quality improvement to transform itself into a manufacturing powerhouse centred on qualitative growth. As for South Korea, to take advantage of Industry 4.0 as an opportunity for industrial development, the country is expanding its investments in areas that have significant industrial and economic ripple effects, including labour, legal systems and IoT. The Industry 4.0 strategies of major countries are compared in Table 4.1. The annual average growth rates of market capitalisation in areas related to Industry 4.0 in major countries (%) are presented in Table 4.2. In most of these

Table 4.1. Comparison of Industry 4.0 Strategies of Major Countries. Classification Major policy

The United States

AMP Industry 4.0 (Advanced (2012.3) Manufacturing Partnership) 2.0 (2013.9)

Characteristics Private leadership through technology and funds Core Industrial IoT, technology big data, AI

Method

Germany

Private leadership

Data source: The author’s own data.

Participation of small and medium businesses Industrial IoT, automation facilities, solutions Public–private cooperation

Japan

China

Leading strategy for the Fourth Industrial Revolution (2016.4) Reorganisation of industrial structure

Chinese manufacturing 2025 (2015.5)

Industrial IoT, industrial robots

Industrial IoT, ICTs

Public–private cooperation

Government leadership

Expectation of quality growth in manufacturing

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countries, the growth of industries related to Industry 4.0 is faster than the growth of other industries. In particular, the market capitalisation growth rates in the pharmaceutical and biotechnology sectors were both higher than the overall market capitalisation growth rate. The market capitalisation percentage changes in areas related to Industry 4.0 in major countries are presented in Table 4.3. The United States has attempted to transplant its information and communication technology (ICT) strengths to its various industries, and the government supports expanding the R&D investment in basic technologies by developing a pre-emptive system (Table 4.4). Japan is focusing on utilising data by developing national innovation projects using relative-dominance technologies like robots. China relies on the strong support from the government and the large domestic market. South Korea has a high share of hardware and equipment. The relative technology levels of major countries in Industry 4.0 are presented in Table 4.4.

Impact of Industry 4.0 on Future Employment The effect of Industry 4.0 on future employment varies from job to job, but 65% of the current jobs are expected to disappear in the future. In particular, these jobs are the low-paying ones requiring low-level skills and involving carrying out repetitive tasks, such as jobs related to transportation, production, administrative support, sales, services and construction. Technological advances (e.g. robots, AI, ML and software automation apps) will eventually lead to a point where the ability of these workers to perform most of their daily tasks will be commensurate to the robots’ ability to do the same, or may even be exceeded by the latter. Thus,

Table 4.2. Annual Average Growth Rate of Market Capitalisation in Areas Related to Industry 4.0 in Major Countries (%). Classification Capital good Pharmaceutical and biotechnology Semiconductor and related equipment Software and service Hardware and equipment Communication service Overall market capital increase (%) Data source: BioINpro (2017).

United States

Germany Japan China

South Korea

5.2 11.5

4.1 22.8

1.7 4.4

36.3 33.2

15.3 29.5

2.6

4.4

22.8

38.7

24.8

13.0 8.9 10.8 2.4

6.0 20.7 1.6 9.2

1.3 0.5 4.4 20.1

44.8 33.4 10.0 32.4

37.2 11.4 3.6 14.6

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Table 4.3. Percentage Change in Terms of Market Capitalisation in Areas Related to Industry 4.0 in Major Countries (%). United States Classification

Germany

Japan

China

South Korea

2006 2015 2006 2015 2006 2015 2006 2015 2006 2015

Capital good Pharmaceutical and biotechnology Semiconductor and related equipment Software and service Hardware and equipment Communication service

8.5 6.1

6.9 18.2 10.5 13.0 13.8 10.1 12.9 13.1 12.2 8.4 3.5 9.0 3.6 4.8 3.6 3.7 1.0 2.7

3.7

2.4

2.2

1.3

1.7

1.2

0.5

0.7

2.5

4.7

7.6

11.9

8.4

5.7

3.4

3.5

1.0

2.2

1.5

6.6

4.6

5.2

0.3

0.1

7.1

6.8

4.3

4.5 29.3 19.8

1.6

2.0 10.1

4.6

4.3

5.8

1.9

0.3

8.2

2.9

Data source: BioINpro (2017).

these tasks are likely to be carried out by robots and AI in Industry 4.0. The aforementioned advanced technologies, however, are expected to affect not only these types of jobs but also jobs requiring advanced skills, education and training, such as those of doctors and lawyers. No job is entirely safe, but jobs requiring empathy, communication skills and close human relationships (e.g. those of nurses and customer service providers) are difficult to replace with robots or automation. This is because talking to machines can never replace talking to one’s fellow humans, and humans will sooner or later get tired of the former. This notwithstanding, Industry 4.0 is likely to result in wide-scale structural unemployment. With the emergence of platform chemistry, though, which consolidates knowledge in the chemistry, chemical engineering and food technology fields, and

Table 4.4. Relative Technology Level of Major Countries in Industry 4.0. Classification Industrial IoT Big data AI

The United States

The European Union

100

85.6

82.9

70.6

80.9

100 100

88.9 86.8

87.7 81.9

66.4 66.1

77.9 70.5

Data source: Trend of Farm Household (2017).

Japan China

South Korea

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eventually of the platform economy, work conditions are becoming more flexible. The platform economy is a form of economic activity in which suppliers and consumers of goods and services transact with each other based on a digital platform that connects the businesses and consumers in the network. The employment type in this system does not allow employment contracts, wage standards, labour-time regulations, fixed jobs and union membership. A case in point is Uber. Uber focuses only on the connection between supply and demand. It does not own cars but became the world’s largest carrier. It also has no employment contracts, paying its drivers only when they work and the drivers are responsible for their own social protection, workplace health and safety. Digital management will thus have a huge impact on labour–management relations. Managers will be able to manage the company efficiently with digital and smart equipment. From the point of view of the employees, they will lose their autonomy in the workplace. Their work will be completely monitored, and they will need to justify their position and to earn the trust of their managers and the company’s other employees. The new technology should also be able to clearly predict the needs and delivery plans of the customers of restaurants, retailers and other companies. The customers will be interested in creating a just-in-time schedule for the workers. Work without frontiers such as this is more likely to cause stress and burnout. Mobile work based on ICT will also lead to labour concentration. Holland’s theory seeks to find a job climate in which people’s careers and professional aptitudes are classified into six categories capable of displaying their abilities and skills and expressing their attitudes and values. Job selection is also determined by the interaction between the work environment and the employee’s characteristics, and between the employee’s personality and interests. To illustrate this, RIASEC is presented in Fig. 4.1. Holland’s theory can be turned into a research model for Industry 4.0. The said research model is shown in Fig. 4.2.

R (Realistic)

I (Investigative)

C (Conventional)

A (Artistic)

E (Enterprising)

Fig. 4.1.

S (Social)

RIASEC. Data source: Nauta (2010).

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Confrontation Strategies for Employment in Industry 4.0 Government Industry 4.0 is the most important strategic motivation for enhancing the competitiveness of a country and its businesses because it increases productivity and threatens jobs. It is important for the government to establish policies that will allow the technologies in Industry 4.0 to increase the corporate productivity while creating new jobs. It is also important to set policies for the development of the country’s human resources and of their roles in industry and labour. The government should drastically lift all restrictions in this regard. Regulations should be removed from all industrial areas, except safety and hygiene, so that enterprises can pioneer new industrial areas and create new jobs. As Industry 4.0, however, is characterised by the platform economy and monopoly by a handful of companies under such system, it is also necessary to take countermeasures to abuse. The government should play a central role in setting a new direction for labour–management relations in response to the rapidly changing industrial structure and labour conditions, and should create a foundation for enhancing the workers’ capabilities. The government should also lead the efforts to analyse the tasks common to all the industries and to reflect these in the training qualification tests that are required to be passed. It should also strengthen the social safety nets for those who will become unemployed in Industry 4.0, and education and financial and other forms of support should be provided to them. Lastly, it is necessary to establish policies to foster creative digital talent.

R (Realistic) I (Investigative) C (Conventional) Industry 4.0 A (Artistic) E (Enterprising) S (Social)

Fig. 4.2.

Research Model. Data source: Fig. 4.1. RIASEC utilised as the research model for Industry 4.0.

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Enterprises Many enterprises around the world are already adopting smart factories by combining their existing production processes with advanced technologies like robots, AI, IoT, virtual and augmented reality (VRAR), big data and three-dimensional (3D) printers. New products featuring advanced technologies are constantly being released, and many start-ups are entering the market with new business models utilising online platforms. Enterprises, however, should create workspaces centred on the workers. Germany’s Industry 4.0 and Work 4.0, for instance, promote worker-oriented workplaces. Workplaces centred on workers have two meanings: highly ergonomic workplaces and workplaces pursuing production innovation led by skilled engineers. Improving the workplace to make it more ergonomic means improving the workplace environment in a way that will enhance worker productivity by installing an automated system in the technical field while also reducing the employees’ physical and mental burdens. Production innovation led by experienced engineers, on the other hand, is a strategy of converting digitalisation into a smart factory with a flexible production system, and into a system that can make the most of the workers’ skills. In a smart factory, high agility is important in an emergency. Unexpected accidents are unlikely to happen in a smart factory, but when they do, the loss is bound to be enormous, requiring prompt judgement and action by experienced technicians. Experienced technicians’ accumulation of the usual know-how is important because many accidents cannot be addressed by referring to a prepared manual. Thus, enterprises should foster skilled technicians rather than machines. An enterprise cannot expect better innovation if it is only filled with machines and does not have skilled engineers who can actively utilise the Industry 4.0 technologies. Enterprises should also expand their markets and develop global competitiveness. This is the management goal of all enterprises, and is also the most basic strategy for creating jobs. Enterprises should focus on retraining and fostering their employees. While promoting process and product innovation, enterprises should prepare their employees by proactively analysing what employee tasks and capabilities are required for the changes that are bound to happen. Education and training programmes should be developed based on the results of the newly required job analysis. Also, employees should be given many job training opportunities. Labour and management should lead Industry 4.0 together. They must understand each other and actively work together to promote Industry 4.0, such as in the area of factory automation. Enterprises should also actively deal with the expected changes in the technology environment by flexibly rebuilding their organisation and personnel management system, such as the workplace environment, employment and employee education and training, so that they would be able to cope with such changes.

Education The proposed educational strategy for preparing for Industry 4.0 is based on the following expected changes and requirements. Job change and capacity

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improvement will be required. Knowledge-intensive rather than repetitive activities will increase in the manufacturing production lines. There will also be an increase in the number of tasks requiring high levels of expertise and skills. Digitising the work style will reduce the role of the skilled technician or will allow one person to assume multiple responsibilities; thus, the employees will need digital literacy. Regarding the required skills for the employees, these will be the more common and general skills rather than expertise in specific fields. Critical thinking, empathy, creativity, convergence, cultural diversity and collaboration skills will be important, and the employees will have to be capable of adapting to the rapidly changing environment. In the future, the use of software and digital devices as well as digitalisation and understanding of ICT will be essential at all worksites. As such, education should be provided to the employees to enhance their digital literacy. Basic education training systems should therefore be created, and these should enable the employees to better adapt to the rapid changes in technology and production methods. The vocational training capacity of the field employees should also be increased. In the Industry 4.0 era, more learning should take place in the workplace because the knowledge and skills that need to be acquired by the employees will be more atypical, and the importance of problem-solving skills will thus increase. Innovation should be pursued in terms of the employee training methods to be employed, and professional engineers should be utilised for training purposes. In addition, training contents using advanced technologies like VR and AR should be developed and expanded by platform. On the whole, the education and training system should be changed so that it would be able to respond to the changes that are expected to occur in the industrial structure.

Employees To survive the global competition, productivity improvement and innovation are needed. This will call for automation and digitalisation, which will eliminate many jobs, with some jobs inevitably being affected. When the technology employed for a particular task is replaced, however, people who can perform the new tasks involved will be needed. Thus, even when AI and robots are applied to business, humans will still be essential to the economy and industry. Employees, though, need to be prepared to actively understand the changes that will occur in the global economic and technological environments. Employees, for their part, should have the basic attitude of actively trying to understand the changes that are bound to happen in Industry 4.0. As the employee positions will surely be reduced with technology advancement, it is important for companies to increase their competitiveness and to find promising business areas. On the other hand, it is important for employees to develop new capabilities and to actively seek to acquire know-how in the utilisation of new technologies. In the Industry 4.0 era, the industrial environment should be given more importance, along with critical thinking skills and know-how; as such, highly skilled engineers will be at the centre of the workplace and will implement technology acquisition roadmaps so

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that the employees can be relocated to the future industrial sites. Technology introduction should be actively engaged in, but it should be ensured that the technology acquisition process will not just improve the company’s productivity but will be an innovation centred on the employees. In Industry 4.0, the employees should develop an interest in improving their own work environment. The Industry 4.0 technologies will affect not only jobs but also the employment type, work style and work–home harmony. Therefore, it is necessary to safeguard the employees’ rights by actively seeking the employees’ opinions on how to revise the labour laws and private regulations in light of the existing labour issues.

Policy Discussion and Research Implications For ideal future employment, new issues in various areas should be negotiated to seek a new social consensus. This is possible if the state behaviour, wage negotiations, etc. are carried out specifically through the enterprises. First, an innovative and learning society is needed. This requires responding to new risks and safeguards. A new road has to be built in terms of the digital economy, an innovative process consistent with the social market economic principles. Correction methods should be presented for the flaws in the new business models and for the uncertain job configurations and data use. Second, labour and the national society must always be considered together. The social security system should provide prior and reactive support to businesses and employees. The fundamental social and protection rights of all the employees worldwide should be upheld. The government should work flexibly with the social infrastructure. Small and medium businesses and their employees as well as self-employed individuals should also be considered, and national financial support and public finances should be provided to them. Third, wage negotiations and joint decision-making authority are also very important in the digital economy as these enable flexible solutions to be worked out and a consensus to be reached. The government needs to make room for negotiations, and to devise institutional measures like the minimum wage system. Fourth, the living corporate culture (communication, leadership, personnel management) is a critical factor affecting the work conditions. When voluntary self-management and mutual control are possible, joint decisions will be respected. Health is a very important value and an important factor affecting the quality of life of people. It has important implications for capacity development, innovation and motivation. Employee happiness is a very important factor contributing to the success of an organisation. It is a crucial element of competitiveness and an important corporate culture element for investment decisions. All in all, ensuring better jobs is very important as it will enable enterprises to secure outstanding manpower and to boost the productivity of the national economy.

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Conclusions The evolution of employment in Industry 4.0 is a major issue that concerns everyone. Many of the current jobs will disappear then, and many new jobs will emerge. Robots and AI will usher in many changes in people’s daily lives and are the most essential factors that will determine the direction of the evolution of employment. Industry 4.0 will promote the evolution of employment as robots and AI will work in cooperation with humans. Platforms have the same characteristics as living creatures that evolve into arbitrary forms, not fixed networks, eliminating the distinctions among the producers, sellers and retailers. The concept contrasts with the economy in which production, distribution and consumption are connected in a single value chain. Institutional and legal improvements are needed to ensure good employment in Industry 4.0. It is also necessary to implement work involving creative knowledge, and to foster employees who can establish their own labour supply plans. In the future, it is likely that flexibility will be a priority; the future employment will be a far cry from the current employment paradigm. Therefore, it is necessary to prepare for it. In this chapter, the changes in the industrial structure and global trend that are likely to occur in Industry 4.0 are presented and discussed. Also discussed is the impact of Industry 4.0 on future employment. Confrontation strategies for employment in Industry 4.0 are proposed and discussed in terms of the government, enterprises, education and employees. Also proposed and discussed are response strategies from the perspective of the government, industry, education and labour. Policy discussions based on such response strategies are also featured. It is hoped that this study will provide an accurate direction for the future employment and will contribute to the study of employment policies and Industry 4.0. In the future research, we will discuss and present the government’s institutional support, economic and social effects of the evolution of employment in Industry 4.0.

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Calabrese, A., Dora, M., Ghiron, N. L., & Tiburzi, L. (2022). Industry’s 4.0 transformation process: How to start, where to aim, what to be aware of. Production Planning & Control, 33(5), 492–512. ¨ Dujin, A., Geissler, C., & Horstkotter, D. (2014). Industry 4.0: The new industrial revolution. Roland Berger Strategy Consultants. Frey, C. B., & Osborne, M. A. (2013). The future of employment: How susceptible are jobs to computerisation? Oxford Martin School. Gebhardt, J., Grimm, A., & Neugebauer, L. M. (2015). Developments 4.0 Prospects on future requirements and impacts on work and vocational education. JOTED, 3, 117–133. Goos, M., Manning, A., & Salomons, A. (2009). Job polarization in Europe. The American Economic Review: Papers & Proceedings, 99(2), 58–63. Jiang, H., Sun, S., Xu, H., Zhao, S., & Chen, Y. (2020). Enterprises’ network structure and their technology standardization capability in Industry 4.0. Systems Research and Behavioral Science, 37(4), 749–765. Kagermann, H., Wahlster, W., & Helbig, J. (2013). Recommendations for implementing the strategic initiative Industrie 4.0. Report. Industry 4.0 Working Group. Kergroach, S. (2017). Industry 4.0: New challenges and opportunities for the labour market. Foresight and STI Governance, 11(4), 6–8. Liu, Y., & Xu, X. (2017). Industry 4.0 and cloud manufacturing: A comparative analysis. Journal of Manufacturing Science and Engineering, 139(3), 1087–1357. Nauta, M. M. (2010). The development, evolution, and status of Holland’s theory of vocational personalities: Reflections and future directions for counseling psychology. Journal of Counseling Psychology, 57(1), 11–22. Rosin, F., Forget, P., Lamouri, S., & Pellerin, R. (2020). Impacts of Industry 4. 0 technologies on lean principles. International Journal of Production Research, 58(6), 1644–1661. ¨ Smit, J., Kreutzer, S., Moller, C., & Carlberg, M. (2016). Industry 4.0.Report. European Parliament. Trend of Farm Household. (2017). 15. Korea Rural Economic Institute. https://www. krei.re.kr Wang, D. (2018). Building value in a world of technological change: Data analytics and Industry 4.0. IEEE Engineering Management Review, 46(1), 32–33. Weber, E. (2016). Industry 4.0 – Job-producer or employment-destroyer? Current report (pp. 1–7). Institute for Employment Research. Xie, Y., Yin, Y., Xue, W., Shi, H., & Chong, D. (2020). Intelligent supply chain performance measurement in Industry 4.0. Systems Research and Behavioral Science, 37(4), 711–718. Xu, L. D., Xu, E. L., & Li, L. (2018). Industry 4.0: State of the art and future trends. International Journal of Production Research, 56(8), 2941–2962.

Chapter 5

Framing the Digital Transformation Journey for Sustainability Based on the Lenses of Integrated Skills and Competencies for Future Work Joseph Odhiambo Onyango

Abstract This chapter frames the digital age transformation journey for sustainability from the lenses of transformation skills and competencies required for future work. It provides a synopsis of the digital transformation considering digital technologies, connecting digital transformation to future work and reflections on the new digital age to sustainability issues. In detail, this chapter comprehensively reviews digital technologies transformation skills, including digital skills and integrated skills for the digital economy linked to integrated skills. This chapter takes into consideration the possible effects from a competency point of view from the domains on issues like: global independence, trust, a shift in skills and ways of work, commitment to justice, improving the know-how, financial inclusion, data and data privacy that are critical imperatives for sustainability. Developing a digital economy requires integrated sustainable development competencies; this chapter considers combined skills for digital transformation in triple connecting points of human skills, business skills and digital building blocks skills to argue for sustainability. Because attaining Sustainable Development Goals (SDGs) requires input from different quotas globally, sustainable competencies are needed to ensure individuals work cohesively through new-age digital technologies. This chapter further highlights emerging competencies such as critical thinking, appreciative equity, open communication and acting on collective well-being as imperatives transforming digital disruptions. The final section of this chapter puts into perspective the implication of required digital technologies for the future of work and its significance on the need to

Fostering Sustainable Development in the Age of Technologies, 63–77 Copyright © 2024 Joseph Odhiambo Onyango Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231007

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Introduction Digital transformation today forms part of many organisations’ strategies to gain a competitive advantage. At a general level, digital transformation encompasses a shift in how people operate, learn and communicate in everyday work using digital technologies (Rappitsch, 2017). At the organisational level, the profound digital transformation shifts embody a change in work, communication and consumer engagement (O’Brien, 2022). It also involves leveraging digital technologies to build novel business systems, nurture a novel digital mindset and exploit emerging digital opportunities. At the individual level, digital transformation depicts cultivating a culture and value that involves upskilling to reinvent ways to achieve digital competencies for future work (Smaje & Zemmel, 2022). Digital transformation not only provides agility but unlocks new value or talent. Key to the understanding of digital transformation is ‘digitisation and digital technologies’ (Vrana & Singh, 2021). In particular, digitisation describes translating analogue data into digital. On the other hand, digitalisation represents using technologies like software platforms to change processes (Accenture, 2022). In many forms, digital transformation takes more digitalisation than digitisation. The overarching digital transformation building blocks start by acknowledging digital technologies essential in creating environmental disruptions (Vial, 2019). Digital technologies like applications and devices provide opportunities that facilitate blended digital transformation in different settings (Tulinayo et al., 2018). Social media technologies drive digital change from the cognitive mindset that promotes new thinking through learning and reflection (Sebastian et al., 2017). Analytic technologies are utilising data for better decision-making. Also, cloud technologies are increasingly used to improve business domains to enhance agility and collaboration (Udovita, 2020). These disruptive digital technologies have, remarkably, impacted work design with possible expectations of changing work environment, thus, optimising business processes (Magomedov et al., 2020).

Connecting Digital Transformation to the Future of Work Digital transformation significantly changes future work, including the quantity, nature and quality of jobs. It pushes societies across different settings to a new ` 2021). Important aspects of this for the future of work are: reality (Schiliro, remote working, flexible work environment, job displacements and emerging digital jobs and borderless world-inclusive workforce. The interplay of digitisation and digital technologies accelerates changes across different economic sectors

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(Felstead & Henseke, 2017). This is expected to create new professionals for the digital economy. As such, digital transformation is causing significant shifts in labour markets with requests for novel digital skills and competencies (Donnelly & Johns, 2021). In remote working, digital transformation provides a scope of work from various locations (Irani, 2015). Digitalised roles today can be performed in places other than in office places. Rather, it can be completed digitally from several areas, such as home (Kylili et al., 2020). What this implies is enabling multidimensional disintegration of work. Recently, World Economic Forum (WEF) (2020) estimated that nearly 84% of employers across 15 industries in 26 industrialised and emerging markets plan to digitalise their working models radically. This includes expanding remote working. Studies have further revealed that emphasis will increasingly be centred on a person’s ability to use artificial intelligence applications, robotics, the Internet of Things (IoT) and big data at work (Morgan, 2014; Muro et al., 2019). Digital transformation suggests massive reconfiguring of job designs, including roles and skills. Essential to the success of the digital economy will be novel digital skills, which will be necessary to remain competitive (Jones, 2022). At the core of digital transformation will be increasing demand for new talents for sustainability in the future of work. Demand for cybersecurity, cloud and coding and social media skills will radically drive future work to a new level (Hughes, 2022). Moreover, digital transformation is making the world more borderless. It provides opportunities for companies to recruit talent overseas for remote jobs. This will create an advantage in accessing a wider pool of talent, a more diverse and inclusive workforce and a flexible working environment for remote workers (Sakamoto & Sung, 2018).

The New Digital Age and Possible Effects on Sustainability From Sustainable Development Goals (SDGs) perspective, digital transformations mean designing environmentally, economically and socially friendly digital products, including mobile applications or other digital platforms (Santander, 2022). The United Nations Environment Programme (UNEP) (2022) outlined that digital transformation conveys novel prospects and allows the ability to measure and track SDGs progress, optimise the use of resources and facilitate a greater circular economy. WEF (2022) further acknowledged that digital technologies have completely changed the traditional approaches to addressing global concerns. The contribution of digital technologies became more apparent during the COVID-19 pandemic. Emerging from a global pandemic like COVID-19 (Saiso´ et al., 2022) reasoned that global crises and conflicts have uncovered underlying deficiencies in economics, environment, climate, well-being and leadership worldwide, particularly in frontier markets. Given these challenges and the need to develop a resilient approach, digital transformation has made the world realise that no single country has all the essential knowledge, creativity and innovation to address the

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challenges. Instead, digital transformation has created opportunities for countries to share information, and knowledge, and work together. This has proved essential in delivering key sustainability plans, including addressing global health challenges. Considering the possible effect, ElMassah and Mohieldin (2020) argued that digital transformation has boosted localisation of SDGs at the government levels. The authors explained that digital transformation has enabled governments to tailor SDGs strategies to community needs. This includes effective planning and resource allocations to prioritise community needs. Ufua et al. (2021) explained further that digital transformation has increased stakeholder engagement on SDGs between countries and the community. As such, digital transformation has improved local-oriented commitment and the attainment of SDGs. The United Nations (UN) Secretary-General (2019) report exemplifies that technologies have enabled novel interactions that support trust, primarily by providing the ability to verify information. For instance, several business platforms like e-commerce (Alibaba) have enabled global trade, thus, winning the trust of many consumers worldwide. Additionally, with remote working in place as Sullivan (2020) encapsulates, many sites offer remote jobs, allowing many people to share their confidence in the genuineness of such platforms in offering remote work. These experiences demonstrate the effectiveness of digital transformation in reimagining excellent customer experience through building trust. Marr (2022) propounded that digital transformation has caused significant changes in skills and roles in the labour market. It has made some jobs obsolete while creating new ones. Advancements in digital technologies have resulted in remote working where people do not have to go to the office but work from home or their perceived flexible work environment. With this revelation, Gibbs (2022) submits that technology is creating a new pool of talent with the skills needed for the digital economy and future work. It implies that some jobs must be redesigned in today’s economy to align with market changes and the SDGs. Technology allows people to share their experiences on specific oppressions and create internet engagement. In this regard, a report by Purdue University Global (2018) contended that people are using various technology tools today to call out for injustices at work or the community level. This ultimately forces people to call for relevant authorities in the government to take action. Ideally, this demonstrates the commitment of digital technologies to ensure justice is served where necessary. Through big data and rapid identification systems, digital technologies are increasingly used to protect human life and improve criminal justice systems. Lechman and Marszk (2021) noted that access to mobile internet and free download of various mobile applications in the digital age of smartphones has brought marginalised societies into the digital economy. With mobile money a growing reality, mobile applications have made it easy for people from low-income areas to save money and take financial credits easily when they need cash. Adeola et al. (2022) add that digital transformation has ensured secured mobile money services like M-Pesa in Kenya’s context. This promotes financial

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saving culture while simultaneously providing monetary credits at low rates to achieve financial inclusion.

Digital Technology Transformation Skills Digital transformation requires essential skills related to cloud computing, programming and new technologies (Andriole, 2018). Consequently, Morandini et al. (2020) elucidated that though cognitive skills like numeracy, literacy and digital are vital, non-cognitive skills like flexibility, communication, cooperation, decisive reasoning, innovation and readiness are also gaining importance in digital transformation. Again, whereas Antonopoulou et al. (2021) stressed digital skills like mobile app development and analytics, Prestiadi et al. (2020) clarified that advancement in digital transformation needs leadership skills, which focus on the commitment, experience, integrity and capacity of people in charge of digital transformation.

Integrated Skills for the Digital Economy Integrated skills concerning digital technologies illustrate how digital skills can be integrated with non-digital skills to improve technology results. It entails bringing various digital skills together and combining them to understand better digital technology transformation (Burning Glass/BHEF, 2018). The emphasis for improving the digital economy is to put people at the centre of the digital transformation with both sustainable digital and integrated skills (Banga, 2021). Malkawi and Khayrullina (2021) mentioned human skills as one of the integrated skills for the digital economy. Human skills emphasise the development of an idea at the conception phase. It is the foundation for developing other skills and abilities to sustain the digital economy. Guryanova et al. (2020) postulated that key skills at the level of idea conception are critical thinking, collaboration, communication, creativity, entrepreneurship and analytical skills. Aboobaker and Zakkariya (2020) pointed out that human skills emphasise change readiness. These skills help people to identify market gaps for certain digital products (technologies) and then think, design, innovate and build technologies to solve identified gaps. Second to the integrated skills for the digital economy is business enabler skills. As Carruthers (2022) pointed out, digital transformation is dynamic and is not a one-fit-all tool. Instead, it should be integrated with all aspects of an organisation. This can only be successful with business enabler skills. Bayrak (2015) noted that business enabler skills are responsible for identifying and integrating digital capabilities with business goals to achieve results. Argawal (2019) stated that business enabler skills include communicating data, digital design and project management. The skills allow individuals to manage business projects, digital design products and frequently share information with the team or organisation. The third integrated skill critical to the digital economy is digital building block skills. Payne (2022) detailed that digital building block skills describe the

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ability to know and use digital technologies like analytics. They are skills that leverage digital tools like available software to build and design new applications for the digital economy. McGarity (2019) provided digital building block skills, including computer programming, software development and data analytics. People with these skills can design data visualisation applications and use their analytical skills to analyse, present and communicate data convincingly and succinctly that speaks to the target audience.

Developing Digital Competencies for Sustainability Digital advancement in the age of sustainability goals entails acquiring technologies and engrossing digital capability to improve value-creation skills for sustainability purposes (Bikse et al., 2021). Digital competencies describe digital knowledge, skills and attitudes that allow successful task performance and problem-solving concerning sustainability goals (Grigorescu et al., 2021). Previously, Vega-Marcote et al. (2015) posited that one competency that must always stand out for SDGs actors is the realisation multitude of solutions. This can be related to various digital technology perspectives and different parties working together to achieve sustainability goals. Competency means being aware of different opinions and respectfully appreciating every opposing view.

Dimension of Digital Competencies Different studies have explained dimensions of digital competencies from different perspectives. Schiuma et al. (2021) constructed six capabilities for digital change from the concept of transformative leadership. The leadership competencies outlined were the ability to grasp the core of digital change, envision digital wealth creation goodness and shape the context of creating knowledge for digital change. Besides, the study also emphasised the ability to communicate the essence of digital transformation, engage individuals to act with digital transformation and make digital transformation everyone’s job. Imran et al. (2020) pinpointed five leadership competencies for digital revolution including digital vision, failing fast, digital knowledge, empowerment and ability to manage diverse teams. In particular, digital vision illustrates ability to have a strategic vision that envisions a digital future. Digital knowledge-related competencies describe ability to understand digital capabilities and how they can improve customer engagement. Failing fast as a competency explains the ability to take digital risks even after failing for the first time. It provides a learning opportunity for digital transformation. Empowerment competencies describe the ability to delegate a task and foster digital participation. Managing a diverse team encompasses bringing people together, developing a common purpose and aligning group ideas to digital transformation. In a study of a panel of 16 experts to develop a ranking for competencies needed for digital change, Fonseca and Picoto (2020) touched on digital competencies related to evaluating data, information and digital content for digital

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transformation. Similarly, the study mentioned competency of searching for information and other digital content as critical for digital transformation. Other digital competencies identified in the study were the ability to interact through digital technologies, manage data and collaborate through digital technologies. Moroz (2018) demonstrated that digital collaboration competency is essential for digital sustainability as it enhances sharing and knowledge creation in the organisation. Another study conducted among 284 employees from German component manufacturers uncovered that highly developed cognitive and processual as well as social competencies of persons promote digital transformation processes (Butschan et al., 2019). A similar quantitative questionnaire survey of 450 participants from different mining organisations identified two capabilities as important competencies for digitalisation and digital maturity. The first competency identified is the ability to perceive direct effect of disruptive change as a motivation for digital transformation. The second digital competency is increasing technological process innovation and moving towards digital transformation (Al-Edenat, 2021). Gilli et al. (2022) alluded to strategic thinking, customer orientation, leading diverse teams, communication and collaboration as important leadership capabilities for digital transformation. On the same note, the study mentioned pro-activeness, willingness and creativity as essential competency traits for digital leaders. As cited in Kunaka (2019), digital transformation leaders must be nimble and adapt quickly to the ever-disruptive digital age. Digital leaders should possess knowledge of a positive mindset that is mindful of emerging digital technologies, innovativeness and networking to promote collaboration in the digital age. Alhazmi and Yamani (2021) provided digital competencies to include ability to build a fitting culture that includes a clear vision and objectives of digital transformation in the organisation. The second competency is the ability of digital leaders to create diverse digital roles due to emerging digital technologies to improve strategic and operational digital roles for purposes of strategic thinking. The third dimension of digital competency provided in the study is the ability to upskill and reskill by training employees to adopt emerging critical high-demand digital positions in the organisation.

The Implications of Digital Competencies on the Future of Work Chalutz and Cohen (2022) expressed that competencies should be responsible for allowing individuals to adjust, and accumulate experience and expertise for future work. According to the authors, individuals with these competencies will be critical thinkers and innovators. They will be able to manage teams and projects crucial for future work. Besides, these people will be able to re-evaluate their careers or skills and quickly integrate into the digital economy. Their experience, deep acquaintance with digital tools, and accumulated work-related skills will be vital to them in increasing digital transformation. Additionally, Deloitte (2021)

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acknowledged that developing the right competencies will enhance people’s ability to generate insights necessary for future work. Amorim et al. (2019) highlighted that digital-related competencies would demonstrate the level of education and training preparedness needed for future work. It will enable individuals to use various digital platforms to complete tasks efficiently. Those with digital-related competencies will leverage new digital technologies like automation platforms to make informed decisions. Digital-related competencies will display the ethical judgement and complex problem-solving skills of and for the future workforce. Schaffers, Vartiainen, and Bus (2022) denoted that individual, team and social-related competencies will represent intangible resources that individuals need to meet future work demands. The author adds that individuals who possess digital competencies will develop resilience capacities to absorb external labour shocks and develop the necessary skills and leadership to address the gaps.

Retooling and Upskilling for Digital Transformation Technologies like automation, artificial intelligence (AI) and robotics are redefining the value of knowledge and skills. The impact cuts across sectors and suggests a greater demand for retooling and upskilling for individuals (Chui et al., 2015). Retooling and upskilling take the form of an effort to get training, learning and cutting-edge skills or competencies for career development. It involves deepening knowledge and understanding of essential skills needed for digital transformation, the digital economy and future work (Raimi, 2021a). In essence, retooling and upskilling in this digital age transformation is obtaining a unique attitude, novel knowledge, skill or expertise either by updating the skills or launching a new career to rejoin the labour market (Raimi, 2021b). Achieving significant retooling and upskilling needs for a compelling future workforce requires a solid fundamental knowledge base in digital skills (Li et al., 2021). A considerable approach to bridging this gap is transforming traditional educational practices into more data and analytics centred in all sectors. Updating educational programmes in nearly all subjects cutting across different industries with data-related skills and domain knowledge would help to improve skill gaps (Marcial, 2020). Reforming education approaches to include digital training would assist individuals in upskilling their skills or gaining new knowledge and competencies for emerging digital skills (Lyons et al., 2019).

Importance of Retooling and Upskilling for Sustainability Big and small organisations are starting to understand the impact of SDGs on their strategic objectives. Increasingly, some organisations are adjusting to SDGs through digital transformation partnerships and collaborations (World Economic Forum, 2021). It has resulted in organisations retooling and upskilling their members on the need and importance of digital technologies on sustainability. With retooling and upskilling, organisations have increased innovation and

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creativity of members, thus, developing digital technologies that are environmentally friendly (Samuel et al., 2022). This has been experienced in areas like developing recycling and waste dumping technologies to improve the environment (Sparviero & Ragnedda, 2021). Similarly, providing people with opportunities for learning and training has dramatically enhanced education, skills and knowledge. This has reduced gender gaps and inequalities in society or work areas (Sabatini et al., 2018). Companies that train their employees help create an innovative mindset that can address economic challenges, thus contributing to developing applications that promote financial inclusion (Haddad, 2019). With a boost in upskilling, individuals will be able to compete and fill the growing digital economy, create new opportunities and improve investments in areas of education, and the green economy, thus, mitigating poverty challenges (Forbes, 2022). Consequently, digital technologies are changing the world, forcing learning institutions and industries to collaborate and identify relevant digital skills for future work (Sasmita & Kumar, 2018). This multidisciplinary collaboration between academia and industry should prepare individuals with adequate, relevant training skills and knowledge in statistics, big data and machine learning. This kind of collaboration ensures that individuals are upskilled or reskilled in broader skills and knowledge aligned with labour market needs across different sectors. Besides, the partnership will ensure that the training customises digital skills and learning priorities according to the essential digital skills for emerging roles. Upskilling through the facilitation of creativity and an innovation mindset can help anticipate the right skills for the future, lay the right attitude and identify practical training in digital technologies to enhance digital competencies (Anshari & Hamdan, 2022). WEF (2016) outlined that response to digital transformation changes require creativity and innovation, which can only be possible through recognising upskilling, reskilling and retooling as a priority. According to the report, upskilling as a priority brings change management in all spectrums of the organisation. This includes gaining better digital skills and leadership aligned with the digital creativity and innovation needed for future work.

Opportunities and Challenges Digital transformation comes with changes in cultural practices (Manda & Backhouse, 2017) that must either be dropped or acquired to make the process successful. It brings cultural practices of competition, creativity and globalisation. The mindset and perception towards digital transformation can enhance or derail the adoption process. Hai et al. (2021) added that organisations must constantly work on changing the mindset of employees through information systems training, which includes how to use new technologies to complete various tasks. Organisations that go slow on training their members or providing career prospects miss enjoying digital skills, competencies and capabilities that come with operating the best digital technologies. With increasing data mining practices, organisations should be wary of cybersecurity threats to their businesses and data.

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The demands of digital transformation redefine the roles and functions of individuals, which has to link to digital conversion (Heavin & Power, 2018). It requires a sense of urgency, which may get many individuals and organisations unplanned. This poses a challenge for digital transformation processes. McKinsey & Company (2016) highlighted that if the organisation is ready to adapt to the new digital technologies, it may also mean identifying existing digital skills and capabilities currently available to meet future needs. This may demand extensive digital retooling or upskill both at the individual and organisational levels. Thus, it may only be possible with adequate commitment and willingness.

Conclusion The advancements in digital transformation have resulted in new digital technologies driving sustainability goals. From the review, digital technologies have brought significant benefits to SDGs processes, and the reflections of the new digital age demonstrated this. Among the considerations are global interdependence, commitment to justice, commitment to the green economy, sustainable supply chains, energy, climate change and peace. These initiatives are primarily driven by digital technologies like big data, IoT, machine learning, artificial intelligence, cloud computing and other mobile applications, positively influencing future work and the digital economy. So far, digital technologies are perceived as a strategic tool for enhancing sustainability with an emphasis on human skills at the centre of it. Digital technologies skills are critical to successfully applying digital technologies in pursuit of sustainability. However, this will mostly be possible with sustainable digital competencies like system thinking, and strategic and adaptive competencies are also critical for retooling and upskilling. This chapter concluded by providing opportunities and challenges of digital transformation.

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Chapter 6

Role of Social Networking Technologies in Developing Public Services Supply Chain During COVID-19 Kali Charan Sabat and Som Sekhar Bhattacharyya

Abstract The purpose of this research study was to examine the role of Social Networking Technologies (SNT) in developing Public Services Supply Chain (PSSC) during COVID-19 pandemic. Due to lack of sufficient support from corporations and non-government groups, citizens in developing democracies were dependent upon their governments for the delivery of vital public services. During the COVID-19 epidemic, a number of organisations attempted to assist governments in managing the supply of public services. However, organisations often lacked a thorough grasp of how to cultivate social ties for the delivery of efficient and effective public services for citizens. In this research work, to study the delivery of efficient and effective public services to citizens, the authors have proposed a social network viewpoint. This was at a ‘meso-level’ lens so as to examine the intersection between organisational SNT and PSSC. According to the qualitative study conducted in this research work, it became evident that organisational social ties could play a significant role in facilitating homophilic and heterophilic ties. This was specially so for the distribution of public services in pandemic situation like COVID-19. However, the research study findings also found out that these network forces were highly dynamic and dependent upon a set of factors. These factors included tie frequency, the sequencing of interaction with social ties and the prevailing norms. This research study enriched the understanding regarding the role of SNT. This was in the context of developing PSSC during critical crisis situations such as prevalent during COVID-19 pandemic. This research study offered a better understanding of social ties and motivational factors in the social networking environment. The social ties were analysed based on the contact incidents of six participants focusing on the PSSC during the COVID19. Future research studies could consider a diverse set of participants in Fostering Sustainable Development in the Age of Technologies, 79–92 Copyright © 2024 Kali Charan Sabat and Som Sekhar Bhattacharyya Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231008

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Kali Charan Sabat and Som Sekhar Bhattacharyya complex global PSSC consisting of multiple constraints. Furthermore, this research study had practical implications for managers. The study revealed that homophilic social ties were more supportive as compared to the sequence of interactions starting with heterophilic ties. Therefore, managers needed to develop better PSSC especially as compared to unrelated institutions. Keywords: Social networking technologies; COVID-19 pandemic; sustainability; public services; supply chain management; social network analysis

Introduction The COVID-19 pandemic outbreak was a major health and humanitarian calamity (Bhattacharyya & Thakre, 2021). India had a total of 44,600,000 COVID-19-positive cases and 529,000 COVID-19-related deaths by September 2022 (Worldometer, 2022). Since the COVID-19 outbreak in mid-March 2020, the Government of India (GOI) had taken a variety of strategic measures to contain the virus’s spread (Krishnakumar & Rana, 2020). These included a complete lockdown in the country, followed by partial relaxation, night-time curfews and others (Government of India, 2020). Tens of millions of people were placed at risk of sliding into extreme poverty, malnutrition and health-care emergency as a result of the GOI’s efforts to contain the spread of COVID-19 (Krishnakumar & Rana, 2020). The World Health Organization (WHO) reported that the informal sector workers in poor countries were more likely to get sick during the COVID-19 outbreak (World Health Organization, 2020). This was because they didn’t have access to good health care or social security and furthermore did not own productive assets (World Health Organization, 2020). According to Unicef (2020), enhancing national PSSC system was an effective method for addressing this issue. Nonetheless, inefficiency and resource limitations in the PSSC of a large country like India posed a significant obstacle during the COVID-19 outbreak (Tirupakuzhi et al., 2020). Several public and private companies had initiated measures to assist the PSSC system in this difficult environment (Madhukalya, 2021). Under the corporate social responsibility (CSR) initiatives, large Indian corporations such as Tata Sons, Reliance Industries, Adani Group, Mahindra and Mahindra, ITC, Maruti Suzuki and Hyundai India provided oxygen, arranged for hospital beds, donated funds and vaccinated their employees and the general public (Bhattacharyya et al., 2021; Madhukalya, 2021). This was based on mandated CSR requirements (Garg & Gupta, 2020; Gatti et al., 2019; Nair & Bhattacharyya, 2019). Furthermore, this research employed the institutional theory of CSR to appreciate how firms institutionalised pandemic-related sustainability measures via social networking platforms (Aggarwal & Jha, 2019; Halkos & Skouloudis, 2016; Yang & Rivers, 2009). This research study aimed to address the three research questions listed:

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• What PSSC components backed by enterprises’ sustainability initiatives led to

the formation of social network ties? • How much would these social network ties help in the streamlining of PSSC,

given that CSR initiatives had required certain expectations? • Which types of corporate social network ties were most common in PSSC

during the COVID-19 pandemic? To find answers to the research questions, social network analysis (SNA) (Freeman, 2004; Scott, 1988) was used to investigate social network connections between organisations’ sustainable development practices and PSSC using networks and graph theory (Goldenberg, 2019).

Theoretical Foundation In this section, the authors have presented the theoretical foundations of this research study. First the concept of PSSC has been presented. Finally, the perspective on SNT has been presented.

Public Services Supply Chain (PSSC) Public services were viewed as essential to the development and advancement of any nation’s economic, social and industrial systems (Alberto, 2013). The creation of an integrated approach to delivering public services was a response to the emerging notion that governments increasingly faced an inherent inability to finance public services (Grimshaw et al., 2002). The PSSC was founded on the premise that public services systems must be able to provide services that are always in line with citizens’ expectations and demands (Alberto, 2013). The operations of public service organisations were based on procedures that had a significant impact on organisational outputs and the perceived value by users (Qureshi et al., 2016). Therefore, policymakers and consumer groups have asked for a more robust involvement of corporations in the governance and delivery of a diverse range of public services (Simmons & Birchall, 2005). In response to the streamlining of PSSC, organisations had begun to create a variety of alternative social network ties (consumer councils, panels and forums and involvement in agencies governing structures) to augment the traditional means of managing public services (Lowndes et al., 2001).

Social Networking Technology (SNT) Perspective One of the objectives of the SNT perspective was to comprehend what was the position of a focal actor within the social network of other actors (Qureshi et al., 2016). This analysis provided the chances and constraints for societal growth (Mehra et al., 2001). The field of PSSC grew out of dissatisfaction with the dominant structuralist paradigm underlying institutional theory (Aggarwal & Jha, 2019). However, research on SNTs arose out of dissatisfaction with the

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contention that individuals were expected to make decisions in isolation (Borgatti et al., 2009). Accordingly, the SNT (often known as social media or Web 2.0, such as blogs, wikis and public social networking sites) perspective sought more understanding (Vallor, 2020). This was regarding how different contextual and technological linkages exerted pressure on organisations and individuals to plan actions (Kilduff & Tsai, 2003). Social networks influenced a focal actor’s behaviour in several ways (Qureshi et al., 2016). Social networks shaped viewpoint by providing financial and/or emotional support to a focal actor in the pursuit of its goals (Jack, 2005). SNTs also provided knowledge and information to reinforce the focal actor’s preconceptions or, at times, refute the preconceptions (Uzzi, 1996). The focal actor was usually the one who was influenced by all of the other actors in its network (Kurt & Kurt, 2020). However, the focal actor could also be influenced by other actors (Qureshi et al., 2016). For dynamically managing network influences, the focal actors usually decided when, where and with whom to interact (Fang et al., 2015). The literature on SNTs primarily discussed two types of characteristics (Kilduff & Tsai, 2003). The first one related to the overall SNT and the second to the types of social networking ties (Kilduff & Tsai, 2003). In terms of SNT characteristics, scholars examined how factors such as centrality, network density and reachability normally worked to shape the behaviour of actors (Morrison, 2002). Furthermore, scholars often explored how structural holes in the network (Sasovova et al., 2010) provided opportunities for strategic action (Burt, 1997). ‘Network ties scholars’, on the other hand, had primarily focused on the dyadic relationships between the focal actor and other actors as a means of shaping behaviour (Qureshi et al., 2016). While there could be many different distinctions between types of ties, classifying the ties as homophilic and heterophilic was pertinent to the studies related to institutional practices (McPherson et al., 2001). Homophilic ties referred to highly similar relationships, while heterophilic ties referred to relationships that were dissimilar (Mehra et al., 1998). Perceptions of similarity were often based on characteristics such as social class, education and historical connections (McPherson et al., 2001). Homophilic ties served to reinforce shared attributes and identities among members in a social network, whereas heterophilic ties work to augment diversity and inclusiveness across different social spheres (McPherson et al., 2001). To explore the potential effects of social network ties, this study aimed to examine tie type in combination with tie frequency (these being frequent homophilic, infrequent homophilic, frequent heterophilic and infrequent heterophilic). The extent to which social network ties enabled or constrained social change was highly complex, given the dynamic nature of social networks (Castells, 1996). Therefore, the authors applied a qualitative method in this study. This was towards studying the different, and possibly time-specific, effects of SNT ties in PSSC during the COVID-19 pandemic.

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Research Study Methodology The context for this study was to identify the role of public and private social networks in streamlining the PSSC within India during the COVID-19 pandemic times. In the last few decades, the GOI’s focus was on rapid economic growth (Parikh et al., 2016). However, this also resulted in reduced attention towards issues related to the development of PSSCs for the poor, elderly and underprivileged people, as well as the rural population (Balasubramanian et al., 2020). As a result, during the recent pandemic situation, government institutions were not sufficiently prepared to handle the economic and social issues aroused by the catastrophic disruption in the supply of public services (OECD, 2020). Without wasting any time, most public and private sector companies in India jumped to support the GOI in streamlining and managing the PSSC (Bhattacharyya et al., 2021). Even though there was a mandatory requirement for companies in India to perform CSR (Garg & Gupta, 2020), PSSC was still in its relative infancy within India and remained a highly unconventional form of behaviour on the part of organisations and individuals involved in public service activities. There was also very little awareness regarding the existence of public service systems on the part of the general public in most parts of the country (Afridi, 2017). As a result, it served as a fruitful context for exploring the role of SNTs in streamlining the various stages of PSSC during the COVID-19 pandemic. In this research work, in-depth expert interviews (Campitelli et al., 2019) were conducted with experts to explore how organisational CSR in India was conceptualised. This was regarding both homophilic and heterophilic social networking ties as advocated by scholars (Qureshi et al., 2016). The experts included CSR managers, individuals working with NGOs and public service managers who were supporting the PSSC during the COVID-19 pandemic period. To begin, the experts were asked to more generally discuss topics related to public services within India and how it was perceived by the general public during the pandemic. Subsequently, the experts were asked to relay, and compare, their individual stories regarding the critical role of their social and organisational network ties during the COVID-19 pandemic period. Within the context of PSSC, a homophilic tie was considered to be someone that resides within the same ‘social sphere’ as the focal actor. The social sphere could be a result of affiliation, job or belonging to a common linguistic, religious or ethnic (Qureshi et al., 2016). Thus, homophilic ties indicated similarity in terms of certain practices and traditions based on common background or shared history (M¨akel¨a et al., 2012). Comparatively, heterophilic ties were considered to be between individuals who belong to a different social sphere in terms of affiliation, job or belongingness (Qureshi et al., 2016). Heterophilic ties were typically formed during university or college attendance or through working relationships with individuals from various organisations. The stories relayed by the participants indicated that their perception of homophilic and heterophilic ties was very much consistent with how they were presented in the literature (Louch, 2000). The concepts of ‘frequent’ and ‘infrequent’ ties were also confirmed as highly

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consistent with how they were presented within the literature on social networks (Qureshi et al., 2016).

Data Collection and Analysis The procedure of collecting data began with the identification of people from six distinct organisations engaged in CSR activities and assisting residents in accessing various public services at the time of the COVID-19 outbreak. The data collection for the study started with an initial diary study as advocated by scholars (Rausch et al., 2022). This was subsequently followed by a series of semi-structured interviews to challenge and reinforce initial themes (Brown & Danaher, 2019). Finally, the authors undertook checks to ascertain the extent to which the themes were common (Qureshi et al., 2016) across the public supplies of different services. Contacting various organisations that promoted organisational CSR during the COVID-19 period yielded a pool of possible volunteers for the diary study. A preliminary interview was done with three possible participants from the pool of participants to evaluate the following criteria: • Whether their initial ideas were consistent with our definition of public service

and CSR. • Whether they were actively involved in the PSSC during the COVID-19

pandemic. • Whether or not they had shared ideas with their social network ties.

Based on the answers to these questions, the authors recruited six participants for the diary study. This has been presented in Fig. 6.1. At the beginning of the diary study, the terms ‘homophile’ and ‘frequency’ were discussed with each expert participant to ensure a unified understanding of network ties as advocated by scholars (Qureshi et al., 2016). The participants were then given an Incidence Record Sheet (refer to Fig. 6.1), including a series of questions that needed to be answered. Questions concerned their relationship with the tie, the tie’s response to their initiative and the tie’s nature. Table 6.1 provided a summary of the participants’ information. The six experts who took part (all men) wrote down a total of 26 contacts with people in their social networks (mean 5 5.2, SD 5 2.59). The number of each type of social network tie that respondent interacted with was: frequent homophilic ties, 7 (mean 1.4; SD 1.14); infrequent homophilic ties, 4 (mean 0.8; SD 0.45); frequent heterophilic ties, 9 (mean 1.8; SD 1.10); and infrequent heterophilic ties, 7 (mean 1.4; SD 0.55). Table 6.1 also provided information on how many of each type of tie was approached by each study participant and the sequence in which these ties were approached. To analyse the patterns in the diary data, we created a graphical representation of each contact incident for all six participants (refer to Fig. 6.3).

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Demographic details 1. Your Name:

2. Organization (that initiated CSR):

3. Gender:

4. Age:

5. Education:

Social Ties 1. Number of Social Ties (ST) 1.a Number of incidents of ST with different PSSC participants (within the organization and outside the organization) during the pandemic period: 1.b. Number of ST within the organization: 1.2. Number of ST outside the organization: 2. Type of Social Ties 2a. How many incidents were Frequent Heterophilic Ties (FHT): 2b. How many incidents were Infrequent Heterophilic Ties (IHT): 2c. How many incidents were Frequent Hemophilic Ties (FHM): 2d. How many incidents were Infrequent Hemophilic Ties (IHM): 3. Provide the sequence of interactions (FHT, IHT, FHM, IHM) in the PSSC since the beginning of pandemic: 4. Social network ties believed social issues are government’s responsibility Strongly Disagree

1

2

3

4

5

Strongly Agree

5. Awareness level of “Social Ties” about public service activities Very Low

1

2

3

4

5

Very High

6. What was majority of “Social Network Ties” response to your (or your company’s) idea/initiatives? Extremely Discouraging -5

-4

Fig. 6.1.

-3

-2

Indifferent -1

0

Extremely Supportive 1

2

3

4

5

Incident Record Sheet. Source: Author’s own creation.

The maximum numbers of ties were frequent homophilic ties. In most cases, the social networks started with frequent homophilic ties. And, in maximum cases, it ended with infrequent heterophilic ties (refer to Fig. 6.4). In an attempt to evaluate whether the themes that appeared in the initial diary study were reflective of the CSR experiences in PSSC, the authors subsequently conducted semi-structured interviews with the same set of participants. Discussions with the participants suggested that most ties disagreed with the common belief that ‘social issues were the government’s responsibility’. Also, it was found that the awareness level of social networking ties about public service activities was high. In most cases, a majority of social networking ties were extremely

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ID

Gender

Age

Education

Incidents

IHT

FHT

IHM

FHM

Sequenceb

P1 P2 P3 P4 P5 P6

M M M M M M

35 40 32 38 36 41

PhD Masters PhD Masters Bachelor Masters

4 5 2 6 9 4

(3)a (3) (1) (2) (4) (3)

1 1 0 1 1 1

1 1 0 2 3 1

1 1 1 2 2 1

3a 1 1 1 3 1

FHM→FHM→FHT→IHM→IHT IHM→IHT→FHM→FHT IHM→FHM FHT→FHM→IHT→FHT→IHM→IHT FHM→IHM→IHT→FHT FHM→FHT→IHM→IHT

Source: Author’s own creation. a

Number in parentheses indicated the number of social network ties outside the organisation, for example, 3 out of 4 incidents happened outside their working organisation b Order in which ties were approached. For P5, the sequence indicates that FHM (1) was approached first then IHM (3), IHT (3), FHM (2) and finally FHT (3). Refer to Fig. 6.2 for additional details.

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Table 6.1. Diary Participants and Number of Social Network Ties Contacted.

Social Networking Technologies

Fig. 6.2.

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Analysis of Participants’ Diary. Source: Author’s own creation.

supportive of the company’s PSSC ideas and initiatives. The social networking ties supported the organisations in the conduct of initiatives such as vaccination drives, arranging hospitals for employees (and their families) and streamlining the supply of oxygen cylinders. They also supported the firms in raising funds for the state and central government through various collaborations.

Discussion and Conclusions The primary purpose of this research study was to apply a social networking technological lens to the institutional CSR practices during the COVID-19 pandemic time. While several previous studies used a micro- or macro-level lens to explain why some actors came to engage in non-conforming behaviour while others did not (Battilana et al., 2009). The authors focused on social networking ties as meso-level spaces where individual actors and institutional forces interacted (Qureshi et al., 2016). At the basic level, while comparing the data across the graphical representations of the contact incidents for each of the six participants within the initial diary study, several patterns emerged. First and foremost, the sequence of interactions started with homophilic ties. Homophilic social ties were more supportive as compared to the sequence of interactions starting with heterophilic ties. The findings were in line with institutional theory (DiMaggio & Powell, 1983) that proposed that related institutions could develop ties for a social cause more easily when compared to unrelated institutions.

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Fig. 6.3.

Analysis of Individual Participant’s Diary. Source: Author’s own creation.

Furthermore, the research study found that the support from social networking ties could be influenced by the frequency of tie contact. The frequency of contact was having a moderating effect on the relationship between interaction and support from social ties (Qureshi et al., 2016). Studies in future could be undertaken to investigate such a moderating effect. Moreover, the graphical

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Fig. 6.4.

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Summary of Participants’ Diary. Source: Author’s own creation.

representations of the data obtained from the initial diary study suggested that the order in which organisational participants interacted with each type of social tie had a significant impact on an organisation’s decision to launch a public service initiative. As depicted in Fig. 6.4, organisations were least likely to adopt new CSR practices if the heterophilic ties the organisations approached first were infrequent. During the semi-structured interviews, the effect of tie sequencing observed in the initial diary study was reaffirmed. The majority of successful CSR initiatives began with homophilic ties and concluded with heterophilic ties. Consequently, only a specific sort and sequence of early-stage interactions with network ties could initiate networking in PSSC. The frequency with which these patterns occurred might help in explaining why institutions were often able to adapt to frequent changes in the demand for public services at the level of the supply chain.

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Chapter 7

Adopting Technology for Sustainable Development: Reflections on Innovative Ecosystem Jasmandeep Kaur, Kirandeep Kaur and Ramanjeet Singh

Abstract The pandemic has brought to light the importance of quickly adopting new technologies and building resilient organisations. Also, the Sustainable Development Goals (SDGs) can be addressed in large part through technological innovations. The development of smart systems which are linked with the Internet of Things (IoT) can create different opportunities to strategically face the barriers linked with the SDGs and make sure that there is an environmentally sustainable, equitable and healthy society. This study has utilised secondary and qualitative data and has adopted the interpretative and deductive approaches. It has given significance to several aspects of the SDGs and has linked them with digital technology such as accessibility to safe and clean portable water, production of sustainable food along with the generation of green energy and its utilisation. This study has evaluated the advantages of digitalisation so that it can catalyse the transition towards SDGs and improve the health of the citizens by giving digital accessibility specifically to the underserved community. The research has selected the most essential themes which are linked to the context of SDGs and has deeply evaluated a lot of information obtained from authentic secondary resources. At last, it provides a conclusion and recommendations where it has suggested several initiatives which could be made for enhancing the overall scenario and has also disguised the limitations that were identified while completing the study. Keywords: Sustainable Development Goals; innovative ecosystem; technology; health; environment; digitalisation; Industry 5.0

Fostering Sustainable Development in the Age of Technologies, 93–111 Copyright © 2024 Jasmandeep Kaur, Kirandeep Kaur and Ramanjeet Singh Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231009

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Background Science, technology and innovation have the ability to create new economic opportunities, creating wealth and jobs in a way that is ecologically sound and inclusive in terms of the social aspects. As a matter of fact, science, technology and innovations are considered as core for the achievement of SDGs (Shrivastava et al., 2016). And to realise the ability of technology, science and innovation to attain the goals of the UN agenda, 2030, it is imperative to integrate sustainable development with the acceleration of the shift towards the knowledge economy (Yuan & Zhang, 2020). Indeed, technology is a subset of ‘knowledge’ consisting of instruments, tools, processes and practices that can be used for fulfilling ‘certain human purposes’ in a reproducible and specifiable manner and innovation is a process through which technology is recognised, codified, developed and implemented (Wang et al., 2021). It goes without mentioning that science and technology have immensely evolved right from the period where the focus had been on figuring out the world and the external phenomenon. The various technological revolutions have fundamentally changed the way humans work, live and interact with each other with the help of a highly interconnected world. Here a pool of ideas, data and knowledge move freely and help to foster collaboration and brainstorming while bringing innovation (Tabrizian, 2019). Since, it is the period where people’s focus is on controlling the world around them and transforming it. This industrial revolution is known as the Fourth Revolution or Industry 4.0 Era (Vatananan-Thesenvitz et al., 2019). This modern and transformative era beholds the potential to integrate the greater social goals that are beyond the economic gains and encompasses the social and environmental goals. When clients start tailoring to what they want, Industry 4.0 starts to transition to Industry 5.0. Indeed, Industry 4.0 ecosystem is all encompassing consisting of cyber security, artificial intelligence (AI), mass customisation, IoT, Big Data, etc. Sustainable innovation efforts can benefit from leveraging Industry 4.0 technologies and ideas since innovation is a major driver of sustainability and it is a widely accepted fact amongst the scholars, the various industrial professionalisms and also amongst the government representatives (Shan et al., 2020). This is because ‘Sustainable development’ is basically a pressing issue that needs instantaneous acts as well as changes from government, societies and industries. The ‘no one left behind’ tenet of the 2030 Agenda calls for international collaboration and involvement in the integration of environmental, social, economic and governance components in the process of development (Berawi, 2019). Innovative ecosystems assist in achieving these goals since an innovation ecosystem refers to ‘the collaborative arrangements through which enterprises combine their unique offers into a coherent, customer-facing solution’ (Adner, 2006, p. 2). It refers to a set of actors, activities and artefacts that are always changing, together with institutions and relationships, including complementary and substitute relationships that are crucial for an actor or population of actors to perform (Granstranda & Holgersson, 2020). Innovative ecosystems are socio-technical in nature, so in order to increase social benefits, increase economic returns and lessen environmental consequences, suitable and sustainable technical

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MATERIAL RESOURCES

INNOVATIVE ECOSYSTEM

INSTITUTIONS

Fig. 7.1.

HUMAN CAPITAL

Components of Innovative Ecosystem. Source: Author.

development, scale-up and transfer will be accelerated by strong collaboration in private and public partnerships through these ecosystems (Anadon, 2016). The essential components of innovative ecosystem are depicted in Fig. 7.1. Indeed, the achievement of SDG targets, including the eradication of poverty, the improvement of food security and the reversal of climate change, depends on the development of technology, the creation of innovation and the production of ground-breaking solutions through the innovative ecosystems (Berawi, 2019).

Literature Review Table 7.1 provides a glimpse of some literature on adopting technology for sustainable development ecosystem from 2015 onwards:

Role of Technological Innovation in Sustainable Development Technology is defined as the application of ‘scientific knowledge’ for developing various techniques for producing a product and offering a service while innovation can be defined as extracting benefits from new and developed services or goods or processes (Fu et al., 2019). It is imperative to note that technological innovation lies at the centre of ‘Sustainable Development Goals’ and the innovation within itself is one of the most significant goals (SDG 9) and hence is considered to be a potential means to achieve the other SDGs as well (Song et al., 2019). Technological innovations provide various opportunities for the entrepreneurs that help them to create new organisations, and develop competence. Moreover, the combination of science and technologies can entirely replace a manual process such that digitisation can enhance the efficiencies and minimise wastages (Fu et al., 2019). Digitisation develops the overall notion of connectivity, availability and accessibility, along with inheritability and adaptability. Therefore, it enforces economic as

Author

Title of Paper

Journal Name

Objectives

2015 Singh et al. Technology for Journal of Sustainable Agriculture: A Cleaner review Production

To review the role of technology in sustainable agriculture

2016 Quaddus et al.

To identify the success factors for technology adoption in sustainable development

Technology Adoption for Journal of Sustainable Development: Cleaner A Review of Success Production Factors

Findings

Technology can improve the efficiency and productivity of agriculture, reduce waste and promote sustainable practices. However, there are concerns about the potential negative impact on small-scale farmers and the need for appropriate policies and regulations. The success factors for technology adoption in sustainable development include organisational readiness, stakeholder engagement and government support. However, there are challenges related to affordability, accessibility and digital literacy that need to be addressed.

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Year

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Table 7.1. Literature Review.

Technology for Sustainable Energy: A review

Renewable and Sustainable Energy Reviews

2018 Mishra et al.

Technology for Sustainable Urban Development: A Review

Habitat International

To review the use of Technology can enable the technology for sustainable transition to renewable energy systems energy sources, improve energy efficiency and reduce greenhouse gas emissions. However, there are challenges related to the integration of renewable energy into existing systems and the need for investment in infrastructure and research. To review the potential of Technology can improve technology for sustainable urban planning, urban development transportation and waste management, leading to more sustainable and liveable cities. However, there are challenges related to data privacy, equity and the need for community engagement in decisionmaking.

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2017 Mishra et al.

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Year

Author

Title of Paper

Journal Name

2019 Singh et al. Technology for sustainable Journal of water management: A Environmental review Management

2020 Granstrand Innovation Ecosystems: A Technovation et al. conceptual review and a new definition

Objectives

Findings

To review the use of Technology can improve technology for sustainable water conservation, water management treatment and distribution, leading to more sustainable use An ecology’s ability to To review the existing innovation ecosystems and compete with other associated concepts, and ecosystems can suggest a synthesis of these occasionally be aided by ecosystems with examples. an innovation ecosystem. The evolution of telecommunication networks serves as an example of how innovation ecosystems change over time, involving transitions between several communications generations

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Table 7.1. (Continued)

2021 Silva et al.

Addressing societal Technovation challenges through the simultaneous generation of social and business values: A conceptual framework for science-based cocreation

2022 Bradu et al. Recent advances in green technology and Industrial Revolution 4.0 for a sustainable future

Mechanisms for integrating tangible and intangible inputs, appropriate operational models and enhancing certain competencies and practises be addressed in policy design. To provide information on Industry 4.0 and green green technology and developments are Industrial Revolution 4.0 intertwined. They include the social, economic and environmental aspects that are a vital source of sustainability for the future.

Reflections on Innovative Ecosystem

Source: Author.

Environmental Science and Pollution Research

To establish a conceptual framework describing how the diversity of the agents involved affects science-based co-creation.

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well as social development in a sustainable manner. In fact, digital entrepreneurship is an emerging concept of economic sustainability as well as social and environmental sustainability, as with digital entrepreneurship people can do jobs sitting at home just through a computer or smartphones with internet. Thus, eradicating poverty, reducing transportation needs and also saving office space, infrastructural expenses and so on (Kalenov et al., 2019). This concept also has huge scope for handling climatic changes and social-setup issues. So, it can be said that innovation potentially responds to the apparent and interacting social issues such that it has been incorporated by digital technologies within ‘Entrepreneurial Enterprises’ such that these issues are associated with digital sustainability in general. Moreover, the most interesting thing about innovation is that it is an area that can result in ‘innovation spillovers’ and can thus allow greater and faster improvements and new applications in other areas. It is to be noted that when new knowledge tends to become largely accessible, it can become a ‘Global Public Product’ by developing a foundation for further innovations (Herrero et al., 2021). ‘Global Positioning System Technology’ had been invented for army applications; however, it is also broadly incorporated in many other areas such as for enhancing the targets for ‘Disaster Relief’ and so on. Thus, it can be said that in order to promote inclusive wellbeing, supportive innovation is needed that considers the possible ‘Positive Spillovers’. Also, the ‘2030 UN agenda’ consists of a potential persuasion to leave nobody behind. Resultantly, the framework of stakeholder engagement and inclusiveness are the paramount considerations of technological innovations for supporting sustainable development. Therefore, if the final users of these ‘Sustainable Focused Innovations’ are actually supposed to be a part of the process of innovation, it is necessary that they are at the heart of the ‘National Innovation System’ for SDGs (Cancino et al., 2018). Fig. 7.2 presents technological innovation affecting three pillars of sustainability:

Fig. 7.2.

Technological Innovation Affecting 3 Pillars of Sustainability. Source: Author.

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Technological Innovation for Social and Environmental Challenges Global environmental issues like depletion of various natural resources, different types of environmental pollution, health hazards, climatic changes and loss of biodiversity have been rising in a drastic manner (Kalenov et al., 2019). Therefore, societies have been increasingly becoming more aware of the change and there has been an increasing trend of adopting new technologies and scientific innovations to tackle these issues and to foster global sustainability (Camilleri & Ratten, 2020). Societies have been aware of these challenges and it is being realised that pursuing sustainable practices is vital for protecting the built environment and societal stability and economic growth. Indeed, technological innovation is referred to as a key and it can influence prosperities, consumption patterns, lifestyles, societal relationships, as well as cultural development (Kihombo et al., 2021). Hence, it is imperative to note that technologies determine, to a great extent, the demands for raw materials as well as energy and also efficiencies of manufacturing products and performances. With the help of technological innovation, minimising waste, fostering safe and physical well-being and optimising transportation and infrastructure become easier, thus, promoting economic, environmental and social sustainability (Adenle, 2020). IKEA has successfully integrated ‘Sustainability Practices’ within the ‘Supply Chain Management’. Thus, IKEA suppliers assure the provision of tidy, private, noise-free, secure and hygienic living-space. The mission is ‘to establish a better everyday life for many people’ and the vision ‘to provide a wide range of well-designed, functional home furnishing products at prices so low that as many people as possible will be able to afford them’ (Laurin & Fantazy, 2017). Furthermore, advanced technologies like AI, machine learning (ML), blockchains, IoT, geospatial maps and so on have been constantly powering the Industry 5.0 revolution with the aim of achieving various climatic goals. These advanced technologies have also been powering organisations to solve various traditional issues and problems, for example, the adoption of technologies for waste minimisation such as the ‘Activated sludge model’ (in wastewater treatment plant Anjana in Surat, India), can solve waste management issues (Muradi, 2018). Thus, technological innovation can become support for all kinds of strategies and policies that are developed for ensuring sustainable economic development (Camilleri & Ratten, 2020). Again, with a similar direction, the advancement of ‘highly productive green technologies’ and sustainable development tends to become the components of the ‘Innovation Vector’. It is also important to note that ‘innovation’ has been a potential increasing driver for sustainability. Digital evolution has greatly helped to deal with climatic changes and foster sustainability (Kihombo et al., 2021). Moreover, it has also helped the ‘entrepreneurial companies’ in embracing innovative approaches so as to deal with various difficulties and issues that are not flexible. A number of developing and developed nations are at the forefront in terms of ‘technological innovation’ facing numerous potential challenges pertaining to innovations and

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embracing new technologies. In countries like India, the United States, China and Japan, governments, organisations and enterprises have been increasingly adopting the usage of digital technologies and scientific innovations such as cloud technologies, ML, edge technologies, 3D printers and so on to save time, resources like papers and trees, and hence foster environmental and societal innovation (Adenle, 2020). Around the world, both developed and developing nations have been laying down various plans and setting numerous targets to enhance the sustainability of the current world by 2050 (Fatimah et al., 2020). Many of the plans and targets have been ambitious, and, with the help of ‘progressive new technological developments’, they have gained the ability to be a reality (Mikhno et al., 2021). Hence, it can be said that technology had been potentially altering the way people lead their lives and work and in the last few years, sustainability had been one of the main drivers of ‘technological innovation and advancements’. In the present day, as the world tends to face a number of unprecedented difficulties, technologies can help achieve sustainable development. When sustainability is being talked about, the environment is what people often think about but social and economic aspects are also equally important to attain all the SDGs, and it is not to be forgotten that technology tends to play a crucial role in all these three areas (Mikhno et al., 2021). For example, technological advancements such as Smartphone Applications have enabled people to control all things with a few clicks of buttons (Fatimah et al., 2020). Technological advancements in health and business areas tend to provide organisations with a wealth of opportunities by introducing new employment options, and by streamlining the various operational processes such that traditional life sciences and healthcare companies are taking steps to revitalise their ‘innovation ecosystems’. Telehealth is becoming more popular and practical, meeting the needs of all the stakeholders especially during COVID-19 and now when different health-care platforms are available to meet the needs of the patients like Practo, etc. The market for AI-enabled health-care products will reach $34 billion by 2025 (Businesswire, 2018). Indeed, AI has made health care easier through chatbots, virtual health aides and nurse robots, among other things. Also, it goes without saying that green technological developments have helped to replace the various practices and processes that tend to harm or deteriorate natural resources with more and more sustainable and effective ones (Mikhno et al., 2021). Some of the recent developments in technologies that promote environmental as well as social sustainability are the newly developed wind turbines that also act as an ‘apartment block’, ‘hotel’ or ‘tourist attractions’ to pipes that enable people to produce electricity when they turn on the water taps or while flushing toilets (Satish, 2021). The recently developed smartphone applications also tend to foster sustainable living and hence make it much easier for the people to care for the environment, leverage the nature and non-renewable resources in a more efficient manner and enhance savings (Bradu et al., 2022). For example, ‘Greenease’ is a mobile application that helps users to find eateries and restaurants that source foods and raw materials from ethical and sustainable suppliers

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(Springwise, 2019). Therefore, it can be said that these types of technology foster social sustainability by enabling businesses and customers to monitor as well as analyse data allowing them to become more sustainable in terms of saving money and time. Here, the example of EC Electronics (a UK-based company in Hampshire) can be considered, that had helped manufacture ‘Commercial Fridges’ with in-built ‘Data Management Technology’ that checks the fridges on an hourly basis so as to ensure that they are not over-exerting the energy and helps minimise wastes by assuring that the food is stored in the best and optimum conditions (EC Electronics, 2022). Moreover, it is also worth mentioning that automation is a potential feature of technology as with the help of AI and robotics, industries can automate various processes so that the human workforce can just focus on the tasks that are not accomplishable through robots, and hence increase overall efficiency (Satish, 2021). Waste reduction technologies are another contribution to the sustainable development movement, and new technologies like ‘recycling robots’, ‘smart waste management software’, ‘e-waste stations’ and so on help to reduce the consumption of limited resources and minimise pollution. Blockchain technology can also be used for sustainable and eco-friendly practices as this can track down the goods from their origin and minimise their wastage and inefficiencies by increasing the transparency of the whole process (Springwise, 2019). A new technology that can be referred here is ‘Decentralised Financing (DeFi)’ which is an emerging financial blockchain technology aiming to challenge the present banking systems and eliminate the fees charged by financial companies and banks in return for their service usage and foster ‘peer to peer transactions’ (Laurin & Fantazy, 2017). Furthermore, by integrating blockchain into ‘Smart grids’, the community can maintain the transactions in the system unanimously, hence, increasing social sustainability and also the combination of blockchain technology and sustainable energy within a smart grid can be a great way to leverage and manage sustainable power (EC Electronics, 2022). The framework in Fig. 7.3 demonstrates blockchain technology fostering sustainability and the attainment of UN SDGs.

Recent Technological Advancements In the present Industry 4.0 Era, the focus is on developing green technologies so that it brings only growth and development for society and community and no pollution or resource degradation. It goes without mentioning that climate change had started to show its impact on the surroundings, and also the recent coronavirus pandemic had also wreaked havoc in the lives of people around the world, posing deadly consequences at the socio-economic level (Laurin & Fantazy, 2017). However, in order to balance the crises, it is important to transform towards ‘Green Technologies’ so as to produce eco-friendly, bio-degradable, durable and pollution-free goods to foster a sustainable world (EC Electronics, 2022).

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Fig. 7.3.

Blockchain Technologies Fostering Sustainable Development. Source: Author.

The green technology encompasses all kinds of innovations that tend to contribute to the development of some potential services and products that reduce the environmental harm while increasing the ‘natural resource utilisation’. For example, Microsoft is a company which qualifies as the ‘greenest technology company’ around the globe (Satish, 2021). The company uses more than 1.3 billion of kWh of green energy annually and also it works round the clock to assure that its electric power needs are supported by ‘green energy’. A significant recent invention in the field of green energy are the sensors that are used in the ‘IoT environmental monitoring applications’ to foster environmental safety as it helps to nurse the quality of air and water and atmospheric conditions. It also enables monitoring of movement of species within their habitat (EC Electronics, 2022). Governments round the world, by collaborating with the industries have developed new green revolutions such as ‘the green new deal’, ‘carbon pricing’, ‘use of bio-based products as bio-pesticides within the biopharmaceuticals’, ‘green building materials’ and so on (Bradu et al., 2022). The engineers and environmentalists around the world have been focusing on ‘green chemical engineering’, ‘bio-based materials for separating pollutants’ and so on to pave the path towards the UN SDGs agenda 2030 and to foster a sustainable future. It is important to note that solar power is considered to be one of the most potential green technologies and in many countries such as India, China and Australia, the installation of renewable energy like solar power is cheaper by more

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than 12%–29% than the cheapest of fossil fuel (non-renewable) energy (Mikhno et al., 2021). Another example of a recent innovation in the field of green technology are the ‘nanotechnology solutions’ which greatly helped to alleviate the problem of the medical, agricultural and food sectors. Nanoparticles help in developing ‘biopesticides’ for improving crop production and eco-friendly and organic farming procedures (Fatimah et al., 2020). Again, bio-based nanomaterials such as ‘nano-crystalline starch’, ‘lignin’ and ‘cellulose’ can enhance the bio-availability of various nutrient supplements (Fatimah et al., 2020). Here, the example of India can be considered as the recent aggressive task of ‘Clean Development Mission (CDM)’ organised by the Indian Government, where clean and green innovation, white biotechnology, have made huge promises towards ‘Sustainable Development’ (Bradu et al., 2022).

Challenges in Adopting Technological Innovation Numbers of hindrances come in the way of adopting technological innovation. The problems preventing innovation also prevent technical innovation from being mobilised for sustainable development. Also, the poor, marginalised and future populations lack the economic and political clout to influence innovation systems as per their requirements. For instance, the population of developing countries, which bears the majority of the burden of ‘neglected diseases’, lack the resources to encourage worldwide investment in research and development of medications (Pedrique et al., 2013). Further, future people cannot directly influence existing innovation systems, so present investment in low-carbon energy may not entirely reflect the interests of those who will be affected by climate change in the near future (Nemet et al., 2007). Too frequently, technologies are either not produced at all because there isn’t a market that is sufficiently lucrative, or if developed, they are not readily available or well-suited to end-user needs. Replacement, optimisation and redesign of technology are also not easy and require large investments to foster technological development. Changes in institutions values and culture are all necessary for sustainable growth. Innovation can result in unintended consequences, especially as technology is used more frequently and as unexpected effects show up. For instance, the introduction of biofuels has been impacted by regional regulations that have been established in several countries (Zilberman et al., 2013). In this setting, maximising inclusive well-being necessitates taking scale-related effects into account. Thus, for regional and global cooperation, sustainable development must be incorporated into mainstream policies (Berawi, 2019). Industrial symbiosis serves as an illustration of the existence of favourable network externalities in facing technology adoption challenges. The EcoTEDA initiative in Tianjin, China, is an example of industrial symbiosis model where adding more users significantly increased the value of the network. Also, the perception of the mundaneness of the technology should be removed such as in

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the case of System of Rice Intensification (SRI) in Madagascar for the broader interest of small farmers. When it came to SRI, existing research centres doubted its potential advantages and favoured laboratory methods for creating novel hybrid crops. Due to this prejudice, they downplayed a technology that could be helpful for small farmers (World Bank, 2011). Thus, socio-technical linkages should be developed and studied for technology adoption. It is also argued that the more worldwide patenting regime will lessen opportunities for technology transfer and competitiveness in underdeveloped nations, especially for a number of significant technology fields addressing sustainable development (Maskus et al., 2004).

Conclusion From the whole discussion about the adoption of technologies and scientific innovation towards achieving the ‘SDGs’ set by the UN 2030 agenda, it can be concluded that technology is regarded as a broad term which touches all aspects of the modern life. The points that had been discussed in this chapter are just a small glimpse of technology bringing sustainable revolution and positively contributing to the struggles for sustainability. Therefore, it can be concluded that with the development of technology, keeping sustainability as the top priority will keep on playing an imperative role in attaining a more sustainable and eco-friendlier world. Also it has been seen that there are various challenges in adopting innovation, and each innovation system has some feedback loops which need to be taken care of to deliver maximum benefit. Principal agent problem can be avoided by involving the local community in adopting the technology. Technology development in secure niches can enable crucial experimentation and early user interaction to include the input that is required (Lebel & Lorek, 2008). Such as, when developing clean biomass cookstoves for Darfur, user participation at an early testing phase, made possible by seed money and in-kind work, led to 14 iterations of stove models, resulting in designs that were more suited to the region’s cooking customs (Booker et al., 2012). Sustainable development will not grow into a strong enough organising principle to align actor behaviour in most innovation systems without more effort from practitioners, politicians and scholars. It is necessary to mobilise the various forms of power that can be used to transform institutions at all stages of innovation systems, from creation through widespread usage at various scales, from local to global, in order to realign them towards sustainable development. This is why governments from developed and developing nations are being urged to make a worldwide fund for biomedical R&D (WHO, 2016), a perfect example of restructuring institutions concurrently at the local, national and international levels (World Bank, 2011). The pandemic produced a special climate where businesses from a variety of industries saw the use of technologies as crucial, advancing more of these initiatives than ever before. The IoT ecosystem is

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continuously changing. Although traditional IoT platform suppliers, cloud solution providers and system integrators continue to play important roles in the value chain, the growing importance of cloud hyperscalers is an obvious phenomenon. According to a 2021 Omdia Enterprise IoT survey, 92% of businesses using IoT solutions anticipate increased sustainability. Increased sustainability will promote brand equity and cost savings. Thus, technology gives businesses the tools they need to not just commit to environmentally sustainable practises but also to make these efforts pay off financially (Informatech, 2022).

Recommendation To effectively promote environmental and economic sustainability, it is primarily important to address social sustainability. Thus, it is imperative to get people to commit to ‘sustainable development practices’ like conservation of water and other renewable and non-renewable resources, saving electricity, recycling and so on (Fatimah et al., 2020). Technological development, deployment and their diffusion and transfer is basically a very complex process. Thus, the environmentally sound technologies should have sound compatibility with the developmental goals and the priorities of the national environment, socio-economic aspects and culture (Peris-Ortiz et al., 2019). In terms of science, an appropriate picture of the current status can be highlighted from a futuristic perspective. Hence, it is imperative to have a conceptual understanding of the crucial roles of new technologies and the way to bring about innovation to improve knowledge in the current field (Shan et al., 2020). These might provide assurance of sustainable economic development along with a sense of prioritisation of research in some fields like informational technology and communication, depletion of natural resources, environmental degradation and climatic change. In order to reorient innovation systems towards sustainable development and ensure that all innovation stages and scales are taken into account, it is necessary to establish channels for regularised learning across domains of practise, develop measures that take the interests of underserved populations into account throughout the innovation process and reform institutions (Anadon et al., 2016). Also, as mentioned earlier, actors with different types of power have the ability to restructure institutions in ways that encourage innovation for sustainable development. Thus, the relationships between institutions and actors of various sizes and sectors over the many stages make innovation systems complicated and flexible. So, modular technology be adopted for easy penetration and adoption in initial stages (World Bank, 2011). Interoperability with already existing IT systems, industry-wide standardisation of AI assessment and success, the adoption of standardised legislation and governance, as well as a stronger push to increase diversity in the industry are some of the suggestions (Informatech, 2022). Also, the ability of less powerful groups be increased to speak on their behalf in international forums such that technology can be adopted for sustainable development.

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Implications for Research and Practice Research needs to be continuously done and adapted to, in the changing technology scenario such that the developing disruptive technologies like ChatGPT, metaverse, etc. can be used for the good of all negating the drawbacks if any. SDGs can be easily achieved with the adoption of innovative disruptive technologies. Adoption of environmental, social and governance practices also becomes possible with innovative technology and is a must for sustainability. Indeed, the adoption of innovative technology like AI would empower humans to concentrate on critical tasks and save time, resources and energy on routine tasks. Upskilling and continuous learning would be a default for all.

Future Research Directions Future research can help in putting the innovations to the best use without harming humans, accordingly developing and researching the innovative ecosystem, required for the same. Also, research can be done on sustainable vocations and sustainability with innovative technologies. Research on collaborations for technological sustainability can be conducted. More studies on cyber security can be conducted as security only can boost adaptation of innovation. Innovative ecosystems of the different sectors can be studied for sustenance, which is the need of the hour.

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Camilleri, M. A., & Ratten, V. (2020). The sustainable development of smart cities through digital innovation. Sustainability. https://www.mdpi.com/journal/ sustainability/special_issues/Smart_Cities_Digital_Innovation Cancino, C. A., La Paz, A. I., Ramaprasad, A., & Syn, T. (2018). Technological innovation for sustainable growth: An ontological perspective. Journal of Cleaner Production, 179, 31–41. EC Electronics. (2022, February 14). Keeping the world connected through electronics. https://ecelectronics.com/news/electronics-keeping-the-world-connected Fatimah, Y. A., Govindan, K., Murniningsih, R., & Setiawan, A. (2020). Industry 4.0 based sustainable circular economy approach for smart waste management system to achieve sustainable development goals: A case study of Indonesia. Journal of Cleaner Production, 269, 122263. Fu, B., Wang, S., Zhang, J., Hou, Z., & Li, J. (2019). Unravelling the complexity in achieving the 17 sustainable-development goals. National Science Review, 6(3), 386–388. Granstranda, O., & Holgerssonb, M. (2020). Innovation ecosystems: A conceptual review and a new definition. Technovation. https://doi.org/10.1016/j.technovation. 2019.102098 Herrero, M., Thornton, P. K., Mason-D’Croz, D., Palmer, J., Bodirsky, B. L., Pradhan, P., Barrett, C. B., Benton, T. G., Hall, A., Pikaar, I., & Bogard, J. R. (2021). Articulating the effect of food systems innovation on the Sustainable Development Goals. The Lancet Planetary Health, 5(1), e50–e62. Informatech. (2022). Top digital transformation trends 2022. https://informatech.turtl. co/story/top-digital-transformation-trends-2022 Kalenov, O., Kukushkin, S., & Kamanina, R. (2019). Innovative technological potential as the basis of mining regions sustainable development in the era of knowledge. E3S Web of Conferences, 105, 04028. Kihombo, S., Ahmed, Z., Chen, S., Adebayo, T. S., & Kirikkaleli, D. (2021). Linking financial development, economic growth, and ecological footprint: What is the role of technological innovation? Environmental Science and Pollution Research, 28(43), 61235–61245. Laurin, F., & Fantazy, K. (2017). Sustainable supply chain management: A case study at IKEA. Transnational Corporations Review, 9(4), 309–318. Lebel, L., & Lorek, S. (2008). Enabling sustainable production-consumption systems. Annual Review of Environment and Resources, 33, 241–275. Maskus, K. E., & Reichman, J. H. (2004). The globalization of private knowledge goods and the privatization of global public goods. Journal of International Economic Law, 7(2), 279–320. Mikhno, I., Koval, V., Shvets, G., Garmatiuk, O., & Tamoˇsiūnien˙e, R. (2021). Green economy in sustainable development and improvement of resource efficiency. Central European Business Review, 10(1), 99–113. Mishra, S. K., Sharma, V. K., & Niazi, K. R. (2017). Technology for sustainable energy: A review. Renewable and Sustainable Energy Reviews, 74, 235–242. Mishra, A. K., Srivastava, M. K., & Sharma, K. (2018). Technology for sustainable urban development: A review. Habitat International, 80, 18–27. Muradi, M. A. (2018). Evaluation of Vocs Fluxes from sewage treatment plants in Surat City (Doctoral dissertation). Gujarat Technological University.

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Nemet, G., & Kammen, D. (2007). U.S. energy research and development: Declining investment, increasing need, and the feasibility of expansion. Energy Policy, 35, 746–755. Pedrique, B., Strub-Wourgaft, N., Some, C., Olliaro, P., Trouiller, P., Ford, N., P´ecoul, B., & Bradol, J. H. (2013). The drug and vaccine landscape for neglected diseases (2000–11): A systematic assessment. Lancet Global Health, 1(6), e371–e379. Peris-Ortiz, M., Ferreira, J. J., & Merigo, J. (Eds.). (2019). Knowledge, innovation and sustainable development in organizations. Springer. http://hdl.handle.net/10400.6/ 6598 Quaddus, M. A., Islam, S. M. R., & Azam, M. F. (2016). Technology adoption for sustainable development: A review of success factors. Journal of Cleaner Production, 121, 142–157. Satish, K. (2021). Embracing environmental sustainability: The case of Microsoft Corporation. https://doi.org/10.2139/ssrn.3882786 Shan, H., Li, Y., & Shi, J. (2020). Influence of supply chain collaborative innovation on sustainable development of supply chain: A study on Chinese enterprises. Sustainability, 12(7), 2978. Shrivastava, P., Ivanaj, S., & Ivanaj, V. (2016). Strategic technological innovation for sustainable development. International Journal of Technology Management, 70(1), 76–107. Singh, S. K., Gautam, R. K., & Tyagi, S. (2019). Technology for sustainable water management: A review. Journal of Environmental Management, 232, 858–871. Singh, K. K., Kumar, P., & Kumar, V. (2016). Technology for sustainable agriculture: A review. Journal of Cleaner Production, 112, 4292–4307. Song, M., Fisher, R., & Kwoh, Y. (2019). Technological challenges of green innovation and sustainable resource management with large scale data. Technological Forecasting and Social Change, 144, 361–368. Springwise. (2019, May 9). App helps customers find local restaurants that share their values. https://www.springwise.com/app-helps-customers-find-local-restaurantsshare-food-values/ Tabrizian, S. (2019). Technological innovation to achieve sustainable development—Renewable energy technologies diffusion in developing countries. Sustainable Development, 27(3), 537–544. Vatananan-Thesenvitz, R., Schaller, A. A., & Shannon, R. (2019). A bibliometric review of the knowledge base for innovation in sustainable development. Sustainability, 11(20), 5783. Wang, M., Pang, S., Hmani, I., Li, C., & He, Z. (2021). Towards sustainable development: How does technological innovation drive the increase in green total factor productivity? Sustainable Development, 29(1), 217–227. WHO. (2016). Health product research and development fund: A proposal for financing and operation. Special Programme for Research and Training in Tropical Diseases. World Bank. (2011). The changing wealth of nations: Measuring sustainable development in the new millennium. Environment and Development. https://open knowledge.worldbank.org/handle/10986/2252

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Chapter 8

Exploring the Relationship Between Digital Initiatives, Dynamic Capabilities and Market Performance: A Conceptual Framework Lan Phuong Ho Dang

Abstract This chapter delves into the impact of digital initiatives on firms and sheds light on how they can be explained through market reactions and the resource/capabilities mechanism. By providing a novel conceptual framework that reflects the potential impact of digital initiatives on the sensing, seizing and transforming capabilities of dynamic capabilities, this chapter reveals the tremendous potential of digital initiatives to help firms become more adaptive to their environment and create sustainable competitive advantages that elicit positive market responses. This conceptual framework represents an original contribution to the literature. It enhances the understanding of the resource-based view and efficient market hypothesis, providing a fresh perspective on the influence of digital initiatives on firm performance and the dynamic capabilities mechanism that has hitherto been overlooked. As a result, this chapter enables researchers to develop testable hypotheses that examine the causal relationships between digital initiatives, dynamic capabilities and market performance using robust quantitative research methods. Furthermore, this chapter offers valuable insights for managers seeking to develop a more focused approach to digital transformation and enhance their competitive advantage. By exploring the impact of digital initiatives on sensing, seizing and transforming capabilities, managers can gain a deeper understanding of how they can leverage digital initiatives to improve their organisational performance and respond more effectively to the demands of an ever-changing landscape.

Fostering Sustainable Development in the Age of Technologies, 113–128 Copyright © 2024 Lan Phuong Ho Dang Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231010

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Keywords: Digital initiatives; market reactions; resource/capabilities mechanism; dynamic capabilities; sustainable competitive advantage; digital transformation

Introduction The ever-evolving landscape of digital initiatives and their widespread adoption has captured the interest of scholars who are studying their values and impacts. The event study approach has gained popularity as a means of assessing the potential of digital initiatives through market reactions. A positive market reaction to the adoption of a digital initiative indicates that it brings value to firms and holds promise for the future (Dang, 2022). The advantages of this approach are the immediate, accurate and efficient evaluation of the impact of digital initiatives on the company, as well as the ability to predict and assess the potential of digital initiatives for the future (Fama, 1970, 1998, 2021; Malkiel, 1989). Numerous digital initiatives have been examined and found to receive positive market reactions, such as big data, cloud computing, blockchain, digital websites, social media channels and artificial intelligence (AI) chatbots (Chen et al., 2019, 2022; Dang, 2022; Fotheringham & Wiles, 2022; Liu et al., 2022; Son et al., 2014; Yu & Shengbin, 2022; Zhang et al., 2017). However, studies have yet to provide a clear and systematic explanation for why the market reacts positively to these digital initiatives. Some studies have begun to apply the resource/capabilities mechanism to explain how their digital initiatives contribute unique strategic resources and capabilities that are difficult for competitors to imitate, thus being positively evaluated by the market (Dang, 2022; Fotheringham & Wiles, 2022; Lam et al., 2019; Liu et al., 2022; Son et al., 2014; Zhang et al., 2017). However, these resources are often fragmented and presented independently across different studies. Therefore, it is challenging to identify a systematic resource/capabilities framework for different digital initiatives, especially given the countless and diverse appearances of digital initiatives across different industries. As such, the primary objective of this chapter is to address the gaps in the existing literature by answering the question ‘What is the impact of digital initiatives on firms and how can it be explained through market reactions and the resource/capabilities mechanism?’. To be more specific, this chapter aims to achieve the following goals: • Introduce a conceptual framework aimed at elucidating the impact of digital

initiatives on firms via market reactions. The adoption of a digital initiative is deemed to have a favourable impact on a company’s value if it elicits a positive market reaction. • Explain the underlying mechanism behind the positive market reaction to digital initiatives. This chapter postulates that the resource/capabilities mechanism is responsible for this phenomenon, wherein the dynamic capabilities of the firm are augmented by the implementation of digital initiatives.

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The conceptual framework demonstrates the relationship between digital initiatives and market performance through the mediating role of dynamic capabilities. Dynamic capabilities refer to the firm’s ability to sense changes in the market environment, seize opportunities and reconfigure its resources accordingly (Teece, 2007; Teece et al., 1997). They play a critical role in the sustainability of the corporation and the competitive advantage of the firm (Wu et al., 2013). Firms can secure their competitive advantage and navigate shifting market landscapes by consistently refreshing their resources and capabilities. This proactive approach equips them to withstand economic downturns and unforeseen disruptions that could affect their industry. In today’s digital age, markets are characterised by constant and rapid changes driven by advancements in technology, globalisation and changing consumer behaviour. These changes create both challenges and opportunities for firms seeking to maintain a competitive edge. In such a dynamic environment, traditional sources of competitive advantage such as natural resources or economies of ¨ et al., 2021). To scale may quickly become obsolete or less relevant (Ellstrom address this challenge, firms need to have the ability to continuously sense, seize and reconfigure their resources in response to changes in the market environment. Dynamic capabilities, therefore, are crucial for firms to survive and thrive in such a dynamic environment. From an investor’s perspective, dynamic capabilities can be a critical factor to consider when evaluating the effectiveness of a firm’s digital initiatives (Jacobi & Brenner, 2018; Karimi & Walter, 2015). Firms with strong dynamic capabilities are more likely to successfully implement digital initiatives and create sustainable competitive advantages. As such, they are more attractive to investors and more likely to outperform their competitors in the long run. Therefore, investors and markets should consider dynamic capabilities as a key factor when evaluating digital initiatives and investing in firms. Investing in digital initiatives can have a positive impact on a company’s dynamic capabilities in three key dimensions: sensing, seizing and reconfiguring (Battleson et al., 2016; Chen et al., 2014; Li, Tong, et al., 2022; Mikalef et al., 2019; Xiao et al., 2020). As a result of these benefits, investing in digital initiatives can increase a company’s dynamic capabilities, making it more agile, innovative and adaptable. This, in turn, can lead to improved market performance, as the company is better able to respond to changing market conditions, exploit opportunities and meet the evolving needs of its customers. This chapter makes significant contributions to both theoretical and practical aspects. Theoretically, this chapter presents a new conceptual framework that integrates two essential theories, the resource-based view (RBV) and efficient market hypothesis (EMH), in the digital discipline. While previous studies have attempted to combine RBV and EMH, the integration has not been well-defined and systematic. RBV has primarily been used to support the explanation of findings, leaving the information regarding the specific resources/capabilities that a digital initiative can bring to a company and how it can generate positive market reactions vague and unsystematic. This chapter identifies dynamic capabilities as a strategic benefit that a digital initiative can provide to a company and

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consequently generate positive market reactions. Dynamic capabilities, however, have not been adequately addressed in previous studies on market reactions to digital initiatives. From a practical perspective, this chapter provides companies with a systematic reference for any digital initiative that they have already implemented, currently using or planning to use. By combining external market information and internal dynamic capabilities, companies can make better-informed decisions about digital initiatives. Moreover, this chapter helps companies understand the specific mechanisms through which digital initiatives can provide sustainable competitive advantages and the reasons why investors respond positively to digital initiatives. The subsequent sections of this chapter are arranged as follows. A literature review will ensue, aimed at providing a comprehensive understanding of the current state of knowledge and identifying gaps in the literature. Subsequently, the conceptual framework will be presented, delineating the specific processes involved. Lastly, the concluding section will furnish a summary of the discussions, offer theoretical and managerial implications and suggest avenues for further research.

Literature Review Nowadays, digital initiatives have become indispensable for companies to stay relevant and competitive. Therefore, studying the role and impact of digital initiatives on firms has attracted the attention of many scholars. One of the commonly used approaches is to evaluate the market and investor reactions. This approach is based on the fundamental principle of the EMH that suggests information is quickly and accurately reflected in the price (Fama, 1970, 1998, 2021; Malkiel, 1989). As a result, any event that occurs is rapidly evaluated based on its intrinsic value. Thus, studies using market-based methods have evaluated digital initiatives by examining how investors react to them. If a digital initiative receives positive market reactions, it means that it has a positive and significant contribution to the firm. Digital initiatives found to receive positive market reactions include cloud computing (Li, Wang, et al., 2022; Son et al., 2014), digital websites (Dang, 2022), blockchain (Chen et al., 2019, 2022; Liu et al., 2022), AI adoption (Fotheringham & Wiles, 2022; Lui et al., 2022), social commerce initiatives (Lam et al., 2019) and big data (Zhang et al., 2017). To explain the positive market response to digital initiatives, most studies have applied the theoretical framework of RBV. RBV argues that firms achieve economic rents and sustainable competitive advantages only when they possess strategic resources and capabilities that possess attributes such as value, rarity, inimitability and non-substitutability (Amit & Schoemaker, 1993; Barney, 1991; Collis & Montgomery, 1995; Dierickx & Cool, 1989; Grant, 1991; Lippman & Rumelt, 1982). Empirical scholars have leveraged RBV to explain that the reason

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why a digital initiative can receive a positive market response is that it genuinely helps firms to possess such strategic resources and capabilities. For example, in a recent study on the impact of website adoption on commercial banks, Dang (2022) postulated that the market reacts favourably to website adoption due to the strategic resources and capabilities such as human, culture and knowledge that website adoption provides. Similarly, Liu et al. (2022) observed positive market reactions surrounding blockchain events of sample firms, attributing this to the ability of blockchain technology to furnish firms with strategic resources, including intellectual property and technology that positively influence their market performance. Table 8.1 provides more detailed information on recent studies that examine the impact of digital initiatives using market-based approaches. It also indicates whether and how RBV has been utilised to support the reported findings. The literature shows a growing diversity in studies on digital initiatives which provide valuable insights into the value and impact of each individual digital initiative. Market-based methods and the EMH framework have been widely applied and have demonstrated the positive impact of digital initiatives on the market value of companies. Moreover, previous studies have used the RBV as a theoretical framework to explain why investors and markets respond positively to digital initiatives. However, it can be observed that the resources and capabilities used and explained in previous studies remain quite independent and vague. There is still a lack of conceptual frameworks that specifically indicate the role of particular resources/capabilities that impact a company’s performance through the adoption of digital initiatives. For instance, Liu et al. (2022) argue that blockchain helps companies to own strategic resources such as intellectual property and technology, while Zhang et al. (2017) suggest that big data helps companies to own important knowledge. Clearly, these resources are presented discretely and independently for each study, and there have not been any experiments that show their relationship with digital initiatives and market performance. Therefore, it is challenging for both practitioners and managers to identify systematically which resources/ capabilities they should focus on monitoring and evaluating. Furthermore, there are many digital initiatives currently available, and they may not match the digital initiatives that have been studied. This requires more consistent and structured conceptual frameworks that can be applied to various digital initiatives.

Conceptual Framework As previously discussed, the existing literature lacks a comprehensive and systematic conceptual framework related to investigating the impact of digital initiatives on firm value and the key mechanisms that play a crucial role in that relationship. Therefore, the objective of this conceptual framework is to fill this gap by proposing a systematic framework that demonstrates the relationship between digital initiatives and the market performance of the firm, with the mediating role of dynamic capabilities.

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Table 8.1. A Review of Studies on the Relationship Between Digital Initiatives and Firm Market Performance (With or Without Applying RBV). Authors

Chen et al. (2022)

Chen et al. (2019)

Dang (2022)

Digital Initiatives

Outcomes

Applied RBV

Blockchain There has been a No significant increase in the value of listed firms following blockchain announcements. No FinTech FinTech innovations benefit both innovators and the financial sector as a whole. Digital The market reacts Yes website positively to the adoption of a digital website.

Fotheringham AI chatbot Implementing AI Yes and Wiles adoption customer service (2022) chatbots results in a positive abnormal stock return, indicating that investors respond favourably to this practice. Lam et al. Social Firms experience Yes (2019) commerce increased stock initiatives returns from social commerce

Explanation Using RBV

Digital websites provide firms with access to important digital resources such as digital culture, tacit knowledge and digital-related human resources. AI chatbots serve as a valuable resource for firms, enhancing customer value.

Social commerce provides firms with the opportunity to tap into valuable

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Liu et al. (2022)

Blockchain On the release day, blockchain announcements generate a considerably positive market response.

Yes

Son et al. (2014)

Cloud Firms’ cloud computing computing initiatives have been received positively by the market.

Yes

Zhang et al. (2017)

Big data

Yes Announcements of big data investments by listed firms in a sample lead to an overall increase in stock prices in the stock market.

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social media resources, thereby gaining a competitive edge. Blockchain technology enables firms to acquire strategic resources such as intellectual property and technology, which can have a positive impact on their market performance. Cloud computing provides organisations with instant access to a range of off-theshelf IT capabilities, as well as increasing their slack resources that can be redirected towards core business activities. Big data not only offers a vast resource for knowledge creation, but effective knowledge utilisation and transfer are necessary for communicating insights derived (Continued)

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Table 8.1. (Continued) Authors

Digital Initiatives

Outcomes

Applied RBV

Explanation Using RBV

from big data within an organisation, thereby maximising the value of big data investments. Source: Author’s creation.

The conceptual framework proceeds as follows: (1) The framework is based on the RBV, which posits that dynamic capabilities are a critical factor in a firm’s long-term competitive advantage. According to the literature, the competitive advantages of a firm based on its resources may become obsolete in a dynamic and continuously changing market (Yeow et al., 2018). Hence, in the era of digitalisation where the market is frequently disrupted by new digital innovations, dynamic capabilities are ¨ et al., 2021). Various scholars have emphasised the deemed crucial (Ellstrom significance of dynamic capabilities to enable companies to continuously develop their resources, attain sustainable competitive advantages and retain their competitiveness over time in a dynamic market (Ambrosini et al., 2009; Hess et al., 2016; Teece, 2007). As such, when markets and investors evaluate a firm’s performance, they are likely to consider the firm’s dynamic capabilities as a driver of performance. Therefore, dynamic capabilities have a positive impact on performance. (2) The framework argues that digital initiatives can create or enhance a firm’s dynamic capabilities at all three dimensions: sensing, seizing and transforming (Battleson et al., 2016; Chen et al., 2014; Li, Tong, et al., 2022; Mikalef et al., 2019; Xiao et al., 2020). By leveraging digital technologies such as data analytics, machine learning and automation, firms can develop new products and services, improve operational efficiency and increase agility in responding to changes in the environment. As a result, digital initiatives can enhance a firm’s dynamic capabilities. (3) The framework argues that with the creation or enhancement of dynamic capabilities through digital initiatives, firms are likely to receive positive evaluations from the market.

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Fig. 8.1. Conceptual Model of Digital Initiatives and Market Performance Mediated by Dynamic Capabilities. Source: Author’s creation.

Fig. 8.1 provides a detailed representation of the conceptual framework that explains the specific ways in which digital initiatives impact a firm’s market performance through the mediating role of dynamic capabilities. The framework proposes that digital initiatives impact the three dimensions of dynamic capabilities: sensing, seizing and transforming, ultimately enhancing a firm’s dynamic capabilities. This, in turn, leads to positive market reactions.

Dynamic Capabilities and Market Performance Dynamic capabilities refer to a firm’s ability to adapt and respond to changes in its environment, specifically its ability to reconfigure its resources and capabilities to achieve competitive advantage (Teece, 2007; Teece et al., 1997). Dynamic capabilities involve three key processes: sensing, seizing and transforming. Sensing involves the ability to identify changes in the external environment that could potentially impact the firm’s performance. Seizing involves the ability to quickly and effectively capitalise on these changes by reconfiguring the firm’s resources and capabilities. Transforming involves the ability to change the firm’s existing resources and capabilities in response to changes in the environment.

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Dynamic capabilities are considered essential for firms operating in rapidly changing industries or markets. By being able to adapt quickly to changes in the environment, firms can maintain their competitive advantage and sustain long-term success (Wu et al., 2013). Wu et al. (2013) proposed three ways in which dynamic capabilities can aid companies in improving their sustainability efforts. Firstly, dynamic capabilities can assist companies in establishing and enhancing open communication channels with both direct and indirect stakeholders. This includes engaging with customers, suppliers, employees, regulators and other relevant stakeholders to obtain a better understanding of their sustainability concerns and expectations. By doing so, companies can quickly adapt to the fast-changing sustainability trends and gain new sustainability information and knowledge. The newly acquired sustainability insights are then forwarded to individuals or planning units capable of interpreting and making sense of them. This process ensures that the company’s sustainability knowledge base is continuously updated and relevant. Secondly, dynamic capabilities enable cross-functional knowledge sharing and experimentation with new technologies. This process helps identify potential sustainable development opportunities that may be overlooked when using a single-function approach. By sharing knowledge and experimenting with new technologies across different functions, companies can discover innovative and sustainable solutions to complex sustainability challenges. This approach can lead to more efficient and effective decision-making, as well as a better understanding of the interdependencies between sustainability issues and business functions. Lastly, dynamic capabilities can help companies develop relationships with external stakeholders and promote the learning and training processes of the company. This includes establishing partnerships with non-governmental organisations, academic institutions and other external entities to enhance the company’s sustainability performance. Through these partnerships, companies can gain access to new knowledge, expertise and resources that can help them develop more sustainable business practices. Additionally, dynamic capabilities can facilitate the learning and training processes of the company by promoting a culture of continuous learning and improvement. This approach can lead to a more engaged and committed workforce that is better equipped to tackle sustainability challenges. The significance of dynamic capabilities has increased in the era of digitalisation. It is imperative for firms to first develop digital sensing capabilities to effectively respond to the constantly changing business landscape and take timely action to manage change (Jacobi & Brenner, 2018). To understand, capture and evaluate potential business opportunities, firms must improve their rules and ¨ routines, strengthen leadership and refine strategies (Ellstrom et al., 2021). However, when introducing new technologies into existing firms, there may be a capability gap (Karimi & Walter, 2015). Therefore, having a seizing capability is crucial to capturing value from new opportunities. Moreover, many firms may lack the necessary internal resources such as digital expertise, to succeed in digital transformation (Yeow et al., 2018). Hence, such firms need to develop a reconfiguring capability to access and build new resources.

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Digital Initiatives and Dynamic Capabilities As previously mentioned, dynamic capabilities encompass three distinct capabilities, namely sensing, seizing and transforming. A review of prior research suggests that digital initiatives can positively impact on all three facets of dynamic capabilities. Firstly, digital initiatives can provide firms with sensing capabilities, allowing them to quickly recognise and respond to changes in the external environment. Digital initiatives can enable real-time data collection, enabling firms to gather data from new digital channels and enhance their sensing capacities to better understand user behaviours across contexts and marketplaces (Li, Tong, et al., 2022; Li, Wang, et al., 2022). Moreover, digital tools can enable sophisticated data analytics, helping firms identify patterns and trends that may not be immediately apparent, thus allowing them to anticipate changes in the external environment and take proactive measures to address them. For example, big data can help process unstructured and varied data sources in shorter cycle times, improving the speed, effectiveness and efficiency of generating insights (Mikalef et al., 2019). Additionally, digital initiatives can facilitate collaboration and crowdsourcing, enabling firms to tap into the collective intelligence of employees, customers and other stakeholders. This can help firms identify changes in the external environment that may not be immediately apparent to any one individual or group. By leveraging this collective intelligence, firms can develop new and innovative ways of responding to changes in the external environment. For example, crowdsourcing can be used to generate new product ideas or to identify new market opportunities, enabling firms to stay ahead of their competitors (Felin & Powell, 2016). The application of digital initiatives can significantly enhance seizing capabilities, which refers to a firm’s ability to quickly and effectively reconfigure its resources and capabilities in response to changes in the external environment. By leveraging digital tools and knowledge processes, firms can develop successful dynamic capabilities that enable them to capitalise on opportunities and mitigate threats (Wamba et al., 2017; Xiao et al., 2020). Additionally, digital initiatives can facilitate the dynamic allocation of resources in accordance with business needs and provide on-demand access to configurable Information Technology (IT) resources. For example, cloud computing is found to have dynamic discovery and the ability to bring together IT resources based on current needs, which may help organisations identify and compose relevant services to create customised solutions (Battleson et al., 2016). Digital initiatives can have a significant impact on transforming capabilities by enabling it to adapt its resources and capabilities to changes in the environment. Through the use of digital technologies, firms can gain new tools and capabilities that allow them to quickly and effectively respond to changes in customer preferences, market conditions and competitive pressures. For instance, digital initiatives can help firms develop new products or services that better meet the evolving needs of their customers by leveraging tools such as data analytics and

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machine learning to gain a deeper understanding of customer preferences and behaviour (Xiao et al., 2020). Furthermore, by adopting digital initiatives, firms can improve their operational efficiency and agility, which is critical for responding to changes in the environment. A study by Y. Chen et al. (2014) found that the adoption of IT can streamline internal processes, reduce costs, increase productivity and improve responsiveness to market changes.

Digital Initiatives and Market Performance As indicated in the literature section, there is a growing trend among scholars to employ a combination of the EMH and the RBV to elucidate the relationship between digital initiatives and market reactions (Dang, 2022; Fotheringham & Wiles, 2022; Lam et al., 2019; Liu et al., 2022; Son et al., 2014; Zhang et al., 2017). According to this theoretical framework, investors and markets are more likely to have a positive reaction to firms that possess strategic resources or capabilities that allow them to create and sustain a competitive advantage. In the digital era, markets have become more dynamic and constantly changing due to the rapid advancements in technology and the increasing globalisation of business. As a result, firms need to be able to adapt to these changes and continuously renew their resources in order to remain competitive. This is where dynamic capabilities come into play, as it refers to a firm’s ability to sense changes in the market environment, seize opportunities and reconfigure its resources accordingly.

Conclusion In today’s rapidly evolving landscape, companies are increasingly compelled to embrace digital transformation to remain competitive and relevant in their respective industries. As such, it is crucial to comprehend the value and impact of digital initiatives and the mechanisms through which they create value for firms. Various digital initiatives, such as websites, blockchain, big data and cloud computing, have been analysed using market-oriented approaches. This approach offers a comprehensive and timely assessment, as digital initiatives are evaluated through market and investor reactions, which aim to optimise profits and provides objective, multidimensional and predictive evaluations. Most authors in this field have demonstrated that digital initiatives have a positive impact on a company’s performance, and they use the RBV as the basis for their explanations. RBV suggests that a company’s resources and capabilities are the primary drivers of its performance and competitive advantage. However, despite the extensive research in this area, the resources and capabilities presented are still fragmented and lack systematisation. This fragmentation may be due to the diverse range of digital initiatives studied and the specific contexts in which they are implemented. Therefore, there is a need for further research that systematises the resources and capabilities required for successful digital initiative implementation and explores the potential impact on a company’s performance.

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Therefore, the objective of this chapter is to propose a new conceptual framework that provides a comprehensive and systematic approach to identifying the value and impact of digital initiatives. By highlighting the importance of dynamic capabilities, this framework aims to identify the mechanisms through which digital initiatives continually create value for firms and receive positive market reactions. The proposed framework takes a market-oriented approach and EMH that evaluates the value of digital initiatives through market and investor evaluation. It also incorporates the RBV to identify the resources and capabilities necessary for digital initiatives to create value. The RBV emphasises that a firm’s resources and capabilities are key drivers of competitive advantage and, as a result, the framework focuses on dynamic capabilities, which are the firm’s ability to adapt and respond to changes in the market. This chapter makes original contributions to the field of digital transformation by advancing the relationship between the EMH and RBV. While prior studies have utilised RBV to support explanations, this study takes a novel approach by emphasising the importance of dynamic capabilities as a mechanism for digital initiatives to create value for the company. This aspect has received limited attention from market researchers, which highlights the originality and innovation of this chapter. The proposed conceptual framework provides a strong foundation for future research in this area and can aid researchers in developing testable hypotheses that investigate the causal relationships between digital initiatives, dynamic capabilities and market performance using quantitative research methods. At a practical level, this chapter provides valuable insights for managers to evaluate their digital initiatives more systematically. By considering a combination of external market factors and internal resources, managers can assess the potential value and impact of their digital initiatives more effectively. Furthermore, dynamic capabilities can help managers identify the critical factors that contribute to the success of digital initiatives and develop effective strategies to enhance market performance. By applying the proposed conceptual framework, managers can better understand how digital initiatives create value and how they can leverage their dynamic capabilities to sustain their competitive advantage in the digital age. There are some limitations that need to be addressed. One significant limitation is the lack of identification of the specific variables that act as mediators in the relationship between digital initiatives and market performance, for example, the industry characteristics, company demographics and macroeconomic conditions. The effectiveness of their digital initiatives may vary across different industries due to their unique demographic profiles and regulatory frameworks. Similarly, company-specific factors, such as size, ownership structure or management practices, can affect the impact of digital initiatives on firms’ market performance. Furthermore, macroeconomic factors, such as interest rates, GDP and government policies, can impact the relationship between digital initiatives and market performance. These are aspects that future research can consider and develop further.

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Acknowledgements Sincere thanks to Professor Santiago Carbo-Valverde (Professor of Economics, Universitat de Val`encia (Spain)), Professor Wing Lam (Executive Dean Bangor College China, Bangor University, United Kingdom), Dr Gwion Williams (Director of Postgraduate Taught Programmes in Business, Management & Marketing, Bangor University, United Kingdom), Dr Saverio Stentella Lopes (Universit`a Roma, Italy) and other academic staff of Bangor Business School, Bangor College China, Bangor University for their academic advice and support.

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Felin, T., & Powell, T. C. (2016). Designing organizations for dynamic capabilities. California Management Review, 58(4), 78–96. Fotheringham, D., & Wiles, M. A. (2022). The effect of implementing chatbot customer service on stock returns: An event study analysis. Journal of the Academy of Marketing Science, 1–21. Grant, R. M. (1991). The resource-based theory of competitive advantage: Implications for strategy formulation. California Management Review, 33(3), 114–135. ¨ Hess, T., Matt, C., Benlian, A., & Wiesbock, F. (2016). Options for formulating a digital transformation strategy. MIS Quarterly Executive, 15(2), 123–139. Jacobi, R., & Brenner, E. (2018). How large corporations survive digitalization. Digital Marketplaces Unleashed, 83–97. Karimi, J., & Walter, Z. (2015). The role of dynamic capabilities in responding to digital disruption: A factor-based study of the newspaper industry. Journal of Management Information Systems, 32(1), 39–81. Lam, H. K. S., Yeung, A. C. L., Lo, C. K. Y., & Cheng, T. C. E. (2019). Should firms invest in social commerce? An integrative perspective. Information & Management, 56(8), 103164. Lippman, S. A., & Rumelt, R. P. (1982). Uncertain imitability: An analysis of interfirm differences in efficiency under competition. The Bell Journal of Economics, 13(2), 418–438. Li, L., Tong, Y., Wei, L., & Yang, S. (2022). Digital technology-enabled dynamic capabilities and their impacts on firm performance: Evidence from the COVID-19 pandemic. Information & Management, 59(8), 103689. Li, Z., Wang, N., & Ge, S. (2022). Exploitative or explorative innovation? An event study of cloud computing business value. Electronic Commerce Research, 1–24. Liu, W., Wang, J., Jia, F., & Choi, T.-M. (2022). Blockchain announcements and stock value: A technology management perspective. International Journal of Operations & Production Management. https://doi.org/10.1108/IJOPM-08-20210534 Lui, A. K. H., Lee, M. C. M., & Ngai, E. W. T. (2022). Impact of artificial intelligence investment on firm value. Annals of Operations Research, 1–16. Malkiel, B. G. (1989). Efficient market hypothesis. In J. Eatwell, M. Milgate & P. Newman (Eds.), Finance (1st ed., pp. 127–134). Palgrave Macmillan. Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics capabilities and innovation: The mediating role of dynamic capabilities and moderating effect of the environment. British Journal of Management, 30(2), 272–298. Son, I., Lee, D., Lee, J.-N., & Chang, Y. B. (2014). Market perception on cloud computing initiatives in organizations: An extended resource-based view. Information & Management, 51(6), 653–669. Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350. Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533. Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356–365.

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Wu, Q., He, Q., & Duan, Y. (2013). Explicating dynamic capabilities for corporate sustainability. EuroMed Journal of Business, 8(3), 255–272. Xiao, X., Tian, Q., & Mao, H. (2020). How the interaction of big data analytics capabilities and digital platform capabilities affects service innovation: A dynamic capabilities view. IEEE Access, 8, 18778–18796. Yeow, A., Soh, C., & Hansen, R. (2018). Aligning with new digital strategy: A dynamic capabilities approach. The Journal of Strategic Information Systems, 27(1), 43–58. Yu, C., & Shengbin, H. A. O. (2022). Impact of entrepreneurial orientation and network orientation on new venture growth in digital world. Journal of Systems Management, 31(4), 708. Zhang, T., Wang, W. Y. C., & Pauleen, D. J. (2017). Big data investments in knowledge and non-knowledge intensive firms: What the market tells us. Journal of Knowledge Management, 21(3), 623–639.

Chapter 9

Reverse Logistics: Rebuilding Smart and Sustainable Transformation Based on Industry 4.0 Leena Wanganoo and Rajesh Tripathi

Abstract Climate change and digitisation are unquestionably the two defining features of this era. Both present immense challenges with unimaginable consequences for humankind while promising enormous rewards for those who can adequately address their adverse effects. These two critical factors must be considered while establishing strategies for the businesses’ future operations. Hence, post-pandemic, especially with the rise of online commerce, packages and documents are delivered around the globe nearly every day, propelling the logistics industry’s growth. This is not the critical challenge in logistics, the issue of sustainability, particularly as the returns are increasing exponentially, leading to a significant impact on transportation is and its reliance on fossil fuel has made it a prime target for society’s growing environmental concerns. Thus, real-time visibility, collaboration and integration in reverse logistics (RL) are imperative for business sustainability. The most applicable Industry 4.0 technologies in RL are the Internet of Things (IoT), cloud computing, blockchain and digital twin that enable the defragmentation of the RL market. This chapter analyses the technological impact of Industry 4.0 on RL. This research investigates the challenges faced by the logistics industry in the context of sustainability and how digital transformation can bring many potential benefits across the entire value chain. This chapter also presents a guidance for a framework based on the literature review that tends to favour the development of elastic logistics, implying improved company responsiveness to market conditions. The study contributes to the body of literature and the establishment of the framework for planning on the application of various Industry 4.0 technologies in developing eco-friendly and sustainable reverse logistics framework. Fostering Sustainable Development in the Age of Technologies, 129–143 Copyright © 2024 Leena Wanganoo and Rajesh Tripathi Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231011

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Keywords: Reverse logistics; Industry 4.0; sustainability; advanced technologies; real-time visibility; decision support system

Introduction E-commerce has seen significant growth over the past decade; according to Hung (2022), by the end of 2022, e-commerce will account for 20.4% of global retail sales, up from 10% five years ago value wise according to Statista (2022). The COVID-19 pandemic has played a role in the growth of e-commerce, as many consumers have turned to online shopping as a result of stay-at-home orders and social distancing measures. It is likely that the trend towards e-commerce will continue post-pandemic, as more and more consumers become comfortable with making purchases online and as technology continues to improve and become more widely available. Further, estimation shows that it has lot of room to expand, and it could grow from $3.3 trillion today to $5.4 trillion by 2026. The fact that growth persisted in 2021 is evidence of a real behavioural shift to shopping online (Morgan Stanley, 2022). Fig. 9.1 shows the growth trend across region, which explicitly illustrates the upward trend for e-commerce. Online trade has the potential to greatly impact both consumer behaviour and logistics operations in urban areas. The growth of e-commerce has led to an increase in home deliveries, which can have a significant impact on traffic congestion and delivery logistics in urban areas. Additionally, online shopping can change the way people consume goods, as they have more options and can make purchases from a wider range of retailers, potentially leading to changes in the retail landscape (Bjerkan et al., 2020). E-commerce companies often have a high volume of small package deliveries, which can be challenging for traditional logistics providers to handle. This has led to the development of new logistics

Fig. 9.1.

E-commerce Growth Trend. Source: Created by author.

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models, such as ‘last-mile’ delivery companies, which specialise in delivering packages to residential areas. Additionally, e-commerce has also led to an increase in the number of returned goods, as online shoppers may be more likely to return items they are not satisfied with. This can put pressure on logistics providers to have efficient processes in place for handling returns, and to ensure that returned goods can be restocked and sold quickly (Vakulenko et al., 2019).

Growth of Global Parcels Returns Consumers will continue to be more accustomed to online shopping, and that may lead to a higher percentage of returns as customers become more comfortable with the process. Additionally, the growth of subscription-based models, such as clothing rental services, will also increase the number of returns. Hence the consumer returns around 5%–10% of what they purchase in store but 15%–40% of what they buy online (Timlin, 2022). Country-wise, China, the United States and Japan accounts for 87% of global parcel volumes in 2021 (Buchholz, 2022). Further, as e-commerce accelerated during the pandemic, return rates surged, increasing from 10.6% in 2020 to 16.6% in 2021 (Babcock, 2022). Other studies have found that at least 30% of all global e-commerce orders end up as returns, compared to 8.89% of regular shop sales (Das et al., 2020; Hud´ak et al., 2017; Pei & Paswan, 2018). Reverse logistics is developing rapidly. Logistics has become RL and refers to the process that focuses on managing returned goods awaiting reuse through processes such as reuse, repair, recycling or complete disposal (Euchi et al., 2019). Hence, the volume of e-commerce orders has increased and return of products, adding to the environmental impact of this consumption (Manerba et al., 2018; Guo et al., 2020). Further, according to Shen et al. (2022), consumer returns can be a significant challenge for logistics companies in the e-commerce sector for several reasons: Volume: E-commerce companies often have a high volume of small package deliveries, which can be challenging for traditional logistics providers to handle, especially when it comes to returns. This requires logistics companies to have efficient processes in place for handling returns, and to ensure that returned goods can be restocked and sold quickly. Cost: Returns can add extra costs to the logistics operations of e-commerce companies, as they need to manage the logistics of both outbound deliveries and returns. The cost of returns can include transportation, inspection, restocking and disposing of unsellable items. Complexity: Managing returns can be complex, as e-commerce companies need to coordinate with multiple parties, such as the customer, the carrier and the warehouse. This can lead to delays and inefficiencies if the process is not wellmanaged. Reverse Logistics: Returns can also create additional pressure on warehousing and inventory management, as items need to be received, inspected and restocked in a timely manner.

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Quality control: Returns can also be a challenge for quality control, as e-commerce companies need to ensure that returned items are in good condition and can be resold. This can lead to additional costs, as items that are not in good condition may need to be disposed of. Environmental impact: Returns can also have an environmental impact, as they can increase the amount of waste and carbon emissions associated with transportation. Overall, consumer returns can be a significant challenge for logistics companies in the e-commerce sector, as they need to manage the logistics of both outbound deliveries and returns while keeping costs and environmental impact in check (Cullinane et al., 2019). Further, B2C e-commerce has also raised urban issues such as traffic congestion, noise, increased fossil fuel consumption and concerns about levels of gaseous emissions (Arnold et al., 2017). With effectively maintained in RL, the environment that can be protected with total costs are reduced across the entire closed-loop supply chain. Previous research in RL has primarily focused on network design models. The relationship between sustainability and reverse flows was not factored in the closed-loop models presented by some researchers (Quak et al., 2016; Zhao et al., 2016).

Reverse Logistics (RL) Systems A typical RL system, focusing on urban exchange and return collection and distribution of products purchased through B2C e-commerce also is known as returns management or RL (Ignat & Chankov, 2020). These collections and deliveries are typically designed to meet the needs of consumers (exchange, final return or warranty repairs). Fig. 9.2 illustrates the RL systems below from end user to distribution centre and further after the repair, repackaging back to the consumer. The trips comprise of the driving of the vehicle from the to the first consumer, the collection of the product, the trip to the next consumers, and repeating this process until the last customer is collected served along the way with a subsequent return to the DC (De Mello Bandeira et al., 2019).

Fig. 9.2.

Reverse Logistics (RL) Process. Source: Author.

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While RL can be beneficial in terms of waste reduction and resource conservation, it also contributes to carbon emissions. Returning goods can cause greenhouse gas emissions, and processing returned materials can also have an environmental impact (Nahata, 2022). The fleet drivers rack up more miles, to collect the returns and exchange, leading to congested streets and higher carbon production (Lawton, 2021), with relevant direct consequences to human health and environment (Manerba et al., 2018).

Factors Influencing Carbon Emission in e-Commerce Returns According to Lv & Liu (2022), Nanayakkara et al. (2022) and Van Loon et al. (2015), there are several factors that can influence emissions in consumer product returns in e-commerce: • Transportation: The transportation of returned products, whether by truck, rail

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or air, can generate significant emissions. Factors such as the distance travelled, mode of transportation and the weight and volume of the products can all impact emissions. Processing: The processing of returned products, including sorting, repackaging and refurbishing, can also generate emissions. This can include emissions from equipment and machinery used in these operations. Disposal: The disposal of unsellable returned products, such as through incineration or landfilling, can also generate emissions. Packaging: The packaging of returned products for reshipment can generate emissions from materials and energy used in the packaging process. Volume: The volume of returned products can also influence emissions, as a larger volume of returns requires more transportation, processing and disposal. Product type: Some products may have a higher environmental impact than others, for example, products that are large, heavy, fragile or hazardous may require more energy and resources to transport, process and dispose. Technology: The use of advanced technologies such as automation, data analytics and IoT can help to reduce emissions by improving the efficiency and effectiveness of the RL process.

Overall, to reduce emissions in consumer product returns in e-commerce, companies should focus on reducing transportation, processing and disposal emissions while also looking for ways to reduce the volume of returns and selecting products with less environmental impact. ¨ (Schoder et al., 2016; Wang et al., 2021)

Industry 4.0 Technologies in Logistics New technology, such as automation and data analytics, can improve the efficiency and effectiveness of RL operations. For example, Radio Frequency Identification (RFID) technology can be used to track the movement of returned

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products and automated systems can be used to sort and process them. Additionally, data analytics can be used to identify patterns and trends in returns, which can help companies make better decisions about how to handle them. Overall, the integration of new technology in reverse logistics can lead to cost savings and improved sustainability. The Fourth Industrial Revolution, also known as Industry 4.0, refers to the incorporation of advanced technologies such as the IoT, artificial intelligence (AI) ¨ and big data in manufacturing and logistics operations (Ozdemir & Hekim, 2018). Industry 4.0 technologies can be used to improve the efficiency, accuracy and speed of the returns process in the context of RL. IoT-enabled devices, for example, can be used to track the movement of returned products, allowing for real-time visibility into the RL process. This can assist businesses in identifying bottlenecks and optimising their operations. AI and machine learning (ML) can be used to predict which products are likely to be returned and to prioritise return processing based on this information (Sun et al., 2022). The development of the Industry 4.0 paradigm enables the improvement of RL services quality and more efficient energy (and other limited resources) utilisation in several ways: • Automation: Industry 4.0 technologies such as automation, robotics and IoT

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• •

•

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allow for the automation of repetitive and labour-intensive tasks, reducing human error and increasing efficiency. Real-time data collection and analysis: IoT-enabled devices and sensors can collect and transmit real-time data on logistics operations, allowing for real-time monitoring and control of logistics processes. This can enable more accurate and efficient utilisation of resources. Predictive maintenance: ML and AI can be used to predict when equipment is likely to fail, allowing for proactive maintenance and reducing unplanned downtime. Smart routing: Advanced algorithms and data analytics can be used to optimise routes and scheduling, reducing transportation costs and emissions. Intelligent warehousing: Robotics, automation and IoT can be used to optimise the use of warehouse space and resources, improving the efficiency of inventory management and reducing energy consumption. Cyber-physical systems: Industry 4.0 technologies such as IoT and cloud computing allow for the creation of cyber-physical systems that can optimise logistics processes by coordinating the actions of various physical devices and systems in real-time. Network collaboration: Industry 4.0 can also enable collaboration between different companies in logistics networks, allowing for a more efficient use of resources and a better flow of information. Overall, the development of the Industry 4.0 paradigm enables the improvement of logistics services quality by increasing efficiency, reducing errors and allowing for more accurate and efficient resource utilisation, including energy. (Glistau & Coello Machado, 2018; Kostrzewski et al., 2019; Shen et al., 2022)

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However, there is relatively limited academic literature that specifically examines the role of Industry 4.0 technologies in enabling RL in e-commerce. The field of RL in e-commerce is a relatively new area of study, and research in this area is likely to increase in the coming years. Additionally, many of the concepts and technologies associated with Industry 4.0, such as the IoT, big data and AI, have been widely studied in other areas and can be applied to RL in e-commerce. For example, the use of IoT devices for tracking and monitoring products throughout the RL process, and the use of big data and AI for optimising sorting, remanufacturing and recycling processes are all areas where Industry 4.0 technologies can play a significant role in improving the efficiency and sustainability of RL in e-commerce. A smart framework for RL in e-commerce could be based on the integration of several technologies and applications: • Internet of Things (IoT): IoT-enabled devices can be used to track the move-

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ment of returned products, providing real-time visibility into the RL process. This can help companies identify bottlenecks and optimise their operations. Automation: Automated systems can be used to sort, and process returned products, reducing the need for manual labour, and increasing efficiency. Data analytics: Data analytics can be used to identify patterns and trends in returns, which can inform decisions about how to handle them. This can include data on the most frequently returned products, the reasons for returns and the most cost-effective method for handling returns. Artificial Intelligence (AI) and Machine Learning (ML): AI and ML can be used to predict which products are likely to be returned, and to prioritise returns processing based on this information. Cloud computing: Cloud computing can provide a centralised platform for storing, analysing and sharing data on returns, enabling companies to make data-driven decisions about how to handle returns. Augmented Reality (AR): AR could be used for returns inspection, reducing the need for physical handling of products, and for providing guidance for repackaging, refurbishing and disposing of products. Blockchain: Blockchain technology could be used to create a transparent and secure system for tracking the movement of returned products, ensuring that returns are handled in an efficient and environmentally responsible manner.

Overall, the smart framework for RL in e-commerce should be based on the integration of these technologies and applications in a way that can improve the efficiency, accuracy and speed of the returns process, reduce the environmental impact and provide a better customer experience. Employing advanced technologies for the planning and management of business processes across the entire value chain in e-commerce reverse logistics can increase the levels of economic competitiveness in several ways:

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• Cost reduction: Automation and data analytics can improve the efficiency of

RL processes, reducing labour costs, inventory costs and transportation costs. • Increased productivity: Industry 4.0 technologies such as IoT and automation

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can increase the speed and accuracy of RL operations, resulting in increased productivity and reduced downtime. Improved customer service: Advanced technologies such as IoT and data analytics can provide real-time visibility into the RL process, enabling companies to respond quickly to customer needs and improve the overall customer experience. Better decision-making: Data analytics can provide insight into patterns and trends in returns, allowing companies to make better decisions about how to handle them. Better inventory management: Advanced technologies can be used to optimise inventory management, reducing waste and improving the use of resources. Increased sustainability: Industry 4.0 technologies can help companies to reduce emissions and waste in RL operations, increasing sustainability and helping to lower the environmental impact. Network collaboration: Industry 4.0 technologies can enable collaboration between different companies in the value chain, leading to better coordination and cooperation, which ultimately leads to a more efficient and effective use of resources. (Kostrzewski et al., 2019)

Overall, by employing advanced technologies for the planning and management of business processes across the entire value chain in e-commerce RL, companies can improve efficiency. The key Industry 4.0 technologies, such as IoT, Cyber-physical systems (CPS), AI and autonomous robots, are enablers to support the smart RL transformation in several ways: Internet of Things (IoT): IoT devices can be used to track the movement of returned products, providing real-time visibility into the RL process. This can help companies to identify bottlenecks and optimise their operations. Cyber-physical systems (CPS): CPS can be used to coordinate the actions of various physical devices and systems in real-time, allowing for more efficient and effective RL operations. Artificial Intelligence (AI): AI and ML can be used to predict which products are likely to be returned and to optimise the handling of returns. AI can also be used to classify, identify and sort returned products, reducing the need for manual labour and increasing efficiency. Autonomous robots: Autonomous robots can be used to sort, repackage and refurbish returned products, reducing the need for manual labour and increasing efficiency. Real-time data collection and analysis: IoT-enabled devices and sensors can collect and transmit real-time data on RL operations, allowing for real-time monitoring and control of the process.

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Predictive Maintenance: ML and AI can be used to predict when equipment is likely to fail, allowing for proactive maintenance and reducing unplanned downtime. Smart routing: Advanced algorithms and data analytics can be used to optimise routes and scheduling, reducing transportation costs and emissions. Overall, Industry 4.0 technologies such as IoT, CPS, AI and autonomous robots can help to improve the efficiency and effectiveness of RL operations by providing real-time visibility, automation, data analytics and predictive maintenance capabilities, which can lead to cost savings, improved sustainability and enhance the customer experience.

Industry 4.0 Based Framework for Managing Reverse Logistics (RL) A framework for managing RL services in e-commerce using AI, blockchain and IoT could include the following elements: (1) IoT-enabled tracking: IoT devices such as RFID tags, sensors and Global Positioning System (GPS) can be used to track the movement of returned products in real-time, providing visibility into the RL process. (2) Blockchain-based tracking: Blockchain technology can be used to create a transparent and secure system for tracking the movement of returned products, ensuring that returns are handled in an efficient and environmentally responsible manner. (3) AI-based predictive analytics: AI and ML can be used to predict which products are likely to be returned and to prioritise returns processing based on this information. (4) Smart contract-based automation: Smart contracts can be used to automate the returns process, reducing the need for manual intervention, and increasing efficiency. (5) Automated sorting and processing: Robotics and automation can be used to sort, repackage and refurbish returned products, reducing the need for manual labour and increasing efficiency. (6) Big data analytics: Data analytics can be used to identify patterns and trends in returns, which can inform decisions about how to handle them. (7) Cloud-based data management: Cloud computing can provide a centralised platform for storing, analysing and sharing data on returns, enabling companies to make data-driven decisions about how to handle returns. Overall, this framework using AI, blockchain and IoT can enable companies to optimise their RL operations by providing real-time visibility, automation, data analytics and security, ultimately leading to cost savings, improved sustainability and better customer service.

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The conceptual framework for improving RL service in e-commerce using AI, blockchain and IoT would involve several key components working together. Fig. 9.3 illustrates the essential technologies that can integrate to provide real-time visibility and support in decision-making. IoT devices such as RFID tags, sensors and GPS would be used to track the movement of returned products in real-time, providing visibility into the RL process. Blockchain technology would be used to create a transparent and secure system for tracking the movement of returned products, ensuring that returns are handled in an efficient and environmentally responsible manner. AI and ML would be used to predict which products are likely to be returned, and to prioritise returns processing based on this information. Smart contracts would be used to automate the returns process, reducing the need for manual intervention and increasing efficiency. Robotics and automation would be used to sort, repackage and refurbish returned products, reducing the need for manual labour and increasing efficiency. Big data analytics would be used to identify patterns and trends in returns, which would inform decisions about how to handle them. Cloud computing would provide a centralised platform for storing, analysing and sharing data on returns, enabling companies to make data-driven decisions about how to handle returns. All these components would work together in a seamless and integrated way to optimise the RL process and improve the overall efficiency, accuracy and sustainability of the service.

Block Chain

AI and Machine learning

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Fig. 9.3.

Robotics & Automation

Big Data Analytics

Essential Technologies for Reverse Logistics (RL) in Digital Era.

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Companies can use Industry 4.0 technologies, such as the IoT and big data, to monitor fuel emissions in reverse logistics in the e-commerce sector. One approach is to use IoT sensors and devices to collect data on fuel consumption and emissions from vehicles and equipment used in the transportation and delivery of products. These data can then be analysed using big data and AI techniques to identify patterns and trends in fuel consumption and emissions. This can help companies identify areas where they can improve their operations to reduce fuel consumption and emissions. Another approach is to use GPS tracking and real-time monitoring to optimise routes and schedules for transportation and delivery. This can help minimise the distance vehicles need to travel, reducing fuel consumption and emissions. Companies can also use data analysis and AI to identify more efficient modes of transportation, such as electric vehicles or cargo bikes, that have lower emissions than traditional diesel trucks. Furthermore, companies can also use predictive maintenance to optimise their fleet and equipment, which can also help in reducing emissions. By using Industry 4.0 technologies to monitor and analyse data on fuel consumption and emissions, companies can take a data-driven approach to reducing their environmental impact in RL. A digitalised platform can enhance better communication and information sharing among different stakeholders in real-time, and a data-driven intelligent decision support system can improve resource planning and utilisation in RL in e-commerce in several ways: Real-time communication: A digitalised platform can provide real-time communication among different stakeholders, such as customers, suppliers, logistics providers and manufacturers. This can enable real-time coordination and collaboration, leading to more efficient and effective RL operations. Data-driven decision-making: A digitalised platform can provide real-time data collection and analysis, allowing for data-driven decision-making. This can include data on the most frequently returned products, the reasons for returns, and the most cost-effective methods for handling returns. Resource planning: A data-driven intelligent decision support system can provide insight into patterns and trends in returns, allowing for better resource planning and allocation. This can include the optimisation of transportation routes, warehouse space and labour resources. Predictive Maintenance: ML and AI can be used to predict when equipment is likely to fail, allowing for proactive maintenance and reducing unplanned downtime. Network collaboration: A digitalised platform can enable collaboration between different companies in the value chain, leading to better coordination and cooperation and improving the flow of information. Transparency and traceability: Blockchain technology can be integrated into the digitalised platform to enable transparency and traceability of the RL process, allowing all the stakeholders to have a clear view of the process and improve accountability.

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Conclusion Overall, a digitalised platform and data-driven intelligent decision support system can improve communication and information sharing among different stakeholders in real-time, enabling better resource planning and utilisation in RL operations in e-commerce, leading to cost savings and improved sustainability and customer service. Industry 4.0 technologies, such as the IoT, big data and AI, can greatly improve RL processes. Smart collection systems can use IoT devices to track and optimise the collection of used products. Smart sorting and process management systems can use AI and ML to sort and process materials efficiently. Smart remanufacturing and recycling systems can use data analysis to optimise the reuse and recycling of materials. Smart transportation and distribution systems can use real-time data and optimisation algorithms to minimise transportation costs and improve delivery times. Smart disposal systems can use data analysis to identify environmentally friendly disposal methods and track compliance with regulations. Overall, Industry 4.0 technologies can help make RL more efficient, cost-effective and sustainable. Decarbonisation, or reducing carbon emissions, can be achieved through the integration of Industry 4.0 technologies in RL service. By using advanced technologies, such as IoT, big data analytics and automation, companies can optimise their supply chain operations and improve their energy efficiency, which can lead to reduced carbon emissions. Additionally, Industry 4.0 technologies can also be used to improve the tracking and reporting of carbon emissions, enabling companies to better monitor and manage their environmental impact. Decarbonisation in RL using Industry 4.0 technology can be achieved through several methods, such as: Smart transportation: Using IoT-enabled vehicles and route optimisation algorithms, companies can reduce their transportation emissions by reducing the number of unnecessary trips and optimising delivery routes. Automation: Automating RL operations can lead to significant energy savings and improved efficiency, which can help reduce carbon emissions. Predictive Maintenance: Predictive maintenance is a way to predict when maintenance is needed and schedule it accordingly; this can help reduce downtime, minimise energy consumption and increase the lifespan of the equipment. Real-time monitoring: IoT-enabled sensors can be used to monitor the energy consumption of logistics equipment and facilities in real-time, which can help identify areas where energy consumption can be reduced. Material recovery: Industry 4.0 technologies such as ML and big data analytics can be used to improve the recovery and recycling of materials, which can help reduce the carbon footprint of RL operations. Green energy sourcing: By utilising renewable energy sources, companies can reduce their carbon emissions, and this can be achieved through smart energy management systems that can optimise energy consumption and sourcing.

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Carbon footprint tracking: Industry 4.0 technologies can be used to improve the tracking and reporting of carbon emissions, enabling companies to better monitor and manage their environmental impact.

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Chapter 10

Reflections on Sustainable Development, Sustainability and Business Practice: Lessons From Measurement, Scalability and Bias in Artificial Intelligence (AI) Luisa F. Melo

Abstract This chapter suggests that enhancing sustainable development in the age of technologies requires reflection about the relationship between business practice and sustainable development, as well as clarification of the relationship between sustainability and sustainable development. At the core of business activity is the definition of sustainable development defined by Brundtland (1987) as ‘meet[ing] the needs of the present without compromising the ability of future generations to meet their own needs’. Although that captures only one aspect of the sustainability story and its relationship to sustainable development, it nonetheless shapes business approach in research and in sustainability practices. To illustrate the contradictions and tensions in practice so far, this chapter uses three lenses: measurement in environmental, social and governance (ESG) investment, the problem of scalability and the challenge of bias in artificial intelligence (AI). It is not clear that we need a paradigm shift, but a shift in mindsets around sustainability business practice will be needed if sustainable development is to be enhanced in the age of technologies. Keywords: Sustainable development; sustainability; ESG investment; emerging technologies; scalability; bias in AI; corporate social responsibility

Introduction We live in the age of technologies. This is in an age where technologies, particularly those emergent, offer the promise of tackling every challenge that we face. Fostering Sustainable Development in the Age of Technologies, 145–161 Copyright © 2024 Luisa F. Melo Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231012

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We also live in the age of sustainability. We recognise at some level, the impact of human activity on the natural world, the relationship of that activity to the environment and to our hopes for economic development. Thinking about sustainability in the age of technologies requires some reflection about sustainability and business practice. It also requires examining the relationships between the broader sustainability movement and ideas about economic growth, sustainable development and business. These concepts are entwined but represent different paradigms. In business study, we rely on the definition of sustainable development by Brundtland (1987) as ‘meet[ing] the needs of the present without compromising the ability of future generations to meet their own needs’ (p. 16). Sustainability in business practice has been associated with ‘green’ or environment efforts, but definitions of sustainability are particular to individual firms. A report by Berns et al. (2009) found that 70% of respondents in a survey of 1,500 global executives said that their companies had not developed a clear case for sustainability. This was despite agreement that sustainability was likely to have increased impact on competition. At the same time, there has been an observed shift in how business approaches questions about sustainability, although the relationship of the firm to sustainable development is more complicated. Nonetheless, scholars are increasingly examining how firms can address the Sustainable Development Goals (SDGs) set forth by the United Nations (Sinkovics et al., 2022; Van Tulder et al., 2021; Virtual Roundtable, 2022). This chapter suggests that for technologies to aid sustainability challenges, reframing is needed. It begins with changing mindsets around sustainability in business practice and clarifying the relationship between business, theory and the SDGs. This is necessary work that should be considered as we also pack in technologies. This chapter begins with examining relationships between sustainable development, sustainability and the role of business in economic growth. This is through examining theoretical development about the firm’s role relative to development and sustainability. The context is the age of technologies. I highlight three lenses for thinking about sustainability practice and where changes in that thinking might be needed, given the nature of theory. Each section highlights theoretical and practical implications. The lenses are ESG practice, failure to scale in public policy and the emergence of bias in AI and machine learning (ML). ESG investment represents a dominant sustainability practice of firms which constitutes some $35 trillion USD (Three letters, 2022). ESG is underpinned by technology investment and development. Scalability failures highlight gaps in research design and how research informs policy. Finally, the promise of AI is hampered by the fact that algorithms trained on data learn bias. This is because data reflect our histories and larger social reality. This chapter sits in intersections. The intersection between sustainability and technologies is one. The intersection between sustainability and business practice, related to technologies, is another. To a great extent, we live with the promise that

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technologies will save us from ourselves. But this might be too simplistic. Caradonna (2014) writes that ‘creating a sustainable society that thrives within its biophysical limits is no longer seen as a distant and utopian objective; it’s now an urgent matter’ (p. 233). For sustainable technologies to thrive, the mindsets must shift.

Does Business ‘Do’ Sustainable Development? Drucker (2001) wrote that there was one ‘valid definition of business purpose: to create a customer’ (p. 20). Profit, in his view, was an indicator of how well business was meeting its purpose. From international business theory, we also understand that business searches for markets outside its borders when domestic markets become saturated. In the larger context, increased activity of business in the developing countries is directly connected to growth decline in rich countries after the oil shocks of the 1970s (Banerjee & Duflo, 2019). Yet, in current writing there is an expectation that business ought to, can or should, implement the SDGs (Van Tulder et al., 2021; Sinkovics et al., 2022). Moreover, there is an expectation that business, through technological innovation, offers the best hopes for addressing environmental degradation, sustainability and sustainable development. How did we get here?

Sustainable Development Brundtland (1987) defined sustainable development as ‘meet[ing] the needs of the present without compromising the ability of future generations to meet their own needs’ (p. 16). This definition was the result of the work of the World Commission on Environment and Development, chaired by Brundtland, which some years earlier was tasked with helping to ‘define’ shared global perceptions of long-term environmental issues and what could be done about them. The report addressed the ‘global community’ with a focus on intergovernmental co-operation. Sustainable development is defined in economics, at the level of the state rather than the firm. Economic growth for a given country relies on efficient markets that may in turn promote efficient resource use and minimise environmental degradation (Perkins et al., 2001). This comes about from the recognition that degradation of the environment is a limiting factor to growth. Development as a movement arises post World War II and is entwined with post-colonial reality and the founding of the international financial institutions, including the World Bank (the Bank) and the International Monetary Fund (IMF). The underlying force behind the development movement has been that growth matters because it frees the poor from hunger and disease. Nevertheless, as early as 1970, Robert McNamara (former President of the Bank) acknowledged that economic growth attained in the ‘development project’ was doing little to alleviate poverty. In fact, while the absolute and relative incomes of many nations increased, welfare improvements lagged far behind (Arrighi, 2002). This was evident in continued high infant mortality, low life

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expectancy, widespread illiteracy, endemic and growing unemployment and the uneven distribution in income and wealth across the developing world. By the late 1980s, hopes for sustainable development were dwindling. Brundtland (1987) highlights that the commission went much further in defining sustainable development. The definition implied limits, particularly stemming from earth’s inability to keep up with our use of resources, required a ‘new era of economic growth and an assurance that the poor get their fair share of resources to enable that growth’, and meant that ‘the affluent must adopt lifestyles within the planet’s ecological means’ (p. 16). This suggests a recognition of global inequality, a recognition of ecological reality and also a sense that the excessive consumption of the industrial world was the problem.

Sustainability and Sustainable Development Economics found a way to fuse sustainability with development, but the definition of sustainable development represents a limited vision of sustainability within business, given the larger sustainability movement. Sustainability is an abstraction as powerful as ‘democracy’, an ‘explicit social, environmental, and economic ideal’ that serves as a counterbalance and corrective to the excess of industrial society and its obsession with growth (Caradonna, 2014, p. 3). Sustainability in this paradigm is directly connected to climate change and requires a conceptualisation of the economy as nested in society, both supported by and fully dependent on the environment as the foundation. Growth, despite the lack of global growth on a global scale, is the problem. This is the essence of the critique of business from the sustainability movement. To the sustainists, ‘those who embrace sustainability in the fullest sense’, sustainability requires rejection of growth and business as usual and (rejection of) a mindset that threatens our very survival (Caradonna, 2014, p. 5). This differs from the conceptions of economy, environment and society as interdependent but as separate entities, and from the view that sustainability involves finding ways to grow while mitigating environmental damage. Notwithstanding, Banerjee and Duflo (2019) argue that in the last few decades there have been significant improvements for the global poor even though ‘many poor countries have not grown as predicted’ (p. 161). Data suggest a decrease in maternal and infant deaths, and increased access to education and literacy. Between 1980 and 2016, the bottom 50% of the population, not including Europe and the United States, experienced an increase in income that translates to approximately 13% of global growth (Banerjee & Duflo, 2019, p. 180). Absolute poverty rates, defined as those living on $1.90 per day at purchasing power parity (PPP), decreased by half since 1990. These are all evidence economic development, though likely not ‘sustainable’. Data also show that environmental degradation continues, and emissions have grown even as the focus of development has shifted to the environment. The Brundtland commission is not as far from the sustainists as it might appear. The report rightly notes that the environmental is not separate from

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economic development. More importantly, it was evident that poor nations bore, and would continue to bear, the brunt of industrial activity. This is important because business relies on Brundtland in theory. But that relationship highlights the disconnect. The definition of sustainable development put forth by the commission, arises from the understanding that environmental degradation is an issue of the industrialised world. Environmental degradation was also seen as a by-product of industrialisation and business activity. In practice, the concepts were still treated separately at the intergovernmental level. Mary Robinson (2019), former President of Ireland, former UN High Commissioner for Human Rights (HR) and former UN Special Envoy on Climate Change, notes that as HR Commissioner she rarely, if ever, considered climate change. It was not until the 2000s that she came face to face with the impact of climate change and environmental degradation in the developing world through her non-governmental work. Robinson (2019) promotes the term climate justice, which implies that climate change is an issue of human rights and justice for those at the front lines. The implications of three decades of thinking in practice is noted by researchers across disciplines. Poor countries continue to have the smallest ecological footprints and continue to be the most vulnerable to climate change and environmental damage (Henderson et al., 2020). Desjardins (2002) notes that the Global North comprises 25% of the world’s population, and accounts for 80% of consumption of goods. Robinson (2019) states that ‘1.3 billion people do not have access to electricity and 2.6 billion cook over open fires’ (p. 8). It is the world’s poor who are the least responsible for environmental damage, who remain vulnerable due to an accident of geography and lack of climate resilience.

Expanding the Role of Business In the 1980s, there was parallel evolution in thinking about the responsibility of business to broader society, and the larger corporate mission, that has an important relationship to Brundtland. The shareholder view embodied by Friedman (1970) that the ‘social responsibility of business is to increase its profit’ remained dominant until very recently. Even business ethics recognises the general responsibility of business to maximise profit, albeit through efficient allocation of resources and ‘optimal satisfaction’ of consumer demand (Desjardins, 2002). Buono and Nichols (2005) trace the emergence of stakeholder theory to changing demands on business and changing expectations from society, rooted in societal discontent beginning in the 1970s, exacerbated by the excess of business in the 1980s. They highlight stakeholder theory, as embodying the view that business activity impacts a broader set of stakeholders, who also have the capacity to affect the activity of the firm. The shift is a recognition that ‘profit goals are to be pursued within the broader context of the public interest’ (Buono & Nichols, 2005, p. 2). Under the stakeholder model, the firm rationally pursues its self-interest (profit) with enlightened

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understanding that socially responsible behaviour is necessary to ensure its long-term survival. Similar changes in terms of business responsibility to the natural environment are also evident. Desjardins (2002) illustrates a shift that begins in the 1970s and a significant period of regulation. Prior to the 1970s, business was perceived as having the responsibility to ‘do no harm’. This was referred to as the liability stage, when business was responsible for compensating those who could prove that they had been harmed by business activity. The role of business shifted to preventing harm and an expansion of business responsibility towards the environment (Desjardins, 2002; Lawrence & Weber, 2020). Much writing today, seems to collapse the understanding of the social responsibility of the firm into a view that business does sustainable development and sustainability. This is at present, operationalised through incorporation, or consideration, of the SDGs. The Brundtland (1987) definition of sustainable development is ubiquitous in current writing on sustainability in business and in business and society textbooks (see also Lawrence & Weber, 2020). Business has gone further than definition, and it may be said that some incarnation of stakeholder theory is now mainstream. Bakan (2020) highlights the primacy of ‘stakeholder capitalism’ at Davos 2020, the meeting of the World Economic Forum, where the focus was on ‘renewing the concept. . . to overcome income inequality, societal division, and the climate crisis’ (p. 11). The question remains whether this represents a true shift in paradigm. Several contradictions emerge. The part of the definition that we use does not fully capture the message of Our Common Future, and the assumptions of growth in that definition are at odds with business ethics argument about economic growth and with the larger sustainability movement. Moreover, the use of the definition obscures that the purpose of business is to create markets, and that the agreement with society allows business to pursue profit with some consideration of stakeholders. Desjardins (2002) noted that economic growth came to be seen as a way to address inequality between the Global North and the Global South. But the interpretation was not in terms of shifting resources to the global poor as Brundtland (1987) suggested, or by changing behaviours in consumption. Rather, the mission became one of exporting markets and investments to the Global South. Gehl Sampath (2021), for instance, provides a review on how AI exemplifies structural inequality, tracing the growth of large global firms in digital efforts in developing countries that largely benefits firms rather than people. The contradictions outlined above using theories about the role of business in development, matter for conceptualising business practice around sustainability and in turn, for possibilities of sustainable development in the age of technologies. For business, climate change is about risk and opportunity. The pressures on the firm to innovate and provide added value are not necessarily the same as those of meeting a grand social challenge. Pucker (2021) defines the current effort around sustainability as pushing a ‘theory of how business can prosper while pursuing greener and more socially responsible agendas’ (Par. 1).

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To be fair, business response has led to innovations in particular sectors including, farming, renewables, clean energy and electric vehicles that will move us from our dependency on fossil fuels, but it also means creating products to satisfy the demand for ‘sustainable’ products and services coming from the advanced countries (Caradonna, 2014; Haanaes et al., 2013; Henderson et al., 2020). Although outside the scope of this essay, business efforts in clean energy are also leading to new mechanisms of exploitation in poor countries as firms search for minerals necessary for clean energy systems (Searcey et al., 2021).

The Practice and Problem of Environment, Social and Governance Investing (ESG) It would appear that ESG investing has little relationship to technologies. As a practice, it is not a technological solution. Nonetheless, evaluating ESG as a dominant sustainability practice has value. ESG has become synonymous with the firm’s sustainability effort. It also tells us something about the focus of business. Growth in ESG investment constitutes one third of all professionally managed assets and is valued at $35 trillion USD (Three letters, 2022). This ‘diverse set of standards, frameworks, and metrics’ (Sætra, 2021) surrounding environment, social and governance reporting very much depends on technologies. For investors interested in businesses that address sustainability, social and corporate governance concerns, ESG is an important signal. The initial idea behind ESG was about measuring firm activity relative to sustainable challenges and beyond commercial performance. This assumed that there was a direct relationship between what the firm reported in terms of sustainability activity, and what the firm was doing in terms of sustainability (Pucker, 2021). In practice, Suleyman (2018) notes that ‘a majority of tech investment has flowed into areas that are tangential to social progress’ (par. 18). Examining the current state of ESG shows that the reporting practice became synonymous with sustainability activity attached to the firm, notwithstanding reality.

What Does Environment, Social and Governance Investment (ESG) Measure? It emerges that sustainability is not at the core of ESG investment. Firm practice is not at the core of ESG investment. The risk to the firm in terms of environmental threats to profitability, social threats in various areas and lack of stability from poor corporate governance structures is the core of ESG (BlackRock, 2022). ESG investment is a critical practice, but it does not measure what we have assumed. This focus on risk to the firm is the only unifying factor among companies that provide ratings. The largest ESG firm on Wall Street, MSCI, publicly clarified that ratings do not measure company impact on society; they rate the ‘potential impact of the world’ on shareholders (first) and the company (Simpson et al., 2021). In fact, MSCI does not consider carbon emissions in rating of firms, as long

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as regulations to mitigate climate change do not pose a threat to a firm’s bottom line. Despite clarifying focus, what firms actually measure is unknown. A team out of MIT Sloan compared the largest six rating agencies and found significant divergence in measurement. It is worth noting that to these researchers, ‘the purpose of ESG ratings is to assess a firm’s ESG performance’ (Berg et al., 2022, forthcoming, p. 8). This is despite noting that what constitutes ESG performance is not well defined. Berg et al. (forthcoming) find that each rater makes different choices in what to measure and there is a lack of consistency in measuring even within rating agencies. This does not mean that the rating agencies are acting badly. Refinitiv, a service of the London Stock Exchange, and one of six ratings included in the Berg et al. (forthcoming) study is transparent about its methodology (A closer look, 2022). The firm employs 7001 analysts to develop over 630 ratings pertaining to relative ESG activity for firms based on company documents (Methodology, 2021). Refinitiv quantifies firm activity and compares against its ecosystem of firms. Several recent critiques of ESG echo the concern around measurement. ESG does not measure what we think; ratings are arbitrary and based on self-reporting (Pucker, 2021). ESG ratings are not correlated with financial standards or measures, as credit rating (Pucker, 2021; Simpson et al., 2021; Three Letters, 2022). This is in addition to the realisation that ESG does not measure firm activity or impact. Theoretical and Practical Implications In theory, ESG practice follows from an understanding of the firm’s role in sustainability. Current developments in understanding of ESG practice, as outlined by this section, suggest that ESG is not tied to an idea about the firm’s role in sustainable development. By focusing on risk, ESG emerges as a response to the competitive environment that the firm faces, and as a response to societal pressure with which the firm continues to grapple. Recently, some observers have suggested the focus should be ‘purpose-driven’ ESG (Hung et al., 2022), one aligned with stakeholder capitalism, focused on the purpose of the firm. This is a recognition that ESG in its initial incarnation is about the firm. A recent report from The Economist is less forgiving, suggesting a first needed step is to unbundle ESG in practice. In its estimation, the ESG are so distinct as to render many measures unable to account for all activities (Three letters, 2022). That report went as far as to suggest that carbon ‘emissions’ should be the only focus of ESG. This might be because significant data continues to show accelerated environmental damage from increased carbon emissions, even as ESG investment grows (Pucker, 2021). But if rating agencies omit emissions as long as there are no liabilities to the firm, and are concerned with risk to the firm, it is hard to see what might be gained by decoupling ESG reporting.

Scalability Whatever happened to One Laptop per Child (OLPC)? In the mid-2000s, a group at MIT Media Lab headed by Nicolas Negroponte set the goal of creating a $100

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laptop that would reach every child in the developing world, regardless of lack of infrastructure in country (Negroponte, 2006; Robertson, 2018). That is, the laptop did not need electricity to charge, as it would be charged by a hand crank. The initiative was billed as an education effort although eventually data would show it had ‘no impact on what children actually learn’ (Banerjee & Duflo, 2019, p. 188). What happened is that it did not happen. This example is not about a business idea, per se. This example is about the concept of scalability and the power of hubris. To be clear, the $100 laptop was a not-for-profit and higher education initiative, primarily. But it benefitted from the example of what Apple, Microsoft and Toshiba were doing on a limited scale in the developing world (Robertson, 2018). Google was one of the first major investors (Negroponte, 2006). In fact, the story of the OLPC does say something about sustainable development efforts in business. The Chicago economist John List has been leading the call to reflect on scalability. List focuses on the problem of scalability in research and programme design with the goals of developing better science to inform public policy in real ways. There are two key areas of intersection for business thinking. The first is that technology is the application of science, and to write of sustainability in the age of technologies, is to consider sustainability in the application of science. The second is that scalability is a problem of economics research and how it translates to policy. To the extent that business wants to participate in some form to address the SDGs and solve other grand challenges, scalability should be considered. Many experiments that show great promise in one context, fail when tried in a different context or broader context (larger). This is the problem of scalability (Al-Ubaydly et al., 2019; Dubner, 2021, 2022). For some time, this was seen as a failure of policy. In the last decade, the work of John List and various co-authors began to ask whether the failure should be examined at the level of research and programme design. This was in part because List and other Chicago economists had created the Chicago Heights Parenting Academy and shown incredible success in education outcomes of young children in Chicago, attracting interest from policymakers in the United Kingdom. There, the parenting academy failed spectacularly. The world-class researchers did not anticipate why: No parents signed up (Dubner, 2021).

The Elements of the Scale-up Problem List set out to understand and define the problem of scalability, and its role in economic modelling. The findings suggest three elements of the scale-up problem: (1) statistical inference and understanding when evidence is actionable, (2) the properties of the population and (3) the properties of the situation (Al-Ubaydly et al., 2019). For the lay audience, these are better understood as general buckets where: (1) the evidence is not there to justify scaling, (2) the researchers studied the wrong people and (3) researchers used the wrong situation (Dubner, 2021). None of these happen at the level of policy implementation. They are problems of research design.

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The problem of a lack of evidence is not particular to research. Banerjee and Duflo (2019) highlight a Silicon Valley consulting firm, Dalberg, which has promoted the internet as the ‘undisputed force for economic growth in Africa’ despite having no evidence, and there being no evidence for such claims (p. 186). In reality, the Nobel Prize winning economists are extremely critical of an exceptionally long ‘bottom of the pyramid’ list of innovations from tech enthusiasts, which include clean cookstoves, rapid testing kits, telemedicine and others. But lack of evidence is only one element. Small-scale studies that permeate our efforts in education, public health and other key areas of sustainable development that inform public policy tend to study ‘best-case scenarios’ rather than on-the-ground realities (Dubner, 2022). Researchers rarely consider the constraints of reality. The sample selection may be biased to the groups where the largest effect (of the intervention) will be evident, or the sample that comprises treatment and control groups does not reflect the populations where a programme might be scaled up (Al-Ubaydly et al., 2019). Finally, researchers model the wrong situation. List contends that we do not understand properties of the situation or features of the environment that will matter in the longer term (Dubner, 2021). This becomes all the more problematic when considering that after decades of research and global effort, ‘we don’t understand very well what can deliver permanently faster growth. It just happens (or not)’ (Banerjee & Duflo, 2019, p. 179). Watching Negroponte (2006) today it is easy to point out the failures of scalability. One, the evidence that a $100 laptop could be made was simply not there, and he stated as much. The $100 laptop was a long-term project and at the time, the price was closer to $150. It would end up costing $200 and as mentioned little was explained about education gains (Banerjee & Duflo, 2019). Two, Negroponte (2006) mentions studies in Senegal and Cambodia where small scale projects showed education gains and then extrapolated to all children across the developing world. Finally, there was no understanding of the situation. In the TED Conference Negroponte states clearly what the team did not need to consider. There would be no studies of marketing and sales, and distribution. Successful programmes in the developing world such as anti-malaria net distribution and the African Measles Initiative of the American Red Cross were successful primarily based on understanding of distribution networks. There was little testing of the laptop on people and how it would work in practice, despite the famously reported event where the hand crank came off in the hand of then Secretary General Kofi Anan (Robertson, 2018). The hand crank never worked.

Theoretical and Practical Implications Already scholars are interested in how firms can further the SDGs. This may be a worthy cause, but this chapter highlights practical implications that can shed light on how firms and scholars ultimately approach the goals. It is difficult to see how a world-class team at a world-class institution could fail as it did. It is easy to

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point to Negroponte who went as far as to say it was ‘stupid’ to question the initiative. But as researchers and technology enthusiasts, it might be better to draw on humility and ask those questions about scalability as a starting point: what is the evidence? Who are the people that will benefit from our involvement with these SDGs? What is the context of the situation?

Bias in Emerging Technologies We turn to emerging technologies. The consideration in this chapter is around hopes for sustainability in relation to the age of technologies. The focus of this section is emerging technologies as embodied by algorithms and machine learning (ML), collectively referred to as AIs. According to The Royal Society (2017), ‘if the broad field of artificial intelligence (AI) is the science of making machines smart, then machine learning is a technology that allows computer systems to perform specific tasks intelligently, by learning from examples’ (p. 16). ML algorithms learn based on data. There have been significant advances in data gathering and computing power, which have changed the possibilities that AIs offer. AIs are present throughout many aspects of ordinary life including voice and facial-recognition software, social media, credit, scoring and recommender systems and limited applications in telehealth, transportation and other areas. Nonetheless, there is also a recognition that AIs pose a risk given their lack of transparency, or opacity (Gehl Sampath, 2021) and the tendency for bias. The excitement, and the fear, around AI is often centred on its ‘potentially transformative’ applications, rather than on current capabilities which are still approaching human-level intelligence. For some observers, AIs offer immense potential in furthering societal goals, and specifically in helping achieve the SDGs (Chui et al., 2019). Banerjee and Duflo (2019) contend that AIs are ‘nothing new’ and ‘do nothing for growth’ (p. 151). Still, it does not seem to be an exaggeration from those in the AI world to suggest that AI embodies ‘what is currently impossible’, especially as the field experiences acceleration (Suleyman, 2018).

How Do AIs Learn? ML systems ‘are set a task and given a large amount of data to use as examples of how this task can be achieved or from which to detect patterns’ (The Royal Society, 2017, p. 19). This differs from the traditional approach where a rule is programmed to a system that then solves a problem or tests for relationships between variables. The type of research described in the scalability section follows the traditional approach. In contrast, an algorithm finds relationships and/or patterns in significantly larger sets of data. In addition to data, the algorithm needs something to train on, a dependent variable called a ‘definition of success’, or the ‘thing that you are looking for’ (O’Neil, 2017). The data train an algorithm to select on the dependent variable.

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This too, must be specified by humans. Advances in data have changed the nature of ML but are also at the core of its limitations and challenges.

The Problem of Bias and Implications for Environmental Justice Both data and how we specify constructs, such as ‘success’ or ‘performance’, are at the core of bias increasingly observed in AIs (Gehl Sampath, 2021). This is evident in the US context. In the last decade, there have been multiple, and disturbing, examples of AIs learning bias. Google, Amazon and other technology firms have faced embarrassing situations due to racist or sexist algorithms (Young & Hagan, 2021). Significant bias has been found in hiring systems with the added problem that high-level executives expect much from systems that they do not readily understand (Melo et al., 2019). There are implications in a more global context. Cathy O’Neil, a Harvard mathematician, refers to algorithms as ‘opinions embedded in code’ (O’Neil, 2017). This speaks first to the role of the technologist in defining ‘success’ or what the algorithm needs to look for. Definitions of success require changing mindsets around sustainable development and business applications. The issue of bias in data speaks to increasing the time horizon of a particular data set or cleaning data in ways that remove potential sources of bias. The problem is that technologists and engineers are not always aware of their own bias, and do not always understand how we encode data. That is, even when racial data are removed, algorithms can still select on variables that serve as proxy for bias. A classic example is zip codes which reflect particular neighbourhoods, in the US context. A second area of consideration is about choosing the definitions of success – the determinant variable. Here, engineers both apply concepts that do not translate in every context and may inadvertently transpose western bias into developing world contexts (Filgueiras, 2022). Gehl Sampath (2021), for instance, writes that the challenges of AI are universal, and that tends to allow western engineers to apply the same theories across multiple contexts. This results in compounding the challenges of AI (Kitchin, 2017). Similarly, engineers are not likely to know about structures of power within countries. The research in this area is limited but several studies have shown impact of AIs in the developing world (Arora, 2019; Heng et al., 2022). An engineer might assume a particular racial make-up in Nigeria or religious experience in India, for example, not realising the realities of post-colonial history, or the nuances of relations between men and women, or treatment of lesbian, gay, bisexual, transgender, and queer (LGBTQ+) peoples and other minority or marginalized groups (Shifting Demographics, 2022). In no uncertain terms AIs ‘exemplify structural inequality in the global South’ (Gehl Sampath, 2021).

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Theoretical and Practical Implications The simplicity of AI tends to gloss over a real shift in research. Mayer¨ Schonberger and Cukier (2013) write that predictions based on algorithms may ‘often be too intricate for most people to understand’ (p. 178). Although working with algorithms means being able to move away from causality, and not understanding ‘why’ something happens, explainability is the greater challenge. In traditional research, when things are ‘off’ the engineer can refer to problems with code. In ML, the AI becomes a ‘black box’ that offers no ‘accountability, traceability or confidence’ and will require ‘new expertise and new institutions’ ¨ (Mayer-Schonberger & Cukier, 2013). Interestingly, the role of theory becomes all the more important to defining ‘success’ or ‘performance’ in sustainability, and to explaining outcomes. In practice, we need data that accurately reflects the people of the Global South. Issues in data should challenge us to think about whom it is that an AI will serve and the implications of our assumptions about race, gender and other demographic characteristics across borders. If the applications are to serve people in the developing world, what are the data considerations?

Do We Need ‘a’ Paradigm Shift and Where? A main argument of this chapter is that for sustainability to thrive in the age of technologies, a paradigm shift is needed. That shift begins with changing mindsets around sustainability in business practice, and the relationship to our view of, and practices around, technologies. At the same time, the use of the term is so common across research, practice and popular culture, that there is a loss of meaning in calling for a paradigm shift. The concepts of technologies and sustainability and sustainable development represent differing fields, theories and different levels of conceptualisation. The interdisciplinary perspective of this book adds more complexity. Should the shift happen in each field? Or is there a combined paradigm shift to be understood? Would many small changes and tweaks in mindset around particular themes come to represent changing paradigms? This chapter might not provide a definitive answer, but those questions are central to reflection.

The Nature of Paradigms and Paradigm Shifts Hollis (1994) writes that in trying to write a history of science, Kuhn came to understand that science, in its ‘normal’ state, exists in a framework of ‘intellectual assumptions and established practices, which it takes for granted’ (p. 84). That framework is what Kuhn meant by paradigm. The normal state of science is that which is dominant and accepted. The paradigm shift happens when the taken-for-granted view of normal science ‘comes under strain’ because the process of normal science ‘starts to throw up consistently unexpected results’ and new ways, or fresh ways of viewing those unexpected results emerge (Hollis, 1994). Kuhn had more than 20 ways of looking

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at what a paradigm might be, because he documented concurrent paradigms (Lombrozo, 2016). For him, a shift represented a reframing of an existing framework based on new evidence and understanding. Notwithstanding, basic definitions are not as expansive. Merriam-Webster now provides a simple, ‘broad’ definition of paradigm as ‘a philosophical or theoretical framework of any kind’. Where Kuhn saw paradigms as coexisting, MerriamWebster defines a paradigm shift as ‘an important change that happens when the usual way of thinking about or doing something is replaced by a new and different way’. This emphasises replacement. In reality, what is perceived as a shift is the result of reasoned debate around multiple existing paradigms (Hollis, 1994). In other words, the shift is not sudden replacement of old ideas and depends on recognition at various levels about that which we take for granted. Why does it matter? The lessons from inconsistencies in ESG measurement, the scale-up problem and bias in AI suggest that we need to consider why unexpected results emerge. Each area suggests disconnect from the broader context or foundations upon which we build measurement systems or projects. It might be that we have not done the work of operationalising sustainable development efforts of the firm in ways that are consistent with the nature of the firm or with the demands of sustainable development. It may be that growth eludes us. Hollis (1994) further notes that a paradigm has two principal aspects; one intellectual and the other institutional. When we call for a paradigm shift, we tend to focus on the intellectual aspect. It is a set of principles, ideas, axioms, bundled in a framework. In contrast, the institutional aspect of the paradigm considers that the framework, the knowledge that we have about something and the way we think about it, is itself embedded and dependent on highly organised, hierarchical power structures or broader social and political systems. I have tried to illustrate this aspect. It is the embeddedness that explains the persistence of a paradigm. What then is role of business with respect to sustainable development, when the goals differ vastly from the purpose of business? Several researchers from multiple fields have all noted the need for our institutions to change if we are to successfully manage the gains from AI. That is a long-term undertaking, but the time is now, when AI is still in its infancy. And that should change our consideration of what it means to say that for sustainability to thrive in an age of technologies, a paradigm shift needs to occur.

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Chapter 11

Digital Healthcare and Patient Transformation: Review Research and Future Agenda Nimesh P. Bhojak, Suresh N. Patel and Mohammadali K. Momin

Abstract Digital healthcare once again emerges due to pandemic (Covid-19). Digital healthcare can be minimising the issue of accessibility, availability, accuracy and affordability of healthcare service during a pandemic. Digital healthcare playsa significant role to provide healthcare equity during the pandemic. This article presents the current trends and scenario of digital healthcare with a focus on health equity. The main objective of this chapter is to review the four aces of health equity in the digital healthcare literature. The scope and challenges faced by the policymakers to implementation of digital healthcare to improve health equity. This chapter considers the hybrid literature review based on the bibliometric and the systematic literature based on the various theme, sub-theme, concept and context-related health equity through digital healthcare. This study provides the previous and current research trends and preposition for the future researcher, healthcare professional, policymakers and digital healthcare innovators to invent the tool which leads the health equity through the digital healthcare in the healthcare. Keywords: Digital healthcare; patient transformation; bibliometric review; systematic literature review; COVID-19; telemedicine

Introduction Digital healthcare emerged again due to the need for health equity in the healthcare sector during the COVID-19 pandemic. Digital healthcare can minimise the Accessibility, Availability, Accuracy and Affordability of healthcare services pre and during a pandemic. Digital healthcare is essential for developing countries’ communities to provide healthcare and enhance healthcare equity. Fostering Sustainable Development in the Age of Technologies, 163–185 Copyright © 2024 Nimesh P. Bhojak, Suresh N. Patel and Mohammadali K. Momin Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231013

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Health equity improves through digitalisation in the healthcare industry (Chauvin & Rispel, 2016), such as gender and power dynamics discrimination in Low-Middle Income Countries (LMICs) like Asia, Africa, the middle east and Latin America (Sinha & Schryer-Roy, 2018). The previous study (Azzopardi-Muscat & Sørensen, 2019) emphasises that digital healthcare raises healthcare inequities like older age, education level, socio-economic condition and geographical disadvantages like limited infrastructure and resources. This chapter has focused on measuring the trend in healthcare equity in digital health literature using a proper systematic review method, as previous authors did a minimal study. This chapter will provide a clear picture of the Accessibility, Availability, Accuracy and Affordability of digital healthcare equity during the pandemic of COVID-19. Digital healthcare once again emerges due to the COVID-19 pandemic. This chapter aims to measure the trend in patient transformation in digital health literature. This chapter’s main objective is to review patient transformation in digital healthcare literature. This narrative review chapter is the hybrid review methodology, which involves a bibliometric and systematic literature review to achieve the objectives. This chapter provided the network analysis of the primary keyword from previous articles. It derived the various clusters from the bibliometric study’s sub-themes and main themes. The systematic literature review of 34 articles provides a narrative review based on the critical elements of health equity in digital healthcare. This chapter provides the future researcher with the research trend and direction. Communities benefit from digital healthcare equity, and policymakers improve health equity by properly designing and implementing digital healthcare. Digital health scientists develop such digital healthcare tool which helps to reduce health inequity in the healthcare sector. This chapter outlines the literature, methodology, result, discussion and conclusion.

Literature Review of the Study A pandemic like COVID-19 has distressed the communities to get healthcare services. Digital healthcare emerges during the pandemic, like COVID-19. Digital healthcare operates for the surveillance of the communities and diagnostic and treatment procedures in the healthcare settings in the world. According to the World Health Organization, digitalisation is critical in improving patient and healthcare staff safety by reducing the infection rate. The healthcare sector should use digital healthcare to improve the accuracy of healthcare services. The communities must increase their digital literacy to access digital healthcare and services. The nation’s government should provide digital healthcare resources available and affordability to all communities and reduce discrimination based on geography, social and economic wise. Healthcare professionals, digital inventors, policymakers of the government and healthcare researchers of social communities should focus on digital healthcare based on the four As: Availability, Accessibility, Accuracy and Affordability, critical elements of health equity. This chapter aims to know whether digital healthcare help gets the four As of health equity.

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Digital health can be defined as using various technologies to administer healthcare services to enhance the health of the communities. Digital health is a healthcare innovation providing a platform for digital technologies for patients’ healthcare services (Iyawa et al., 2016). Digital healthcare has many components like health information technology, tele-imaging services, health analytics, a social platform for health awareness, personalised healthcare like m-health, e-health, healthcare innovation and a digital ecosystem in healthcare. Digital healthcare is also known as digital health, m-health, e-health and information communication and technology in the healthcare sector. The convergence of science and technology in this digital era has resulted in innovative digital health devices that allow easy and accurate processes in health and disease aspects. Technological advancements in technology and various diagnostic instruments like smartphone-connected mobile health (m-health) devices and other innovative health technologies have increased enthusiasm for patient care with promises to decrease healthcare costs and improve outcomes (Bhavnani et al.). The digitalisation of healthcare engages various services like physician appointments, diagnostic and treatment of the patients, keeping patient records, promotion of the service through social media, surveillance and governance by the government in the healthcare sector. Health equity is a significant concept for digital healthcare worldwide. It is part of the ‘universal healthcare’ goal and ‘healthcare for all’ in the nation’s communities. The United Nations also reflects health equity as part of its Sustainable Development Goal (SDG), like healthcare for all. Digital healthcare reduces the health inequity of the communities in the nation’s healthcare sector. It means digital healthcare provides healthcare services to all communities irrespective of their different characteristics related to the geographic, demographic, social and economic status in the nation’s healthcare sector. There are many classifications based on geographic statuses like remote, rural and urban communities and the status of Availability and Accessibility of digital healthcare. Demographic characteristics like gender, race and ethnicity make a difference in the Accessibility and Affordability of digital healthcare – the social determinants like caste and friends. Create a difference in the Accessibility and Affordability of digital healthcare. So, there is a need to remove the health inequity and not create the worst situation of health equity through digital healthcare in the healthcare sector. Health equity plays a significant role in the digital healthcare sector. The nation’s communities have different geographic, demographic, social and economic characteristics to adopt digital healthcare services in the healthcare sector. Health equity has four major As: Availability, Accessibility, Accuracy and Affordability of digital healthcare by the nation’s communities. Table 11.1 represents the definition of health equity and its four As of health equity in digital healthcare. Digital healthcare requires intellectual capital and resources to develop innovative tools like telemedicine. The competent healthcare staff provides digital healthcare services to the whole communities of the nation with all four As of health equity. The previous study (Chauvin & Rispel, 2016) highlights health equity improvement through digitalisation in the healthcare industry (Azzopardi-Muscat & Sørensen, 2019). Emphasising digital healthcare raises healthcare inequities like older age,

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Table 11.1. Concept of the Digital Health Equity. Particulars

Definition

Digital Digital healthcare use is based on the health equity patient’s need and not the other criteria like affordability of the communities. Consider providing healthcare services. Availability Digital healthcare resources are available for all the communities of the nation. Accessibility The nation’s communities are easily aware and use digital healthcare resources to improve their healthcare services. Accuracy The healthcare provider connects digital healthcare to improve the quality of care with physical evidence during the healthcare services Affordability Regardless of their economic status, the nation’s communities can easily get digital healthcare services based on their needs.

Sources

Rodriguez et al. (2020)

Nittas et al. (2020) Wang (2007)

Mosadeghrad (2014)

Crawford & Serhal (2020)

Source: The table is prepared by the author from the previous literature.

education level, socio-economic condition and geographical disadvantages like limited infrastructure and resources. There is a need for health and digital literacy improvement, scrutinising access, utilisation and impact across communities to reduce healthcare inequity rather than aggravating it (making it worse). Crawford and Serhal (2020) argued that the digital health equity framework is beneficial to an individual, institutional and social level through person-centred care and digital health equity factors and healthcare providers training in the context of poverty, limited access, meagre engagement and poor digital and health literacy. Digital healthcare helps to determine the accountability of the healthcare staff at the upward and downward levels in healthcare (Sinha & Schryer-Roy, 2018). Developing countries and low- and middle-income countries like India have minimum healthcare resources, and the requirement is high. India will be available in mobile phones, transforming internet technology from the first generation to the fourth generation and the fifth generation. The government of India approached and promoted digital technology and launched Digital India for all sectors, including health. Artificial intelligence (AI) is now the next giant technological bounce similar to electricity and internet facility (‘index @ raise2020.indiaai.gov.in’, n.d.). In the second global survey of e-health conducted in 2009, telemedicine is for healthcare delivery system by use of information and communication technology (ICT) (Combi et al., 2016). Telemedicine combines medical science and information technology to provide healthcare to urban and rural areas to achieve four As. In India, with the scope of ICT and the number of users of mobile technology, we can fulfil four As to obtain ‘Health For All’.

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Indian government started e-governance to reach everyone, minimise time and increase service availability at a low cost. After telemedicine, the government started an android-based application in health, like safe delivery, to make awareness about pregnancy. Its related grievance cell in health Mera Hospital or My Hospital, national disease surveillance programme for infectious disease, recently introduced ‘Mission Indradhanush’ and TECHO technology in community health, retrieve hospital data government launched hospital management information system and during COVID-19 pandemic condition access to all and reach population for healthcare and COVID-19-related awareness launched mobile caller tune and Aarogyasetu application, tracing COVID-19 patient by bluetooth technology. So, from the data mentioned above, we can say that digital health or e-health can minimise the issue of Accessibility, Availability and Affordability of healthcare services during a pandemic.

Methodology This chapter fulfils the above limitation through the main objective is the systematic literature review of health equity in digital health literature. This chapter considers a mixed literature review based on bibliometric and framework-based systematic literature reviews. This chapter accomplishes objectives based on the insert keywords like ‘digital healthcare’, ‘digital health’, ‘health equity’ and ‘health inequity’ and collection of the articles from PubMed. It uses them for bibliometric analysis through VOSviewer software. The systematic literature review is based on the selected articles which met all the inclusion criteria to develop the digital health equity framework. This chapter combines the bibliometric and systematic literature review methods to achieve the study’s objective.

Bibliometric Review The bibliometric study is significant due to the scientific mapping of the research in various fields like science, psychology, society and healthcare. In the healthcare field, many researchers (Chahrour et al., 2020; Hossain, 2020; Park et al., 2020) used the bibliometric study during COVID-19. This chapter applied the research design shown in Fig. 11.1 to achieve the research objectives. This chapter is drawn from articles from the PubMed database based on the objectives of the study authentication of the data sources essential in the healthcare field. This chapter identified the previous article based on the main keywords like ‘digital healthcare’, ‘digital health’ and ‘health equity’ from the medical field-related authentic information from PubMed – the national library of medicine. The previous researcher (Park et al., 2020) considered PubMed to collect previous articles. Some authors assessed articles from the Web of Science (WoS) for a previous study (Chahrour et al., 2020). Fig. 11.1 shows the research process to identify and review articles for this study. The bibliometric study is a science mapping method that provides the network analysis and the density analysis of the concept in the previous research articles. It leads to providing the main keywords used in the article as clusters.

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Identification

Article found (n=1168)

Screening Article based on Abstract Article found (n=84) Eligibility Article based on Full text

Included

Article found (n=34)

Fig. 11.1. Research Process for Articles Selection. Source: Prepared by the author using Microsoft Powerpoint Presentation.

Systematic Literature Review The science mapping method helped to derive the main article based on digital health equity. This chapter considers 30 articles for the systematic literature review. Table 11.1 shows the list of 34 articles for digital health equity. The systematic literature review considers the four As of health equity in digital healthcare literature. The hybrid review method would be assisted in getting the future research trend through science mapping, manually reviewing the literature and finding the various fields related to research in digital health equity.

Result and Discussion Many articles were published in digital healthcare from 2000 to 2020 based on research, survey, case study, narrative, systematic reviews and meta-analysis cohort studies. Digital healthcare-related article has been published more in the

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last few years due to the growth of digital technology like AI, blockchain technology, cloud computing and data analytics. Digital healthcare articles are also emerging nowadays due to the benefit of the COVID-19 pandemic. Digital health equity plays a significant role, not due to pandemics but the inception of digital healthcare. Less literature on digital health equity was available in the journal. A total of 11,534 articles were received in PubMed based on the keyword ‘digital healthcare’, ‘inequity’ and ‘equity’ searching. Fig. 11.1 helps us understand the researcher’s work on the various vital variables in digital healthcare. Fig. 11.2 provides information on the various densities of the keyword in the result. This crucial result assists in knowing which aspects are primarily considered by the researcher to research digital healthcare. The articles preferred only

Fig. 11.2. The Keyword Link of Healthcare Equity Literature in Digital Healthcare (2000–2020). Source: Authors prepared from various articles through VOS-viewer.

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English language-related due to the limitation of the researcher’s language. A total of 1,168 articles were found to read all article titles based on the concept and remove the duplicate article. The 84 articles received the read abstract of all 1,168 related to the concept. Thirty-four articles based on the digital health equity concept relate four As through reading the full articles. A systematic literature review has been done on the 34 articles. The article described various critical concepts related to digital health equity in the overall world. Fig. 11.3 gives a picture of density resolution of healthcare equity literature in digital healthcare. Digital healthcare should increase the community’s standard of living, and it also increases healthcare outcomes. It means digital health provides the healthcare service based on the community’s needs and not on the affordability of the nation’s community (Ricciardi et al., 2019). It has defined the

Fig. 11.3. The Density Resolution of Healthcare Equity Literature in Digital Healthcare (2000–2020). Source: Authors prepared from various articles through VOS-viewer.

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digitalisation of the healthcare impact to achieve the healthcare sector-main goal like quality, efficiency and healthcare equity. Government plays a significant role in implementing funding and monitoring the digitalisation of centralised and decentralised healthcare through improving education and regulating digital health and financial investment (Were et al., 2019). The digital health equity impact assessment from Whitehead and Dahlgren policy action involves assessing the scope, examining the impact, developing and monitoring mitigation strategy, interpreting the result and giving suggestions for change (Chauvin et al., 2016). Look at the use and contact of digital technologies for population health and health equity gains. National Academies of Sciences and Medicine (2016) suggested that suitable digital healthcare implementation helps reduce healthcare inequality in the individual based on race and ethnicity. It also improves the healthcare outcomes of the United States (Mullangi et al., 2019). The healthcare system should control the knowledge economy of information technology to get patient characteristics, and social media needs to improve the quality of healthcare outcomes. Mouton et al. (2019) suggest the need for a new conceptualisation of digital divides like socio-economic rise among individuals and health promotions at the institutional level to improve health equity. Jackson et al. (2020) described digital health with the significant implication in the inequitable social structure increase the health literacy and equity and improve the overall health of the communities. Table 11.2 describes the summary of propositions for future studies that emerged in each theme (Rich et al., 2019). Digitalisation of health improves the relationship between digital health policy and health equity. Digital health helps with data sharing with the patient, a collaboration between the service receiver and provider to create value, leading to equity in healthcare services. Digital health increases create the worst situation of health inequalities in the neoliberal

Table 11.2. Summary of Propositions for Future Studies That Emerged in each Theme. Themes

Digital healthcare and availability Digital healthcare and accessibility Digital healthcare and accuracy Digital healthcare and affordability

Propositions

Digital healthcare is beneficial to provide healthcare facilities without any discrimination. Digital healthcare literacy provides the community to access healthcare services. Digital healthcare improves the accuracy means quality care of the healthcare services, not including cost. Digital health should be affordable for all the community to provide healthcare services.

Source: The table is prepared by the author from the previous literature.

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approach. Brewer et al. (2020) proposed that digital health can increase unintentional health inequity in healthcare. There is a need for the researcher to understand the problem of the underprivileged section of society. With community, cooperation must develop advancing digital health technology to achieve health equity for all (Mason et al., 2015). The VicHealth framework for health equity examined four types of social innovation: social movements, service-related social innovations, social enterprise and digital social innovations (Rodriguez et al., 2020). Digital health and health equity play a significant role in the 21st century’s cures act era. Digital health equity is the community’s necessity for the availability, Accessibility and Affordability of digital health in the nation (Antonio et al., 2019). The proposed digital health equity framework with components like governance structure, policies and patient social and cultural values create health inequity in using the portal hence needs the proper implementation of the design and intermediary strategy (P´erez-Lu et al., 2018). Pregnant women benefit through digital health programmes like digital technologies like visual displays during the waiting time, SMS messages, prenatal checkups and electronic health records (Nittas et al., 2020). Despite the opposing force of socio-demographic inequities and the emerging nature of mobile health technologies, evidence of the equity implications of mobile health interventions for HIV care remains scarce. Not knowing how the effects of mobile health technologies differ across population subgroups inevitably limits our capacities to equitably adapt, adjust and integrate mobile health interventions towards reaching those disproportionally affected by the epidemic(Breen et al., 2019). Digital health, like electronic health records, sensor information and wearable device information, provides more access and accurate data than traditional data. Digital health was beneficial to providing personalised healthcare to various healthcare inequities based on socio-demographic inequity. The following theme is derived from the main keywords collected in the previous articles on digital healthcare. Table 11.3 describes the collected keywords, the sub-theme and the central theme for all the keywords. The various themes provide insight into how the researcher used the field to investigate digital healthcare based on various critical considerations.

Previous and Recent Trends in Healthcare Equity Many researchers in the past have conducted various studies on digital healthcare and healthcare equity about inequality towards access to digital health services, challenges towards the transformation in the healthcare system, patient’s attitudes towards the acceptance of digital healthcare, making the promotion of healthcare equity in public for the acceptance, mobile technology and digitalisation of healthcare, information and communication in healthcare services, AI in healthcare, providing the digital solution to the patients with increasing health literacy and innovation in the society for the acceptance of digital healthcare. Currently, researchers are studying bibliometric analysis, digital contact tracing

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Table 11.3. Keywords From Previous Articles Related to Digital Healthcare and Healthcare Equity Research. Themes

Resources of digital healthcare

Sub-themes

Technology

Healthcare staff

Hospital Management Information system Core services of digital Diagnose healthcare

Treatment

Determinant during core services of digital healthcare

Process

Quality

Keywords

Algorithm, system, network, deep learning, digital image, digital mammography, digital photography, digital radiography, digital subtraction, angiography, digital tomosynthesis, digital tomosynthesis, digital workflow, droplet digital PCR, full-field digital, machine, machine learning Pathologist, paediatric, dermatologist, radiologist, dentist, orthodontist, Clinical decision support system, personal health record, clinical decision support, her Cone beam, convolutional neural network, detection, diabetic retinopathy, digital breast tomosynthesis, Prescription, radiation, nursing, patient care, palliative care, home care, primary healthcare, clinical care, digital cognitive behavioural therapy Case report, case series, clinical decision support, detection, diagnostic, general practice, image, MRI, prescription, workflow, complication, incidence, path, best practice Accuracy, correction, error, reliability, principle, reality, transparency, security, ethical issue, accuracy, (Continued)

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Table 11.3. (Continued) Themes

Sub-themes

Trust Human factors of digital healthcare

Determinant of human health

Parts of human body Human diseases

Study of digital healthcare

Country

Keywords

characterisation, classification, combination, contrast, correction, diagnostic accuracy, diagnostic performance, error, estimation, image quality, optimisation Agreement, promise, trust, quality assurance body mass index, day, fruit, high risk, patient preference, patient satisfaction, macular degeneration, adults, sex, alcohol, digital health literacy, culture, ethics, adolescent, gender, smoking Prostate, hand, head, palm skin acute ischaemic stroke, dentist, orthodontist, smile, aesthetic, brain, breast, breast cancer, breast cancer screening, cone beam, convolutional neural, dental practice, dermatology, diabetic retinopathy, eye, digital breast tomosynthesis, fatigue, field, mammography, implant, inflammatory bowel disease, macular degeneration, mammography, melanoma, Parkinson disease, pathologist New Zealand, Saudi Arabia, African American, Korea, Malawi, Taiwan, Ghana, Uganda, world, middle-income country, Iran, Norway, Pakistan, South Korea, the United States, Austria, Bangladesh, Denmark,

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Data analysis

Data representation

Data technique Time

175

Finland, France, Germany, Hongkong, Ireland, Israel, Italy, the Netherlands, Spain, Sweden, Switzerland, Tanzania, Zambia, Brazil, Scotland, European country, Indonesia, the United Kingdom, Japan Comparative analysis, cross-sectional analysis, evaluation study, quantitative analysis, retrospective study, multicenter study, retrospective cohort study, preliminary study, questionnaire study, experimental study, retrospective analysis, validation study estimation, associated factor, preliminary result, significance, momentary ecological assessment, image analysis, creation cross-sectional analysis, comparative analysis, evaluation study Characterisation, classification, combination, contrast, word, mortality, number, prostate health index, qualitative exploration Optimisation, validity, correlation, prediction Day, new era, decade, screen time, past, present, real-time

Source: The table is prepared by the author from the previous literature.

and increasing digital health literacy as digital healthcare is necessary for the 21st century, maintaining the psychological impact on patient minds and revolution in the healthcare system due to the COVID-19 pandemic.

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Resources of Digital Healthcare Much digital technology impacts health equity based on technology and social resources. Mainly digital technology is available in secondary and tertiary care services compared to primary care services. Hence, digital healthcare is mainly available in urban areas compared to rural areas due to tertiary and secondary care services. It improves health inequities in terms of digital health resources. The various healthcare staff used digital technology resources to provide patient healthcare services.

Core Services of Digital Healthcare Digital healthcare services are used in both core services like diagnoses and treatment of the patient health services; therefore, it benefits all the patients and improves the accuracy of the output in the health services.

Determinant during Core Services of Digital Healthcare The core services mainly focus on the trust in the services received by the patient, the process adopted by the healthcare staff and the quality of core healthcare services. The above things consider the marketing strategy of healthcare settings. Trust means a relationship between the service provider and services receiver, process means ease and convenience to provide services and quality care means the product uniqueness of the hospital.

The Human Factor of Digital Healthcare There are many tools available to check the various measures of the health of human beings. Human is also considered the digital technology for assessing communicable and non-communicable diseases.

Study of Digital Healthcare Services The researchers have explored digital healthcare and its impact on health equity through comparative, cross-sectional and experimental studies in developed countries like the United States, the United Kingdom and emerging countries like Brazil, India and China. The digital healthcare study is regarded as the present, past and future era of digital healthcare and health equity in diverse communities. Digital health includes technology adopted in healthcare services delivery systems and ICT. Digital health architecture, a combination of software and hardware technology with healthcare delivery and management, includes several domains, from wearable devices to AI, each associated with widely disparate interaction and data collection models (Garg et al., 2018), digital software like HMIS, mobile applications like Aarogyasetu, digital hardware like mobile and computer and related accessories.

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Table 11.4 mentions digital technology in the healthcare delivery system based on the world’s four As of health equity. The following explanation of digital healthcare technology to fulfil the community’s needs is based on health equity’s four As (Accessibility, Availability, Accuracy and Affordability). Electronic health records (EHRs) are an emerging information technology in the hospital record system or medical record department (Foley et al., 2017). Healthcare information technology helps eliminate human effort and error in the healthcare delivery system and improves health outcomes (Kruse et al., 2018). EHR system consists of handling data quality, increasing healthcare communication and communication between different health units, enhancing the quality of care, eliminating paper system and decision support system and accelerating clinical workflow, clinical outcome and financial outcome (Shahmoradi et al., 2017). Health informatics, getting health-related data to form the human body, vital data, neurological data, heart-related data, muscle stimulation, eye function data, DNA, RNA, all these types of data need signal or ways or channel, and that is health informatics (Kurnat-Thoma et al., 2020). There are different areas of health informatics like public health, medical imaging, bioinformatics, medical informatics and pervasive sensing (Ravi et al., 2017). AI advances technology and has emerged in the healthcare delivery system (Kurnat-Thoma et al., 2020). AI uses a complex algorithm for the machine, and reasons to perform a cognitive function, including problem-solving and

Table 11.4. Digital Technology Based on the Four As. Availability

Mobile technology Contact tracing Bluetooth technology Digital health intervention Tele-pathology Teleophthalmology Short message-caller tune

Accessibility

Accuracy

Electronic health record Health informatics

Electronic health record Health informatics

AI

AI

Telemental health ICT

Telemental health ICT

Digital handheld android-based geographic information system

Digital handheld android-based geographic information system

Source: The table is prepared by the author from the previous literature.

Affordability

Mobile technology Contact tracing Bluetooth technology Digital health intervention Telepathology Teleophthalmology Short message-caller tune

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decision-making. AI elements are machine learning (ML), language processing, artificial neural network and computer vision (Emin et al., 2019). AI, ML, is helpful for fetal monitoring, objectively helping to determine whether a caesarian section is necessary during intrapartum care. Telemedicine is based on ICT, a combination of medical science and ICT, aiming to provide healthcare services like diagnostics, therapeutic, health intervention and consulting services. Telemedicine services include telemental health, telepathology, tele-ophthalmology and related ICT. Telemedicine is ‘the use of ICT in medicine’. Telemedicine is ‘the delivery of health care services, where distance is a critical factor, by all healthcare professionals using information and communication technologies for the exchange of valid information for the diagnosis, treatment, and prevention of disease and injuries, research and evaluation, and for the continuing education of health care providers, all in the interests of advancing the health of individuals and their communities’ (Medialdea, 2020). Web-based self-help intervention, a self-guided programme, provides essential information and intervention or information only, where clients can disclose the information provided at their own pace (Kandeger et al., 2018). Internet-operated therapeutic software, including robotics simulation therapists, rules-based expert systems, games and virtual 3D systems (Kandeger et al., 2018). M-Health Voice Message Service (mMitra), interventions for maternal, neonatal and child health to improve antenatal and neonatal service uptake in low and middle-income countries, impact health outcomes related to Maternal, Newborn and Child Health (MNCH) (Murthy et al., 2019). Mobile Alliance for Maternal Action (MAMA) implementation in India from Jan 2015 to Dec 2017, called mMitra, improves the health and well-being of pregnant women and their newborns and infants by age and stages based on tailored voice or text messages delivered via mobile phone. Like the mMitra application in MNCH for mothers and their newborn’s intervention, the Government of India launched a short message caller tune in mobile for prevention and awareness of COVID-19 conditions (Naslund et al., 2017). Caller tune has been used by the Ministry of Health and Family Welfare, Government of India, to raise awareness about COVID-19 and maintain hygiene through hand washing. The government has also encouraged the digital media campaign run by the corporates alerting everyone to ‘Stay Home, Stay Safe’. Contact tracing-Bluetooth technology: Digital contact tracing applications are being developed by governments worldwide to track and trace contact (Hegde & Masthi, 2020). It is helpful to break the chain of infection. It has been a pillar of infectious disease control in public health for a decade and successfully eradicated smallpox and controlled polio and Ebola outbreak worldwide. During this pandemic, Government of India launched the Aarogyasetu application to trace corona-infected patients to the outbreak chain of infection in public. DICOM and PACS: Digital imaging and communication in medicine is used in the imaging department to pass different departments like same function picture archiving and communication system, interoperability between a device (Sansare et al., 2013). It is an internationally accepted format in radiological imaging, with images sent from scanners and digital X-ray devices.

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Digital Healthcare Technology and COVID-19 Digital healthcare technology used to intervene plays a significant role in battling the COVID-19 pandemic. India also adopted this strategy to prevent public health and outbreak chain of infection. COVID-19 is an infectious disease caused by severe acute respiratory syndrome, breakout the chain of COVID-19 imposed digital healthcare technology like AI replicating human intelligence to use in tracking outbreaks, diagnosis patients, disinfecting areas and speeding the process of finding a cure for COVID-19 (Sarbadhikari & Sarbadhikari, 2020). The objective is global surveillance for human infection with coronavirus, monitoring trends of human-to-human transmission, detection of new cases, providing information related to the pandemic and awareness of preparedness and response measure for COVID-19. Mobile applications or M-apps for tracing and tracking persons and notifying authorities using Bluetooth technology, the Aarogyasetu application was launched by the Ministry of Health and Family Welfare in the Government of India. Digital healthcare technology and COVID-19 global scenario exist in the United Kingdom, China, Singapore and the United States (Ting et al., 2020). Digital healthcare and Accessibility: The rapid proliferation of health informatics and digital health innovations has revolutionised clinical and research practices. Undoubtedly, these fields will continue to have accelerated growth and substantially impact population health (Brewer et al., 2020). This review studies the current integration of digital health technology in cancer care by subdividing digital health technologies into the following sections: connected devices, digital patient information collection, telehealth and digital assistants (Ahmed et al., 2020). The rapid growth of technology and its use as a development solution has generated much interest in digital health (Garg et al., 2018). Digital healthcare and availability of resources: Digital technologies shape how individuals and health systems interact to promote health and treat illness. Their propensity to exacerbate inequalities is increasingly highlighted as a public health concern (Crawford & Serhal, 2020). Health equity should be incorporated into health provider training and championed at the individual, institutional and social levels (Jackson et al., 2020). Those remedies can inform policies, research and interventions that touch on health communication and digital health issues (Antonio et al., 2019). Digital healthcare and accuracy: Adoption of new digital healthcare technology by replacing traditional technology, for example, a digital blood pressure monitor with a replaced mercury-based sphygmomanometer, a digital stethoscope with a replaced crystal-based transducer, an AI-based robot clean and sanitise replaced human intelligence, electronic health records replaced by the manual paper record and so much (Breen et al., 2019). Digital healthcare technology and the accuracy test of three different blood pressure measurement techniques (Shahbabu et al., 2016) presents some examples of positive experiences in India, and considers the difficulties in achieving this potential to accelerate the translation of health disparities studies. India’s two-tiered healthcare system (viz the public and private sectors) has been suffering from various ailments. Each sector has been criticised for its deficiencies (Ghoshal, 2015).

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Digital healthcare and affordability: EHRs have emerged among health information technology as ‘meaningful use’ to improve the quality and efficiency of healthcare and health disparities in population health (Kruse et al., 2018). The predominant focus on portal use barriers may inadvertently place individual responsibility in addressing these barriers on patients already experiencing the most significant health disparities. This approach may mask the impact of the socio-technical-economic-political context on outcomes for different populations. Digital contact tracing applications are being developed by governments worldwide to track and trace contacts (Hegde & Masthi, 2020).

Challenges of Digital Healthcare Equity ‘Health For All’, the policymakers fulfil four As, Accessibility, Availability, Accuracy and Affordability, by Digital health technology to reach rural and remote areas through telemedicine, AI, mobile application, voice message, robust EHS, health informatics, and so beyond. However, in every condition, there are two parts: positive and the second is negative, and advantages and disadvantages. So digital health has a massive advantage in terms of three As, Accessibility, Availability and Affordability, but also disadvantages in enormous finance, digital security, ethical challenges, and so much towards different stakeholders’ payers, hospitals and suppliers. Complicated and complex healthcare information causes concern to patients and healthcare providers. Digital security and cost can be the most challenging for digital healthcare. Data collected by providers are considered as patients’ data, and so much is the responsibility of providers to save it. Hence, is not traceable by another person. Data security challenges also include cyber-attack, hacking of databases and data kidnapping (Vayena et al., 2018). They are implementing digital healthcare technology that initially required considerable funding. Hence, its concern with the digital economy is a challenge for the digital healthcare technology, for example HMIS. Digital technology is updated daily and comes with new ideas and technology. Like digital health technology is disruptive, most challenges question the practice and production of a model of exciting services. Production capability and robust digital healthcare technology need human skill capital for challenges like ICT to build and maintain. A concern with approval and certification of digital healthcare technology, which the Food and drug administration authorised for Digital healthcare technology performance and precision level of digital equipment like BP monitors and stethoscopes run by mobile technology to compare traditional equipment (Alami et al., 2017). Implementing digital healthcare technology initially required a considerable amount of funds. Hence, its concern with the digital economy is a challenge for the digital healthcare technology, such as HMIS.

Conclusion Digital healthcare services include primary, secondary and tertiary care providers in an emerging country, the public and private sectors. Among them, most

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healthcare services are provided by the private sector. The SDG of the United Nation considers ‘Health For All’ to fulfil the fundamental right of healthcare. We have to go to rural and remote areas with digital technology. The main reasons for not using devices to access digital health were the lack of awareness, discomfort, differences in regular care-seeking habits, lack of understanding and skills and proximity to a health facility. It emphasises that digital healthcare raises healthcare inequities like older age, education level, socio-economic condition and geographical disadvantages like limited infrastructure and resources. There is a need for health and digital literacy improvement, scrutinising access, utilization and impact across communities to reduce healthcare inequity rather than aggravating it (making it worse). The digital health equity framework benefits at an individual, institutional and social level through person-centred care and digital health equity factors and healthcare providers training in poverty, limited access, meagre engagement and poor digital and health literacy.

Limitations of the Study Due to the less availability of previous research on healthcare quality, a systematic review has been done of 34 articles. Article mining is possible manually and technically, but mining manually has limitations; hence, data mining software like VOSviewer is used and various keywords used by the previous articles were collected and different keyword links from various articles were found.

Future Possible Research This chapter has considered the digital healthcare and health equity of the patient during the COVID-19 pandemic. Further research can be done by measuring the patient satisfaction from digital healthcare after COVID-19, patient transformation after COVID-19 and the core services of digital healthcare.

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Chapter 12

A Comparative Framework Analysis of the Strategies, Challenges and Opportunities for Sustainable Smart Cities Oluwagbemiga Paul Agboola and Meryem Muzeyyen Findikgil

Abstract The goals of the contemporary environment in this new era of the Internet of Things (IoT), digital technologies (DTs) and smartisation are to enhance economic, social and environmental sustainability while also concentrating on the citizens’ quality of life. As these initiatives advance, more determination is required to offer effective approaches to the problem posed by the accomplishment of the Sustainable City Project in Nigeria as a developing nation. To address these problems and facilitate the process for Nigeria’s major cities to become ‘smart cities’, universities, research institutions and other stakeholders must collaborate alongside. This chapter aims to establish a model or framework that addresses urban intelligence, social inclusion, resilience and technological innovation, mobility, urbanisation and residents’ quality of life. The reviews of the characteristics and management of smart cities in developed countries were documented to serve as a comparison study of the cities in African sub-Saharan regions. This will assist in building models that can produce predictions about possible smart solutions in the areas of mobility, urban infrastructure and ecological problems brought on by climate change in African cities. This chapter brings attention to the body of knowledge by envisioning the benefits to the government and citizens in making appropriate decisions to enhance sustainable development, a better resilience environment, improved infrastructure, smart city environments and residents’ quality of life. The study’s implications centre on how the government could prioritise urban features and services as indicated in the smart cities framework. Keywords: Smartisation; Internet of Things (IoT); digital technologies (DTs); smart cities framework; cities’ resilience; sustainable cities Fostering Sustainable Development in the Age of Technologies, 187–211 Copyright © 2024 Oluwagbemiga Paul Agboola and Meryem Muzeyyen Findikgil Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231014

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Introduction The term ‘smart city’ as defined by the European Union makes investments in technologically sophisticated facilities, evolving itself into a place that is financially viable while simultaneously promoting a higher standard of living and the more efficient use of its assets. Additionally, it incorporates various technologies to obtain data and then uses that data to control and manage a wide range of municipal processes. Essentially, these would be cities that are capable of reinventing themselves by utilising technology to create a smart society, economy, governance, habitat and mobility starting with current urban structures. By utilising their limited resources wisely through new technologies and creative strategies, the cities generate answers to the challenges and demands of the future while respecting the environment and its resources. The Internet of Things (IoT) and other advanced technologies give globalisation and urban life a new dimension. Smart cities adopted smart technologies that allow cities to conduct municipal services more efficiently and at a lower cost. Technology is such an integral part of our life that the dependency on its benefits is awesome. Similarly, improved accessibility to information through technology enhances the sustainable expansion of the nation’s economy. A smart city’s objective is to build a sustainable, digital and environmentally friendly environment that spans a variety of industries, including transportation, education and intricate networks of structures, roads, bridges and electrical grids. Citizens’ quality of life is better enhanced with the advent of smart city models. Through the availability, accessibility and use of digital technology in urban inhabitants’ daily lives, this social revolution is gradually changing the configuration of urban space into a smart space. To overcome urban challenges as we transition to a smarter modern city in both industrialised and developing countries, these technologies transform traditional roads into digital information flows, connecting users and with their environment via the internet, social media and mobile terminals (Mahmood, 2018; Moyo et al., 2020). In fact, according to Aurigi (2017), the narrative surrounding smart cities has recently grown to be strongly related to the idea of urban ecosystem sustainability. It relates to urban ecology in developing nations, which includes all elements of urban areas, such as their populations, food and transportation networks, economy and business (Lindley, 2018; Mahmood, 2018). A smart city is significant in the attainment of urban service systems where information and communication technologies (ICTs) fuses to stimulate sustainable growth through effective resource management. In other words, cities’ livability and functional efficiency remain the major focus of smart cities of the twenty-first century. Increasing rapid urbanisation, inadequate physical infrastructures, urban populations, poor quality social services and vulnerability to disasters and climate change are the problems facing most African cities. In view of these problems, little research has been explored in the area of smart city initiatives for better understanding of the connectivity of human and material developments. Therefore, as most African cities are striving to become more digitalised, more research is required to meet the expectation of the citizens and affordability. In support of this assertion, Vainio and Sankala (2022) viewed that accomplishing sustainable development in the modern digital environment, smart city technology is important to urban life. Most of the frontline smart cities in developed countries are rapidly expanding, and the ideas should serve as a general guideline for African cities. To

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address some related smart city issues in Africa, adequate research is needed (Hussein et al., 2019; Mahmood, 2018; Moyo et al., 2020). Thus, this research explores a framework to fast-track the journey of African cities towards being more digitalised and responsive. The objective of this chapter is to compare the reviews of the characteristics, status and management of smart cities in both developed and African sub-Saharan regions. This comparison will be illuminating for developing models that can forecast potential smart solutions for issues with transportation, urban infrastructure and ecological issues in Africa caused by climate change. The findings of the study will advance our understanding of the significance of smart cities and their advantages for the government and all citizens in making decisions to enhance urban sustainable development, a more resilient environment, better infrastructure and the quality of life for citizens across all of Africa. Importantly, this chapter’s novelty is vested in its comparison documentation of the significance and uniqueness of smart cities for both developed and developing nations of the world. The study’s implications centre on the necessity for emerging nations like Nigeria to give urban amenities and digital revolution technologies a top priority in their long-term development plans.

The Global Development and Characteristics and Framework of Smart City Models The growth of the smart city started in the 1970s; when urban environments adopted a digital architecture that concentrated on technology and immaterial structures incorporated into the actual city space (Ishida & Isbister, 2000). The focus has recently shifted to more complex innovations, enabled by the network infrastructure and intellectual capacity, guiding the growth of the city (Elmquist et al., 2009; Schaffers et al., 2011). With the use of a smart city framework, towns will be able to create a standardised database system for gathering city statistics, recording them and making it easily accessible for the management of smart city solutions. The latest concepts, frameworks, ideas and benchmarks for smart cities have indeed been explored by Meijer and Bol´ıvar (2016) and Anthopoulos (2015). It was revealed that the outcome of their framework’s studies presented benefits to the governance, economy, residents and the environment at large. Recently, ideas have concentrated on the notion of smart cities in light of worldwide advocacy for changing technology developments. To accomplish a long-lasting and attaining sustainable economy, urban areas must combine all intervention domains based on the contribution of ICT to raise the quality of life for urban actors (Anthopoulos & Tougountzoglou, 2012). The use of smart gadgets has increased as a result of technological developments and even seen the unimaginable potential of the IoT platforms. These avails result in smart environments and infrastructures around the world, due to appropriate actions taken by several individuals and organisations (Giffinger et al., 2007). Such organisations consist of academics, government officials and businessmen and women. Smart city developments and initiatives have shown various models founded on high-quality qualitative information, which are crucial for creating smart cities. Notably, data from the social, economic, technical and environmental

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domains provide clever answers to researchers and decisions for urban development as well as businesses that finance eco-friendly cities. According to Giffinger et al. (2007) and Angelidou (2016), six urban-focused components make up traditional smart city strategies: smart economy (creation of pro-business environments), smart people (networking), smart governance (growth of social and cultural capital), smart mobility (use of technology in transportation), smart environment (use of smart buildings) and smart living (digitalised environment). Other basic infrastructural components of smart cities include: (i) solid waste management, (ii) digital housing, (iii) effective urban mobility, (iv) safety and security, (v) advanced materials and technology, (vii) cleanliness, including waste disposal, (viii) efficient urban transportation, (ix) low-cost housing, (xi) Robust IT networking and digitalisation and (xii) Good governance, including e-governance and citizen involvement. The potential components and initiatives for smart cities are depicted in Fig. 12.1. It presented the plethora of government decisions on diverse regions to prioritise.

Fig. 12.1.

Smart City Initiatives and Features. Source: South African Smart Cities Framework (2021).

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The six major urban-focused components incorporate the following: (i) The role of technology in a smart environment Technology’s purpose in a smart environment is to gather, organise and make a large amount of data accessible to city people. Technology’s development and accessibility enhance the functioning of cities as they become more thoroughly interconnected detectors and the IoT. When access to information in daily activities is made easier, residents are quite fascinating. While urban people have access to efficient interventions, smart mobility and smart communication, quality of life and utility monitoring, it has also become easier to document admirable ideas and better decision-making activities (Komninos, 2011; Schaffers et al., 2011). As a result, the integration of digital environments contributes to the enhancement of municipal services, enhancing sustainability practices and the creation of a smart city (Angelidou, 2014; Cruickshank & Allwinkle, 2011; Tranos & Gertner, 2012). Characteristics of technology’s dominant role in a smart environment are shown in Fig. 12.2.

Fig. 12.2.

Characteristics of Technology’s Dominant Role. Source: Author’s own creation.

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(ii) Advancement of human knowledge and social capital The construction of new modes of innovation, increased involvement and digital literacy and expertise creation and distribution are all ways that smart cities can improve on their second quality. In smart cities, a significant portion of the information that is available is created jointly; intelligence is a resource that results from everyone’s input. A competent workforce and highly skilled individuals are attracted to smart cities and desire to employ technology in new and creative ways. This in turn promotes the growth of intellectual ecosystems that are profitable for the metropolis. Additionally, it is now well established that highly talented and creative individuals are the most effective catalysts for urban improvements (Edvinsson, 2006; Florida, 2005; Hollands, 2020), by creating innovative concepts and tactics through online communities (Komninos, 2009; Nam & Pardo, 2020; Whelan et al., 2014). Fig. 12.3 indicated the characteristics of the advancement of both social and human capital.

Fig. 12.3.

Characteristic in Terms of the Growth of Both Social and Human Capital. Source: Author’s own creation.

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(iii) Smart commerce and business sector advancement A great track experience in new firm formation and innovative dynamism are all goals of the smart city movement that aim to advance the business sector. Urbanisation is enhancing the adoption of smart enterprise or intelligent market approaches for a balanced economy, and socio-digital innovations are a key factor in this (Mahmood, 2018). Smart governance and business-led urban development are distinctive features of smart cities. By providing entrepreneurs with cutting-edge smart mobility technologies, they hope to create business-friendly surroundings. The socio-digital technology that enables the proper road flow of traffic, internet banking and organizational skills for a low-priced revolution for every resident is the basis of smart mobility (Savithramma et al., 2022; Turetken et al., 2019; Zavratnik et al., 2020). Mahmood (2018) asserts that the incorporation of smartphone services into routine urban interaction enables smart governance since it enables efficient engagement, sustains the business and fosters social ties. Overall, promoting and diversifying urban entrepreneurial environments is a top objective for both the smart city paradigm and European initiatives. The potential characteristics of the expansion of the business sector are revealed in Fig. 12.4.

Fig. 12.4.

Characteristics of the Expansion of the Business Sector. Source: Author’s own creation.

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(iv) Smart networking Nowadays, networking is mostly accomplished through online digital media through transnational economic and multinational collaboration, particularly in the area of smart cities. Networking inside and between municipalities and regions is emphasised in the analytical analysis of smart cities to create a positive public image, disseminate best practices, diversify the manufacturing base and provide efficiencies of scale (Fig. 12.5 refers). City officials are under growing pressure to provide more high-quality and innovative services while garnering more public support in today’s information-based economy and society. The majority of cities already have these partnerships in existence. Urban metropolis focuses on establishing alliances and collaborative networks to share information and coordinate resources while highlighting the unique and distinctive character of their centre. Approaches for marketing and communicating have made their way into plans for new urban development, including smart cities.

Smart Cities in the African Sub-Sharan Continent Nigeria, Ghana and South Africa are located in the African sub-Saharan continent (Fig. 12.6), and all are taking steps to enhance different areas of their capital cities to fulfil the smart city requirements. The focus has recently shifted to intellectual capacity, guiding the expansion of the urban metropolis (Elmquist et al., 2009;

Fig. 12.5.

Networking-Related Characteristics. Source: Author’s own creation.

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GHANA

195

NIGERIA

SOUTH AFRICA

Fig. 12.6.

Map of the African Sub-Saharan Continent. Source: https://www.googlemap.com/.

Schaffers et al., 2011). This is due to the incorporation of new components in daily life, focusing on one or more factors that support the smartisation process has helped the method for building smart cities grow. By 2050, the United Nations projects that urban and metropolitan areas will house 70% of the world’s population which will increase emissions and energy consumption each year. However, smart city programmes in Africa are to overcome some difficulties and create a foundation for a sustainable society. Environmental, social and economic sustainability are all trying to keep up with the rapid increase in urbanisation (Sadiq & Wen, 2022). Stakeholders, government and non-governmental agencies, academics, researchers and related professionals in African countries are worried about implementing smart technology to improve environmental sustainable development in the current face of the global digital revolution (Mahmood, 2018; Zavratnik et al., 2020). Numerous obstacles are preventing urban centre growth in Africa. This includes, among other things, urbanisation, environmental degradation and global climate change, all of which have had an impact on the commercial development of Africa and indeed the city’s sustainable planning initiatives

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(Guma, 2020; Vainio & Sankala, 2022). Therefore, including the IoT and digital communication in urban planning would further boost connectedness and socio-economic endeavours, putting the continents on pace with their counterparts in developed nations. African cities are expanding rapidly, as such the sub-Saharan region is among the few industrialised in the world in 2014 along with Asia is currently showing industrialisation and urbanisation rates. According to the United Nations (2014), the African population is expected to reach 2.4 billion within the next several decades, prefer cities over rural regions (Huet, 2022). The crucial aspects include the requirement for transport and access to urban services, safety and policy-related concerns. Therefore, the process of urbanisation can only promote growth if measures are taken to address the structural problems that it brings about, and if attempts are made to establish equitable, secured and viable cities as envisioned by the UN Sustainable Development Goals (SDGs) (Institutes for security studies, 2022).

Framework for Case-Study Evaluation and Synthesis This chapter employs multiple case study analysis method that has previously been used by Eisenhardt (1989), Yin (2009), Miles et al. (2013) and Angelidou (2014). This style of qualitative analysis summarises and contrasts the key conclusions of qualitative research in a thorough and organised manner. The smart city frameworks, the evolution of smarter cities and smart city strategies were examined. This material included journals, conferences, books, websites and reports. To document the study’s search engines related to smart cities, the literature review examined various concepts, initiatives, domains, components and frameworks. Five significant smart cities, Singapore, Istanbul, Amsterdam, Barcelona and Oslo, were studied using a case study review methodology. The pieces of information about smart cities in the developed nations’ cities were documented, while the highlight of the countries’ strategies in tandem with the African cities such as Nigeria, Ghana and South Africa were presented. The analysis is accomplished by the examination of various case studies using the contents reviewed method. These arrays enable systematic cross-case comparison of findings and examine behavioural trends, similarities and differences. Table 12.1 indicates the adopted scorecard of a smart city. Similarly, a detailed summary of the critical requirements of the smart city needs and requirements are depicted in Fig. 12.7.

Smart Cities’ Insights Across Developed and Developing Countries Most of the world’s most important cities have already begun to adapt to the shifts that smart technology adoption is bringing about. While most of the advancements ushered about by smart technology have a positive influence on how people live in these cities. Singapore, Istanbul, Amsterdam and Oslo were chosen because they are all among the industrialised nations with the most

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Table 12.1. Adopted Scorecard of a Smart City. Drivers Smart economy Smart people

Smart governance

Approaches Smart commerce and business sector advancement Human contact effectiveness in cities

Features Entrepreneurship and innovation

The contribution of ICT to the growth of social investment and human knowledge Service integration for Smart networking and instruments for improved quality of life collaboration

Smart mobility

The adoption of ICT in transportation Smart Quality of life living/ satisfaction and environment effectiveness resources

Sustainable and inter-modal transport systems, safe and secure transportation system Natural resource management

Literature Bronstein (2009)

Giffinger et al. (2007), B´elissent (2010) Kolsaker and Lee-Kelley (2008), Maltby (2013) Bifulco et al. (2016) Tanguay et al. (2010)

Source: Author’s compilation.

advanced cities (Smart City Index Report, 2022). Therefore, the insights from the smart city movements in industrialised nations and developing countries such as Nigeria, Ghana and South Africa smart cities are succinctly presented.

Singapore Smart City Irrespective of the ranking criteria, Singapore continuously comes out on top as the world’s smartest city, which demonstrates the city’s dedication to smart technology. In connection with smart technology, Singapore is often recognised and often time takes the lead in smart city initiatives (Fig. 12.8). To increase productivity in the nation’s most sophisticated economy, the country is concentrating on digital technologies and projects. The Institute for Management Development and Singapore University of Technology and Design (SUTD) released their yearly report, which rates cities, according to economic and technological statistics as well as residents’ opinions of how smart their respective cities are. The existing plans in Singapore involve a shift towards a digital healthcare system by establishing virtual consultations and adopting smart IoT devices to constantly track patients. One aspect of Singapore’s continual progressive developments is how the transportation system is evolving and how artificial intelligence (AI) benefits the country.

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Fig. 12.7. Critical Requirements of the Smart City Needs and Requirements. Source: Authors’ conceptualisation. The goal of Singapore is to create the world’s first vehicle-free, eco-smart city, which will be built in the western district of Singapore called Tengah. By the year 2030, about 80% of Singaporeans will reside close to a train station. Singapore is recognised as one of the most technologically advanced smart cities in the world for a variety of reasons, namely: (i) the development of a multi-route, (ii) an aerial network for drones that will transport packages, letters and information (iii) automated walking projects for the elderly in which self-driving wheelchairs are anticipated to be better designed and integrated into the traffic system and (iv) the use of facial recognition technology to identify clients as they enter banks or to gain access to offices.

Istanbul Smart City The Directorate General of Geospatial Informatics, Planning and Coordination, Application and Development was established by the Ministry of Environment and Urbanisation to assist in the development of smart cities in Turkey. This division is in charge of all national smart city applications, including 3D data modelling and city information system software, and has created a National Smart City Strategy and Action Plan for the year 2019–2022. In Turkey, the

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Fig. 12.8.

199

Singapore Smart City (2023). Source: https:singaporesmart-city.html.

deployment of smart grid technologies has started, and the stages of implementation differ from one DISCO to another, deploying the installation of GIS and SCADA systems. With a population of about 15 million, Istanbul’s smart city (Fig. 12.9) is on track to become a permanent member of the world’s mega list. Turkey’s growing urbanisation is requiring the nation to enter the smart city eco-system as soon as possible (NOVUSENS, 2022). The Sustainable Cities I and II Projects in Turkey received $133 million and $91.5 million in loans, respectively, from the World Bank in the years 2016 and 2018 (Cakilcioglu, 2022). By giving municipalities access to money for their investments in enhancing services to their inhabitants, this programme seeks to increase the economic, financial, environmental and social sustainability of Turkish cities. The funds help communities by executing infrastructure investments required to meet service delivery standards in areas such as waste management, energy services, public transportation, wastewater systems and other areas.

Amsterdam Smart City, Norway Through a significant and complementary local partnership, the Amsterdam Smart City project uses a combined approach to sustainable energy and green smart

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Fig. 12.9. Union of Turkey Smart Cities (2023). Source: https://smartcity.com.tr/tr/.

technologies. The private sector’s involvement is likely to ensure the results’ sustainability, and they serve as an excellent illustration of applied innovation for major EU cities seeking to develop in a way that is socially, economically and aesthetically sustainable while having a significant regional impact. The project ‘Amsterdam Smart City’, which supports this programme, aims to demonstrate how energy conservation may be achieved while fostering innovation-based economic growth by supporting potential clusters in the West Netherlands (Fig. 12.10). The Amsterdam Smart City project serves as a springboard for fresh developments in the field of smart energy technologies. Parts of the project’s activities include establishing and validating at least 12 test projects in the areas of sustainable housing, employment, mobility and public space; disseminating project information; and building the platform Amsterdam Smart City (Sˇ ˇta´ hlavsk´y, 2011). With the ultimate goal of lowering CO2 emissions, this partnership’s objective is to transform the Amsterdam metropolitan region into a smart city. The smart city platform in Amsterdam brings together all of the city’s players to generate and put into action shared ideas and solutions to the city’s problems. The programme now consists of 32 projects that are spread around the neighbourhoods of Amsterdam and provide fresh concepts and business approaches. Smart and energy-saving technologies were introduced to conserve energy and lessen their carbon footprint (Amsterdam Smart City official website, 2014; Baron, 2012).

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Fig. 12.10. Smart City Amsterdam (2023). Source: https://www.aboutsmartcities.com/amsterdam-smart-city/.

Oslo Smart City The population of Oslo, the capital of Norway, is about 670,000 people. The city of Oslo, surrounded by the Oslo Fjord on its South side, is a city that is constantly growing and changing. A vision for urban development called the ‘Smart City’ aims to make city life better for residents by being transparent, connected, sustainable and creative. The citizen often time accrues profit from the intelligent application, exploitation and integration of new technology, sectors and services. The Oslo Smart City develops and oversees a city’s major area by securely integrating various ICT and IoT technologies. In Oslo (Fig. 12.11), there is a network of public transportation options, including trains, trams, subways, buses and boats. By 2020, all Oslo public transportation will be powered by renewable energy, and by 2028, all public transportation will be electric. The city’s wide range of smart city initiatives includes the testing of electric buses, the creation of zero-emission construction sites, the renovation of existing structures and the creation of green energy and circle-based trash management systems. Oslo’s goal of becoming a fossil-free city by 2030 and its aim to be a green capital are both driven by a core Norwegian value known as a connection to nature. The six emphasis areas used to create a city that is more age-friendly include housing, recreation, outdoor spaces, physical exercise, participation in the community and healthcare services. The main goal is to reduce emissions to address both climate concerns and public health and wellness.

Nigeria – Lagos Smart City Context Internet infrastructure will be required to play a significant part in people’s trips from mega city to smart city with the anticipated Smart City Project in

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Fig. 12.11. Oslo Smart City (2023). Source: https://www.theagilityeffect.com/en/case/oslo-leads-the-way-ingreen-and-inclusive-smart-cities/.

Lagos (a Mega City in Nigeria with an estimated population of 21 million). Eko Atlantic, Nigeria (Fig. 12.12) is an ambitious multi-billion dollar project that aims to transform Lagos, the country’s most populated city. People, smart gadgets and other stationery and moving government assets will all be able to efficiently collect data for residents of the proposed smart city. As a result, social services will be improved, employment will be created, public services will be provided, more people will have access to financial services and the government will produce its revenue. To supply the thousands of systems and devices required to actualise the vision of the smart city, MainOne’s Digital Lagos effort aims to build essential internet infrastructure throughout Lagos State. About 3,000 kilometers of fibre optic cable have already been installed as part of the present first phase of planning for the implementation of the anticipated project. According to Sanwo-Olu, the Nigerian government has given support to more than 20 innovative businesses in industries like agriculture, environmental sciences, educational technologies and small-scale businesses. The administration of Lagos State has generously provided financial support to several researchers so they can carry out roughly 70 research proposals across four academic institutions. In addition, the administration of Governor Sanwo-Olu made it easier to secure money for the Fourth Mainland Bridge project, which is listed in the yearly budget for 2021. Once finished, this bridge will be the longest in Africa. Similar to this, Lagos’ technology infrastructure will be modernised by the current administration. Lagos State will soon become Nigeria’s high-tech power powerhouse as a result of this smart city-initiated project.

Accra- Ghana Smart City Context The Accra economy is expanding overall, with the information technology sector leading the way. Ghana has very adaptable legal systems that encourage the

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Fig. 12.12. Eko Atlantic, Nigeria (2023). Source: https://infomineo.com/african-smart-cities/.

expansion of businesses. Accra was awarded a grant from the IBM Smarter Cities Challenge, which will significantly advance the social and infrastructure advancement of the city (Fig. 12.13). In Ghana, a US$50 million Smarter Communities Challenge was introduced in 2014, with the assistance of The International Business Machines Corporation (IBM). IBM sends teams of experts from a variety of fields to assist cities in developing plans to enhance the smartisation process of Ghana as well as to improve the quality of life of its citizenry. Overall, the government has implemented several policies to encourage and maintain both domestic and foreign investments in the nation to aid in trade. Ghana has fully implemented some initiatives to guarantee that it matches other African nations in launching the smart city project. Numerous laws and regulations have been enacted and are still in effect to encourage innovations and advance national development (The Ghana Smart City Journal, 2022). Notably, Ghana was the second nation in sub-Saharan Africa to have a complete internet connection in terms of ICT in Accra, Ghana, in which about 30,000 people used the internet as far back as the Year 2000. Through the incubation of ICT company start-ups, the Ghana Multimedia Incubator Center has assisted in bridging this gap and boosting ICT Entrepreneurship Development. The recent upgrading of the internet service for the numerous communications technology will further increase the availability of information and technology within the city.

Johannesburg, South African Smart City The Department of Cooperative Governance (DCoG) created the South African Smart Cities Framework (SCF) to offer municipalities, the federal and provincial

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Fig. 12.13. Smart City in Accra-Ghana. Source: The Ghana Smart City Journal (2022).

governments and other role actors unbiased, factual information regarding smart cities in South Africa (A South African Smart Cities Framework, 2021). The City of Johannesburg’s strategy is defined as having modest aims, starting with connectedness with an outline of the city’s smart city plan. As part of the implementation Roadmap for 2014, the City of Johannesburg places a strong emphasis on coordinating its smart city strategies with its IDP process. Johannesburg’s municipality has developed a Smart City Unit with a programme described by Lawrence Boya, the director of Johannesburg’s Smart City Unit. The City of Johannesburg (Fig. 12.14) is now implementing smart city efforts that include automated and integrated police enforcement management systems, via optical fibre and Wi-Fi. It was discovered that, among other things, a call centre-based system that was inefficient and a lack of route planning were causing delays in the delivery of services. In this vein, the government looked into adopting technology to digitise and optimise business operational processes to boost productivity. The focus was also to enhance customers’ process efficiencies through the semi-automation of tasks, lower costs and enhance service delivery. Many precinct cities being developed as smart cities in South Africa have also been the focus of private sector projects in Johannesburg. The most well-known was the Modderfontein project, which promised to create a brand-new urban neighbourhood portrayed with tales of intelligent and sustainable urbanisation.

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Fig. 12.14.

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Sandton Smart City of Johannesburg. Source: South African Smart Cities Framework (2021).

Summary of the Smart Cities for Developed Countries and Sub-Saharan African Countries The goal of the contemporary environment in this new era of the IoT, digital technologies (DTs) and smartisation are really to enhance economic, social and environmental sustainability while also improving the citizens’ quality of life. The cities in developed countries are getting smarter every day and this will continue for a prospect as envisioned in their policies. Similar to this, more cities around the world are now relying on IoT-powered smart city solutions to deal with challenges, including traffic congestion and environmental issues as well as expanding urbanisation. This is awesome news for both locals of these places and tourists from other countries exploring them. A summary of the comparative analysis of the smart city’s intervention for developed and African sub-Saharan Countries is presented in Table 12.2. Comparatively, while giant strides have been made by the developed countries in vast areas of smart city initiatives and sustainability, more serious attention is required from the sub-Saharan African counterparts. The Smart City Index Report (2022) specifically supported these scenarios. Using a chosen collection of variables, the Smart Cities Index report offers a fresh look at the performance of global smart cities. The survey listed 31 smart cities from around the world, but none of the African sub-Saharan Cities were deemed deserving of inclusion.

Developed countries

Sub-Saharan African Countries

1. Singapore Smart City 2. Istanbul Smart City 3. Amsterdam Smart City, Norway 4. Oslo Smart City 5. Nigeria-Lagos Smart City Context 6. Accra-Ghana Smart City Context 7. Johannesburg-South African Smart City

Advanced Technology Coverage and Capacity Building

Digital Smart Power Funding and Smart Smart City Smart and Energy and Network Legislation Business Models Infrastructure Cyber Management in the Areas of Connectivity and and System Security Smart Cities Policies Transportation Advancements System

‘F’

‘F’

‘F’

‘F’

‘F’

‘F’

‘F’

‘F’ ‘F’

‘F’ ‘F’

‘F’ ‘F’

‘F’ ‘F’

‘F’ ‘F’

‘F’ ‘F’

‘F’ ‘F’

‘F’ ‘L’

‘F’ ‘L’

‘F’ ‘L’

‘F’ ‘L’

‘F’ ‘L’

‘F’ ‘L’

‘F’ ‘L’

‘L’

‘L’

‘L’

‘L’

‘L’

‘L’

‘L’

‘F’

‘F’

‘F’

‘P’

‘F’

‘P’

‘F’

Source: Author’s Compilations. Note: Level of compliance: ‘F’-denotes ‘Full compliance’, ‘P’ denotes ‘Partial compliance’ and ‘L’ denotes ‘Low compliance.

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Smart Cities

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Table 12.2. Summary of the Comparative Analysis of the Smart Cities Intervention for Developed and African Sub-Saharan Countries.

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Conclusion and Recommendation Conclusion The majority of African cities are striving to become increasingly digitalised; however, this has led to issues with citizen expectations. African cities require more innovative technology in the management of their urban planning, public transit, communication and other areas (Guma, 2020; Hussein et al., 2019; Moyo et al., 2020). In other words, to accelerate the transition of African cities into digitally advanced and adaptive status, more decisive and collective actions are required. In this vein, modern technology has become such a crucial component of modern life to ameliorate the negative effects of environmental and other socio-economic problems. Additionally, increased knowledge accessibility is made possible by technology acting as a potent driver of sustainability and economic progress. This chapter simply outlined all the key tactics that smart cities must employ to encourage the growth of their technical infrastructure. Given this, the government can enhance its citizens’ quality of life with the advent of the concepts of smart cities and the IoT. This makes the widespread adoption of ICTs in African sub-Saharan urban settings essential for their development. It will take bold and ambitious policies on the development of human and infrastructure capacity to realise a smart city in African nations. This chapter identified several obstacles to the development of African smart cities, which includes: (i) the need for advanced technology coverage and capacity building; (ii) the need to resolve digital and cyber security; (iii) issues with legislation and policies; (iv) funding and business models in the areas of smart cities advancements; (v) more infrastructural facilities in areas of energy, water and transportation systems. As it is understood that for sustainable development, actions must be put in place to strike a balance between social, economic and environmental sustainability. Sustainable cities and communities are the emphases of Goal No. 11, of the Millennium Development Goals. Meanwhile, sustainable development cannot be accomplished without fundamentally altering how we plan, design and maintain our cities. Building resilient societies and economies, safe and affordable housing and business possibilities are all necessary components of sustainable city development. Investments in public transportation, the development of green public areas and enhanced urban planning and administration using inclusive and participatory methods are important. All stakeholders should be involved in adopting new technologies as tools for smart technology, which goes beyond improving sustainability. Urban intelligence, social inclusion, resilience and technological innovation should all be included in global efforts to concretise smart city initiatives and developments. The effects of providing services will strengthen the bonds between the public sector, people and businesses, influencing society and government in the years to come. Similarly, through appropriate services and incentives, as well as collaboration chances between businessmen, the government and research institutions, smart city policies aim to improve and consolidate connections between the

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government and the citizenry. Some smart city ideas offer businesses the chance to display their goods and services while also allowing capital and investment capacity. Initiatives for smart cities will also have a positive impact on global networking and collaboration.

Recommendation This chapter suggests that socio-digital technology integration should be taken into account for the sustainability of African cities. In other words, the smart urbanism model should be properly taken into account if the sustainability of the cities is to be feasible. In terms of adequate planning, African cities with an emphasis on sustainability should emulate developed nations’ concepts for building a new megacity that addresses all aspects of smart cities. It is the responsibility of professionals, decision-makers, urban designers and other related stakeholders to incorporate digital technologies into the conceptualisation of their city. Similarly to this, African authorities should make an effort to regularly tell the public about their smart city plans and to communicate their overall development strategy, concepts, objectives, goals and priorities. Additionally, a platform must be offered so that all stakeholders can share their knowledge of smart cities. This would help establish communities, foster a strong learning culture and increase national capacity for smart city planning and implementation. There must be an effort to incorporate a set of guiding principles and values into African cities’ planning procedures for sustainable development.

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Chapter 13

Leveraging Blockchain Technology in Adopting Digital Tokenization of Green Bonds Pulak Chugh

Abstract In February 2022, the Finance Minister of India in the Union Budget 2022 announced that the government proposed to issue sovereign green bonds to mobilize assets for green infrastructure. These bonds are a sort of fixed-income instrument where the money raised from investors is used exclusively to finance projects having a positive environmental impact. The announcement was in sync with India’s commitment to achieving net-zero carbon emissions by 2070. However, many issues come with it such as the complexity of green data, and the lack of uniform standards to measure the impact of green investments leading to allegations of “greenwashing,” among others. Its solution lies in the digital tokenization of green bonds using blockchain technology. Foreign investors scout for green bonds issued by growing markets like India, which have attractive valuations and good growth prospects. Marketing and issuing green bonds properly would have a far greater potential to bring investment to the security markets and the much-needed advancement in the sustainable sector. It is much more likely that green bonds will bring investment to the security markets and much-needed advancement to the sustainable sector if they are marketed and issued through digital tokenization. Financial regulators and policymakers can create a global framework for the application of blockchain technology in sustainable finance. This might entail tokenizing eco-friendly assets, issuing eco-friendly bonds, trading renewable energy and 2-2 carbon credits in a decentralized ecosystem, and decentralizing crowdfunding for ecofriendly enterprises. This chapter seeks to demonstrate how blockchain technology can help issue green bonds and increase the overall efficiency of green finance in the economy. It also aims to scrutinize how such digital tokenization of green bonds would affect the security market and increase the standards of environmental, social, Fostering Sustainable Development in the Age of Technologies, 213–224 Copyright © 2024 Pulak Chugh Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231015

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and governance (ESG) worldwide. While discussing how this process is shaping up and impacting the economies of various countries, it also seeks to provide suggestions to be taken into consideration while adopting the digital tokenization of green bonds. Keywords: Green bonds; Blockchain Technology; Security Market; Sustainability; greenwashing; ESG; Investment; Digitalisation; Digital Tokenization

Introduction Today, the planet is warming up at an alarming rate; therefore, it has become more than necessary that we work towards a sustainable future. Green finance is the need of the hour to address the challenges of capitalism and environmentalism. The term ‘Green finance’ refers to various financial instruments and systems such as energy trading, green bonds, green investment funds and carbon market as well as institutions such as green banks and green funds (Naderi & Tian, 2022). All these facets are centred on working towards a global environment. The green bond market had been rapidly expanding since it first appeared on the scene in 2007. According to market data, emerging market issuers issued USD 182 billion in green, social and sustainability or sustainability-linked bonds in 2021, more than triple the amount issued in 2020. The Union Minister for Finance and Current Affairs recently gave a nod of approval to India’s first Sovereign Green Bonds Framework. With this clearance, India will demonstrate an even stronger commitment to the goals that it established for its Nationally Determined Contribution (NDC), which were part of the Paris Agreement. Additionally, it will assist in attracting investments in environmentally responsible initiatives from India and the rest of the world. The proceeds from the sale of these bonds will be used to fund initiatives within the public sector that contribute to the reduction of the economy’s overall carbon footprint. The framework is designed to comply with the four components of Green Bond Principles (2021) – use of proceeds, process for projection evaluation and selection, management of proceeds, reporting and key recommendations by the International Capital Market Association (ICMA). Tokenization and financing, both of which are made feasible by blockchain, could pave the way for a future that is more environmentally friendly and sustainable. New financial resources and a diverse group of investors are required to achieve the Sustainable Development Goals (SDGs) outlined by the United Nations (Tsalis et al., 2020). Alterations need to be made to the financial strategies for environmentally friendly projects, and the capabilities of emerging technologies need to be treated more seriously. Because governmental spending on green finance is insufficient, the functioning of the market needs to be modified to increase the rate at which money and investments are funnelled into environmentally friendly enterprises. Therefore, decision-makers in government should pay attention to the amount of money flowing into environmentally friendly and sustainable

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investments. Green finance needs new financial tools and sources of funding for it to be able to assist the world in achieving its green goals. There has been a significant decrease in new investments in environmentally friendly initiatives across the world as a direct result of the COVID-19 pandemic. This demonstrates how crucial environmentally responsible finance is. Blockchain-based solutions can mobilise and expand private money, as well as make it easier for the community to work together and participate in environmentally friendly projects. These improvements are made possible by improving security, transparency, audibility and traceability (Naderi & Tian, 2022).

Objective and Methodology Environmental deterioration and climate change pose significant physical and transitional risks to the stability of the financial system (Niyazbekova et al., 2021). These risks include disruptions to business operations, the destruction of assets, a decline in the value of stranded assets and increased premiums for insurance. Investors are developing new financial products and rethinking existing ones to take advantage of the opportunities presented by sustainable finance. They do this to discover new opportunities, lower their risk or ensure that their values are congruent with one another. Merging sustainable finance and digital technology can bring much-needed development in the Environmental, Social, and Governance standards worldwide. This chapter follows the qualitative methodology of research. Green bonds and their problems – The first ever green bond was issued by the European Investment Bank in the year 2007. Climate Awareness Bond was the name given to this instrument. It was a structured bond, and the proceeds from it went to initiatives that made use of renewable energy sources and reduced overall energy consumption (Jain et al., 2022). Green bonds, which are also sometimes referred to as climate bonds, have been in existence for somewhat more than a decade. They demonstrate that investors are interested in maintaining a sustainable environment. When an investor purchases a bond, he or she is lending the bond issuer money for a certain period in exchange for a fixed interest rate and principal amount. In exchange for their capital, investors get paid interest on their money. The issuer is then responsible for reporting the impact these projects have. The fact that the proceeds from green bonds are put towards initiatives that are beneficial to the environment is what sets them apart from other types of bonds (Niyazbekova et al., 2021). Corporate green bonds accounted for 36% of issuance which is the highest ever, followed by municipalities with 15% (Caramichael & Rapp, 2022). In 2015, India issued climate bonds for the first time to facilitate the financing of renewable energy projects such as solar, wind, renewable energy, energy efficiency and biomass. They spread rapidly, and several financial institutions and banks have been responsible for their issuance. As demand for green bonds has increased, the stock market and the Securities and Exchange Commission (SEC) have taken steps to make it less difficult for companies to issue green bonds (Niyazbekova et al., 2021). The Centre’s approval

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of the framework for sovereign green bonds will further solidify India’s commitment to its green finance projects. Considering the numerous advantages associated with green securities, industry professionals and investors are highly concerned about a practice known as ‘greenwashing’. Greenwashing involves making an unsubstantiated claim to deceive consumers into believing that a company’s products are environmentally friendly or have a greater positive environmental impact than they do (Lutts, 2021). This term was originally coined by prominent environmentalist Jay Westerveld in a 1986 essay in which he claimed the hotel industry falsely promoted the reuse of towels as part of a broader environmental strategy, when, in fact, the act was designed as a cost-saving measure (Orange & Cohen, 2010). Thus, the term is now used to refer to any organisation that seems to adopt new environmental practices that are, in fact, cost savings and nothing more. This is when companies say they are investing in green projects to attract investors who care about the environment, but they are investing in projects that don’t do much for the environment. Another indirect example could be electric vehicles, which use electricity thus saving plenty fossil fuels, and avoiding air and water pollution to a great extent. This is the USP of the EV automobile industry. But, when looked deeper, one finds two major issues here. One is the production of batteries which consumes lots of water and the entire manufacturing process itself is not at all eco-friendly (Nimesh et al., 2020). Furthermore, the electricity to run these vehicles is mostly produced from thermal coal, which again is not in sync with the stated objectives of ‘green energy’. The natural question thus follows: if such companies issue ‘green bonds’, are they really on morally sound grounds? Companies adopt this marketing strategy when they want to appear environmentally conscious to attract investors. Issuers would be motivated to engage in ‘window dressing’ to reduce their costs of borrowing, but this would need to be weighed against the additional expenses of the ‘green label’ as well as the good benefits on the stock market for shareholders (Fatica & Panzica, 2020). Greenwashing is another worry because there are no legal mechanisms to ensure that the proceeds are used in the manner that is described in the prospectus for green bonds (Flammer, 2020). This makes it difficult to prevent greenwashing. If greenwashing gets widespread, it is highly doubtful that green bonds will have any genuine benefits that are beneficial to the environment. On the other hand, if green bonds are utilised to finance initiatives that benefit the environment, we should observe an improvement in the environmental performance of businesses that raise money through the green segment. To uncover any real effects associated with green bond issuances, one would ideally need detailed information on the investment projects for which the bond proceeds are earmarked, as well as their ultimate environmental impacts. However, such detailed information is seldom disclosed regularly (Fatica & Panzica, 2020). It is imperative to understand that these investment circumstances should not be hampered by conventional financial challenges such as inefficiency, lack of transparency and complex procedures (Naderi & Tian, 2022).

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Blockchain technology – The world of finance has just begun to adopt a new technology known as the blockchain. Created at the height of the 2008 global financial crisis as the operational backbone of Bitcoin, blockchain’s distributed ledger technology is a safe and secure method to transfer and catalogue data (Zamani & Babatsikos, 2017). Blockchain technology is implemented in a wide variety of financial applications, including payment and settlement, the issuance of shares, the derivatives market, clearing houses, corporate governance and many more (Yermack, 2017). All these scenarios are ideal for implementing blockchain technology. Many businesses are looking into ways to finance themselves by leveraging blockchain technology. It is a system that consists of multiple copies and does not have a central point. To put this into action, a centralised system is not required. Because of this, the ledger can no longer be altered or tampered with by anyone. It appears like a series of blocks lined together in a row. If a block is altered in any way, it will lose its ability to link to any other blocks. It is not possible to modify one block without also modifying the block that is adjacent to it. Someone can create a new block, but the existing ones cannot be modified. Because it is based on a cryptographic hash, there is no actual alteration to the physical object. A piece of text’s hash serves as its unique digital fingerprint, which can be used to locate the text on its own. It’s possible that a seemingly insignificant modification in a massive file could have a significant impact on the hash. Participants may initially be unable to add new transactions. They are unable to do anything besides scan the blockchain. Every new transaction needs to be authorised by either a majority or a supermajority of privileged participants most of the time. It is estimated that Distributed Ledger Technology (DLT), a form of blockchain, has the potential to expand the global economy to $1.76 trillion by 2030, and this possibility has risen with the popularity of blockchain wallets and cryptocurrencies. Tokenization – Tokenization replaces a sensitive data element, for example, a bank account number, with a non-sensitive substitute, known as a token. The token is a randomised data string that has no essential or exploitable value or meaning. It is a unique identifier that retains all the pertinent information about the data without compromising its security (Sockin & Xiong, 2023). A tokenization system links the original data to a token but does not provide any way to decipher the token and reveal the original data. How data tokenization works – Tokenization, concerning, for example, payment processing, demands the substitution of a credit card or account number with a token. The token has no use and is not connected to an account or individual. The 16 digits primary account number (PAN) of the customer is substituted with a randomly created custom alphanumeric ID. The tokenization process removes any connection between the transaction and the sensitive data, which limits exposure to breaches, making it useful in credit card processing. Tokenization of data safeguards credit card numbers and bank account numbers in a virtual vault, so organisations can transmit data via wireless networks safely. For tokenization to be effective, organisations must use a payment gateway to safely store sensitive data. A payment gateway is a merchant service

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offered by an e-commerce application service provider that permits direct payments or credit card processing. This gateway stores credit card numbers securely and generates a random token (Schletz et al., 2020). For example: When a merchant processes the credit card of a customer, the PAN is substituted with a token. 35843-5268-0846-3322 is replaced with, for example, 4! 5$*2%4)6#2. The merchant can apply the token ID to retain records of the customer, for example, 4!5$*2%4)6#2 is connected to Dilip Joshi. The token is then transferred to the payment processor who de-tokenises the ID and confirms the payment. 4!5$*2%4)6#2 becomes 35843-5268-0846-3322. The payment processor is the only party who can read the token; it is of virtually no relevance to anyone else. Also, the token is of significance for that one merchant only. The true data are kept in a separate location, such as a secured offsite platform. The original data do not enter your IT environment. If an attacker penetrates your environment and accesses your tokens, they have gained nothing. Thus, tokens cannot be used for criminal undertakings. Thus, organisations are not required to invest resources in safeguarding tokenised data. Tokenization can provide several important benefits for securing sensitive customer data (Shtybel, 2019): • Enhanced customer assurance – by introducing an additional security layer for

e-commerce websites, thus enhancing consumer trust. • Increased security and protection from breaches – by not requiring capturing

confidential data in their input terminals, keeping it in internal databases or transmitting the data through their information systems, thus safeguarding businesses from security breaches. • Data tokenization improves patient security – by substituting electronically protected health information and non-public personal information healthcare organisations can better comply with regulations. • Tokenization makes credit card payments more secure – by protecting cardholder data, thus complying with industry standards and protecting client-sensitive information. How blockchain can help in green bond tokenization – The financial sector has been undergoing a sea of change ever since the advent of blockchain. Like blockchain technology, distributed ledger technologies (DLTs) hold the promise of introducing new decentralised solutions that might make a variety of processes more transparent and efficient. According to the analysis in the HSBC Green Bonds Report, the primary advantages of utilising blockchain technology for the tokenization of green bonds are efficiency and legitimacy. Blockchain technology improves security in many ways, including the reduction of costs and the prevention of interference from external parties. The formation of a green bond and the subsequent negotiations all start with a smart contract (Ehlers & Packer, 2017). It can automate all the

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complicated stages, providing issuers and investors with an advantage over their competitors. Because the system already incorporates encryption, it is nearly impossible to spoof either the token-based issue or the value transfer that occurs between parties. Tokenised securities make interactions (such as transfers) more efficient, which results in a reduction in transaction costs. These gains may be negligible if they are handled by a single financial institution that is responsible for all these stages. The public aspect of blockchains shows through in situations like these, where numerous businesses collaborate to create and manage tokenised assets. Instead of making integrations between the various parties on the fly, it can be very appealing to set the terms of cooperation in a smart contract and then rely on the blockchain to enforce those terms and keep everyone in sync. This can be done instead of making integrations between the various parties on the fly (Shtybel, 2019). It would also be able to make it simpler for more people to issue these securities, which would bring in more money and assist projects of all sizes in accomplishing their sustainability objectives. The smaller and medium-sized projects may be ‘bundled’ or ‘securitised’ into a ‘pool’ of projects that would have more credibility, reduced costs for issuance, automation and transparency, and would also be easier to understand. Therefore, the combination of digital technologies with environmentally responsible practices represents a massive possibility for strategic development in the financial industry as well as other industries. When these two movements converge, it will be simpler to promote environmental projects, the risk of climate change will be reduced, the green bond markets will expand, more people will be encouraged to issue and invest in green bonds and more money will be put towards achieving SDGs and developing a low-carbon economy (OECD, 2020). How digital tokenization of green bonds can bring better investment – The research conducted by HSBC and Sustainable Digital Finance and titled ‘Blockchain: Gateway for Sustainability-Linked Bonds’ suggests that the use of blockchain technology may be able to reduce the cost of issuing bonds by a factor of 10 (Khan et al., 2022). This indicates that projects and organisations of any size can issue these securities, thereby opening options for a diverse range of environmentally friendly and sustainable enterprises. The use of smart contracts makes it feasible for blockchain technology to reduce the amount of time, operational risks, middlemen and costs that are involved in a transaction. Tokenised green assets can be listed on the primary or secondary market by banks, and then made accessible to small investors via a public blockchain exchange or a stock exchange that permits trading in security tokens. Whether you invest $10 or $10 million, the price of the bonds you purchase on the blockchain will remain the same (Naderi & Tian, 2022). This indicates that a larger number of people will have access to the market for environmentally friendly bonds. The adoption of blockchain technology not only increases liquidity but also increases the number of people who can invest by reducing the amount of currency that needs to be transacted. People who are interested in investing could do

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so according to the amount of money they have access to, thanks to the process of ‘tokenization’, which allows the investment amount of a bond, which is typically rather substantial, to be divided up. Thus, as more people enter the market, more cash and savings would also be brought into the market (Benedetti & Rodriguez-Garnica, 2021). Issuers and financial institutions can manage a greater number of investors and communicate with them in a wider variety of locations, thanks to technology. It is also possible that operations on the secondary market would be improved, which would make it simpler for issuers to obtain additional funding and for investors who require cash to acquire it. Tokenised green bonds would help in reducing the time it takes to settle a transaction. It still takes roughly two days for security to settle, even though the settling process has become increasingly more efficient over time. The requirement that certain procedures have to be complied with in the correct order, which is done to reduce counterparty risk given that the buyer of a security does not interact directly with the seller, is responsible for a significant portion of this delay. Many of these tasks can be automated and completed in parallel with the help of smart contracts and real-time information symmetry. Since tokens can be coded, smart contracts may also be designed to ensure that they adhere to the established guidelines. This eliminates the need for effort and makes it possible to adhere to the regulations. The token’s functionality and how it is utilised can both be managed and governed by the smart contract. To illustrate, if a piece of property is moved, tokens can be programmed in such a way that they can only be sent to wallets. This prohibits the token from being distributed to individuals who are not qualified to receive it, thus maintaining transparency and accountability ¨ (Narayan & Tidstrom, 2020). Tokens do not exist in the physical world; rather, they only exist digitally and may be accessed via the internet. Therefore, tokens can be issued and traded all over the world through the internet, with the only limitations being those that are programmed into the token’s smart contracts (for example, to meet legal and regulatory requirements), as well as the availability of and limits on any relevant intermediaries (e.g. exchanges and custodians). Tokenization of green bonds would aid in eliminating the need for middlemen using smart contracts hosted on a blockchain to automatically confirm transactions about renewable energy finance. This eliminates the requirement for the involvement of a third party. The shared trading platform for a wide variety of renewable energy commodities is made simpler to use as a result, which benefits both the physical and financial trading markets (Benedetti & Rodriguez-Garnica, 2021). Since traditional securities may only be bought and sold during business hours, investors are unable to capitalise on news or events that take place over the weekend using these securities. In addition to this, they are required to adhere to the guidelines and operating hours of the clearing and settlement systems. These issues are rendered moot because trading and settlement can take place around the clock, seven days a week, for tokenised assets. This must be considered against any potential operational requirements that may arise as a result of trading 24 hours a day, seven days a week. Tokenised green bonds would provide all market

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participants with a single source of information, which makes it simpler to document ownership and enables permitted people to learn throughout their lifespan who the beneficial owner is, thereby bringing accountability to the process and reducing doubts of ‘greenwashing’ which brings a bad name to the noble intentions of sustainable finance (Rizzello, 2022). Tokenization of green bonds would bring features that can be programmed, such as automatically paying dividends, simplifying the voting process, automating vesting periods, etc. and because transactions on the blockchain are immutable, they give an accurate record of who owns specific securities and in what proportions. Blockchain and smart contracts make financial institutions more efficient on the inside. Some of the savings resulting from this increased efficiency will be passed on to the end issuer or investors and would come back as additional investments. At present, authorities in the industry need businesses that trade in renewable energy to turn in a great deal of data so that they may identify businesses that don’t follow the regulations and other regulatory difficulties. It is difficult to obtain and clean the data using the tools and procedures that are now available, and there is a significant risk that the data will get into the wrong hands as a result. All of the issues that have been brought up until this point can be resolved with the help of blockchain technology. It possesses the highest level of transparency, immutable data and the most advantageous ownership rights (Heines et al., 2021). Several platforms provide ‘do-it-yourself (DIY)’ bonds. These bonds enable issuers to create their own ‘green’ blockchain-based bonds at a lower cost. Bonds that can be purchased and managed by the investor, without the assistance of a professional financial advisor, are known as DIY bonds. These new platforms will be able to market these bonds after they have started distributing security tokens. They make it simpler for smaller and medium-sized firms as well as communities to issue environmentally friendly bonds without requiring the costly assistance of a bank (Naderi &Tian, 2022). Furthermore, tokenising green assets allows for the distribution of shares in an asset, which is one of the most useful applications for this technology. Investors can own smaller portions of green bonds and other assets by breaking them up into smaller chunks. Small investors will be able to monitor their holdings’ performance in real time if fractional ownership and automated reporting are combined.

Conclusion It is much more likely that green bonds will bring investment to the security markets and much-needed advancement to the sustainable sector if they are marketed and issued appropriately. However, one of the biggest problems in the field of renewable energy is that there are not nearly enough clear-cut regulations. These projects must largely rely on the regulations because they will not be

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evaluated in comparison to other initiatives. The projects, for instance, cannot proceed until several prerequisites are satisfied, such as agreements to expensive payments, preferential access to electricity grids, investments in vital infrastructure and the assurance that the outputs would be purchased. Some of the recommendations made by the author include the following: • To increase the effectiveness and transparency of sustainable financing, gov-

ernments must embrace new regulatory frameworks and work to reinforce the ones they already have. Especially when tokenising green assets, this is one of the trickiest problems to solve to develop green digital tokenization. It is uncertain how the current frameworks can be used for the trading of new types of renewable energies because they were designed for traditional securities. Significant factors contributing to the uncertainty include taking excessive risks, monitoring the way markets operate, engaging in fraud and dangers associated with technology. • Financial regulators and policymakers should create a global framework for the application of blockchain technology in sustainable finance. This might entail tokenising eco-friendly assets, issuing eco-friendly bonds, trading renewable energy and carbon credits in a decentralised ecosystem and decentralising crowdfunding for eco-friendly enterprises. Blockchain technology can increase this industry’s openness to fresh ideas and give investors more assurance and trust. Distributed ledger technology offers practical ways to promote and reward investments that are good for the environment. The IT community is highly motivated to help make the world more sustainable by ensuring that there is openness, accountability and a strong sense of emergency, even though some people enjoy the taste of cryptocurrency. As a result of the creation of new projects that have an impact on green finance and sustainable growth, the landscape of green digital finance is fast changing. Most of them, nevertheless, are still in the early stages of development. However, if they are supported by the right regulations, they can aid and enhance green investments, particularly in the areas covered in this chapter, such as attracting private green finance, tokenising green bonds, extending the reach of microfinancing, directing private capital to the green investment projects that best suit it, increasing system clarity and lowering uncertainty and supporting the Green Climate Fund.

References Benedetti, H. E., & Rodr´ıguez-Garnica, G. (2021, December 15). Tokenized assets and securities. SSRN. https://ssrn.com/abstract54069119. http://doi.org/10.2139/ ssrn.4069119 Caramichael, J., & Rapp, A. (2022). The green corporate bond issuance premium. International Finance Discussion Papers, 1346. Washington, D.C.: Board of Governors of the Federal Reserve System. https://doi.org/10.17016/IFDP.2022. 1346

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Ehlers, T., & Packer, F. (2017, September 17). Green bond finance and certification. BIS Quarterly Review. SSRN. https://ssrn.com/abstract53042378 Fatica, S., & Panzica, R. (2020). Green bonds as a tool against climate change? Working Papers, Article 2020–10. https://ideas.repec.org//p/jrs/wpaper/202010.html Flammer, C. (2020). Corporate green bonds. SSRN Scholarly Paper No. 3125518. https://doi.org/10.2139/ssrn.3125518 Heines, R., Dick, C., Pohle, C., & Jung, R. (2021, July). The tokenization of everything: Towards a framework for understanding the potentials of tokenized assets. In PACIS 2021 Proceedings (p. 40). Jain, K., Gangopadhyay, M., & Mukhopadhyay, K. (2022). Prospects and challenges of green bonds in the renewable energy sector: Case of selected Asian economies. Journal of Sustainable Finance & Investment, 0(0), 1–24. https://doi.org/10.1080/ 20430795.2022.2034596 Khan, N., Kchouri, B., Yatoo, N. A., Kr¨aussl, Z., Patel, A., & State, R. (2022). Tokenization of sukuk: Ethereum case study. Global Finance Journal, 51, 100539. https://doi.org/10.1016/j.gfj.2020.100539 Lutts, R. H. (2021). Ecokitsch and the landscapes of our desire. ISLE: Interdisciplinary Studies in Literature and Environment, 28(2), 641–661. https://doi.org/10. 1093/isle/isaa087 Naderi, N., & Tian, Y. (2022). Leveraging blockchain technology and tokenizing green assets to fill the green finance gap. Energy Research Letters, 3(3). https://doi. org/10.46557/001c.33907 ¨ Narayan, R., & Tidstrom, A. (2020). Tokenizing coopetition in a blockchain for a transition to circular economy. Journal of Cleaner Production, 263, 121437. https:// doi.org/10.1016/j.jclepro.2020.121437 Nimesh, V., Sharma, D., Reddy, V. M., & Goswami, A. K. (2020). Implication viability assessment of shift to electric vehicles for present power generation scenario of India. Energy, 195, 116976. https://doi.org/10.1016/j.energy.2020.116976 Niyazbekova, S., Moldashbayeva, L., Kerimkhulle, S., Dzholdoshev, N., Dzholdosheva, T., & Serikova, M. (2021). “Green” bonds—A tool for financing “green” projects in countries. E3S Web of Conferences, 244, 10060. https://doi.org/ 10.1051/e3sconf/202124410060 OECD. (2020). The tokenisation of assets and potential implications for financial markets, OECD blockchain policy series. www.oecd.org/finance/The-Tokenisationof-Assets-and-PotentialImplications-for-Financial-Markets.html Orange, E., & Cohen, A. M. (2010). From eco-friendly to eco-intelligent. The Futurist, 44(5), 28–32. Rizzello, A. (2022). Beyond greenwashing: An overview of possible remedies. In A. Rizzello (Ed.), Green investing: Changing paradigms and future directions (pp. 107–132). Springer International Publishing. https://doi.org/10.1007/978-3-03108031-9_5 Schletz, M., Franke, L. A., & Salomo, S. (2020). Blockchain application for the Paris agreement carbon market mechanism – A decision framework and architecture. Sustainability, 12(12), 1–17. Shtybel, U. (2019). A new era of private securities: Application of Blockchain in private capital markets infrastructure. Journal of Digital Banking, 4(2), 152–160. Sockin, M., & Xiong, W. (2023). Decentralization through tokenization. The Journal of Finance, 78(1), 247–299. https://doi.org/10.1111/jofi.13192

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Chapter 14

Digital Technologies and Education for Sustainable Development Renji George Amballoor and Shankar B. Naik

Abstract Education for sustainability has become the mechanism for creating a pool of graduates who can understand, appreciate, practice and support the achievement of Sustainable Development Goals (SDGs). In a world with diverse cultures, demographics, political ideologies, etc. faster progress towards sustainable development needs increased use of digital technologies. Integration of digital technologies like artificial intelligence (AI), metaverse, visualisation techniques, cloud computing, Internet of Things (IoT), open data repositories, geographic information system (GIS), etc. with classroom teaching can build awareness, skills, attitudes and values among students in the journey towards sustainable development and scale up the efforts towards the goals. In this chapter, the authors have tried to bring out a list of digital technologies and the way in which they can be used in classroom teaching to ensure education for sustainability. It may be noticed that there are watertight compartments between those who know the SDGs and those with proficiency in technology. What is also needed is integration between both silos for mapping the digital technologies with the appropriate SDGs. The teachers in the higher education system need more exposure to understand and implement this integration. Keywords: Sustainable development; digital technologies; education for sustainability; integration; multi-disciplinary; classroom teaching

Introduction Sustainability has become a buzzword for every section of society, region and economy. At the dawn of civilisation, when the tribal and nomadic people practiced shifting cultivation, they were championing sustainability. Fostering Sustainable Development in the Age of Technologies, 225–237 Copyright © 2024 Renji George Amballoor and Shankar B. Naik Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231016

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Today sustainable development is like a worn-out cap because everyone wears it. Democracies, autocrats, monarchs, dictators, etc. swear by sustainable development. The present popularity of the word sustainable development can be traced back to the report titled Our Common Future by World Commission on Environment and Development (Visser, 2017). Sustainability involves a better quality of life for now and the generation to come in terms of economic, social and environmental dimensions. The ambitious international community substituted the Millennium Development Goals (MDGs) (2000–2015) with 17 SDGs consisting of 169 targets (2016–2030). To gain local and global endorsement for the ideology of sustainable development, the United Nations declared 2005–2014 as the Decade of Education for Sustainable Development. Unless we prioritise our efforts, the social benefit from every rupee spend will be limited and the country will be able to achieve the goal only by 2059 (Sachs et al., 2021). The SDGs describe the main challenges of economic development encountered by humanity. The SDG 4, Target 4.7 highlights the importance of education for sustainable development, global citizenship education and other transformations for a sustainable and peaceful future for all. Target 4.7 states: ‘by 2030 ensure all learners acquire knowledge and skills needed to promote sustainable development, including among others through education for sustainable development and sustainable lifestyles, human rights, gender equality, promotion of a culture of peace and non-violence, global citizenship and appreciation of cultural diversity and of culture’s contribution to sustainable development’.

Education for Sustainability (EfS) EfS is a framework of teaching and learning for generating awareness and interest among students about sustainable development challenges like poverty, inequality, climate change, irresponsible consumption, etc. Such understanding of the concerns will help students to contribute towards sustainable development initiatives (Jennifer, 2005). EfS aims to integrate ecological, social and economic aspects of humanity, flora and fauna for empowering Homo sapiens in forging a sustainable future (Martins et al., 2006; UNESCO, 2002). Education plays a significant role in ensuring that all students acquire the knowledge necessary to promote and practice sustainable development. This requires the commitment of teachers and researchers through effort, motivation and innovative ideas. In the process of achieving SDG 4.7, teachers and students have to develop competencies for the transition from education to education for sustainability. Teachers will be the major agents of change as they shoulder the major responsibility of imparting the necessary knowledge, skills and attitude for shaping students with sustainable development ideology. Transforming education to education for sustainability requires a change in curriculum, pedagogy, instructional design and assessments. Stakeholders responsible for carrying forward the change will require developing certain competencies. Strong digital competencies will strengthen and enhance the

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transformation. Digital technologies promise high levels of accuracy and time efficiency in the execution of tasks and data-driven decision-making. Sound knowledge of digital technologies and strong skills in their usage will enable the stakeholders including teachers, students and policymakers to efficiently execute their responsibilities in the process of change. Teachers can use them to efficiently deliver instructions and real-time assessments. Students can benefit in terms of being able to receive and understand 24 3 7, while policymakers can use them in developing curriculum, pedagogies and instructional design methods and suggest learning activities and roles for both teachers and students, which are appropriate to impart education for sustainability.

Digital Technologies: Immersive to Translation and Conferencing Digital technologies including computing devices, applications, data, internet facilities, etc. are now better accessible and affordable even for the poor. Using digital technologies is very effective as they provide opportunities for students in experiential learning. They create a powerful learning environment for students to realise the concept of education for sustainability. It can enhance the cognitive, affective and psychomotor learning of education for sustainability. Using digital technologies in learning is effective in nurturing students’ abilities in understanding real-world problems/situations, and acquiring the technical knowledge and skills to develop solutions for them. The experiences and challenges during the use of technologies allow students to critically discuss solutions to problems in a real-time basis. This leads students to reflect upon their attitudes towards the society and world around them, thus a sense of belongingness and emotional involvement with their surroundings. Student education of sustainability quotient can be improved by integration of technologies into the education process. Hochschild (2018) acknowledged the importance of technologies like AI, blockchain, robotics, biotechnology, etc. for achieving SDGs. Immersive technologies like virtual reality (VR), augmented reality (AR), mixed reality (MR) and extended reality (XR) based on Metaverse can be used in the teaching–learning process to conduct experiments without using live animals, plants, fruits and flowers. Further, Metaverse-based learning can replicate their daily socio-economic life through avatars representing real-life actors (Kye et al., 2021), which in turn can improve their learning outcomes (Kemp & Livingstone, 2006). There are a lot of deliberations about effectively tapping the country’s demographic dividend. Skilling the graduates is an important element in minimising the disappearance of the sweet spots. Metaverse technology can help in training the youth in a digital mode without disturbing the existing ecosystem. Metaverse helps us to impart training in VR by avoiding the creation of additional physical infrastructure. Further, experiments using Metaverse can help reduce cruelty on different organisms which are on the verge of extinction. The immersive environment can help in developing Industry 4.0-induced cognitive, emotional and technological skills. Metaverse-based immersive technologies can improve the scope of the learning process in discovering environments beyond our

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reach due to constraints of time, resources, funds, etc. and use the virtual world for solving everyday problems (Tlili et al., 2022). Such immersive technologies can help students to appreciate the need for protecting the life below the water and life on land, ensuring climate justice, etc. Digital technology can be integrated for ensuring quality education in creating, delivering content and accessing content and also in learning management systems, resource allocation, scheduling activities, etc. Electronic content creation can take forms like text, audio, picture, video and animation. Content in electronic form is easy and quick to create, edit, store, replicate, share and improve. In the process, institutions will save scarce resources. Student projects and assignments can move from conventional paper and pen mode to digital mode for achieving the SDGs. Exposure to typesetting applications such as Microsoft Word and Notepad, spreadsheet applications, document creation tools like LaTeX with advanced and sophisticated formatting facilities, presentation software such as Microsoft PowerPoint and Prezi, etc. can help students in their learning outcomes. Exposure to the use of such digital facilities will guide students in analysis, visualisation, interpretation and advocacy about various socio-economic, psychological and technological challenges in the society and economy. Using digital proficiency, students will be in a better position to convince their fellow villagers not to burn stubbles, stop female infanticide, discontinue the discharge of untreated waste into rivers and lakes, reduce the excessive use of pesticides, minimise lifestyle diseases, etc. With classroom learning using content in text, pictures, sound, video and animations can help in creating real-world scenarios for students to understand, think and act upon. The huge amount of satellite images can be used not only for mere academic scores but also to form informed decisions like not buying fish during its breeding season, the need for protecting dunes and preventing the destruction of corals. Educational institutions have a lot of social commitment to their catchment society. The extension cell of the institution can have great use of their volunteers who have mastery in digital technology for translation of text and voice content into other languages. Such digital facilities can be of use in imparting basic Foundational Literacy and Numeracy (FLN) to marginalised sections of society, especially the migrants. Further, translation facilities (Google Translate) will be helpful to improve institutional deliveries, immunisation programmes, sanitary conditions and hygiene, enrich scientific temper, etc. Such translation technology can also assist rural students in better understanding subjects they learn in their mother tongue. Although digital technologies exist for translations, speech and text translations across languages, there is a tremendous need for research and improvement in these areas so as to enhance the quality of translations and cover more languages. Projects involving the development of translation tools such as compiler design and parsers will ensure that learners explore and get more languages on the internet. This will also ensure that minority languages don’t get extinct. More people from different linguistic backgrounds will get connected in cyberspace thereby breaking all the human barriers. Developing computer systems, software and programming tools in local languages will enable more people

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to use technology, reduce the digital gap and contribute to socio-economic and cultural prosperity. During the Covid-19 pandemic, the academic schedules of institutions were disturbed. Google Meet, Zoom, Microsoft Team, Skype, WhatsApp conference calls, etc. came to our rescue. Such facilities helped the student to clarify his/her doubts 24 3 7 3 365 with their teacher and peers. Students with exposure to such applications can help the local administration for managing disasters, build confidence among villagers during the occurrence of natural and man-made events, in giving early warnings to minimise the losses from national calamities, hold people together during emergencies, etc.

MOOCs, Geospatial Technologies, Collaborations and Industry 4.0 In the new normal, classrooms are digitised with interactive touch panels, video cameras, microphones, speakers and internet connection enabling teachers to conduct classes both in virtual as well as hybrid mode. With such equipped classrooms, students can attend the best lectures delivered from any part of the world, clarify doubts in real-time, interact with world-renowned experts and Nobel laureates, etc. with great ease. Such facilities can contribute towards collaborative learning without regional, gender, caste, income, colour or language barriers. The growth of Massive Open Online Courses (MOOCs) enables learners to learn and get certification for quality and reputed courses that are otherwise not available locally. The online proctoring software enables course-offering institutions to conduct examinations in online mode maintaining high ethical standards. The certification provided through MOOCs is emerging as an important part of Skilled Through Alternative Routes (STARs). Online polling features can be used in the classroom and outside to understand the grasping quotient and to devise measures to improve the outcomes. Society’s attitude towards the ideology of ‘Reduce-Reuse-Recycle’ can be easily captured through online polls and interventions can be planned to optimise the said ideology. The mood of the nation about the policies implemented to fight global warming and climate change can be evaluated from time to time. Educational institutions train students in the effective use of bigdata in the decision-making process. Understanding the tools and techniques of data mining will help the country in identifying hidden patterns. Such patterns can reveal new growth engines for the sustainable development of cities, communities and societies. There are a lot of reports and policy documents put up in the public domain by government departments, industry bodies and NGOs. They run into hundreds of pages that common citizens will be handicapped to read, understand and use. Such inequalities in understanding these documents and using them create an unequal society. Curriculum can be modified to teach students, even without coding proficiency, the art of visualisation and infographics. It is not merely the

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normal data visualisation but also those using maps, 3D models, smart arts, animations, etc. Students with such exposures can be roped in by educational institutions, self-governing units and NGOs to create different visualisations of lengthy reports and documents based on the digital literacy of the concerned audience for which it is made. Every year governments release documents on road accidents, but such numbers are inadequate to take follow-up measures. Experts can be roped in to prepare visualisations that can give some patterns beyond numbers for stakeholders to put their acts together. Educational institutions can acquaint students with Google Maps, uses of sensors, etc. Google Maps can help citizens in understanding routes with heavy traffic congestion and select alternate routes to reach their destination. Similarly, projects can have models made by students using sensors that can provide innovative solutions for parking, solid waste management, sensor-based irrigation, responsible consumption of energy, etc. Familiarising students with geo-tagging software can support continuous monitoring, quicker analysis, remote observations and communication. Collecting and processing geospatial information about garbage dumps, potholes, flora, heritage sites, etc. can help governments to take appropriate policy measures. Academic projects on geotagging of plant life such as rare, medicinal and endangered species can develop feelings among learners, making them more sensitive towards life on land and water. In our study, ‘Sustainability Issues of Women Street Vegetable & Flower Entrepreneurs in Goa: Need for State Interventions’ (Amballoor & Naik, 2022), we used various geo-tagging facilities like carto maps, satellite maps, open-street maps, etc. to identify selling clusters for women vegetable and flower entrepreneurs in the process of calculating their sustainability index. Deglobalisation is slowly gaining popularity after the pandemic and is being reflected through protectionist policies, friend shoring, etc. The world urgently requires partnerships, collaborations and alliances to fight global slowdown, poverty, hunger, inequality, green energy, global warming, climate change, etc. The basic theme of collaborations can be imbibed in students when they work on Google Docs, Google Sheets, Colab, etc. Training in such digital tools can prepare students to be great practitioners in the use of technology for partnerships and collaborations. These technologies enable learners from nook and corner of the world across different backgrounds to interact and work together. Viable solutions can be easily identified and transmitted to other parts of the world at the click of a button. The lessons in ‘digital twins’ and Industry 4.0 will tutor students to understand and create virtual models to understand physical objects. The machinery in your firm is fitted with sensors that will send real-time data to replicate virtual machinery. The data from sensors will be processed using cloud technology. Such technologies can help the industry to plan preventive maintenance before the machinery breaks down. Such virtual models can be created across sectors for ensuring greater productivity and inclusive growth. Exposure to Industry 4.0 will help students to analyse the changing landscape of the job market and the profiles. Understanding the skill requirements, essential

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certifications and emerging jobs will help students to improve their employability quotient especially when captains of industry were going hammer and tongs on the low marketability of students.

Cloud Computing, Data Driven Decisions, Social Media and Internet Cloud computing enables the usage and sharing of computational resources from anywhere over the internet without having to own them. Infrastructure as a service (IaaS) allows users to use already existing computing infrastructure to create platforms and run applications without having to invest in creating the infrastructure. Platform and Software as a service (SaaS) have made it possible for scholars and researchers to solve problems without having to invest their time in complex coding and installations. Cloud computing has made powerful computing resources accessible and easily useable to individuals across the world. No longer has access to powerful computing limited to rich societies or countries. Any individual with a computing device such as a desktop pc or smartphone and internet connectivity can use infrastructure, platform and SaaS. Having learners learn this technology either to develop or improve it further or use only this technology will empower more individuals to have access to high-power computing resources and enable us to solve complex problems requiring high computational power such as weather forecasting, natural disaster prediction, etc. Increased use of cloud computing and computation resources can ensure greater computation equality. Websites and web applications are very powerful ways of information dissemination. Learning website development and making students create websites for individuals such as small artisans, farmers and self-help groups in their localities will enable students to interact with the locals around and establish a connection and an understanding of the real world which otherwise the classroom teaching or a corporate workplace would have not offered. Students may be asked to develop websites for heritage places, trades, cultural aspects, cuisines and other specialties of the local places. Such projects can help put the local people and places occupy a prominent place on the global tourism map. Websites for donors of blood, food and used books will help to facilitate the transfer of resources in times of emergency to the needy. A website can be created using HTML or other web technologies. It is also now possible to design websites using online website builders which don’t require the developer to have coding capabilities. Data-driven decision-making is imperative for every economy for solving issues and challenges pragmatically and efficiently. A survey based on the questionnaire is time-consuming, costly and involves man-hours to tabulate and interpret. Online data collection tools such as Google Forms, Microsoft Forms, etc. will enable the researchers and scholars to design questionnaires that can be sent to the respondents over the internet. There are plugins available for the online data collection tools which aid in performing complex analysis, presentation and interpretation of data. Saving time and accuracy are two benefits they offer to the user. Since these

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tools enable the online collection of responses, it gives equal opportunities for respondents across different geographic locations. Students can be encouraged to collect data using online data collection tools for their projects, assignments and thesis. Using online data collection tools enables the learner to reach a large number of respondents with different perspectives, cultures, demographics, social backgrounds, political affiliations, etc. making the world a global village. Such studies and reports will be inclusive, broad-based and of good ethical standards. Social media is a form of communication over the internet. Users can have conversations, share information and create web content using these platforms. Social media includes social networking sites, blogs, micro-blogs, picture-sharing sites, video-sharing sites, instant messaging, etc. Students may be asked to create and contribute to blogs on various topics in their syllabus and also on issues concerning their locality. Blogging will enable students to post their independent views on a topic and in no time get feedback from many others. Understanding social media will help students not only in organising events but also to create innovative idea-based pages and posts on social media to advertise and manage the events. Internet penetration and mobile ownership are very significant in India. All aspects of mobile technology are not fully exploited by its users. Students can be trained to use mobile technology as a means of family livelihood. Mobile banking, taking orders using WhatsApp messages, display of produce using Instagram, etc. can create a level-playing field for entrepreneurship to flourish. If knowledge about how to use such technologies trickles down to every household, India can minimise poverty, inequality and unemployment.

Image Processing, AI, Open Data Repository and Artificial Neural Network Teaching to create and edit movies has become easy due to the availability of advanced yet simple-to-use open-source movie-making and editing tools. The camera feature in smartphones has made capturing videos convenient and cost-effective. Students may be asked to capture videos and create movies and documentaries on nature-related concepts such as flora, butterflies and medicinal plants on the campus. Such projects will bring students from different disciplines such as botany, zoology, computer science, languages and music to come together and interact with each other. They provide an opportunity for students to go beyond the walls of the classroom and get a chance to get connected to nature, appreciate its beauty and understand its challenges. Such projects will equip the creator and their audience to understand the heartbeats of nature in a very organic way. A video-making competition will provide a platform for students to showcase innovative ideas on event management. The machine is intelligent when it learns by itself to identify processes, patterns and resolves in the most efficient ways. A synergy between innovation and sustainability is needed through intelligent machines for designing a better future. Artificial Intelligence (AI) can be applied in many ways for improving sustainable

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development. In the educational domain, AI can be used in tasks that require scheduling and allocating resources such as preparing timetables for lectures and examinations, seat arrangements and classroom allocations. Smart attendance systems with auto notification of low attendance and the ability to predict the final course/semester attendance apriori are the applications of AI for educational institutions. AI can also be used in generating question papers as per previously identified criteria such as Bloom’s Technology. Prediction of a possible traffic jam and accordingly directing traffic to take alternative routes to avoid the jam is possible using AI. AI can also help accurately anticipate the demand and load on resources such as power, water, fuel, etc. and inform the authorities in advance for making necessary arrangements. It is possible to predict the possibility of a natural phenomenon such as a cyclone, tsunami, etc. Waste management can be made efficient by having waste-collecting vehicles incorporate intelligent route control systems based on routing algorithms. The garbage bins can contain a sensor-based system that informs the root control system about their status in terms of the quantity of waste they contain. Smart irrigation systems, smart gardens and smart greenhouses can be implemented using AI systems having sensors that monitor moisture and nitrogen content in the soil, humidity and temperature to predict crop needs and recommend actions. Integrating AI with drones helps farmer surveillance and hyperspectral image analysis for crop disease detection and comprehensive pest control. Systems to detect metals and e-waste in waste management are much a need in sustainable cities. Such systems work using metal detection sensors and image processing. There is a huge scope for implementing such projects at a minor scale through projects and assignments. Not all students involved in such projects need to have sound knowledge of electronics and computers. Being multidisciplinary, students from different disciplines such as chemistry, botany, computers, electronics, etc. can be a part of such projects. A small workshop or a tutorial on microcontrollers using Arduino Complete Starter Kit is enough for students from any domain to understand and implement such systems. Digital image processing deals with the editing of digital images using a computer. It involves analysis using programming languages, image processing software and manual. Enhancing the appearance of an image by removing noise and adjusting the colour, brightness, contrast, sharpness and size of the image is a simple but very useful application of image processing. Removal and addition of a feature, combining multiple images, collage creation, designing banners, invitation cards, certificates and sketching are applications that can be done using image editing software. From aerial and satellite images, students may be asked to identify features of interest such as rivers, roads, buildings, garbage dumps, hospitals, emergency services, etc. in a village/city or infected vegetation, forest fires, etc. also changes in these feature in time, comparison of images to find out effects of natural phenomena. Studies involving simple image processions and analysis like the effect of the expansion of roads, deforestation, conversion of the green cover and soil erosion on beaches can be given to students as projects. This kind of analysis can be done by manually observing images, using image editing tools, online services such as Bhuvan and Google Earth Engine or analysing them

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using programming languages like Python, Scilab, Matlab, etc. The ability to process images and use them to create documents using page layout software such as Publisher along with 2D and 3D printing can help students take projects under Desktop publishing (DTP). This experience will help develop the competencies required to be entrepreneurs in the DTP business. An open data repository is a place that holds data for public use, visualisation and analysis. It allows users to freely submit, receive, reproduce and republish data on online mode. Examples of open data repositories include Kaggle, OpenStreetMap and Open Government Data (OGD) Platform India, Bhuvan, etc. Such data sources can help in taking data-driven decisions for achieving the SDGs. They also act as metrics to evaluate the progress in meeting the goals and provide critical information on government operations, public services, natural resources, etc. Analysis of such data from different sources can work out solutions for local, national and global issues. Making students work on open data serves as a way of training them for critical technological job skills, thereby fostering job creation. There are huge datasets for understanding pollution and identifying and conserving natural resources. These data sets can be used by any citizen for ensuring environmental sustainability in a very democratic and participatory manner. Open data repositories strengthen the connection between the students, individuals and the entities creating data. Projects and assignments involving open data from online data repositories will enable students to study and provide solutions to national and global challenges outside of their classrooms. For example, the open geodata repository Google Earth Engine contains satellite images of every location on the Earth taken over the last 40 years. Data in these images can be used to study the change in the direction of rivers, snow cover, desert, expansion of cities, reduction in forest areas, etc. over the last 40 years. These kinds of studies do not require students to know complex programming knowledge. These datasets are easy to download and there are ready tools available such as QGIS, open source software, which has inbuilt features to perform a range of analyses on such datasets at a click of a button. This will inculcate a feeling of global citizenship and belongingness within them. The main benefit of using open data is that the data available is huge and is available at the click of a button and in formats ready for analysis. As most of the repositories are owned by government and reputed organisations, the data are reliable. Students can also be asked to upload their data onto data repositories which will be accessible to any individual across the globe. This will help inculcate in students the feeling of participation on global platforms. Some open data repositories allow individuals to work in a group on a dataset with different roles such as data contributors, analysts, interpreters, programmers, etc. Working in such diverse groups will build in them the aptitude and skills to work and research problems of a bigger magnitude in a multicultural environment. Challenges in the implementation of the 17 SDGs are difficult to handle with conventional techniques. Artificial Neural Networks (ANNs) are often used as an advanced approach to modelling the complex behaviour of systems (Gue et al., 2020). Developing an ANN and using it requires sound knowledge of fuzzy logic, mathematics and AI. Projects based on ANNs can involve students from the

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domain of computer science. However, ANNs are very powerful in solving complex computation problems. ‘Clean water and Sanitation’, ‘Affordable and Clean Energy’ and ‘Sustainable cities and Communities’ are the most popular subject matter for modelling and forecasting. ANNs can be used to predict the amount of energy consumption based on factors such as the month, season, etc. and clean energy production based upon factors such as direction and speed of winds, cloudiness, seasons, etc. ANNs can also model the relationship between the quality of underground water based on the garbage dumps identified in satellite images. ANNs can also be trained to segregate dry and wet waste based on their images, moisture content and smell.

Database, Blockchain and Gamification The success of any organisation or an individual depends on the quality of decisions made which itself depends upon the quality of the information on the decision on which it is based. One major characteristic of good data is its timely availability which depends upon the efficiency of data search. Data files are stored in two ways, one is as a flat file or unstructured way and the second one is in a structured way in the form of models such as tables. Storing data in a structured way makes updates and searches efficient. Database management systems (DBMS) like MS Access, Oracle and MYSQL are excellent tools to create, update and search databases. Searching records manually in very large datasets is a herculean task. Handling databases becomes easy and efficient with the use of Structured Query Language (SQL). SQL contains simple statements in English called queries used to create, update and delete databases, tables, records and values. Making students learn a DBMS with SQL will enable them to handle complex and large-volume databases more efficiently. They will master the skills of creating databases, storing, searching, updating, deleting, generating reports and presenting data in multiple ways. These skills will help to organise data systematically so as to facilitate easy and quick data retrieval in their workplace. The awareness of blockchain technology (BCT) is another technology that can contribute to education for sustainability. Rocamora and Amellina (2020) have identified 24 different areas in BCT that can be applied to achieve SDGs. BCT can be used for climate change mitigation by bringing about more transparency in tracking carbon emissions and trading (Chapron, 2017). The technology can improve trust, transparency and confidence in issues related to climate finance (UNFCCC, 2021). Other applications include timestamped authentication of digital identities of people below the poverty line for their entitlements, verifying academic certificates for students and BCT-based e-markets can be used for reducing exploitation and discover better prices for self-help groups and small and marginal farmers (Mattila et al., 2022). The method of gamification can have a lot of scope for improving education for sustainable development. The simulated gaming environment can be a powerful instrument to generate interest among students and citizens in the SDGs and to bring about crucial behavioural changes (Rodrigo, et al., 2021; Souza

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et al., 2020). The games like The World’s Future, Go Goals, World Rescue, Oil Springs, For People and Planet, etc. can be of immense utility, for building awareness, encouraging experiential learning and promoting social engagement about SDGs. The gamification technology can be used to impress upon the students the benefits of eco-friendly tourism, protecting dunes, afforestation, responsible consumption, safeguarding micro-living organisms, sustainable tourism, organic farming, etc.

Conclusion Integrating technology with the learning process for creating sustainable development has many benefits. Such blending can lead to a trans-disciplinary approach to address societal challenges. It will also equip students and teachers to shift their focus from what of thinking to how. Today, different departments/ schools in academic institutions are working in silos and there is no common language for communication. It is emerging as the biggest stumbling block in our efforts to achieve SDGs. The stakeholders have to plan elaborate programmes for teachers to understand, appreciate and implement integration between digital technologies and classroom teaching. Such integrations will open new vistas for research, benefitting all communities and sections. The quality of life and the happiness index of society can be improved. The world will witness social justice, peace, climate justice, collaboration, sustainable development, lesser inequality and poverty and so on.

References Amballoor, R. G., & Naik, S. B. (2022). Sustainability issues of women street vegetable & flower entrepreneurs in Goa: Need for state interventions. Journal of Entrepreneurship and Innovation in Emerging Economies, 8(1), 83–93. Chapron, G. (2017). The environment needs cryptogovernance. Nature, 545(7655), 403–405. Gue, I. H. V., Ubando, A. T., Tseng, M. L., & Tan, R. R. (2020). Artificial neural networks for sustainable development: A critical review. Clean Technologies and Environmental Policy, 22, 1449–1465. Hochschild, F. (2018). UN Secretary-general’s strategy on new technologies. United Nations UN Chronicle. https://www.un.org/en/un-chronicle/secretary-general% E2%80%99s-strategy-new-technologies-0 Jennifer, C. (2005). Sustainable Schools Project. USA. https://sustainableschools project.org/sites/default/files/EFSGuide2015b.pdf Kemp, J., & Livingstone, D. (2006, August). Putting a second life “metaverse” skin on learning management systems. In Proceedings of the Second Life education workshop at the Second Life community convention (Vol. 20). The University of Paisley. Kye, B., Han, N., Kim, E., Park, Y., & Jo, S. (2021). Educational applications of metaverse: Possibilities and limitations. Journal of Educational Evaluation for Health Professions, 18.

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Martins, A. A., Mata, T. M., & Costa, C. A. (2006). Education for sustainability: Challenges and trends. Clean Technologies and Environmental Policy, 8, 31–37. Mattila, V., Dwivedi, P., Gauri, P., & Ahbab, M. (2022). The role of blockchain in Sustainable Development Goals (SDGs). International Journal of Management and Commerce Innovations, 9(2). Rocamora, A. R., & Amellina, A. (2020, April 15). Blockchain applications and the Sustainable Development Goals. Analysis of blockchain technology potential in creating a sustainable future. Connected2work. https://connected2work.org/report/ blockchain-applications-and-the-sustainable-development-goals-analyis-ofblockchain-technolgys-potential-in-creating-a-sustainable-future/?utm_source5rss &utm_medium5rss&utm_campaign5blockchain-applications-and-the-sustainabledevelopment-goals-analyis-of-blockchain-technolgys-potential-in-creating-a-sustain able-future Rodrigo, M. M. T., Diy, W. D., Favis, A. M. T., Amante, F. U., Castro, J. C. M., Herras, I. Y., Mallari, J. C. F., Mora, K. A., Torres, J. M. R., & Cuyegkeng, M. A. C. (2021). A RECIPE for teaching the sustainable development goals. In the 29th International Conference on Computers in Education, Asia-Pacific Society for Computers in Education. Sachs, J., Kroll, C., Lafortune, G., Fuller, G., & Woelm, F. (2021). Sustainable development report 2021. Cambridge University Press. Souza, V. S., Marques, S. R. B. d.V., & Ver´ıssimo, M. (2020). How can gamification contribute to achieve SDGs? : Exploring the opportunities and challenges of ecogamification for tourism. Journal of Hospitality and Tourism Technology, 11(2), 255–276. https://doi.org/10.1108/JHTT-05-2019-0081 The good, the bad and the blockchain. (2021, May 17). United Nations Block Chain. https://unfccc.int/blog/the-good-the-bad-and-the-blockchain Tlili, A., Huang, R., Shehata, B., Liu, D., Zhao, J., Metwally, A. H. S., & Burgos, D. (2022). Is metaverse in education a blessing or a curse: A combined content and bibliometric analysis. Smart Learning Environments, 9(1), 1–31. UNESCO. (2002). Education for sustainability from Rio to Johannesburg: Lessons learnt from a decade of commitment. World Summit on Sustainable Development. UNFCCC. (2021). UNFCCC Annual Report 2021. https://unfccc.int. https://unfccc. int/sites/default/files/resource/UNFCCC_Annual_Report_2021.pdf Visser, W. (2017). Our common future (‘The Brundtland report’) World Commission on Environment and Development (1987). In The top 50 sustainability books (pp. 52–55). Routledge.

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Chapter 15

Safety Management in the Era of Emerging Industrial Revolution: The Conceptualisation of Safety 4.0 Shatrudhan Pandey, Kirtika Kiran, Shreyanshu Parhi, Abhishek Kumar Singh and Sanjay Kumar Jha

Abstract The emerging industrial revolution referred to as Industry 5.0 is focusing on leveraging human creativity with intelligent and autonomous systems to derive user-friendly work environment for the businesses. Industry 5.0 stresses on people centric work ecosystem, zero accident policy and the well-being of labour within the production processes. This approach of Industry 5.0 to obtain human-centric safety solutions through the deployment of digital technologies deduces workplace accidents and costs leading to the development of Safety 4.0. This chapter aims to investigate the opportunities and challenges of Safety 4.0 and its enabling technologies aspiring towards the greater impact on safety management. Further, we have proposed a framework for the role of human centric digital transformations concerning safety in the manufacturing industry propelling Safety 4.0. Concluding, we discuss the implications for managers and practitioners. We found that Safety 4.0 will strengthen industrial safety, and instead of reacting to accidents, the concept evolved towards a preventive and proactive approach for a healthy industrial ecosystem. Keywords: Industry 5.0; digital technologies; safety management; Safety 4.0; human-centric safety solution; manufacturing industry

Introduction Industry 5.0 has gained immense academic attention since 2017 (Leng et al., 2022; Maddikunta et al., 2022; Xu et al., 2021). The European Commission officially Fostering Sustainable Development in the Age of Technologies, 239–256 Copyright © 2024 Shatrudhan Pandey, Kirtika Kiran, Shreyanshu Parhi, Abhishek Kumar Singh and Sanjay Kumar Jha Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231017

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endorsed Industry 5.0 in 2021, after extensive discussions amongst research and technology organisations as well as funding agencies across Europe in two virtual workshops organised by the directorate ‘Prosperity’ of the Directorate-General for Research and Innovation on 2nd and 9th July 2020. This endorsement resulted in the release of a formal document titled ‘Industry 5.0: Towards a Sustainable, Human-centric, and Resilient European Industry’ on 4th January 2021 (Breque et al., 2021). Industry 5.0 encompasses three interconnected core values: human centricity, sustainability and resiliency, and represents a new level of human-centric industrial transformation. Industry 5.0 aims to achieve social goals outside employment and growth, focusing on safer working conditions for industry workers. The implementation of new technologies under Industry 5.0 has the potential to improve job satisfaction, achieve safer workplaces and reduce workplace accidents and fatalities. Eurostat data on fatal and non-fatal accidents in 2020 shows that dangerous, repetitive work, handling heavy loads, activities involving strong visual concentrations, repetitive movements, use of machine tools, chemicals, dust, fumes, smoke or gases, noise or vibration, slips, trips and falls, which are prevalent in the top-3 sectors with higher accident rates, could be automated relatively easily to reduce accidents. Eurostat statistics for 2020 showed that around 2.7 million non-fatal accidents, with 66.5% affecting male workers, and 3,355 fatal accidents were reported (Eurostat, 2020). The details are shown in Fig. 15.1. According to recent statistics, workplace accidents may be underreported due to work culture and inappropriate accident reporting systems, implying that the actual number of non-fatal accidents may be higher. To enhance workplace safety for workers, the use of robotic technology, combined with artificial intelligence (AI), can take over hazardous and repetitive tasks. Additionally, virtual reality, augmented reality and AI-based technology can enable workers to execute specific tasks that would require expertise and training. Digitalising industrial processes can lead to remote work, making it possible for people living in far-off places to participate in the labour market, thereby creating a wide variety of new opportunities. In addition to physical health, digitalised workplaces must consider mental health and well-being to ensure the safety of workers. Although digitised ways of working pose new risks, wearable digital and technological applications can assist in educating workers and professionals about physical and mental health issues, further creating a safer working culture. By utilising safety intelligence (SI), safety management practices can be improved through the conversion of raw safety data into useful information (Wang, 2021). By ensuring that production respects the limit of our planet places the health and safety of the industry worker at the centre of the production process. Industry 5.0 recognises the capacity of factories to achieve social objectives beyond jobs and growth to become a resilient source of income. The focus on moving from technology-driven advancement to an entirely human-centric approach is one of the most significant paradigms changes establishing Industry 5.0. In order to refrain from leaving anyone behind, the industry must take societal boundaries into consideration. This has repercussions for a variety of things, which include a healthy and safe working environment, respect for human rights and competency

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Fatal and Non-Fatal Accidents at Work by NACE Section, EU, 2020. Source: Eurostat (Eurostat, 2020).

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requirements for workers. The role of the industrial worker and the narratives surrounding them have undergone substantial changes in Industry 5.0. The worker should not be considered as a ‘cost’ but rather as an ‘investment’ role for industry, allowing both the worker and the industry to progress. This suggests that to accomplish their goals, the worker is concerned with making an investment in the expertise, abilities and existence of their workers. Such a strategy is rather different from just balancing production costs with profit, since it places a higher human value on it and regards workers (Commission et al., 2021). The remaining part of this chapter is structured as follows: ‘Literature Review’ presents the literature review. The safety management framework in Industry 5.0 is provided in ‘A Framework of Safety Management in Industry 5.0’. ‘Safety 4.0 Drivers’ discusses the Safety 4.0 drivers. The implications are presented in ‘Implications’, followed by conclusions drawn, and future work is discussed in ‘Conclusions and Future Work’.

Literature Review Industry 5.0 After conducting extensive discussions with various technology and research organisations as well as financial institutions throughout Europe, the European Commission introduced the concept of the Fifth Industrial Revolution (Industry 5.0) in 2021 (Xu et al., 2021). In support of this initiative, the commission published a policy briefing titled ‘Industry 5.0 – towards a sustainable, human-centric and resilient European industry’ (Wang, 2022). Industry 5.0 is viewed as a manufacturing approach that aims to combine the unique capabilities of highly skilled human workers with effective, intelligent and appropriate machinery. This approach is intended to restore the human touch to the manufacturing industry. In contrast to Industry 4.0, the goal of Industry 5.0 is to leverage the distinct expertise of skilled human workers alongside efficient, intelligent and appropriate machinery, in order to achieve manufacturing solutions that utilise resources effectively and are preferred by end-users, thus becoming the next industrial transformation. To achieve increased production and immediate delivery of customised products, various technologies can be considered and utilised to facilitate Industry 5.0 (Maddikunta et al., 2022). Within the process of work, the new approach to factories should combine sustainability and human-centricity with digitised and predictive activities. To meet the cost criteria, such as the implementation of new technologies, energy consumption and safety, these improved and optimised manufacturing processes must be adopted. However, Industry 5.0 prioritises the safety of physical health, and it does not cover the protection of mental health, dignity or privacy of employees at work. Therefore, modern technologies should not compromise the fundamental rights of individuals (Di Marino et al., 2023). In line with the concept of human-centred manufacturing in Industry 5.0, the integration of knowledge-driven, human– machine and environmental safety is important for safety management (Wang et al., 2023).

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The transition of manufacturing towards Industry 5.0 is driven by the key value of human-centricity, which however lacks sufficient technology emphasising sustainability and safety in its development. The emergence of Industry 5.0 highlights the potential for fostering human-centric solutions and the complementary abilities between humans and machines. The increasing use of AI in manufacturing is changing the workforce’s structure and responsibilities. Although some processes can be fully or partially automated through AI, human input or decision-making remains necessary at times (Roˇzanec et al., 2022). In this work, Industry 5.0 is emphasised as a value-driven manufacturing paradigm and revolution that places the welfare of the worker at the centre of the production process while emphasising the significance of research and innovation to support the industry (Xu et al., 2021). The Industry 5.0 revolution aims to address the requirements outlined in the industrial human needs pyramid, which span from ensuring workplace safety to establishing dependable relationships between humans and machines that facilitate the highest level of self-esteem and self-actualisation, enabling individuals to realise and achieve their potential (Lu et al., 2022). The importance of coevolutionary interactions between humans and robots in Industry 5.0 is highlighted, with communication and cooperative intelligence being key factors. To promote the growth of reliable coevolutionary relationships, interfaces must consider organisational objectives and worker characteristics such as age, gender and educational attainment. Cobots, which share a physical environment with humans and have the ability to sense and understand human presence, are an example of how humans and robots can work together either independently, concurrently, sequentially or in a supporting manner (El Zaatari et al., 2019). The new paradigm of Industry 5.0, which focuses on placing humans at the centre of manufacturing processes, may be characterised by the integration of AI in everyday life and their collaboration to enhance human capabilities (Skobelev & Borovik, 2017). The emergence of a new industrial revolution known as Industry 5.0, very soon after the introduction of Industry 4.0, led to debates on the motives and applications of this new paradigm. Industry 4.0 revolves around the concept of a ‘smart factory’, in which intelligent machinery, products, storage systems and data are integrated to form Cyber-Physical Systems (CPS) (Zizic et al., 2022). The concept of Industry 5.0 is proposed to improve productivity and efficiency for the coming generation while reducing the burden on workers. This paradigm is expected to offer a more creative and fruitful approach to work, allowing for better multitasking and a more productive life (Elim & Zhai, 2020). The rapid expansion of digital technologies and AI-based solutions has led to a swift transformation in the manufacturing industry. Manufacturers worldwide are confronted with the challenge of improving productivity while keeping humans engaged in the manufacturing process. The theme of Industry 5.0 has gained more attention among the research community in recent years due to its focus on enhancing human factors such as employee safety and management, training and skill development for workers (Akundi et al., 2022). Fig. 15.2 depicts the three fundamental values of Industry 5.0, the latest industrial revolution:

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Fig. 15.2.

The Core Value of Industry 5.0.

• Human-centricity approach is based on the principle of putting human needs at

the centre of the production process, ensuring that the technology used is beneficial to workers. • Sustainability emphasises the need to reuse, repurpose and recycle natural resources, reduce waste and minimise environmental impact. • Resiliency aims to introduce robustness into industrial production to ensure its continuity even in times of crisis. Industry 5.0 emphasises the significance of alternative forms of governance to achieve sustainability and resilience, enabling the industry to recognise its potential as a pillar of change and empowering employees through digital devices while promoting a human-centric approach to technology (Ineza, 2022). The objective of Industry 5.0 is to enhance productivity and efficiency by converting conventional machinery into self-learning and worker safety systems. This overarching objective is comprised of three fundamental components: ´ human-centricity, sustainability and resiliency (Rybczak & Zieminski, 2022). Industry 5.0 seeks to improve production quality by delegating monotonous and repetitive tasks to robots, thus freeing up workers to concentrate on complex and intelligent responsibilities (Verma et al., 2022). The adoption of Industry 5.0 is leading to a transformation in manufacturing processes globally, with the aim of reducing the burden of monotonous tasks on human workers (Brown & Wobst, 2021). The development of Industry 5.0 has led to more effective automation of production processes through real-time information and improved worker safety on the shop floor through the use of cobots for hazardous and risky tasks. The concept of Industry 5.0 was created to address individualised manufacturing and empower humans in the manufacturing process, with a focus on human–machine collaboration and a more human-centred approach to revolutionise the industry while considering the needs of society as a whole (Martins et al., 2022).

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Safety Management The regulatory need for ‘Safety Management’ was established as a result of the Cullen Report, which was prompted by the Piper Alpha tragedy that occurred in the North Sea in 1988, claiming the lives of 167 people. The safety management system aims to control and regulate employee behaviour, enabling them to anticipate, prevent and mitigate risks when planning and conducting the company’s operations (Hale et al., 1991). The implementation and maintenance of a safety management system is critical to providing employees with a safe and healthy workplace. Such a system establishes the basic safety requirements and outlines management’s expectations through policies and procedures. However, it is important to note that the workers who operate the system establish and maintain the company’s safety standards, and if the system is not implemented appropriately, even well-specified and documented safety mechanisms can be ineffective. The need for a safety management system arose after the Piper Alpha tragedy, as detailed in the Cullen Report, which highlighted the importance of controlling and regulating employee behaviour to predict, prevent and mitigate risk during company operations (Fitts, & Hignite, 1995). Several safety management principles have been derived from the field of quality management, but their application in safety management sometimes neglects their unique benefits for safety (Kearns et al., 1996). The concept of safety management is considered to be a series of problem-solving activities that operate at different levels of abstraction throughout the entire life cycle of a system. The Structured Analysis and Design Technique (SADT) is used to model safety-related actions. To achieve the desired results, specific inputs, resources and criteria/constraints must be met. Risks are modelled as deviations from normal or desirable processes. These principles are essential to ensuring safety in the workplace and should be taken into account when designing and implementing safety management systems (Hale et al., 1997). In the field of safety management, there is a growing understanding that both technical and human failures must be anticipated and managed to ensure safe operations. A safety management system based on the principles of safety in depth is necessary to achieve this objective, which requires a comprehensive plan for managing risks at various levels of the organisation. Effective implementation of the safety management system is essential to ensure a safe working environment despite technical or human catastrophes (Hale, 2003). In safety management, policies, training, audits, corrective measures, improving process safety knowledge, incident investigations, standards of practice and regulations are considered essential elements to ensure a safe working environment (Amyotte et al., 2007). Safety policy, including human factors-based system design, risk identification and mitigation, standards and procedures and safety resources and responsibilities, is a key element of safety management. Safety training covers incident reporting and investigation, ongoing quality control, auditing, change management and monitoring safety performance. The benefits of safety management extend beyond just reducing incidents, as it can also improve competitive

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performance and contribute to economic-financial success (Fern´andez-Muñiz et al., 2009). The Industry 4.0 revolution has enabled robots to identify activities that may pose a risk of injury to workers (Gisbert et al., 2014). The importance of developing safety-conscious, mobile sensing applications that can continuously detect the work environment and the health and safety conditions of employees is being emphasised (Beetz et al., 2015). Recent advancements in Internet of Things (IoT), CPS, cloud computing and intelligent sensors have opened new avenues for safety management applications, as found by research. The study revealed that smart factories are utilising a variety of personal protective equipment (PPE) that is ´ automated to enhance safety management (Podgorski et al., 2017). Opportunities for reducing workplace accidents and risks of injury are provided by Industry 4.0 mechanisms, cyber physical systems and robots, according to recent studies (Tepe, 2020). The performance of health and safety in various industries has shown improvement over the past century, and this improvement is attributed to a combination of factors such as regulatory enforcement, proactive leadership and investment in safety technologies. However, despite these improvements, workplace accidents still occur, prompting questions about the incorporation of lessons from past accidents into organisational health and safety management systems. With the rapid pace of technological advancements, engineering techniques required to address the risks associated with them are lagging behind, resulting in the creation of new hazards and risks. These new risks are attributed to factors such as dependence on information systems, inaccurate or lost data, digitalisation, new types of work organisations and the complex relationships between humans and automation, which result from humans sharing control of automated decision-making platforms (Pillay, 2018). The European Framework Directive on Safety and Health at Work, Directive 89/391/EEC, which was implemented on 12th June 1989, was a significant move towards improving the level of safety and health in the workplace. It guarantees the implementation of minimal health and safety standards in the European Union, which members may maintain, or they may adopt stricter regulations (Lis & Nowacki, 2019). The term Industry 5.0, which describes the collaboration between humans and smart machines, has emerged. This concept aims to increase the productivity of human workers by utilising advanced technologies, including big data analytics, to support robots in performing tasks more efficiently (Javaid et al., 2020). In modern times, the importance of workers’ safety issues is becoming increasingly significant across all areas of activities. Researchers suggest that to effectively address these issues, there is a need for a paradigm shift in safety management, which should include a risk-oriented approach for management in all areas based on system analysis. The development of personal responsibility among managers and employees by educating them about their own behaviour while involved in professional activities is also crucial (Yaremko et al., 2021). According to experts, a safety culture can only be established if there is management commitment and involvement at all levels of the organisation. Poor adherence to worker safety standards can be encouraged by a poor safety culture, which can make it challenging for companies to take appropriate steps to address

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health and safety concerns. Furthermore, companies with a poor safety culture may exhibit a general disregard for all procedures and processes, leading to poor product quality, financial instability and compromised health and safety (Salvi, 2021). Safety management aims to minimise process-related accidents and the release of hazardous chemicals by reducing process hazards to the lowest level that is practically possible (Thirumalainathan & Jaya Krishna, 2022). The transition from Industry 4.0 to Industry 5.0 is characterised by the integration of intelligent cyber-physical socio-technical systems into their physical and cultural host environments, with a focus on the human element. As a result of this shift, workplace hazards are also changing. The United Nations (UN) has identified safety and health at work as a concern in its recent Agenda 2030 for Sustainable Development, which includes 17 Sustainable Development Goals (SDGs) and 169 targets. The third safety development goal aims to ensure healthy ´ lifestyles and well-being for all individuals, regardless of age (Avila-Guti´ errez et al., 2022). According to experts, there is a significant challenge for organisations in the integration of new technologies during the Fourth Industrial Revolution. While implementing new digital technologies, organisations will need to manage safety and health while maintaining their objective and guiding principles to thrive in the new competitive environment (Chalaris, 2022). The EU-OSHA’s report titled ‘Artificial Intelligence and Automation of Cognitive Tasks: Implications for Occupational Safety and Health’ highlights various risks related to AI that policymakers should consider by examining labour laws and data protection regulations. The impact of AI on the workplace can create both opportunities and challenges for OSH, its management and its regulations. The use of AI has also aided in the development of novel approaches to managing and monitoring employees by gathering significant amounts of real-time data (Ramos et al., 2022). Advanced technologies, such as AI and automation, can create opportunities to enhance safety management, surveillance and facilitate early detection to prevent workplace hazards (Pandey & Singh, 2022). However, their use also raises concerns regarding safety management, laws, regulations and ethical considerations that policymakers need to address (European Agency for Safety and Health at Work, 2021).

A Framework of Safety Management in Industry 5.0 The Evolution From Industry 1.0 to Industry 5.0 The four industrial revolutions that have occurred throughout human civilisation have had significant positive impacts on society and have advanced humanity in various ways. The First Industrial Revolution started in the 1760s, and it was characterised by the implementation of mechanical production powered by water and steam. Following that, the Second Industrial Revolution began in the 1870s, which was marked by mass production utilising electrical energy. The Third Industrial Revolution, also known as the digital revolution, began in the mid-twentieth century and employed electronics and information technology to facilitate automated production. Now, the Fourth Industrial Revolution is driven

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by CPS, the IoT and cloud computing. It has the potential to make everything within the industrial ecosystem intelligent, automated and interconnected (Liu et al., 2020). As of 2022, the concept of Industry 5.0 aims to develop personalised autonomous manufacturing processes with a focus on three core values: human-centricity, sustainability and resiliency (Nahavandi, 2019). Fig. 15.3 depicts evolution from Industry 1.0 to Industry 5.0.

The Evolution of Safety Management The implementation of safety policies is determined by safety management, which encompasses a wide range of activities, programmes and events. It refers to all the functions performed within an organisation and emphasises organisational, human and technological aspects. The development of safety management is presented in this study, which identifies four phases of advancement, namely Safety 1.0, Safety 2.0, Safety 3.0 and Safety 4.0, by considering safety principle technologies and methodologies. The evolution of safety management can be seen in Fig. 15.4. In Safety 1.0, safety management was enforced by safety regulations and inspections and was characterised as a passive management approach. This era spanned from the 1760s to the 1930s, coinciding with the First and Second Industrial Revolution, where the transition from manual labour in family workshops to mechanised production in factories led to an increased number of industrial accidents. To address this issue, the first labour legislation was enacted in the United Kingdom in 1802, followed by similar laws in the United States, Japan, Italy, Belgium, Austria and other countries to improve working conditions and reduce working hours. Throughout the Safety 1.0 era, the progress of industrialisation and employee health and safety legislation was closely linked, and safety management was carried out under the observation of inspectors.

Fig. 15.3.

The Evolution From Industry 1.0 to Industry 5.0.

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Safety 3.0 Information and automation technology, and wellestablished safety system, Smart PPE, drones and robots, Internet of things, cloud computing, wearable for workers, Intelligent cameras

Safety 1.0 Safety Legislation and safety inspection 01 1760s

Industry 1.0

03 1870s

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Safety 2.0 Safety management theory and system

Fig. 15.4.

Safety 4.0 Wearable and digital devices, sensorequipped systems, Artificial intelligence based predictive technologies, cobots, blockchain, and digital twin-based risk assessment

The Evolution of Safety Management.

The term ‘Safety 2.0’ refers to a period starting from the 1930s and lasting until the end of the twentieth century, spanning most of the era of Industry 3.0. During this period, active safety management was supported by safety management theory and safety management systems. The Third Industrial Revolution facilitated the automation of manufacturing in factories and the development of safety management techniques. Heinrich’s Law and the accident causation hypothesis, two widely adopted concepts in safety management, were introduced by Heinrich in 1941 and were based on early twentieth-century industrial safety practices. Other safety management theories, including the iceberg theory, the Swiss cheese model, the Bowtie model and the DuPont safety excellence principles, were subsequently introduced and implemented in production. The Robens Report of 1972 emphasised the need for systematic safety management systems for OSH management. In 1991, the HSE issued ‘Successful Health and Safety Management’ HSG65, which followed a Policy Organising Planning Measuring Performance Auditing and Review approach to Operation (POPMAR). The HSE management system was the first systematic OSH to provide a framework for safety management activities. The era of Safety 3.0 is characterised by advanced safety management systems that leverage information and automation technologies, as well as well-established safety systems. This era emerged in the early-twenty-first century, coinciding with the advent of Industry 4.0. The HSE released the third edition of HSG65, which employed the Plan Do Check Act (PDCA) operational paradigm, in 2013. Many businesses have since developed management systems tailored to their specific needs to improve the efficacy of their safety management. The emergence of Industry 4.0, driven by advancements in information and

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automation technologies, has modernised safety management practices. The use of new digital safety equipment, such as PPE, smartphones, intelligent cameras, wearables, proximity sensors, drones and even robots, has enabled greater automation in safety management. For example, PPE equipped with sensors or Radio Frequency Identification (RFID) chips becomes an edge device in the IoT, which can collect and transmit data to the cloud. Safety supervisors can now quickly assess and evaluate the safety status of employees on their PCs or smartphones. Automation forms the basis of factory safety in the Safety 3.0 era. In the current era of safety management, known as Safety 4.0, the focus is on creating human-centric systems that rely on technologies such as AI, big data, digital twin, blockchain, IoT, edge computing, collaborative robots and cognitive systems. Safety 4.0 builds on the previous safety management era, Safety 3.0, which was part of Industry 4.0. In Safety 4.0, AI and blockchain are used for predicting accidents and hazards, while sensors enable real-time sensing and monitoring. Personal protective equipment (PPE) is equipped with digital systems, and collaborative robots can be used in hazardous environments.

Integration of Industry 5.0 and Safety 4.0 There are various opportunities for automating safety management activities with the digitalisation of operations and new safety technology, as outlined in Fig. 15.5, which integrates Safety 4.0 and Industry 5.0. Predictive analytics, enabled by AI, and robots equipped with sensors can gather crucial accident data and allow for preventive actions to reduce accident rates. In addition to improving environmental

Fig. 15.5.

Safety 4.0 Framework in Industry 5.0.

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monitoring, facility sensors can detect chemical breaches and spills. Wearable technology can track workers vital signs and provide notifications when they are exposed to chemicals or toxins, while augmented and virtual reality technology can enhance the effectiveness of PPE. Safety managers in smart factories face challenges in managing the large amount of data generated by intelligent manufacturing, which relies on real-time data gathering and processing. Thorough training is required to ensure that all workers can work safely while using new, advanced equipment. IT professionals can help safety managers develop a comprehensive safety plan and an intelligent safety system that incorporates data-driven safety monitoring and compliance procedures. Collaboration among various stakeholders, including PPE makers, software developers and telecommunications companies, is necessary to create fully integrated solutions that make future smart factories safer.

Safety 4.0 Drivers Safety 4.0 is driven by several key factors that are closely linked to the Industry 5.0 revolution. These drivers include advances in sensor technology, the growing use of automation and robotics and the increasing adoption of cloud-based safety services. One of the key drivers of Safety 4.0 is the increasing availability of advanced sensor technologies. These sensors can be used to monitor a wide range of process conditions, including temperature, pressure, humidity and chemical concentrations. This real-time monitoring allows safety managers to identify potential hazards before they become a problem, and to take proactive steps to prevent accidents and injuries. Another driver of Safety 4.0 is the growing use of automation and robotics in industrial settings. Automation technologies can reduce the risk of injury or fatality from accidents involving heavy machinery or hazardous materials. Additionally, robots can be used to perform tasks that are dangerous or difficult for humans, further improving safety performance in the workplace. The adoption of cloud-based safety services is another key driver of Safety 4.0. Cloud-based services can provide safety managers with real-time access to safety data, as well as the ability to track safety performance over time. This allows safety managers to identify trends and patterns in safety data, and to take proactive steps to improve safety performance. Integrating Safety 4.0 with Industry 5.0 requires a focus on the use of new technologies and approaches to safety management. This includes the adoption of new safety philosophies, the use of advanced sensor data analytics and the integration of safety systems with other industrial systems. By integrating Safety 4.0 with Industry 5.0, it is possible to create a safer, more productive and more efficient work environment. This can lead to improved safety performance, reduced downtime and increased profitability for companies that adopt these technologies and approaches.

Implications Safety 4.0 has significant implications for the Industry 5.0 revolution. Safety 4.0, with its focus on advanced sensor data analytics, cloud-based safety services and

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digital improvements to human–machine interfaces, offers new opportunities for improving safety performance in Industry 5.0. By integrating safety management with Industry 5.0, it is possible to create a safer and more productive work environment. One of the key implications of Safety 4.0 in Industry 5.0 is the potential for real-time monitoring of process conditions, which can help identify potential hazards before they become a problem. This can be achieved through the use of advanced sensors and data analytics, which can detect changes in process conditions and alert operators to potential issues. Another implication of Safety 4.0 in Industry 5.0 is the potential for remote equipment automation. By using automation technologies, it is possible to reduce the risk of injury or fatality from accidents involving heavy machinery or hazardous materials. This can lead to increased productivity, reduced downtime and improved safety performance. Safety 4.0 can also improve compliance with laws, regulations and standards in Industry 5.0. By automating compliance processes, safety managers can ensure that their operations meet all applicable safety requirements. This can help to reduce the risk of fines, penalties and other legal liabilities associated with non-compliance. In summary, Safety 4.0 has important implications for Industry 5.0, including improved real-time monitoring of process conditions, remote equipment automation and automated compliance with safety regulations. By integrating safety management with Industry 5.0, it is possible to create a safer, more productive and more efficient work environment.

Conclusions and Future Work The responsibility of safety management, which determines and implements safety policies related to workers’ safety and health and adapts to industrial revolutions, remains critical in the present Industry 5.0 era. However, there is a lack of research on integrating safety management with manufacturing in this context. Thus, this chapter aims to explore the opportunities and challenges of safety management in Industry 5.0. The analysis begins by examining the characteristics of the previous industrial revolutions and proposes four stages of safety management evolution, namely, Safety 1.0, Safety 2.0, Safety 3.0 and Safety 4.0, considering safety principles, technologies and modes. This chapter then introduces a theoretical framework that integrates Safety 4.0 and Industry 5.0. As research on Industry 5.0 is still in its early stages, there is a gap in identifying the key concepts and traits of safety management in this context. However, this chapter discusses potential opportunities for integrating Safety 4.0 and Industry 5.0. This study contributes to the literature by providing theoretical and managerial implications for safety management in the context of Industry 5.0.

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Chapter 16

Spiritual Approach Among Techies: An Approach for Achieving Sustainable Development Snehal G. Mhatre and Nikhil K. Mehta

Abstract In this chapter, we explain the significance and need for a spiritual approach among techies that would help them be human-centric, compassionate and value-based for sustainable development. We introduced four perspectives of workplace spirituality, higher purpose, interconnectedness, meaningfulness and mindfulness, as significant indicators of sustainable behaviour among the techies. Finally, we discuss how a spiritual approach could help techies contribute to sustainable development. We contribute to the literature by elucidating the role of spirituality among techies that could help advance sustainable technological development and techie’s well-being. Keywords: Techies; sustainable development; workplace spirituality; mindfulness; interconnectedness; higher purpose; meaningfulness

Introduction Techies contribute to the country’s technological innovation and economic development by applying their expertise in advancing technology. The workers in technology-related occupations are called techies. These employees could be engineers or technicians with skills and expertise in science, technology, engineering and mathematics (STEM) (Harrigan et al., 2018). They play an essential role in product development by creating new products and processes (Harrigan et al., 2018; Tambe & Hitt, 2012, 2014). They are central to crafting, planning and leading R&D for technological developments, that is, from product conceptualisation to its realisation in practice. The processes of conceptualisation to practice require techies to have technical skills, be creative and be innovative. They have immense responsibilities that route in from managing to leading Fostering Sustainable Development in the Age of Technologies, 257–267 Copyright © 2024 Snehal G. Mhatre and Nikhil K. Mehta Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231018

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several projects and enhancing productivity. Techies have dual responsibilities as they have responsibilities towards their immediate users and indirectly towards end users. Thus, techies directly and significantly influence the quality of life for all humanity and the environment. However, with the fast-growing technological disruptions happening in this world, sociopolitical and economic pressures may hinder the ethical conduct of the techies, and they may experience dissonances in their values and work expectations (Wijesinghe et al., 2021). In today’s era of globalisation, their contribution has been vast for making the advancement of technological innovation and achieving profits, but this has been achieved at the cost of depletion of natural resources that may have a negative impact on the environment through techie’s unsustainable behaviour. Being a part of such activities could have been an exhausting experience for them. Techies require a balanced mind to develop technical solutions and design technology, and spirituality has the potential to balance. Spirituality at work is essential for humanising the process (Daniel, 2014). Techies can learn to focus and concentrate better on their projects or work they do. The work they do is very significant not only from an industrial or commercial perspective but also from a social perspective. In this vein, the main objective of the chapter is to explicate the significance of spirituality among techies for sustainable behaviour. In this chapter, we introduced four perspectives of workplace spirituality, higher purpose, interconnectedness, meaningfulness and mindfulness as significant indicators of sustainable behaviour among the techies. Techies have accountability towards their job and society; for that, they need to have a stable mind that will help them work with integrity, honesty, compassion and ethics. Therefore, the study of spirituality among techies is significant for making them more responsible towards themselves, society and the environment. Thus, in this chapter, we propose that spirituality would play a vital role in cultivating holistic development among techies.

Sustainable Development The World Commission on Environment and Development (WCED) defined sustainable development as ‘the development by satisfying the needs of the present without compromising the ability of future generations to meet their own needs’ (WCED, 1987). Further, there has been alarming concern over sustainability, for example, CO2 emissions resulting from economic activity (Adebayo et al., 2022). CO2 emissions are prominent for their influence on environmental degradation in the form of pollution, and technological innovation plays an important role in CO2 emissions (Adebayo et al., 2022; Ahmed & Le, 2021; Bekun et al., 2021; Li et al., 2021a, 2021b, 2021c). Adebayo et al. (2022) assert the need to invest in technological innovation for sustainable development. Ol´ah et al. (2020) argue the need for strengthening the technology through a sustainable model since there is a gap between Industry 4.0 and sustainability in practice. In today’s era of globalisation, the emergence of Industry 4.0 could play a vital role in efficient,

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sustainable production, but its related technologies, e.g. the Internet of Things (IoT), however, have a negative influence on environmental sustainability as a result of air pollution, discharge of waste and the exhaustive use of raw materials, information and energy (Ol´ah et al., 2020). Club of Rome (2019) suggested to the EU President the need to ensure that exponential technologies, artificial intelligence (AI) and digitalisation are enhanced for people, the planet and prosperity through delivering a low-carbon, sustainable, socially just, well-being oriented society (Bohnsack et al., 2022). Thus, sustainable development is the need of the hour. Sustainable development strategy endorses that organisations should build economic markets and profits without natural resource depletion (Gladwin & Nordstrom, 1992; Hart, 1994; Jansen & Vergragt, 1992). Sustainable development emphasises achieving balance between people’s well-being, preserving environmental resources and economic prosperity. Therefore, to have sustainable development of the organisation, it is significant to cultivate a holistic perspective for choosing routine strategy, shared vision (Hart & Brady, 2005). Thus, we propose that spirituality would play a significant role in cultivating a holistic perspective among techies for sustainable development.

Workplace Spirituality Workplace spirituality is defined as the inner life nurtured by meaningful work and a sense of connectedness within the community (Ashmos & Duchon, 2000). Fry (2003) stated that workplace spirituality comprises individuals and organisations seeking work through a spiritual path or an opportunity to grow and contribute to society in a meaningful way. When a person’s inner self is directed towards his work and sense of community in the work environment, it is known as workplace spirituality (Daniel, 2010; Kinjerski & Skrypnek, 2008). Workplace spirituality is defined as where employees express themselves in terms of meaningful work, interconnectedness and purpose in their life that connect them to their work (Sorakraikitikul & Siengthai, 2014, p. 178). From an organisational perspective, workplace spirituality is defined as the nature of the organisation’s spiritual values that facilitate employees’ spiritual values and sense of interconnectedness (Van der Walt, 2018). Workplace spirituality, individual spirituality and organisational spirituality are three different dimensions (Pawar, 2017). Individual spirituality means human relationships with higher power (Fry, 2003), transcendence and their feeling of interconnectedness with others (Zinnbauer et al., 1999). According to Weitz et al. (2012, p. 256), spiritual organiations are value-driven, guided by a mission and vision and socially responsible. The organisation should recognise and value employees by emphasising their spiritual development and well-being (Kinjerski & Skrypnek, 2008, p. 262). Workplace spirituality is related to employees’ experience in terms of meaningfulness in work and community at work (Pawar, 2017).

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Further, extant literature reports many positive benefits of spirituality at the workplace; spirituality increases employees’ resilience to handle workplace stress (Cash & Gray, 2000). Spirituality can be beneficial for the inner development of the employees, along with instrumental benefits (Brophy, 2015). Spirituality in the workplace can benefit employees by improving inner effectiveness (Pfeffer, 2003). It bestows intrinsic strength, improves mental well-being, makes human beings mindful of themselves and encourages individual development. Therefore, workplace spirituality is undoubtedly a human need that cannot be overlooked (Hart & Brady, 2005). Thus, workplace spirituality could bring transformation in techies by broadening their perspective through higher purpose, meaningfulness in the work, interconnectedness and mindfulness. Meaningfulness in work: Meaningfulness refers to ‘making sense’ of what individuals are doing (Bailey et al., 2017). Kahn (1990) defined meaningfulness as ‘a feeling that a human being is receiving a return on investments in one’s self in an exchange of physical, reasoning or emotional energy that arises from undertaking work that is valuable, beneficial’ (p. 704). Further, meaningful work is also defined as work that is subjectively meaningful, significant, rewarding or aligned with individual values (e.g. Montani et al., 2017; Nair & Vohra, 2010; Renard & Snelgar, 2016). Employees in the organisation emphases on making sense of the work they do. As an integral element of spirituality, meaningful work creates a joy that connects employees to work for the larger good (Duchon & Plowman, 2005). Extant literature has reported that positive workplace relationships are significant for meaningful work (e.g. Bailey & Madden, 2016; Chen et al., 2011; Isaksen, 2000). Meaningful work increases performance, motivation, commitment and satisfaction (Bailey & Madden, 2016). The psychiatrist Viktor Frankl famously describes ‘how human beings in any calamitous circumstance or events could survive if they have meaning in life. Thus, the significance of meaningful work in the professional life of techies should not be underestimated. Therefore, we propose that if the techies are provided with meaningful work, it would not only result in positive work outcomes like satisfaction and working creatively but also in ‘joy at work’, ultimately enhancing the well-being of techies and motivating them to work for larger good for society by designing a product that is eco-friendly technology.

Higher Purpose Workplace spirituality could facilitate the techies for actualising their higher purpose. An organisation that emphasises creating strong cultural values through higher purpose through strong spiritual leadership could excel in serving the business and environment by producing a product that profits not only the organisation but also the environment. A higher purpose in spiritual leaders provides a motivating force for working towards organisations as well as society (Klaus & Fernando, 2016). A spiritual person transcends their narrow self to contribute towards society’s higher purpose (Parameshwar, 2005). Techies would

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work more sense fully when they have a higher purpose to work towards the betterment of society. The spiritual base value would benefit teamwork and employee commitment (Neck & Milliman, 1994). Organisations that offer a higher purpose and empowerment can invigorate their employees and concurrently meet the organisation’s monetary objectives as well as a higher community purpose (Neck & Milliman, 1994). Further, the organisation’s values should also support offering techies a sense of purpose to enhance their sustainable workplace behaviour. When the organisations and employee’s higher purpose are aligned, they have the potential to bring change for the higher good of the company and society. We propose that if techies have a higher purpose, it could drive their action to create such technology that could benefit humankind and nature and business.

Interconnectedness Interconnectedness plays a vital role in workplace spirituality (Mitroff & Denton, 1999). Interconnectedness is described as having a deep connection to or relationship with others (Ashmos & Duchon, 2000). This perspective among employees could develop belongingness and loyalty to the work and organisation (Karakas, 2010). The extant literature reports that employees who have a strong sense of interconnectedness experience joy and satisfaction by helping others (Khari & Sinha, 2017; Wasko & Faraj, 2000). Spirituality brings the realisation that human beings are connected to each other. The interconnected dimension could be related to many underlying philosophies, for example, UBUNTU. The philosophy of ‘Ubuntu’, which is an Nguni word term from African culture, means ‘I AM BECAUSE WE ARE’; it addresses our interconnectedness and responsibility towards each other that flow from our connections (Nussbaum, 2003). Ubuntu emphasises personhood through community, that is, it is in regard to the community the person is defined (Nussbaum, 2003). Further, interconnectedness could be understood through the eastern spiritual perspective through Loksangrah, the social message stated in Bhagavad Gita illustrates the significance of welfare of all living beings that could facilitate the dimension of interconnectedness. Loksangrah refers to the unanimity of the world and the interconnectedness of society (Radhakrishnan, 1970, p. 139; Pardasani et al., 2014). ‘Loksangrah’ is composed of two words; ‘Lok’ and ‘Sangrah’; ‘lok’ refers to the world, and ‘Sangrah’ means holding together (Pardasani et al., 2014). A society depends on the interdependence of its constituents, including individuals, to function properly. Pardasani et al. (2014) call for the need to address sustainability concerns through spirituality. This could be addressed by encouraging the awareness of selfless service and concern for welfare among employees (Pardasani et al., 2014) and society. Spirituality has the potential for a paradigm shift of techies, making them aware of interconnectedness; that is how we all are connected with others, society and the environment. Thus, inculcating spirituality through training programmes among techies is the need of the hour.

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Mindfulness There has been a significant increase in mindfulness training in organisations. The extant literature reported a positive relationship between mindfulness with organisational productivity, creativity and employee well-being (Sajjad & Shahbaz, 2020; Wolever et al., 2018; Zivnuska et al., 2016). Wamsler et al. (2018) claimed ‘Mindfulness’ could improve understanding and facilitate sustainability that includes all levels, individual level, local, national and global, and should, thus, become a core concept in sustainability science, practice and teaching. Mindfulness has been defined as ‘being attentive and in the present’ (Brown & Ryan, 2003). According to Lynn et al. (2017), ‘Mindfulness’ comprises meditative mindfulness and socio-cognitive mindfulness. Meditative mindfulness, introduced by Kabat-Zinn et al. (1985), describes mindfulness as a technique that emphasises improving psychological and psychical health. Kabat-Zinn asserts that mindfulness comprises two aspects, first is being aware of the present in regard to emotions and cognition. The second is to be non-judgemental towards the experiences. Kabat-Zinn claimed that the non-judgemental facet of mindfulness lessens emotional reactivity and develops tolerance that might lead to improving the physical and psychological well-being of the person (Brown et al., 2007; Lutz et al., 2013). At the same time, socio-cognitive mindfulness is a state of being aware, remaining sensitive to the context or perspective and being adaptive in any circumstances by remaining open to any new information (Langer & Moldoveanu, 2000; Trent et al., 2016). Extant literature suggests positive linkages between mindfulness and sustainability. The extant literature studied the relationship between ‘Mindfulness’ and pro-environmental behaviour (Amel et al., 2009; Ericson et al., 2014; Panno et al., 2017; Pfattheicher et al., 2016; Sajjad & Shahbaz, 2020); feeling connected with the environment (Barbaro & Pickett, 2016) and environmental performance (Umar & Chunwe, 2019). Mindfulness enhances an individual ability to be flexible and learn new things, being creative and problem-solving techniques (Byrne & Thatchenkery, 2018; Colzato et al., 2012). Further, mindfulness enhances spiritual well-being through compassion for oneself and others (Beshai et al., 2016; Condon et al., 2013; Frank et al., 2015; Taylor et al., 2016; Tirch, 2010). Mindfulness reduces negative emotions among individuals (Monzani et al., 2021). Despite the significance of mindfulness in the workplace, Wamsler et al. (2018) state the presence of theoretical, conceptual and empirical blind spots in the academic debate on mindfulness in sustainability research and practice. Therefore, there is scope for scholars to explore the mindfulness and its impact on sustainability through research. Also, organisations should support mindfulness techniques in the workplace to achieve sustainable behaviour among employees in practice. Thus, we posit that if the techie’s mind is cultivated through mindfulness training would benefit their well-being, making them more compassionate with themselves and others. Therefore, widening their horizons may result in a holistic understanding of promoting sustainable development.

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Conclusion Workplace spirituality is very dynamic in nature (Rocha & Pinheiro, 2020). That is, the meaning of spirituality is unique for every individual and is evolving through time. Thus, spirituality should be practiced not by imposition but voluntarily in the workplace. Techies should be given spiritual training with the motive to nourish their inner development and enhance their well-being. The developed inner self of techies would transform them, making them mindful of the interconnectedness that exists between them and organisations, nature, others and society. Further, spirituality would bring about a paradigm shift among techies leading towards the greater good of society, nature and company’s higher purpose that would benefit everyone. We posit that being spiritual at the workplace would help techies change their mindset through higher purpose, interconnectedness, mindfulness and meaningfulness in their work. Thus, spirituality at the workplace will not only help techies to bring sustainability but also enhance their well-being. Further, spirituality at work will also have a positive spillover effect on their personal life.

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Chapter 17

The Evolution of Manufacturing: A Comprehensive Analysis of Industry 4.0 and Its Frameworks Somayya Madakam, Rajeev Kumar Revulagadda, Vinaytosh Mishra and Kaustav Kundu

Abstract One of the most hyped concepts in the manufacturing industry is ‘Industry 4.0’. The ‘Industry 4.0’ concept is grabbing the attention of every manufacturing industry across the globe because of its immense applications. This phenomenon is an advanced version of Industry 3.0, combining manufacturing processes and the latest Internet of Things (IoT) technologies. The main advantage of this paradigm shift is efficiency and efficacy in the manufacturing process with the help of advanced automated technologies. The concept of ‘Industry 4.0’ is contemporary, so it falls under exploratory study. Therefore, the research methodology is thematic narration grounded on secondary data (online) analysis. In this light, this chapter aims to explain ‘Industry 4.0’ in terms of concepts, theories and models based on the Web of Science (WoS) database. The data include research manuscripts, book chapters, blogs, white papers, news items and proceedings. The study details the latest technologies behind the ‘Industry 4.0’ phenomenon, different business intelligence technologies and their practical implications in some manufacturing industries. This chapter mainly elaborates on Industry 4.0 frameworks designed by (1) PwC (2) IBM (3) Frost & Sullivan. Keywords: Industry 4.0; IoT; robotics; digital twins; smart factory

Introduction We had already stepped into Future Internet (FI), the advanced version of the internet. As rightly said by Cardoso et al. (2013), ‘The Internet and future Internet Fostering Sustainable Development in the Age of Technologies, 269–287 Copyright © 2024 Somayya Madakam, Rajeev Kumar Revulagadda, Vinaytosh Mishra and Kaustav Kundu Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231019

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technologies are becoming part of daily human life’. That means from the inception of internet technologies, these technologies have an essential role in our daily life, which is inevitable, including in the manufacturing industry. Many technological devices, so-called Internet of Things (IoT), started being embedded in manufacturing units. Some intelligent devices (IP/CCTV cameras) are used for human security and monitoring processes or events on the shop floor. During plant operations in industries, many authentication technologies, for example, smart cards, have been issued to all the employees of the factory to track the presence of employees. Embedded sensors help to sense the room temperature, humidity, pressure and materials and machines in certain vital places in manufacturing units. Moreover, Hajari et al. (2015) said ‘Technology intelligence is so important to present the best service and product, increase diversity and flexibility, and speed the process of production and innovation’. Besides, Al-Badarneh et al. (2013) pointing, ‘The service sector is the uppermost growth segment of the developed economies, becoming more knowledge-intensive as automation and outsourcing reduce demand for labour in manufacturing’. Finally, now we have reached a stage without technological embeddedness in manufacturing units, operational excellence is handicapped in this global business and competitive world. These advanced automation technologies with the manufacturing process for operation excellence are now called ‘Industry 4.0’. Moreover, the collaboration of manufacturing industry giants and technological developers has given the terminology of the ‘Industry 4.0’ phenomenon. The industry tycoons named the previous industry developments, including Industry 1.0 (steam water), 2.0 (electric power) and 3.0 (internet), based on production process triggering paradigms. However, ‘Industry 1.0’ is a general representation of the First Industrial Revolution. This began in Great Britain after 1750 with mechanisation – specifically with the textile industry, concerning manufacturing equipment (Drath & Horch, 2014; Jazdi, 2014; Shrouf et al., 2014; Xu et al., 2018). Several factors together made Great Britain an ideal place for industrialisation in those days, and the mechanisation of production started using steam water. Around 100 years later, Industry 2.0 was begun in Cincinnati, Ohio. The Second Industrial Revolution submitted with the production of the Ford Model T (the United States). Briefly, this rapid industrialisation phase happened between the nineteenth century (final) and the twentieth century (beginning). That was when Henry Ford mastered and introduced moving assembly line and mass production concepts industries. The other name for Industry 2.0 is the ‘Technological Revolution’. Drath and Horch (2014) said, ‘The development of continuous production lines based on both divisions of labour and the introduction of conveyor belts resulted in another productivity explosion’. The Second Industrial Revolution introduced mass production with the help of electric power (Jazdi, 2014). ‘Industry 3.0’ relies heavily on information and communication technologies (ICTs), the digital revolution. In this phase, automation in the production process in the manufacturing units slowly penetrated. Industry 3.0 (digital revolution) started back around the 1970s. During this period, advanced electronics and IT further developed the automation of production processes (Drath &

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Horch, 2014; Hermann et al., 2016). The Third Industrial Revolution created numerous new business models leading to millions of jobs and finally laid the basis for a sustainable global economy. Moreover, computer usage, Transmission Control Protocol/Internet Protocol (TCP/IP), computer-aided manufacturing (CAM), computer-aided design (CAD), enterprise resource planning (ERP), the internet and several systems and application software are used in manufacturing for operational efficiency. Besides, numerous advanced technologies are converging, including intelligent software, smart devices, embedded new materials and humanoid robots that are more dexterous and a whole range of web-based services. Finally, the Fourth Industrial Revolution (I4) has been initiated, in which the IoT helpfully automates the manufacturing process by connecting even with material things and solid objects. Industry 4.0 is called cyber-physical systems (CPS) (Baygin et al., 2016; Korshunov & Polyakov, 2020; Xu & Duan, 2019). To gain global business opportunity using the Industry 4.0 paradigm shift, many academicians, corporates, researchers and students started collaborating in conferences, workshops, exhibitions, lectures and videos streaming in different parts of the world, specifically at manufacturing units, shops floors, industry clusters and educational institutions to nurture the technology to the public to reap its fruits. Moreover, a tremendous amount of scribing has been done on ‘Industry 4.0’ phenomena recently in the form of research articles, books, blogs and annual reports. The following section has explored more academic and research on Industry 4.0.

Literature Analysis (Web of Science) ‘Industry 4.0’ phenomenon is also called as CPS and Industrial Internet of Things (IIoT). Hence, the authors tried to fetch the research articles from the Web of Science (WoS) using the keywords ‘Industry 4.0’, ‘Industrial Internet of Things’ and ‘Cyber-Physical Systems’ and found up to 6,656 articles dated as of 1/2/2021 right from 2001 to 2021. There may be many more publications which are not available in the WoS but listed in Scopus database, or available in other databases; of course, some may be available in Directory of Open Access Journal (DOAJ) databases free of cost. Moreover, among these 6,656 publications, 5,937 of them are articles; 496 are reviews; and early access (241); editorial material (207); proceedings paper (159); book reviews (3); book chapters (1); news item (6); and data paper (3). However, the citation report for these 6,656 research articles results is around 96,982; among these without self-citations are 81,345. Moreover, the average citations per item are 14.57 where as H-Index for these publications is 113. Some of the well-known research article titles include ‘Internet of Things in Industries: A Survey’, ‘Industry 4.0’, ‘The Internet of Things for Health Care: A Comprehensive Survey’, ‘Implementing Smart Factory of Industries 4.0: An Outlook’, ‘The Internet of Things (IoT): Applications, investments, and challenges for enterprises’, ‘Cyber-physical systems in manufacturing’, ‘Industry 4.0: state of the art and future trends’, ‘Intelligent Manufacturing in the Context of

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Industry 4.0: A Review’ and ‘Industry 4.0 and the current status as well as prospects on logistics’. Fig. 17.1 shows the TreeMap for Research Area Wise Publications. These research area publication includes Engineering (3,303); Computer Science (1,927); Telecommunications (949); Chemistry (839); Environmental Sciences Ecology (535); Automation Control Systems (488); Materials Science (464); Science Technology and other (409); Food Science Technology (388); Business Economics (361); Operations Research Management Science (359); Instruments Instrumentation (358); Agriculture (286); Biotechnology Applied Microbiology (263); Physics (250); Energy Fuels (172); Biochemistry Molecular Biology (100); Public Environmental Occupational Health (85); Metallurgy Metallurgical Engineering(75); Robotics (69); Mathematics (66); Microbiology (64); Construction Building Technology (62), Polymer Science (57) and Water Resources (56), to name a few. The statistics indicate that Industry 4.0 is interdisciplinary, and it has plenty of applications in many sectors. Besides, a few of the well-known authors with more than 15 contributions are LI D (34), WAN JF (33), WANG J (30), CHEN Y (28), ZHANG (27), KUMAR N (26), LI Y (25), IMRAN M (24), WANG Y (24), LIU Y (22), XU LD (22), LI J (21), WANG L (21), CHOO KKR (20), XU X (20), ZHANG L (20), LI X (19), WANG H (19), HUANG GQ (18), KIM J (17), WANG SY (17), YANG LT (17), FERNANDEZ-CARAMES TM (16), FRAGA LAMAS P (16), LI L (60), LEE J (15), TAO F (15), etc. However, Fig. 17.2 depicts the number of publications countrywide of the Republic of China (1,493), England (196), India (483), Spain (440) and so on. Almost all the countries started researching Industry 4.0 and publishing different types of manuscripts. Fig. 17.2 cannot list all the nations, except those that are doing exceptionally well. This implies that Industry 4.0 has many applications, so countries worldwide started Research & Development (R&D), designing, developing and deploying Industry 4.0.

Fig. 17.1.

TreeMap for Research Area Wise Publications.

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Fig. 17.2.

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Publications – Countrywide.

From Fig. 17.3, we can interpret the number of publications (6,656) on Industry 4.0 since 2001, as per WoS. Since then, researchers, academicians and corporate people have started working in various capacities to reap the fruits of Industry 4.0. From the Figure, the number of publications year wise are 37 (2001), 39 (2002), 40 (2003), 30 (2004), 38 (2005), 36 (2006), 58 (2007), 60 (2008), 59 (2009), 75 (2010), 82 (2011), 90 (2012), 91 (2013), 133 (2014), 186 (2015), 335 (2016), 511 (2017), 940 (2018), 1,358 (2019), 2,282 (2020) and 176 (2021). From 2001 to 2013, the number of publications slowly increased. However, there has been a sudden high increase from 2014 onwards. In 2016, 2017, 2018, 2019 and 2020, we can find special publications and tremendous growth in magazines. This shows a good amount of research and development carried out by different academicians, researchers and students on this phenomenon across the globe due to its immense applications with positive and exponential growth.

Theoretical Background The ‘industrial revolution’ phenomenon is not at all a new concept. Moreover, it has changed how the manufacturing process works, society’s lifestyle and, finally, the growth of the global economy. So many manufacturing industries set out over time and substituted the MSME industries worldwide since its inception. The ‘Industry 4.0’ notion was first founded by German industrialists. Industry 4.0 is

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Fig. 17.3.

Year Wise Publications.

primarily based on converting existing manufacturing processes into the smart manufacturing process by various embedded intelligent technologies in the tasks of plants, components, humans and, finally, in the production process. However, Stock and Seliger (2016) also reported, ‘The industrial value creation in the early industrialized countries is currently shaped by the development towards the fourth stage of industrialization (Industry 4.0)’. Almada-Lobo (2015) opines that Industry 4.0 ‘aimed to define Germany’s investments in R&D related to manufacturing for the upcoming years. The main objective was leveraging the country’s dominance in machinery and automotive manufacturing to position it as a leader in this new type of industrialization’. As per the existing literature, ‘Industry 4.0’ is also called the Fourth Industrial Revolution, integrated industry or smart factory (Brettel et al., 2014; Lee, 2015). It is positioned on network and internet architectures to integrate the virtual world using ICT (Patil et al., 2015). Moreover, digitalising the production process is a common practice today. In the early 1990s, CIM gained tremendous momentum in manufacturing industries across the globe. It is a vision of the world in which the natural environment connects to the digital one, using the following driving forces: IoT, cloud computing, big data, CPS and others (Zhou et al., 2015). Wahlster (2014) also mentioned in the seminal paper, ‘Industry 4.0 is

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one of the effects of transformation of the “era of mathematization” to the “era of informatization” of all sciences – medical, energy, media, automotive, biotechnology, computational linguistics, neuroinformatics and finally, manufacturing’. Thus, ‘Industry 4.0’ is a new way of industrial manufacturing compared to existing practices. There is no standard operational definition for ‘Industry 4.0’. Moreover, from a non-professional point of view, it is IoT and manufacturing units for operational efficiency. Moreover, IoT is, as per author Kinnunen et al. (2018), ‘Altogether a novel approach, the field remains somewhat unclear, which creates a need to carry out research, especially from an industrial asset management perspective’. Hermann et al. (2016) discovered Industry 4.0 based on six principles. These six principles support companies in identifying and implementing Industry 4.0 scenarios (1) interoperability, (2) virtualisation, (3) decentralisation, (4) real-time capability, (5) service orientation and (6) modularity. Carvajal Soto et al. (2019) expressed Industry 4.0, ‘In Industry 4.0, the factory condition monitoring and fault diagnosis of components and systems can gain self-awareness and self-prediction, which will provide the management with more insight into the status of the factory’. Further, Karag¨ozoðlu (2017) report also said ‘peer-to-peer comparison and fusion of health information from various components provide a more precise health prediction in component and system levels and force factory management to trigger required maintenance at best possible time to reach Just-In-Time (JIT) maintenance and gain near-zero downtime’. In addition, a study by Berleur and Galand (2005) revealed, ‘modern ICT like CPS, Big Data Analytics, and Cloud Computing will help predict the possibility to increase productivity, quality, and flexibility within the manufacturing industry and thus, to understand the advantages within the competition’. In implementing advanced terms such as Industry 4.0 and CPS, the sole presence of connectivity between machines and using sensors is not beneficial. To leverage these advanced technologies, correct information must be present at the right time for the proper purpose. In this situation, a 6C system is required, including connection, cloud, cyber, content, community and customisation (Lee et al., 2013). Ivanov et al. (2016) mentioned in their report, ‘The Industry 4.0/Smart factories, based on collaborative cyber-physical systems, represent a future form of industrial networks. Supply chains in such networks have dynamic structures that evolve’. Moreover, Lee (2015) also stressed the phenomenon, ‘The smart factory is the integration of all the recent Internet of Things technological advances in computer networks, data integration, and analytics to ensure transparency to all manufacturing factories’. Industry 4.0 initiative is further designed to carry this concept over to things like production processes on the meta-level and products themselves on the instance level. Brettel et al. (2014) described in their manuscript, ‘In the smart manufacturing environment, intelligent and customized products comprise the knowledge of their manufacturing process and consumer application and independently lead their way through the supply chain’. Besides, there are many more supporting studies on the smart factory’s phenomenon by Zuehlke (2010), ‘The Smart Factory initiative was founded by industrial and academic partners to create and operate a demonstration and research testbed for future factory technologies’. This is the last decade; a massive amount of academic

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literature has been written by different researchers, academicians, scholars and students. Many authors published journal articles, books, book chapters, white papers, etc. Thus, the phenomenon penetrated all the disciples as it had interdisciplinary advantages. There are many conferences, workshops, seminars and doctoral colloquiums, industry talks organised on Industry 4.0. This witness flourishes about Industry 4.0 phenomena. Thus, as rightly said by Bag et al. (2021) that ‘Industry 4.0’ technologies provide digital solutions for the automation of manufacturing.

Industrial Internet of Things Technologies Disruptive technologies always play an essential role not only in our daily life but also in industrial operations. Moreover, when it comes to technologies, they are always meant for industry operational excellence by marrying various machines, methods and materials. In this light, many legacy technologies are developed, deployed and used in the form of tally, CAD, CAM, ERP, etc. in manufacturing companies. Nowadays, technologies like digital twins, 3D printing, drones, robots and bots are exponentially penetrating the shop floor, supply chain and office automation operations, to name a few. Moreover, the recent technologies currently empowering under the banner ‘Industry 4.0’ consist of cloud technologies, mobile computing, machine-to-machine (M-2-M) communication, 3D printing, etc. Whereas these are disruptive technologies, the transformation of the manufacturing units is in many folds, and thus Industry 4.0 revolution goes far beyond them, as per Almada-Lobo (2015). However, small and medium-sized enterprises (SMEs) face difficulty purchasing the high-end applications and ¨ technologies of Industry 4.0 (Faller & Feldmuller, 2015). Thus, Industry 4.0 dictates the end of traditional centralised applications for production control. Its vision of ecosystems of smart factories with intelligent and autonomous shop-floor entities is inherently decentralised. Responding to customer demands for tailored products, these plants fuelled by technology enablers, such as 3D printing, IoT, cloud computing, mobile devices and big data, among others, create a very new environment (Almada-Lobo, 2015). Central or state governments across the globe are focusing heavily on this new technology, ‘Industry 4.0’ to secure competitive production and a healthy manufacturing industry. India is also set out to implement manufacturing strategies under the leadership of Prime Minister Shri Narender Modi. The two new industrial slogans, ‘Make in India’ and ‘Digital India’, bring the best Indian manufacturing practices. Moreover, in the coming years, all the factories and manufacturing units will fully automate with different IIoT technologies for operational efficiency. There are numerous IIoT technologies available in the market, like robots, digital twins, 3D printing, Radio Frequency Identification (RFID), sensors and storage solutions, to name a few. The seminal paper by Kagermann et al. (2013), ‘The Internet of Things technologies, Cloud computing, and Big Data Analytics are solution-components of Industry 4.0’. The following sections explore some of the disruptive technologies in crystal clear.

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3D Printing The researchers Somayya and Ramaswamy (2016) communicated about 3D printing, ‘A multitude of 3D printings is rapidly evolving, creating new opportunities to disrupt business models in a variety of industries. 3D printing is a fascinating production technique in this technological world. It allows users to directly translate a digital file into a physical product/s’. Aikhuele and Turan (2018) said, ‘Companies are faced with the need to address their product development challenges innovatively to stay competitive in today’s market. One way of doing that is the integration of lean thinking in their product development process’. In other words, as rightly said by Mishra (2014), ‘“3D printing” is a kind of “Additive Manufacturing" technology, in which a three-dimensional object is created by laying down successive layers of material. It is also known as rapid prototyping and is a mechanized method whereby 3D objects are made in a reasonable size’. The way 3D printers work is like inkjet printers. They work using single-coloured inks. Moreover, the 3D printer uses a powder that is built into an image on a layer-bylayer basis. A study by Berman (2012) revealed, ‘All 3-D printers use 3-D CAD software that measures thousands of cross-sections of each product to determine exactly how each layer is to be constructed’. Moreover, Chinese authors Chia and Wu (2015) reported, ‘3D Printing technologies are being used to fabricate tissue engineering scaffolds, emphasising the ability of these manufacturing technologies to pattern cells and multiple materials along complex 3D gradients’. Nowadays, a few healthcare units are using 3D printing technology. The manufacturing strategy increases the competence of manufacturing and develops capability in different areas such as human resource, production planning, organizational structure, process, technology and facilities (Patil et al., 2015). That is why the author Gunasekaran (1999) opined, ‘3D will help facility planners to visualize the system before constructing it, make alternative designs, program robot paths, obtain layouts for the systems, obtain data for the discrete event simulation, and develop the cell control program’. The future 3D printing applications are expanding to many fields. 3D printing is known as additive manufacturing.

Digital Twins Digital twins are precise, virtual copies of machines or systems (Tao & Qi, 2019). ‘Digital Twins’ is another sister technology in Industry 4.0. As the technology boosts operational efficiency in each operation by embeddedness, the digital twins also give the virtual image of the machine, materials, products and human being of that plant factory or plant in the centralised computer system. These virtual identities of the physical objects/process could help to monitor the people or processes during operations for better operational efficiency. There are some places/functional units/ floors in which human entry needs to be avoided. Originally developed to improve manufacturing processes, digital twins are being redefined as digital replications of living and nonliving entities that enable data to be seamlessly transmitted between the physical and virtual worlds (El Saddik, 2018). Digital twins represent natural

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objects or subjects with their data, functions and communication capabilities in the digital world (Schluse et al., 2018).

Robotics ‘Robots’, ‘robotics’ and ‘robotic process automation’ phenomena are other eye-catching concepts in this technological world. The idea is in both hardware as well as software type. The best examples are Sophia, an official Saudi Arabia citizen of Humanoid. While coming to text bots and voice bots, we are experiencing financial applications and insurance. The robotics industry has been booming exponentially globally, specifically in European countries, Japan, South Korea and the United States. Robotics has often used artificial intelligence (AI) devices in manufacturing units. As per the manuscript by Linner et al. (2014), ‘Ambient Robotics focuses on the co-adaptation and creation of compatibility in a physical and informational sense of assistive environments and service robot systems’. The authors Kehoe et al. (2015) also said: ‘The robots use wireless networking, big data, cloud computing, statistical machine learning, open-source, and other shared resources to improve performance in a wide variety of applications including assembly, inspection, driving, warehouse logistics, caregiving, package delivery, housekeeping, and surgery’. Even Brossog et al. (2015) authored how to reduce the energy consumption of industrial robots in manufacturing systems. Calitz et al. (2017) talked about the future African workplace and the use of collaborative robots in manufacturing. This technology can be used for routine tasks and human risky places. However, there are test cases of the use of robots in industries. Now robotics is taking into robotics process automation (RPA) and hyperactive automation forms for better business analytics. That is why Blue Prism, Anywhere Automation and Uipath and many more companies are investing heavily for industry operational efficiency.

Internet of Things Of course, it is one of the greatest disruptive technological phenomena that have been evaluated since the technology’s inception. The beauty of this technology is even connecting all the physical objects/things on the earth through various embedded intelligent technologies. The best example could be smart cards, QR codes, biometrics including human retina, EPC and GIS and GPS, to name a few. This has the capability of integrating all the isolated function technologies. The role of IoT technologies in manufacturing and supply chain or logistics tremendously increased recently. Sensor data from different machines, intelligent device material mixing in steel plants and chemical industries and heavy RFID usage in mining ores and GPS and GIS adoption in the transportation industry are the best industry applications. Because of IIoT technologies, manufacturing and logistics operations are simplifying with less cost, reducing time and leading to efficiency.

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Big Data Analytics Big data analytics, which is also shortly known as ‘BDA’, is another upcoming field throughout the technological world. That is why BDA is on everybody’s lips. Another reason is the gigantic applications in our day-to-day life, like weather forecasting, financial Sensex, IoT sensors data, e-commerce, medical diagnosis, recommendation systems, etc. Due to humongous IoT connections, continuous data generated from sensors, WhatsApp messages, social media blogs and e-commerce products and services information from different companies, to name a few, are leading to BDA. The BDA concept has capabilities for any business data, including manufacturing units. Because of its 4Vs characteristics (volume, variety, veracity, velocity), it can analyse data from different sources of multiple formats, generating TB/YB/XB/second. Verma (2017) opines, ‘The insights from BDA are used to direct, automate and optimize the decision-making to successfully achieve their organizational goals. Data management and Advanced Analytical techniques are some of the key contributors to making BDA possible’. Nowadays, in Industry 4.0, machines are connected as a collaborative community. Such evolution requires the utilisation of advanced prediction tools so that data can be systematically processed into information to explain uncertainties and thereby make more ‘informed’ decisions (Lee et al., 2014). The beauty of this technology is that it operates irrespective of the data type, i.e. un/semi/structured can also be analysed in a highly sophisticated manner. There are many tools used for BDA, including Pig, mongodB, Cassandra, Hadoop, Zookeeper, open JDK, Oozie, mahout, hive, Sqoop and many more technologies. Based on the application processing, the software can be used for big data analysis.

Cloud Computing Cloud computing is an online computational resource on rental basis from third-party vendors. The main advantages of cloud computing are cheaper, reliable, secure, scalable and services available round the clock. It reduces the ambiguity and confusion in budget and in-house technical staff for maintenance. Even small- and medium-size companies quickly escalate their business operations using cloud services. However, cloud computing is categorised into three kinds: (1) public cloud, (2) private cloud and (3) hybrid cloud. Cloud computing vendors can give three basic types of services: (1) Platform as a Service (Paas), (2) Infrastructure as a Service (IaaS) and (3) Software as a Service (SaaS). The leading IT giants that started offering cloud computing services are Amazon Web Services (Simple Storage Service: S3), Microsoft Azure, IBM Cloud, Google’s GCP (Google Cloud Platform), Rackspace, Verizon Cloud, GoDaddy and VMware, to name a few. These days, cloud technologies have become part of all kinds of manufacturing units and factories in a more significant way to boost the services around the clock. That is why the author Priyadarshinee et al. (2016) opine, ‘Cloud Computing is a model for convenient and on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider

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interaction’. Cloud computing is divided into public, private, hybrid and community clouds. Cloud technologies are ensuring in manufacturing units, all production processes are efficient by optimum data storage along with leading to valuable insights for decisions. However, Gangwar and Date (2015) mentioned, ‘Organizations should develop their information security using a precise and detailed planning process that ensures the right cloud computing acceptance by the users’. Consequently, it is expected that the number of projects, data and services over the infrastructure should have exponential growth. Therefore, cloud-based engineering systems can benefit the emergent Industry 4.0 in a big way, offering infrastructure, platforms and software among the partners (Camarinha-Matos et al., 2015). That is why ‘Cloud computing ecosystems of service providers and consumers will become a significant part of the way information services are provided’ as said by Pym and Sadler (2010). Therefore, manufacturing units had already started to use cloud computing services for their machine, materials and operational-related data storage for manufacturing excellence right from cloud technology inception. Thus, cloud computing plays a significant role in manufacturing for boosting production.

Industry 4.0 – Frameworks Frameworks are essential to understand any phenomenon. Still today, the empirically tested standardised ‘Industry 4.0’ models are a few. However, some of the tech giants like PwC, Frost and Sullivan, IBM and a few of the IT/ITeS industries have given some Industry 4.0 frameworks, consisting of different components, connectivity among members and data flow analysis (connectivity) during operations in manufacturing units with embedded advanced technologies. Besides, there is one good framework by the researcher, Zezulka et al. (2016), the RAMI 4.0 (Reference Architecture Model Industry 4.0) model. Another manuscript by Mittal et al. (2018) explored a critical review of intelligent manufacturing and Industry 4.0 maturity models: Implications for SMEs. These models will give a glimpse of Industry 4.0. The following section has discussed three frameworks: (1) PricewaterhouseCoopers (PwC) Industry 4.0 Framework, (2) Global Electronics Industry 4.0 Solution Lead at IBM and (3) M/s. Frost & Sullivan – Framework. As per Reinhard et al. (2016), the three essential things about the ‘Industry 4.0’ strategy are driven by the PricewaterhouseCoopers (PwC) analytical report, as shown in Fig. 17.4. The Industry 4.0 phenomenon can be viewed in three layers. The innermost layer (core business operations) is again divided into three parts: (1) Digitisation and integration of vertical and horizontal value chains, which means the supply chain process of getting raw material from different suppliers (Supplier 1; Supplier 2, Supplier3,. . .Supplier.): through supply chain management (SCM) best practices. Besides, ordering products online, financial transactions and delivery on time to end customers via customer relationship management (CRM) software, (2) Digitisation of product and service offerings and (3) Digital business models and customer access. The second layer (data)

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Fig. 17.4. Industry 4.0 Framework and Contributing Digital Technologies. Source: Obermayer et al. (2022).

covers data analytics as an essential capability for any manufacturing unit; data is continuously generated from different IoT devices, sensors and machines that need to be analysed with machine learning algorithms. The third layer (applications) discusses devices, technologies and apps for machine operations. These technologies could be IoT platforms, location detection, advanced machine– human interaction, mobile devices, sensors, authentication and fraud detection based on manufacturing type. Of course, 3D, augmented reality, wearable devices, cloud technologies, multilevel customer interaction and advanced algorithms are inevitable in manufacturing units nowadays.

Global Electronics Industry 4.0 Solution Lead at IBM The author Deng (2016) has proposed an Industry 4.0/smart manufacturing solution lead at International Business Machines. The Industry 4.0 framework has been outlined in Fig. 17.5. The author explains that the ‘Industry 4.0’ phenomenon continuously generates full connections-cum-relations with all the stakeholders, from end-customers to manufacturers. As per the author’s observations, the ‘Industry 4.0’ framework is divided into three enablers. Industry 4.0 can have a first enabler of the digital supply chain. Digital supply chain may include collaborative planning, plug-and-play logistics, intelligent procurement and Factory 4.0. Where as smart product and services consists of strategic enabled ecosystems, connected products, customer-driven engineering and service

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Fig. 17.5.

Qin Deng’ Industry 4.0 Framework. Source: Dagnaw (2020).

analytics. In contrast, productive customer insights include functions of omnichannel enablement, demand sensing, shopping, intelligent marketing and social media analytics. All these procedures are backed by different advanced technologies, including IoT, intelligent computing, RPA, hype automation, 3D printing, etc. These industrial internet technologies will become part of every manufacturing process for machine-optimised decisions. Additionally, the author also intensified intelligent manufacturing by leveraging the latest technologies. Due to ‘Industry 4.0’, productivity has been significantly improving, with a quality defect rate dropping, control and flexibility on the shop floor improving along with a reduction in manufacturing cost.

M/s Frost & Sullivan – Framework M/s Frost & Sullivan developed a model/architecture for Industry 4.0. As per the Frost & Sullivan model or framework, Industry 4.0 consists mainly of three

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components, including technologies, collaborations and processes. First, we explain the industry process and collaborations. These two components exist almost right from industrialisation. Moreover, as with the Frost & Sullivan Framework, the business process should concentrate on the latest on Internet of Services (IoS), Life Cycle Assessment (LCA) and, more importantly, sustainable manufacturing practices, including cleaner technologies and green products and corporate social responsibility. Moreover, collaboration requires both horizontal and vertical integration industries, Internet Protocol (IP) centralisation, and especially collaborative social innovations (Living Lab Experiments) to ensure better manufacturing systems. All the factory machines, materials and objects are tagged with a smart identification strategy. This collaborative industrialisation will lead to social innovation through integrated industry mechanisms and IP centralisation of machines. The final dimension is ‘technology’. The technologies are deployed at the respected shop floors in manufacturing units. The current disruptive technologies that are adopted by most of the manufacturing industries are the IoT, Web of Things Cloud Computing, Data Analytics (BDA) Intelligence wireless technologies, etc. Moreover, the technologies can help workers around the clock, availability of services in manufacturing units and prevention of human risks.

Conclusion The technologies like the Web of Things (IoT), Sensors, RFID, QR codes, AI, neural networks, humanoid robotics, cloud technologies, BDA, etc. implementation levels at shop floors and other manufacturing units in global manufacturing hubs are trying to improve the operational efficiency 24/7 under Industry 4.0 phenomenon. This will boost the production in the industries in a significantly bigger way. Hence, the automobile firms, steel industries, shipyards, airports, pharmaceuticals, minerals, steel, chemical plants, etc. are going to reap an enormous benefit. That is why, now people are talking not only about Industry 4.0 but also the upcoming sister notion of Industry 4.0; the Fifth Industrial Revolution (Industry 5.0) is growing very fast across all manufacturing factories.

Future Scope The embedded IoT makes things very simple, easy operations, round the clock services and comfortable human life. Efforts have to be piled up towards the planning, designing and implementation of this noble phenomenon. In future, empirical studies have to be carried out in firms that are already utilising Industry 4.0. This will help to add practical evidence to the literature in this area, making things elementary, easy operations, round-the-clock services and comfortable human life. Efforts have to be piled up towards the planning, designing and implementation of this noble phenomenon. In future, empirical studies have to be carried out in firms that are already utilising Industry 4.0.

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Chapter 18

Application of Industry 4.0 Technologies in Climate-Smart Agricultural Practices Soumya Sucharita Panda, Sudatta Banerjee and Swati Alok

Abstract The United Nations (UN) adopted Sustainable Development Goals (SDGs); agenda 2030 focuses on Climate Action (goal 13), targeting climate adaptability, as well as resilience, awareness and improving policy mechanisms on climate change. In order to enhance climate adaptability, climate-smart agricultural practices (CSAP) is a necessary step. CSAP is a sustainable agriculture approach with a strong focus on climate dimensions. The three pillars of climate-smart agriculture (CSA) are ‘Adaptation’: adapting to climate change; ‘Resilience’: building resilience against it and ‘Remove’: reducing carbon emissions. The new world economy uses Industry 4.0 technologies for sustainable advancement, including blockchain technology, big data analytics, artificial intelligence (AI), augmented and virtual reality, industrial Internet of Things (IoT) and services. Hence, technology plays a significant role in climate sustainable agriculture practices. This chapter shall consider three technologies consisting of IoT, AI and blockchain technology which contribute to CSAP in pre-harvesting (monitoring climate as well as fertility status, soil testing, etc.), harvesting (tilling, fertilisation, seed operations, etc.) and post-harvesting (predicting weather factors, seed varieties, etc.) periods of agriculture. All these three technologies work like the human nervous system; IoT helps in converting various information regarding demography, climate change, local agricultural needs, etc. into world data; AI works like a brain in combination with IoT, helps predict the use of climate-smart technology and blockchain, the memory part of the nervous system which deals with supply-side and ensures traceability as well as transparency for consumers as well as farmers. Hence, this chapter shall contribute to the importance of these three technologies in adopting CSAP in three stages of agriculture.

Fostering Sustainable Development in the Age of Technologies, 289–302 Copyright © 2024 Soumya Sucharita Panda, Sudatta Banerjee and Swati Alok Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231020

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Keywords: Industry 4.0; climate-smart agricultural practices; adaptation; Internet of Things; artificial intelligence; blockchain technology

Introduction The advent of the twentieth century has brought forward various technological advancements in agriculture concerning climate change adversities. An increase in demand for food due to the increasing population in the world has emerged with increasing demand for technology which ultimately contributes to Sustainable Development Goals (SDGs). The United Nations Sustainable Development Goals (SDGs), with its prime objective of establishing peace and prosperity, focuses on various aspects of development. All the 17 goals, along with 169 targets, depend on technological advancement in some way or the other. Hence, for the SDG targets to be met, from ending poverty to enhancing food security to reversing climate change, technology development, innovation and the production of groundbreaking solutions are essential. Technology always helps in utilising limited resources to maximise output. The Global Hunger Index shows a moderate decrease, from 19.1 in 2014 to 18.2 in 2022. Still, the condition is worse because around 828 million people were found to be undernourished in 2021. As per UN Food and Agriculture Organization (FAO), one in three people is undernourished globally. The report from Global Hunger Index 2022 says that South Asian countries are showing the highest hunger level, with India having the highest child-wasting rate (19.3%) and India, Pakistan and Afghanistan having the highest child stunting rate. The reasons include increased world food prices, poverty, conflict in the state and non-state-based activities and an increase in temperature leading to extreme climate vulnerability, affecting agricultural production. Hence, the United Nations Sustainable Development Goals agenda 2030 need advanced technological implications in agriculture to achieve goals like zero hunger (goal 2), good health and well-being (goal 3), affordable clean energy (goal 7) and climate action (goal 13). Increased food production with limited sources using advanced technology will help satisfy the SDGs’ zero hunger goal. Similarly, ensuring traceability using digital technology in agricultural production will help achieve the third goal of SDGs. Recycling and managing food waste using technology will help achieve affordable clean energy, which is the 13th goal. Increasing awareness of using digital technology like smartphones and use of climate-smart agricultural technology will help achieve the 13th goal of SDG. Intergovernmental Panel on Climate Change (IPCC) 2022 report states that climate variability can be a stumbling block in achieving the zero hunger goal of sustainable development. This chapter will deal with the application of Industry 4.0 in agricultural practices to adapt and mitigate climate change in agriculture. This adaptation and mitigation of climate variability through various agricultural practices as per the need of climate is otherwise known as climate-smart agricultural practices (CSAP). CSAP approach is one of the distinguished approaches launched by FAO in 2010 under the Mitigation of Climate Change in Agriculture (MICCA) programme. Its

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Plan of Action was presented at Climate Summit in 2014. This approach was first implemented in Zambia, Malawi and Vietnam, which resulted in detecting various problems in the adoption of CSAP and helped in framing policies and coordinating institutional arrangements; other partner countries got benefited due to workshops for capacity building. CSAP is a dynamic approach that combines various adaptation and mitigation practices depending on location, knowledge and awareness (Chandra et al., 2018; Neufeldt et al., 2013). CSAP was developed to capture climate change adaptation and mitigation measures for achieving sustainable development and food security. It is a tool that provides climate-based solutions to agricultural productivity and food security and its effects are measured based on its implementation into sustainable development in agriculture (Lipper & Zilberman, 2018). The word climate-smart justifies that the practice should involve climate conditions as the primary dimension. Various countries have adopted the CSAP approach as per their requirements. For example, Bangladesh adopted a project to enhance resilience for livestock; China focused on rice production and reduced greenhouse gas (GHG) emissions; Uruguay adopted CSAP to improve soil-management capability and energy efficiency; and Maharashtra in India also adopted CSAP projects which benefitted farmers with improved irrigation and drainage technologies (World Bank, 2021). With its varied climatic condition, India needs climate-focused technology to be involved in attaining the goals of CSAP. The key dimensions of climate-smart agriculture (CSA) are weather-smart, energy-smart, nutrient-smart, carbon-smart, water-smart and knowledge-smart (Bhattacharyya et al., 2020). These dimensions will work as per their needs, which means the difference in climatic needs will decide the type of smart agricultural practice to be followed. This chapter is further subdivided into several sections, such as the introduction of Industry 4.0 and different technologies that contribute to agriculture, the use of these technologies in different stages of agriculture and, finally, the contribution of Industry 4.0 towards converting agriculture into CSA. Hence, this chapter has been designed to illustrate the application of three major Industry 4.0 technologies such as artificial intelligence (AI), Internet of Things (IoT) and blockchain technology in agriculture to transform it into smart-agriculture with a successful case study of ITC.

Industry 4.0 Industry 4.0 is the latest technological advancement known as the Fourth Industrial Revolution. The first three industrial revolutions significantly impacted industrial operations, enabling productivity and efficiency by utilising revolutionary technological advancements like the steam engine, electricity and digital technology (Schuh et al., 2013). Industry 4.0 has emerged with various digital innovations like the IoT, big data, blockchain, AI, robotics and many other smart technologies. This industrial revolution has transformed the whole economy into a digital economy, from agriculture to the manufacturing industry. Technological advancements have transformed almost all sectors to achieve development in terms of production, consumption and distribution. The transformation of

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technology-use due to the advent of Industry 4.0 encouraged the focus on “customer centricity”, emphasising the value of the consumer and environmental sustainability (Zheng et al., 2021). In this chapter, we shall consider IoT, AI and blockchain technologies contributing to CSAP.

Artificial Intelligence AI works like human intelligence in predicting, tracking and tooling. Predicting demand, climatic and other production dynamics helps lower the cost of production and maintain the product’s value chain. Similarly, tracking problems related to production, manufacturing of the product and any other problems, including lack of skill, etc. helps to decrease the cost and enhance awareness about the production process. Tooling the efficiency to control and survive the climate impact is a key feature of AI (Javaid et al., 2022).

Internet of Things The IoT basically talks about things that the internet can control. Daily use objects like home appliances, smart devices, vehicles, etc. which can be readable, traceable or monitored through the internet are known as the IoT (Patil et al., 2012). IoT helps collect and analyse data in the fields like agriculture, industry, health sector, etc. and the obtained data can be utilised using other Industry 4.0 technologies like big data, cloud computing, etc. (Georgios et al., 2019).

Blockchain Technology Blockchain is a logbook in which different blocks keep recording information during transactions. It works with peer-to-peer networking without needing an intermediary (Xiong et al., 2020). In other words, it can be referred to as a digital ledger that is used to record various information interactions across many computer systems, thus assuring cyber security.

Agriculture and Technology 4.0 As per World Bank data 2019, 27% of total employment in the world is employed in agriculture. The 2020 data shows that male labour force participation in agriculture is 27.6% of total male employment, whereas, for females, it is 25.3%. In the case of developing countries like India, female employment mainly relies on agriculture, i.e. 54.7% of total female employment is working in the agriculture sector. Agriculture in most developing countries depends on labour-intensive techniques that need time, skill, resource availability, awareness, etc. The current world has become digitalised due to the use of technology in almost all spheres of life. Mobile technology has brought a revolutionary change in the current world, combining the whole world into a single device. The use of technology in agriculture will help mitigate the problems like lack of resources, lack of

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awareness and information and maintaining sustainability for the future (Berawi, 2019). Agricultural digitisation implies a paradigm shift that will lead to both on-farm and advancements away from farms.

Use of Artificial Intelligence Technology in Agriculture AI plays a significant role in agriculture. It has a massive use in agriculture as it provides a digital solution to various problems in agriculture. It is used in almost all agricultural production stages, from land preparation to final production and further post-production decisions. The use of AI in agricultural decision-making regarding crop management, climate change adaptation and price and weather forecasting plays a vital role in agriculture (Liu et al., 2020). The use of AI has been described more precisely in Table 18.1. Table 18.1 summarises various literature regarding the use of AI in agriculture. The table shows that various AI technologies and models can be used to meet various demands of agriculture. The pre-harvesting knowledge, information and decision significantly impact the whole agricultural value chain. It includes pre-existing knowledge about climate, availability of resources and land preparation. AI uses various technologies, like drones and other image sensors, to have a clear picture of the field using field mapping through these technologies (Dharmaraj & Vijayanand, 2018; Saxena et al., 2020). Additionally, various AI models like MOM, Fuzzy Logic: SRC-DSS, an ANN, etc. are used to collect data regarding soil structure, water necessity, etc. (Eli-Chukwu, 2019). AI gives producers or farmers a clear picture of the field and other input necessities. AI plays a vital role during harvesting, which includes irrigation, crop management, crop health management, etc. The use of AI technology like remote sensing and 3D laser scanning for crop health monitoring (Dharmaraj & Vijayanand, 2018) helps in measuring the growth of crops over the period, and it covers acres of cultivable land which reduces the cost of production. AI collects information regarding crop management, irrigation, disease detection and weed management using various sensors, then use different AI modelling to analyse the problems. AI models like POMME, COTFLEX, COMAX, etc. are used for crop management; text-to-speech (TTS) converter, Fuzzy Logic (FL), Web GIS, etc. are used for crop-disease management; SMARTSOY are used for pest management; and ANN, GA, UAV, SVM, DIA and LVQ are used for weed management (Bannerjee et al., 2018; Eli-Chukwu, 2019; Sharma, 2021). The post-harvest period in agriculture deals with product monitoring, storage of the product, price forecasting and prediction for further crop yield. AI-based sensor technology manages the post-harvest value chain or the supply chain. It uses agricultural predictive analytics technology to predict about the crop, climate, crop pricing, etc. (Liu et al., 2020). The AI models, like the fuzzy logic-based model and ANN, are used to monitor the final product and its storage (Bannerjee et al., 2018) after the harvesting is done.

Table 18.1. Use of AI in Various Agricultural Activities.

Field Analysis

Type of Technology/ Model-Use

Drones

Scanning of Drones fields Mapping of Drones field Prediction MOM, about soil Fuzzy logic: SRC-DSS, ANN

Agricultural Activity

Monitoring crops, disease detection or crop health detection Disease detection or crop health detection Identifying crop maturity Crop management

Pest management Irrigation management Weed management

Post-Harvesting Type of Technology/ Model-Use

Remote sensing and 3D laser scanning Remote sensing and 3D laser scanning White light and UVA light POMME, COTFLEX, COMAX

Agricultural Activity

Type of Technology/ Model-Use

Agricultural product monitoring and storage Crop yield prediction and price forecasting

Fuzzy logic-based model, ANN Agricultural predictive analytics

SMARTSOY, Drone technology Fuzzy logic-based model, ANN ANN, GA, UAV, SVM, DIA, LVQ

Source: Dharmaraj and Vijayanand (2018), Saxena et al. (2020), Eli-Chukwu (2019), Sharma (2021) and Liu et al. (2020). Note: ANN: Artificial Neural Network; UVA: Ultraviolet A; MOM: Management-Oriented Modelling; SRC-DSS: Soil Risk Characterisation Decision Support System; POMME: Pests and Orchard Management Expert; COTFLEX: Cotton Farm Level Expert; COMAX: Crop Management Expert System; SMARTSOY: Soybean Insect Pest Management Expert System; GA: Genetic Algorithm; UAV: Unmanned Aerial Vehicles; SVM: Support Vector Machines; DIA: Digital Image Analysis; LVQ: Learning Vector Quantisation.

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Agricultural Activity

Harvesting

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Pre-Harvesting

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Use of the Internet of Things in Agriculture The word IoT itself justifies the use of the internet in this technology, and it has a significant role in digitalising agriculture using its various forms. It works as a data logger, processor and transmitter using internet-abled things or objects. It basically makes everything digital. IoT works from connecting data with big data networks and detecting the changes in data to processing and providing results from analysed data (Zhou & Zhou, 2012). The different technologies of IoT used for different agricultural activities are summarised in Table 18.2. Table 18.2 describes the use of IoT technology in various agricultural activities. IoT works in layers that contain a collection of knowledge and information for an application or use of the information. At the stage of pre-harvesting, to collect information regarding climatic inputs like pressure, humidity, temperature, etc. IoT uses Radio Frequency Identification (RFID), UWB, NFC, WiFi and cameras. It uses Wireless Sensor Network (WSN), Ad hoc network, coordination treatment technology and middleware technology for data processing and transmission. For data transmission, it uses mobile communication, wireless local area networks (WLAN), satellite communication networks, GPS, Bluetooth, etc. Finally, in the application of processed information in the form of disaster monitoring, IoT is used in combination with cloud computing and peer-to-peer middleware technology (Verdouw et al., 2016; Witjaksono et al., 2018). The harvesting phase needs various sensors to detect crop growth, crop health, monitor irrigation, etc. IoT uses different technologies for different activities during harvesting. IoT uses cameras, GPS sensors, terminals, cable networks, sensor networks and wireless networks (Patil et al., 2012) for measuring agricultural growth status, including crop growth, the need for inputs and location of the products. For crop monitoring, i.e. crop health, disease detection of the crop, etc., IoT uses Node MCU that contains sensors like temperature sensors, soil moisture sensors, air quality gas sensors and soil moisture sensors, which also helps to make irrigation digital (Kumar et al., 2021; Singh, 2019). The use of sensors to detect the need for water and control water use as required can be termed digital irrigation. Mobile phones play a major role in digital irrigation. Post-harvesting phase includes food supply and management. Post cultivation, the product needs storage, safety and waste management. IoT uses various technologies to manage food transparency and traceability. It uses RFID technology to manage food traceability (Patil et al., 2012). For consumers, IoT is a hub of information, which means information regarding raw materials, processing, and packaging till pricing-related information can be provided to the consumers using EPC tags (Zhou & Zhou, 2012).

Use of Blockchain Technology in Agriculture Blockchain technology is an important technology used in all stages of agriculture, from pre-plantation to the final product’s consumption. Ethereum and Hyperledger are considered to be two major blockchain technologies that are used

Agricultural Activity

Climate information

Harvesting Type of Technology/ Model-Use

UWB, RFID, NFC, WiFi and cameras

Agricultural Activity

Agricultural working status

Crop monitoring Digital irrigation

Type of Technology/ Model-Use

Cameras, GPS sensors, terminals, cable networks, sensor networks and wireless networks Node MCU

Post-Harvesting Agricultural Activity

Type of Technology/ Model-Use

Food traceability RFID

Product information to consumers

EPC tags

Node MCU, Mobile phones

Source: Patil et al. (2012); Witjaksono et al. (2018); Verdouw et al. (2016); Zhou and Zhou (2012); Kumar et al. (2021); Singh (2019) Note: UWB: Ultra-Wide Band: RFID: Radio Frequency Identification; NFC: Near field communication; GPS: Global Positioning System; MCU: Micro Controller Unit; EPC: Electronic Product Code.

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Table 18.2. Use of IoT in Various Agricultural Activities.

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in combination or separately in different stages of agriculture, like planting, processing, manufacturing, retailing, etc. (Xiong et al., 2020). This technology uses IoT and other Industry 4.0 to give a better result. For example, in combination with IoT, blockchain ensures food traceability, increases food safety and reduces food waste (Hassoun et al., 2022). Hence, the purpose of blockchain technology is to collect information about the agricultural product at each stage of production and provide peer-to-peer information to producers and consumers with the help of IoT. In short, food safety, transparency in information regarding food, food traceability and waste management are the significant outputs of the use of blockchain technology along with IoT and AI.

Climate-Smart Agricultural Practices and Industry 4.0 Technology Agriculture is going through extreme circumstances like a high population with more demand and lack of resources, climate vulnerability, etc. which need to be mitigated. Agriculture, a climate-dependent sector, always needs integrated practices to be used to tackle the problems related to climate change and enhance production. The fourth revolution of the industry has introduced digital technologies in almost all sectors of the economy, and agriculture is one of the technologically deprived sectors in most developing countries. The term CSA describes the importance of climate-related information and activities in agriculture (Branca et al., 2011). Hence, pre-existing knowledge about climate and information about the existing climate condition need special attention before harvesting. The key dimensions of CSA are weather-smart, energy-smart, nutrient-smart, carbon-smart, water-smart and knowledge-smart (Bhattacharya et al., 2020). These dimensions will work as per their needs, which means the difference in climatic needs will decide the type of smart agricultural practice to be followed. All these smart dimensions need digital technology to be incorporated into agricultural activities, incorporating climate into the agricultural context. Industry 4.0 technologies, which work like the human nervous system, i.e. IoT helps in converting various information regarding demography, climate change, local agricultural needs, etc. into world data; AI works like a brain, in combination with IoT helps in predicting the use of climate-smart technology and blockchain, memory part of nervous system which deals with supply-side and ensures traceability, as well as transparency for the consumers as well as farmers, will help in the adaptation of CSA.

Pre-Harvesting All three technologies have a significant role in making agriculture climate-smart. As discussed above, information about climate factors like humidity, temperature, pressure, etc. using AI and IoT techniques help agriculture be climate-smart in weather forecasting. Apart from that, soil analysis, field preparation and information (using drone, MOM, Fuzzy Logic: SRC-DSS, ANN) about the

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resource availability before cultivation will help make the agriculture knowledge-smart using AI techniques like drones, image-based sensors, etc.

Harvesting During harvesting, the use of technologies, especially in monitoring cultivation, is a necessary step to be taken. Smart irrigation using IoT, i.e. mobile phones and water sensors, makes agriculture water-smart. Whereas crop disease monitoring, pest detection and nutrient-level detection using AI techniques like robotics, computer and machine learning (ML) and Fuzzy Logic models (Saxena et al., 2020) help make agriculture nutrient-smart. Similarly, crop growth monitoring using white/UVA light and field mapping to understand fertiliser and water requirements using drones and copter systems are the forms of AI technology (Saxena et al., 2020) in agriculture that makes it energy-smart.

Post-Harvesting The post-harvesting stage deals with the food supply chain, i.e. food storage, marketing, information about the market, transport of food, food tracking, etc. In the case of product supply chain management, blockchain technology plays a vital role. In combination with IoT, it ensures food traceability, reduces fraud in food-related information using EPC tags and provides peer-to-peer information with no data trap. These additional features of Industry 4.0 technology make agriculture knowledge-smart. Besides that, blockchain and AI provide various digital platforms for farmers to get cost-effective markets for their food exchange. This also makes them knowledge-smart. In all three phases of cultivation, AI, IoT and blockchain technology helps agricultural practices to become climate-smart. With the help of various digital inputs, these technologies are considered to be the stakeholders of CSAP.

A Case Study: Use of Technology in Agriculture ITC E-Choupal: Promoting Climate-Smart Agriculture ITC, a private company, is establishing ITC E-Choupal in order to connect the local market with the global market. It has a vision of reaching each mandi or local market without a middleman and empowering farmers globally. The E-Choupal has recently introduced its website (echoupal.com) with information and assistance about farming and product markets in multiple local languages in India. In order to make use of this facility, ITC has recruited ITC-trained Sanchalaks, who will be the helping hand of farmers using ITC. Three important jobs of the sanchalaks are to help people understand the computer languages, help the farmers assess information about the market and prices of products and evaluate the sample products to make them aware of the prices and marketing of their produce. Sanchalaks also provide information about weather pattern, soil condition, use of fertilisers, type of seed to be used, etc., which helps farmers to adapt

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CSAP and increase productivity. It has also created a market hub of E-choupal called Choupal Saagars. Choupal saagar works as an alternative to mandi using smart facilities. It’s a kind of mandi where farmers can weigh their produces, sell them and get payment easily, which means this alternate mandi also helps farmers save time (Farhoomand, 2008). This case study gives an idea of using smart technology to make farmers knowledge-smart. The use of IoT and AI in E-Choupal helps farmers acquire information and get cost and time-saving markets.

Conclusion This chapter summarises the use of Industry 4.0 technologies in agriculture to make it CSA. The technologies used here are AI, IoT and blockchain technology. With the help of existing literature, this chapter tried to categorise the type of technology used for different agricultural activities into three parts, i.e. pre-harvesting, harvesting and post-harvesting phases of cultivation. We found that these three technologies are intertwined to accelerate the process of agriculture. They started with AI, which is a hub of information and knowledge. With its different techniques and models, AI collects information that is processed using various objects of the IoT. Blockchain technology, combined with IoT, helps provide the processed information to the farmers or other stakeholders in a peer-to-peer manner. Hence, these technologies play a vital role, starting from land preparation, weather awareness, cropping, crop monitoring, disease detection and water management to manufacturing and selling the product. Some findings were found to be interesting when the technological inputs were summarised into CSAP. The technology-advanced agricultural practices can make agriculture weather-smart using its forecasting techniques, knowledge-smart using platforms that aware the stakeholders regarding the products, energy-smart by soil as well as fertiliser monitoring, nutrient-smart using technologies for identifying crop diseases, pest management, nutrient deficiency and water-smart using digital sensors for irrigation like mobile phones. Hence, the use of Industry 4.0 technology in agriculture helps to adapt CSA. The above case study is an example of the use of technology in agriculture. The finding shows that a small initiative of E-Choupal helped many farmers to get awareness of marketing their products cost-effectively. Hence, the study suggests that incorporating technology not only in the marketing of farming products but also in various stages of agriculture may help meet the needs of the growing population and help achieve the SDGs. The use of Industry 4.0 in agriculture can help attain the goals of CSA adaptation. The policy implications could be decentralised into developing nations through research and development, awareness programmes, and incentivising in the initial stages.

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the Society of Instrument and Control Engineers of Japan (SICE) (pp. 1514–1519). IEEE. Tumiwa, J. R., Tuegeh, O., Bittner, B., & Nagy, A. (2022). The challenges to developing smart agricultural village in the Industrial Revolution 4.0.: The case of Indonesia. Torun International Studies, 1(15). Verdouw, C., Wolfert, S., & Tekinerdogan, B. (2016). Internet of Things in agriculture. CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, 11(35), 1–12. Witjaksono, G., Rabih, A. A. S., bt Yahya, N., & Alva, S. (2018, March). IOT for agriculture: Food quality and safety. In IOP conference series: Materials science and engineering (Vol. 343(1), p. 012023). IOP Publishing. Xiong, H., Dalhaus, T., Wang, P., & Huang, J. (2020). Blockchain technology for agriculture: Applications and rationale. Frontiers in Blockchain, 3, 7. Zheng, T., Ardolino, M., Bacchetti, A., & Perona, M. (2021). The applications of Industry 4.0 technologies in manufacturing context: A systematic literature review. International Journal of Production Research, 59(6), 1922–1954. Zhou, Z., & Zhou, Z. (2012, December). Application of Internet of things in agriculture products supply chain management. In 2012 International Conference on Control Engineering and Communication Technology (pp. 259–261). IEEE.

Chapter 19

The Digital Revolution – Implications of Digital Technologies on Women’s Workforce Participation Tanaji Pavani Prabha, Swati Alok, Rishi Kumar and Swati Singh

Abstract Economies and societies are not digitally isolated. Digital technologies are widely recognised as key drivers of information dissemination, knowledge sharing, income and employment. Digital technologies also influence the interlinkages of digitalisation, gender and labour market outcomes. Digital technologies impact every sphere of day-to-day life. It impacts ways of communication, trade and business; influences networking abilities; shapes societal norms, attitudes and behaviours. It is hence argued that digital technologies may have crucial implications for women’s participation in the workforce. Gender equality and increasing women’s workforce participation is an important goal under the United Nations Sustainable Development Goals (SDGs). Research indicates that women are mainly involved in agricultural work, blue-collar formal work, while collar formal work, and entrepreneurship. Digital technologies significantly impact the ways of working in all these sectors. Consequently, it is argued that digital technologies influence women’s participation across all such types of work. This chapter aims at unravelling the linkages between digital technologies and women’s workforce participation. To this end, the influences of digital technologies on women’s participation in agricultural work, blue-collar formal work, white-collar formal work and entrepreneurship are discussed. The implications and impacts of the use of broadband, internet and mobile technologies are also discussed. This chapter also includes important theories of women’s workforce participation and discusses them in light of digitalisation. Keywords: Digital technologies; digital gender divide; gender ratio; sustainable development; ICT; women workforce participation Fostering Sustainable Development in the Age of Technologies, 303–318 Copyright © 2024 Tanaji Pavani Prabha, Swati Alok, Rishi Kumar and Swati Singh Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231021

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Introduction India is emerging as the fastest-growing major economy in the world. Soon would be one of the top three economic powers globally over the next 10–15 years. The universal experience reflects the role of women in boosting economic conditions. It is evidenced that a 10% increase in women’s participation would lead to increased opportunities for a potential Gross Domestic Product (GDP) rise of more than 70% (Woetzel et al., 2015). Globally, the women workforce participation rate is just 50% whereas for men it is 80% as per the World Bank data report 2022. The gender gap remains high in South Asia. Labour force participation is recorded as economically active including both employed and unemployed women looking for jobs. As per the Ourworldindata, Indian female labour force participation of all ages ranging between 15 and 651 years is 139.74 million. Unfortunately, the percentage of the participation rate in India has been gradually decreasing which was above 30% until 2006 and has fallen to 19.23% in 2021 and has been ranked 171 out of 181 countries in female labour force participation rate (Ortiz-Ospina et al., 2018). As per the Global Gender Gap report 2022, Indian female labour force participation has shrunk by -3% points since 2021. However, the participation of women as legislators, managers and senior officials has increased from 14.6% to 17.6%. The participation of technical and professional workers increased from 29.2% to 32.9%. Firms with female top managers are 8.90% and with a female majority, ownership is 2.80%. Per capita income would rise by 20% by 2030 if there is a balance between the paid women’s employment rates and paid men’s employment rates (Mehrotra & Sinha, 2019). Women are found in almost all the sectors of the formal and informal economy like agriculture, blue-collar workers, white-collar workers and entrepreneurship. However, the greater percentage of women-paid jobs is present mostly in blue-collar jobs with nil job protection (Onyechi & Ukwueze, n.d.). Indian women working age population is estimated to grow by 18.6% of the global workforce by 2027. It becomes important to increase the women’s working population, especially in the managerial cadre because women’s participation at the junior management level was found to be 16%, while at middle and senior levels was 4% and only 1% in organisational leadership positions like CEOs (Misra & Sirohi, 2019). On the other hand, achieving gender equality in all aspects (education, decent work, decision-making processes, etc.) is treated as one of the Sustainable Development Goals (SDGs) that would boost sustainable economies and in turn benefit society. Gender equality is not only a human right but also acts as a foundation for a sustainable world. Despite a rise in the schooling of girls, a decline in fertility and high economic growth female labour force participation rate is decreasing. However, enhancing skills along with digital literacy boost women’s labour force participation (Mehta et al., 2022). Mobile and web-based training enables women to gain self-paced skills and home-based activities which would lead to socio-economic advancement and in turn lead to growth in the productivity of the country. Against this backdrop, this chapter is structured as

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follows: the text presents the theoretical background and a brief discussion on existing work on workforce participation. This is followed by a discussion on the role of digitalisation in increasing women’s workforce participation in blue-collar jobs, white-collar jobs, the agriculture sector, entrepreneurship and digital entrepreneurship. In the next section, theoretical, managerial and policy implications of the use of digitalisation in increasing women’s workforce participation are discussed. Finally, this chapter concludes by highlighting the future research agenda.

Theoretical Background and Existing Literature on Women’s Workforce Participation The human capital theory claims that education is a predictor of employment outcomes (Chaudhary, 2021; Waynor et al., 2018). At the same time, the U-shaped relationship between education and women’s labour force participation has been emphasised. This represents that illiterate women are more inclined towards labour participation as compared to those of pre-primary, primary and middle education levels, and women with the highest education levels are much more inclined (Afridi et al., 2019). Similarly, skill levels also play a significant role in women’s participation. Providing training at all levels of education would be an added advantage to increase the skill levels and thereby increase women’s participation (Chaudhary, 2021). This is also enhanced by the optimistic vision of the future by women, family support, high self-efficacy (Alok et al., 2021) and positive and favourable relationships with male workers (Dukhaykh & Bilimoria, 2021). An employed woman would employ 1.3 people more (Misra & Sirohi, 2019), so it is no surprise that women’s empowerment and gender equality are prioritised under SDGs.

Barriers to Women’s Workforce Participation We used Scopus for articles published from 2015 to summarise this section as shown in Table 19.1.

Women’s Workforce Participation and Sustainable Development Goals (SDGs) Sustainable development and growth can only be ensured with inclusive empowerment and development. Women empowerment, gender equality and equal opportunity to education and work thus drive sustainable development. Women’s workforce participation is linked to two SDGs, viz SDG 5: gender equality and SDG 8: decent work and economic growth. SDGs launched by the United Nations (UN) in the 2030 Agenda for Sustainable Development (UN, 2015) acknowledge the crucial role of women in achieving all SDGs. Goal 5 however is specifically dedicated to women. SDG 5 focuses on gender equality through legal and legislative changes on one hand and

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Table 19.1. Barriers to Women’s Workforce Participation. Author and Year

(Avolio & Ch´avez, 2023) (Rimkute & Sugiharti, 2023) (Endow & Dutta, 2022; Sinha, 2022)

Barriers

Gender roles and stereotypes Small children

Lack of skills, gender-biased business hierarchy, social norms around work, cultural norms ability to balance the burden of domestic and care work responsibilities. (Cislaghi et al., 2022) Increased cost of hiring women, hierarchical gender order, maternal and institutional factors, social factors (Nikore, 2022) Covid-19, gender digital divides, the lack of institutional support at workplaces, the increased burden of unpaid domestic work and mobility restrictions (Menon & Nath, 2022) Low job-finding rates (Diab & Hindy, 2022) Scarcity of public nurseries and the unavailability of safe transportation (Dukhaykh & Bilimoria, Women’s underestimation by men, women’s 2021) social rejection at workplace, lack of access to resources, workplace location (Jayachandran, 2021) Harassment and violence towards women, restrictions on women’s social interactions and movement, control over household finances, intimate partner violence and who should be the family breadwinner, responsibility for household chores and child care. (Finlay, 2021) Early childbearing and lone motherhood continue to poverty (Amulya & Kumar, 2020) Marriage, not able to compete with a skilled workforce, education, ambition (Deshpande & Kabeer, Marriage, primary responsibility for domestic 2019) chores, gender division of unpaid labour, unmet need for paid work among women outside the labour force (Mehrotra & Sinha, 2019) Mechanisation in agriculture, reduction in international demand for products where women’s labour participation was relatively high,

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Table 19.1. (Continued) Author and Year

Barriers

limited cr`eche facility and accommodation facility. (Misra & Sirohi, 2019) Personal capabilities, organisational policies, perceptions, societal factors, restrictions in participating in leadership roles (Klasen, 2019) Historical barriers, Cultural and Institutional barriers, Occupational barriers, Social barriers (Wang, 2019) Differences in gender role attitudes (Chakraborty et al., 2018) Increasing crime against women (Murray & Zhang-Zhang, Gender-biased legislation, work and family care 2018) responsibilities, cultural stereotypes, unsatisfactory self-perception, poor access to finance and networking, norms and traditions, job opportunities and recruitment discrimination, mentors, role models and networking, family pressure and transportation. (Eikhof, 2016) Knowledge work barriers – The need to market one’s skills through networking, the need for mobility. Non-standard form of work barriers – income insecurities, lack of transparency of recruitment decisions (Alcañiz & Monteiro, Greater compliance with traditional gender roles, 2016) social protection regimes and labour legislation (Alonso-Almeida, 2014) Sexual harassment, restrictions at work (Marmenout & Lirio, Childcare responsibilities, training possibilities, 2014) organisational support, business culture, societal norms (Sidani & Feghali, 2014) Society moving away from agriculture to the manufacturing and services industry

providing equal opportunity to get an education and work on the other. Women’s workforce participation ensures gender equality by enhancing financial, social and psychological independence for women. Focus to enhance women’s workforce participation can provide the required impetus to achieve the SDG 5 of gender equality. SDG 8 is linked to decent work and economic growth. Inclusive development fosters growth for all. The main objective of this SDG is to ensure living wages,

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workplace safety and protection against discrimination. Enhancing the workforce participation of women can ensure inclusive economic growth (Klasen, 2019). This however can only be achieved by ensuring proper education to women, providing equal opportunity to work, safeguarding them against harassment and discrimination at the workplace and ensuring decent and equal pay. As the access to economic work is the first step to the economic well-being of several women, providing decent economic work to women becomes a priority.

Role of Digitalisation in Increasing Women’s Workforce Participation Female labour force participation differs along with the level of development, i.e. from agricultural to industrialisation and to further development levels. During the agricultural period, women were contributing to the farm to increase their income levels. As the industrialisation period emerged which is more male labour intensive than female, their participation was found to be reducing. Post industrialisation phase, the development of information and communication technology (ICT) made females participate more in the workforce. However, female labour force participation is frozen due to the sociocultural barriers restricting women to interact with men and mobility constraints. Amidst all barriers and challenges, digitalisation has emerged as a catalyst and a facilitator of women’s participation in the workforce. Digitalisation empowers women at different levels and enables the inclusion of traditionally marginalised groups like women in the workforce (Sovbetov, 2018). One unit increase in the internet per 100 population increases the female–male labour force participation ratio by 0.04% points. As per the Global Gender Gap report 2022, women’s online ICT enrolments have increased from 23.8% to 24.8%. ICT makes it easier to combine work with household chores as it reduces the distance and time needed in organising business. As women are more constrained by lack of information, the usage of ICT is more beneficial to them than men, also due to remoteness and isolation. It improves job searching and matching with reduced costs and increased opportunities for earnings, thereby improving female labour force participation. ICT provides an opportunity to prevail over the critical conditions to start a business. It also helps in creating new jobs and reducing time for home production that is required to enhance female labour force participation as it does not require physical strength. Thus the development of new market platforms due to ICT enhances female labour force participation (Valberg, 2020).

Women in Blue-Collar Jobs and Digitalisation Blue-collar workers also referred to as production worker includes employees engaged in material handling, shipping, warehousing, assembly, fabrication and other related activities (OECD). They are more often engaged in demanding jobs with higher physical workloads (Schreurs et al., 2011). Over the years, women in

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blue-collar jobs have been increasing; more than 30% of blue-collar jobs are occupied by women. India could add $770 billion to GDP by 2025–2026 with an increase of women in blue-collar jobs. Ecom Express has opened second women-only delivery centre and 60% of textile workers are women in India. However, the traditional sociocultural values along with the lack of a healthy climate and lack of programmes for flexible work hours contribute to the low participation of women in blue-collar jobs. Further, women drop out of blue-collar jobs due to a lack of clearly defined maternity policies and a lack of job security. To ensure women take up more blue-collar jobs, firms should assist women with learning the art of breaking barriers in all forms of life, enhance skill development, better infrastructure and undertake gender sensitisation and accessibility awareness programmes for blue-collar workers and their families. Digitalisation for blue collars is considered to be a new challenge for their performance and employability with the advancement in machine learning (ML), 3D printing, artificial intelligence (AI) and robotics. There is an assumption that it is difficult for blue-collar workers to retain their jobs as compared to those white-collar workers. Digital technologies do provide opportunities for blue-collar workers too (Hampel & Sassenberg, 2021). Though blue-collar job demands physical presence and their place dependence makes these jobs inflexible, they have the flexibility to take up new tasks as it changes the work process and present roles to work with new technologies (Sostero et al., 2020). There are benefits for a blue-collar worker of using web-based learning systems, for example, time reduction in task completion, productivity improvement and increased knowledge and career progression (Karaali et al., 2011). Having mastery experience will enhance the blue collar’s enthusiasm towards technology (Hampel, 2023). Also, technology upgradation allows replacing male blue-collar workers with female blue-collar workers (Juhn et al., 2014).

Women in Agriculture and Digitalisation India has 54.6% of the total workforce in the agricultural sector making it an agrarian economy. Women are extensively engaged in agriculture with 80% of rural women but only 15% owning land. Among 80%, 33% are agricultural labour force and 48% are self-employed farmers. They are engaged in all agricultural activities like production pre-harvest, post-harvest processing, packaging and marketing. The labour force participation rate of rural women is higher at 41.8% than that of urban women at 35.31%. Women agriculturalists double up work by providing services to the local population as digitally enabled field agents. But unfortunately, the stereotyped perceptions of women stand as a barrier in agriculture along with work–life balance (Azima & Mundler, 2022). Other barriers are lack of land ownership rights, unavailability of loans and credit facilities, low education level, inadequate training and capital-intensive technologies (Nuhu et al., 2014). Lack of information and local customs hinder women from having land ownership (Ogunlela & Mukhtar, 2009). In practice, women face barriers to participating in digitised agricultural value chains such as social norms, lack of

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access to resources and barriers to digital inclusion resulting in the mobile gender gap. Barriers that are mainly emphasised are low access to a mobile which leads to reduced access to digital advisory services, affordability, knowledge, skills, safety, security and women’s belief that mobiles and services are less relevant to them. However, technology usage among women may reduce gender divisions and shift towards productive farming (Hay & Pearce, 2014). Also, women farmers are enabled with access to market prices and receive inputs for their food processing activities with the help of digital technology. This makes women feel valued and empowered in their work along with access to government schemes and promotion of gender equality (Hay & Pearce, 2014). Agricultural technologies support increased productivity and sales, reducing the cultivation cost and vulnerabilities, provided service providers should be more inclusive towards women customers. Access to finance can be made easier by using the data generated from digital procurement solutions and mobile money data.

Women in White-Collar Jobs and Digitalisation White-collar jobs are office, administrative, professional, sales, clerical and technical works (OECD). White-collar employees are employed in resourceful jobs working with data such as concepts, ideas, knowledge, information, etc. that are more challenging and need more control (Schreurs et al., 2011). Women in white-collar jobs are growing with an increase in education. As per PLFS 2020–2021 data, the ratio of female to male senior officials, legislators and managers is 22.2% whereas the ratio for professionals and technical workers is 50.4%; similarly, the ratio for managerial positions is 18.0% whereas that of senior and middle management is 18.1%. According to the employment websites’ data, white-collar women job postings have declined by 18% in July 2022 as compared to that of February 2022. There is an unfair distribution of unpaid care work among men and women, which makes women participate less in leadership roles. This effect was even largely seen during the Covid-19 pandemic, during which there was a rise in women’s family responsibilities by 30%, resulting in a drop out of women’s workforce at higher rates. There is a need to change the social norms on who bears unpaid work like child responsibilities. Digital inclusion plays an important role in reskilling, flexible working and addressing the gender gap. Also, it will help women to secure higher paid jobs and to become entrepreneurs. The simple registration process along with enabling technologies would ensure women have means of identification through digital ID systems. White-collar jobs are more flexible as compared to blue-collar jobs (Sostero et al., 2020).

Women in Entrepreneurship and Digitalisation Entrepreneurship is the creation of a new organisation as a new venture or a new venture under an existing organisation (Carton et al., 1998). In India, there are

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58.5 million entrepreneurs out of which 8.05 million are women entrepreneurs (Shukla et al., 2014). Women entrepreneurs contribute towards poverty reduction and sustainable development hence engrossed in the economic development of the nation (Joseph Rubert & Sahaya Shabu, 2020). According to IBEF, January 2022, working-age women in India are 432 million and women-owned businesses are 13.5–15.7 million employing 22–27 million people. Further, about 30 million more women-owned businesses are expected to provide 150–170 million jobs by 2030. However, India ranks poorly on Mastercard’s Index of Women Entrepreneurs 2021 with 57 of 65 (Mastercard, 2021). The patriarchal systems and practices made women lack access to entrepreneurial training and expelled from informal communication which makes women disadvantageous and results in gender inequality (Panda, 2018). Unfavourable societal perceptions towards women, lack of family support, lack of information, inflexible laws, mobility restrictions and lack of confidence are some of the barriers that women face in the journey of entrepreneurship (Aljuwaiber, 2020; Banihani, 2020). These traditional barriers to women’s entrepreneurship can be mitigated by digital transformation and are being considered as a driver for opportunity recognition in the context of entrepreneurship (Atembe, 2022). Digitalisation allows entrepreneurs to standardise information by storing, coding, formalising and distributing varied knowledge and also develops entrepreneurs’ attitudes (Chatterjee et al., 2022). According to OECD, digitalisation facilitates entrepreneurial projects by reaching new markets with the help of innovations being incorporated into online payments and e-commerce irrespective of their work location. It also helps in removing constraints in business registrations, receiving funds, developing new networks and skills and accessing entrepreneurial programmes, thus enhancing women’s financial inclusion. But unfortunately the women entrants in ICT are just 17% as per OCED, 2021. According to World Bank data, the accessibility to mobile internet worldwide is 327 million fewer women than men. In India, 81% of women use ICT which includes female business owners using ICT for improving efficiencies, collecting customer information and maintaining marketing channels. At government-run Common Services Centres, 54,800 women have become village-level entrepreneurs in India.

Digital Entrepreneurship and Women Digitalisation opened a unique opportunity for women entrepreneurs. Digital entrepreneurs are self-employed individuals who function via digital platforms. Increasing digitalisation, access to the internet and availability of ICT devices enabled women to have access to resources required for an entrepreneurial venture. Women who earlier felt ignored due to several social and financial barriers are coming forward to showcase their skills and competencies through digital platforms. One of the primary advantages of digital platforms is their wider reach. Women entrepreneurs now sell several local and indigenous products through online mode, reaching out to customers worldwide. Digital entrepreneurship offers an opportunity to women to transform their embodied selves and lived

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realities (McAdam et al., 2020). To this end, Shukla et al. (2021) found that ICT transformed the way of doing business, and if women possessed adequate ICT skills, namely operative, creative and informational, their digital entrepreneurship journey is enriching. Digital entrepreneurship, although provides an opportunity, the journey is far from easy for women. Successful digital entrepreneurship demands digital skills and a drive for innovation. Furthermore, women often face normative barriers to the adoption of the digital platform for an entrepreneurial venture. Similarly, privacy and safety concerns usually keep women away from the digital presence. The cost of ICT devices, unavailability of content in the vernacular language and connectivity issues further plague the digital entrepreneurship intent in rural women. Hence, it is vital to mitigate traditional barriers and technological challenges, boost digital infrastructure and upskill women in digital competencies to enhance women’s workforce participation through digital entrepreneurship.

Discussion and Implications The role of digitalisation in empowering women and propelling women’s workforce participation is crucial. However, for a smooth process and effective outcomes of digitalisation, government support and policy changes are needed. Some of the policies can be taken into consideration for increasing female labour force participation like subsidising quality childcare education and flexible work arrangements (Nair & Vineles, 2021). Alongside government, organisations are expected to provide training programmes under social responsibility to equip women with the required knowledge. Especially for blue-collar jobs it is vital as it involve handling heavy machinery and are completely skill-based. In the subsection below, theoretical, managerial and policy implications are discussed in detail.

Theoretical Implications A key theoretical contribution relates to the importance of developing a theoretical paradigm that goes beyond viewing digitalisation from a functional usage perspective for women’s workforce participation. While viewing digitalisation as a vehicle of positive change and an enabler of women’s workforce participation is valuable, restricting to only this paradigm could be myopic. As the digital space is changing very fast due to new technological advances such as AI, metaverse, mixed reality and augmented reality, a novel theoretical paradigm is required. A theoretical paradigm that views technology as an ally of women in supporting them creates economic value through a job, an offering, a business, etc. Such a paradigm highlighting the differentiated and distinct requirements and abilities of women concerning the ease and convenience of the adoption and use of technology could be valuable.

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Managerial Implications Organisations are crucial partners in women’s empowerment and enablers of women’s workforce participation. To increase women’s participation at work, organisations should focus on talented women who are out of the workforce for several reasons. Re-entry of talented women into the workforce would not only increase women’s workforce participation but also contribute to the income and growth of the nation (Singh & Vanka, 2021). Practices and policies that allow women to re-enter the technology sector after a career break must be designed, such as ‘WomenReBOOT’ in Ireland. Furthermore, organisations are required to take necessary measures to access digital development such as providing access to women mentors. Google has a global platform called Internet Saathi programme for training rural women digitally, helping 10 million women. Similarly, Vodafone offers a product called Vodafone Sakhi to provide enhanced benefits for women’s security. Organisations need to reduce the imbalanced unpaid work among men and women by introducing family-friendly policies like flexible and part-time programmes along with tax or childcare policies that would encourage both mother and father to work equally.

Policy Implications Increasing women’s workforce participation is a top priority of all governments as it impacts the socio-economic well-being of women. More and more governments are coming forward with ideas and initiatives to motivate women for economic activities. For instance, the government of India’s agenda ‘Gender mainstreaming in Agriculture’ provides access to schemes or resources specifically for women farmers to incur 30% expenditure on women farmers by states and other agencies. Department of Biotechnology initiated a programme called Biotech-Krishi Innovation Science Application Network (Biotech-KISAN) especially for women farmers to link innovative agricultural technologies to the farm. Creation of farmer’s associations and memberships must be encouraged, provision of agricultural credit facilities in particular to women with collateral demands and reorientation of agency service delivery systems where female and male clientele are treated equally (Nuhu et al., 2014). Partnership plays a significant role in agricultural value chains by providing digital services. For example, cooperatives and agribusinesses address multiple barriers faced by women all at once by providing bundled digital solutions. Deliberate and extensive outreach efforts are required to make sure that women have access to knowledge and skills for agriculture using the digital agricultural solution. Using short videos or interactive voice responses that can be used by women at their own pace would help in enhancing their agricultural training.

Conclusion and Future Research Agenda This chapter contributes to the growing literature on women’s workforce participation. It presents barriers faced by women in workforce participation. It

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also contributes to presenting a comprehensive account of the role of digitalisation in enhancing women’s workforce participation in different types of jobs, sectors and vocations. Digitalisation supports work-from-home culture which makes women overcome barriers of mobility restrictions, accommodation facilities, sexual harassment, care work responsibilities and flexible working hours and premises thus enhancing the current work situation. It also enhances their networking skills and management skills through web-based learning thereby increasing their job opportunities. This chapter foregrounds that digitalisation can be a crucial vehicle to ensure decent work and gender equality by enhancing the economic well-being of women at large through enhanced participation in paid work. In this context, there is a need to study the role of digitalisation concerning women’s socio-demographic perspectives like parental status, marital status, education and country/state of residence. Similarly, concerning functional perspective studies can emphasise how the flexibility, autonomy, ease of digital use to women and digital literacy be increased. Further studies can target on process perspective on how to motivate women to use the digital form at the individual level and at the organisational level to study the impact of training for enhancing digital skills for both blue- and white-collar women workers. Also, how the innovative financing mechanisms would enhance gender equality along with the government’s outreach or awareness programmes. Such symbiotic partnership will catalyse the effects of digitalisation enhancing women’s participation and contributing to growth and development.

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Chapter 20

Building Resilience Against Ongoing and Future Pandemics: Blockchain Technology to the Rescue Taab Ahmad Samad and Yusra Qamar

Abstract While the world grappled with the COVID-19 pandemic and its externalities, scientists have recommended that the global community brace against potential future pandemics. The need to build resilient systems has never been this urgent. The world, especially emerging economies, faces acute food insecurity, high food prices, failing health infrastructure and rampant misinformation spread, among others. Since blockchain technology (BCT) has been discussed in the supply chain resilience context, and it offers the potential to develop resilient systems, we aim to outline the potential of BCT to help build resilience against ongoing and future pandemics. Mainly, we focus on BCT for healthcare management, disruption management of food supply chains, human resource management, modern education and certification and governance and administration. Keywords: COVID-19; resilient systems; blockchain technology; food supply chains; healthcare; governance; human resource management; education

Introduction Humans have faced epidemics and pandemics caused by infectious diseases since time immemorial, and documented history highlights an epidemic as early as 1350 BC (Amarna Tablet, 2004). The pandemic has had far-reaching consequences throughout systems. The Life Years Index showed that, in terms of Life Years lost, the economic and societal costs of the pandemic in 2020 significantly surpassed the average yearly expenses of all other calamities and the total cost of all epidemics from 2000 to 2019 (Doan & Noy, 2022).

Fostering Sustainable Development in the Age of Technologies, 319–330 Copyright © 2024 Taab Ahmad Samad and Yusra Qamar Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231022

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In the past decade, World Health Organization (WHO) has tracked 1,438 epidemic outbreaks in 8 years from 2011 until 2018 (Global Preparedness Monitoring Board, 2019). The global community is most recently grappling with the COVID-19 pandemic, which was first identified as cases of peculiar pneumonia and reported in China’s Wuhan city in late 2019, and became a global health and social and economic catastrophe in a brief period (Global Preparedness Monitoring Board, 2020). The ongoing COVID-19 outbreak has claimed 6.6 million lives by the end of October 2022 (Dong et al., 2022) and has so far cost the world more than 11 trillion US$ to fund the response and the costs of preparedness in billions (Global Preparedness Monitoring Board, 2020). Although the vaccines have been developed globally, only 68.6% of the global population has received at least one dose of a COVID-19 vaccination, with 25.1% of persons in low-income countries receiving at least one dose (Mathieu et al., 2021). Also, in 2019, the WHO reported several infectious diseases that pose a severe threat to public health, most of which have no vaccines yet (World Health Organization, 2019). Moreover, much like the COVID-19 outbreak, the next epidemic outbreak could be just another flight away due to the ease of global connectivity. Due to the new and dynamic nature of the COVID-19 virus and the lack of a definite treatment approach, social distance (executed through state-wide lockdowns) was recognised as the best possible defence tactic while scientists around the world searched for a possible cure (Chamola et al., 2020). However, lockdowns, although effective in slowing down the virus spread during the initial phase of unawareness and misinformation, led to severe disruptions in almost all sectors of the industry. For example, disruptions caused by COVID-19 have affected more than 90% of Fortune 1,000 companies (Sherman, 2020). The deployment of advanced technology-based products/services, such as robots, smart thermometers, telemedicine, drones and smart wearables, to name a few, have helped in mitigating the impact of COVID-19 (Chamola et al., 2020). Studies like Singh et al. (2020) suggest how three-dimensional printing can be employed to combat COVID-19 outbreaks. However, in the wake of the ongoing pandemic and the researchers outlining potential future pandemic threats (Gray & Abdelgadir, 2021), it is also imperative to prepare a resilient global community that is prepared enough to tackle future outbreaks. Resilience, in simple terms, is defined as the capability to endure disruption(s) and recover to original performance (Hosseini et al., 2019; Spiegler et al., 2012). One of the disruptive technologies, BCT, which was first linked with cryptocurrencies (Tapscott & Tapscott, 2017), has already found use in several industries, including finance, supply chain management and agriculture, to mention a few (Sharma et al., 2021). Since BCT has been discussed for enhancing resilience in the supply chain management context (Dubey et al., 2020; Min, 2019) and it offers the potential to develop resilient systems, we aim to outline the potential of BCT to help build resilience against ongoing and future pandemics. Mainly, we focus on BCT for healthcare management, disruption management of food supply chains and governance and administration.

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Literature Review Blockchain Technology and Its Current Applications BCT caused upheavals in the fintech industry, but it also had the enormous potential to affect many other industries (Wamba & Queiroz, 2020). Now, most Fortune 500 companies are investigating BCT applications with the intention of incorporating them into their products and services (Peck, 2017). BCT project prototypes are already underway and are causing disruptions in the management of agriculture supply chains (Kamble et al., 2020), electronic medical records (Chen, Ding, et al., 2019), banking (Wang et al., 2020), land titling (Thakur et al., 2020) and manufacturing (Mandolla et al., 2019). The fundamental feature of BCT is that it offers a revolutionary method for managing data that is accountable, non-repudiable and immutable (Attaran & Gunasekaran, 2019; Kamble et al., 2020; Mytis-Gkometh et al., 2018). The BCT is an open ledger peer-to-peer transaction system that is decentralised and distributed (Sharma et al., 2021; Wamba & Queiroz, 2020) and doesn’t rely on a trusted third party for transaction verification, settlement or security (Nofer et al., 2017). BCT is frequently viewed as a disruption that primes the technological environment for the Internet of Things (IoT) and acts as the internet’s top layer, coexisting with other internet technologies (Fern´andez-Caram´es & Fraga-Lamas, 2018).

Blockchain Technology Against Ongoing and Future Pandemics The following subsections outline how BCT can be leveraged to build resilient systems. We discuss BCT applicability in healthcare, food supply chains, human resource management, modern education and certification and governance.

Blockchain for Healthcare Management Healthcare services highly depend on the availability of accurate and complete medical records of patients (Hassey et al., 2001) to provide them with timely responses at the time of distress, and it becomes even more critical in situations where time is of the essence, like the COVID-19 pandemic. Using cloud storage and smart contracts, BCT can ensure medical records’ safe storage and sharing (Tseng et al., 2021). In case of emergencies or otherwise, while hospitals and medical agencies can use this protected data to provide better services, patients can visit doctors in different hospitals without needing to undergo medical investigations at the previous institution. In the preventive and predictive medicine domain, BCT has promising potential to help make medical records protected and yet globally accessible via permissioned blockchain (Chand Bhatt et al., 2021). Speaking of COVID-19, extensive testing and isolation of individuals have helped curb the rate of infections. BCT can ensure intelligent testing and accurate reporting by setting up a distributed and shared network of testing facilities. Each facility in the network can provide testing data on the distributed tamper-proof

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ledger, resulting in more accurate findings. These findings can then be utilised by concerned parties to devise effective mitigation plans. The issues pertaining to fake/forged medical records can also be tackled using BCT. In a recent incident in India named Kumbh Covid Test Scam, nearly 100,000 Covid test reports were alleged to be fake (Kumbh Covid Testing Scam, 2021). This incident had allegedly resulted in a super-spreader event for COVID-19’s second wave in India (‘India Covid’, 2021). Apart from testing scams, several incidents of fake COVID-vaccination certificates have also emerged recently (Gujarat, 2021; Telangana, 2021). BCT’s unique advantages of real-time information exchange and audibility can be reflected in preventing such corruption, as the BCT’s unique feature of conducting transaction audits provides enhanced trust, accountability and audibility (Parmoodeh et al., 2023). Moreover, data stored on the BCT can be made accessible to agencies to ensure appropriate action on a real-time basis (Sharma et al., 2021).

Blockchain for Food Supply Chain Disruption Management While the imposition of national lockdowns had helped countries control the spread of the virus, they also resulted in extreme disruptions in the local and global food systems. For some countries, like India, the timing of the national lockdown also overlapped with the peak harvesting season of staple crops like paddy, wheat and barley (Pothan et al., 2020), which were severely impacted due to lockdown-related externalities. The pandemic has also resulted in a significant increment in global food insecurity, affecting vulnerable communities across the globe (Bhargava & Bhargava, 2021), and the surge in food prices due to COVID-19-related disruptions further adds to the task (Food Security and COVID-19, 2020). Statistically, there is an 82% plunge in the number of people estimated to face acute food insecurity due to the ongoing pandemic (Kalla et al., 2020). Moreover, the pandemic has also got people to pay increased attention to their personal health and hygiene (COVID-19 Moves People to Focus on Their Personal Health, 2020). People are also increasingly becoming conscious about the food they eat, and it has shown a natural increase in consumer curiosity about the traceability and visibility of food products from the farm to the fork. However, the food supply chains face efficiency and transparency-related problems that continuously threaten stakeholders (Alexander et al., 2017; Gokarn & Kuthambalayan, 2017). BCT can assist food supply chains in achieving transparency and traceability through real-time data gathering and dissemination across all phases, including processing, shipping, warehousing and distribution, made possible by the data-driven BCT platform. The digital product record in the BCT network can contain critical product-related information, such as expiry date, storage condition and batch number, reducing food waste and environmental footprint (Ahmed & Broek, 2017). As the digital record gathered throughout processes will be tamper-proof and auditable, BCT-enabled food traceability mechanisms will also assist regulators in ensuring food safety, quality and integrity through BCT-based certifications (Lucena et al., 2018). Moreover, BCT’s interoperability with other

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existing technologies, backed by smart contracts specially designed under local regulations, can help achieve efficient contactless deliveries of essential products using technologies like unmanned aerial vehicles and robots during the times of distress.

Blockchain for Human Resource Management Human resource management (HRM) concerns how people are employed, managed and developed in organisations (Armstrong, 2009). The current technology and epidemiological disruptions have significantly impacted it. For managers and HRM professionals, this pandemic has created a complicated and stressful environment in which they must develop creative solutions to maintain their business operations and assist their employees in coping with the difficulties of this unprecedented circumstance (Hamouche, 2021). Firstly, working conditions have been significantly impacted due to the unexpected COVID-19 lockdowns, with employees being instantly forced to work from home, which has created a challenge for managers in planning work schedules (Hamouche, 2021). Secondly, tools required to perform the job remotely, communications and supervision between the organisation and the employees have also been greatly affected, which has led to stress and undermined the employees’ mental health (De Vincenzi et al., 2022). Further, staffing new employees have been entirely dependent on the online information given with no way to check the validity of the information provided by the candidates leading to more cheating and fraud, whereas cases of fraudulent job advertisement have also increased (Ravenelle et al., 2022). Situations of inadequate performance management due to the unavailability of monitoring resources and improper training data tracking have also created a challenge for employees and managers. The disruption has made the employees vulnerable to situations like compensation fraud and exploitation because of the unavailability of formal job contracts (Hamouche, 2021). BCT has the potential to solve HRM issues and transform nearly all HRM functions. Implementing BCT can ease checking and assessing the recruits’ education and skills, thus placing the right candidate at the right job and reducing turnover. BCT can also record individuals’ documents from training, skills, education and workplace performances (Chen, Lv, et al., 2019), thus solving the issues of document tracking and verification in case of virtual onboarding. By creating a more effective payment system, including cross-border payments and tax liabilities, it has the ability to enhance the compensation area. BCT can also increase productivity by automating processes (Hassan Onik et al., 2018; Hsieh et al., 2018). Smart contracts can be utilised as a framework for human resource records that protects the privacy and offers transparency. Smart contracts can also help in facilitating direct agreements between parties without the involvement of third parties and by introducing new mechanisms for negotiating the terms of employment, thus eliminating the threat of exploitation of employees (Kim et al., 2020; Tanana, 2019). Moreover, BCT can significantly prevent fraud and enhance cybersecurity (Singla et al., 2019).

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Blockchain for Modern Education and Certification The COVID-19 epidemic has tremendously impacted educational systems worldwide, forcing a tough transition in the curriculum to an online format. The simultaneous online transformation of all existing courses within days is a test of organisational agility and a challenge for all educational process participants (Almazova et al., 2020). Although converting courses and programmes to the online format is difficult, monitoring and evaluating student performance can be particularly difficult (Mazzara et al., 2022). As a result of the loss of campus networking and connection, collaborative projects also have suffered. The tracking of students’ progress, authentication of certificates and risk of student data privacy and consent through virtual certification and admissions is also rising. The pandemic has also incurred extra costs in purchasing and extending platforms’ licences to ensure secure and private document sharing (Mazzara et al., 2022). BCT is already widely used in educational institutions worldwide, creating enormous prospects for its efficient usage in the future. For instance, BCT is already being actively applied in Japan, Singapore, the United States, Hong Kong, Estonia and the United Kingdom, while the Singapore school system is actively using online learning and is regarded as one of the best (Yakovenko et al., 2019). The application of BCT for use by educational institutions can help enhance teaching and learning processes and foster cooperation among stakeholders, including students, teachers and parents. It can also be utilised for cloud storage, identity management, digital degrees and certifications and e-transcripts (Atienza-Mendez & Bayyou, 2019). The deployment of BCT will significantly increase the trust level and privacy of the credential of the applicants (Malibari, 2020). It will secure a shared-learning atmosphere with an enhanced learning atmosphere and efficient student–teacher communication, thus resolving the issue of collaboration and networking. The issues of lack of awareness of degree apprenticeships and the uncertainty of the quality of apprenticeships can be resolved through BCT (Bandara et al., 2018).

Blockchain for Governance and Administration In addition to the COVID-19 pandemic, governments worldwide were also battling against the so-called Infodemic (Managing the COVID-19 Infodemic, 2020), which refers to the fake news and misinformation spread about the pandemic. In 2020’s first quarter, about 6,000 people were hospitalised due to COVID-related misinformation, out of which 800 are estimated to have died (Fighting Misinformation in the Time of COVID-19, One Click at a Time, 2021). Monitoring numerous social media platforms for fake news is tedious for governmental agencies. BCT can be harnessed to handle this issue, as the agencies can formulate frameworks that require platforms to assign digital identifiers on messages related to the pandemic/emergencies, helping agencies in swift identification and action against the source of a particular fake news.

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The current pandemic has had a differential impact on urban and rural areas. Although the infection rates are pretty high in urban settings, the impact on the infected rural population has been severe owing to a lack of information, preparedness and health infrastructure (Ground Report, 2021). BCT can help minimise such issues by building a shared network of responsible parties, where infrastructural and essential requirements of the concerned area can be updated, verified and acted upon in real time. BCT also offers to help transition towards e-governance, where (at least) some routine governmental operations can be automated. For example, in a recent incident in India, about 1,600 school teachers were reported to have died because of COVID-19 infection after being deployed for poll-related duties during the local elections (Singh, 2021). To avoid such incidents in the future, governments can design and implement BCT-enabled voting systems that will ensure fairness and transparency due to the immutable voting records.

Implications and Future Research Recommendations Implications Our work provides the primary practice implications to outline how BCT can be leveraged to build resilient systems in areas of healthcare, food supply chains, human resource management, modern education and certification and governance. In healthcare services, medical records are stored on the BCT accessible to agencies to ensure appropriate action on a real-time basis. In food supply chains, government can leverage BCT’s interoperability with other existing technologies, which can help achieve efficient contactless deliveries of essential products during the times of distress. In organisations, BCT can ease candidate selection and recruitment and prevent fraud. Educational institutions can leverage BCT to enhance teaching and learning processes. Governments can design and implement BCT-enabled voting systems that will ensure fairness and transparency due to the immutable voting records. The work suggests that BCT can be used to build resilient systems, but there is necessity of considering the moral and legal implications of implementing BCT in different areas.

Future Research Recommendations Future research can pursue several research opportunities to help build resilient systems that are prepared against the ongoing (and potential future) pandemics. Currently, BCT faces several challenges that range from regulatory, legal and privacy-related concerns. There is an urgent need to develop robust legal frameworks and administrative processes to help ease legality concerns worldwide. Moreover, the scalability of BCT has been questioned repeatedly, and future research is required to suggest innovative solutions to ensure operational scalability. Finally, the energy efficiency of BCT has been under constant criticism. For example, Tesla recently stopped accepting Bitcoins as a payment mode due to issues concerning the intensive utilisation of non-renewable energy

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(Tesla Will No Longer Accept Bitcoin over Climate Concerns, Says Musk – BBC News, 2021). Future research should focus on developing computationally inexpensive but robust algorithms.

Conclusion The COVID-19 pandemic and its catastrophic effects worldwide have served as a shocking eye-opener for everyone. It has essentially changed the definition of ‘normal life’ for people everywhere, and human society is trying to adapt to the ‘new normal’. However, it has also exposed the inadequacy of erstwhile systems to cope with future pandemics (if any). Hence, there is an urgent need to develop more robust and resilient systems that can effectively endure future disruptions. We have outlined the utility of BCT to build future-ready resilient systems. Specifically, we focus on healthcare, food supply chains, human resource management, modern education and certification and governance.

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Chapter 21

Impact of Awareness on the Adoption of Electric Vehicles: A Systematic Literature Review Divya Singh and Ujjwal Kanti Paul

Abstract Despite efforts to reduce environmental pollution and wasteful fossil fuel use, electric vehicles (EVs) are still rare on the road. Why is it so challenging to get widespread EV adoption? One significant factor on which it heavily depends is one’s awareness and understanding of EVs. However, due to an absolute lack of knowledge on the part of the populace, this factor becomes a huge impediment to the uptake of EVs. A systematic review of the electronic database Scopus for the years 2003–2022 was carried out on ‘EV awareness and adoption of EV’ while considering the ‘Preferred Reporting Items for Systematic Reviews and Meta-analysis’ (PRISMA) standards. A three-step identification process resulted in the ultimate detection of 41 papers, which were then thoroughly examined. A conceptual framework that encompasses the three key awareness aspects that influence EV adoption is developed. To encourage greater uniformity among EV researchers, this study’s conclusions serve as a foundation for operationalising upcoming research efforts within a predetermined framework. The authors must therefore be optimistic that lingering technological, legislative, cultural, behavioural and business-model barriers may be overcome over time through widespread dissemination of knowledge and awareness related to EVs, making it possible for everyone to switch to greener, more economical and more efficient transportation solutions. Keywords: Electric Vehicles (EVs) adoption; awareness; EV knowledge; Systematic Literature Review (SLR); PRISMA; conceptual framework

Fostering Sustainable Development in the Age of Technologies, 331–357 Copyright © 2024 Divya Singh and Ujjwal Kanti Paul Published under exclusive licence by Emerald Publishing Limited doi:10.1108/978-1-83753-060-120231023

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Introduction The quality of life in cities is decreased as a result of the pollution, noise and other waste produced by automobiles and other motorised modes of transportation. A critical component of contemporary civilisation is private mobility, which is a large source of carbon emissions that contribute to climate change (Chapman, 2007). Due to higher socio-economic development, metropolitan regions are more affected by various transportation-related problems, such as excessive oil use, air pollution and greenhouse gas emissions (IEA, 2021). Despite these drawbacks, automobile usage is frequently motivated by advantages including time savings, convenience, independence and prestige, also contributing significantly to global economic expansion (For instance, Anable & Gatersleben, 2005; Steg & Gifford, 2005). In December 2015, 196 nations signed the Paris Agreement, which intends to keep the rise in the global average temperature to 1.5–2 °C (The UNFCCC, 2015). In addition, the government is urged to maintain its commitment to these programmes through the Sustainable Development Goals (SDGs) plan of the United Nations (UN). Therefore, electrifying the transportation industry or replacing gasoline vehicles or internal combustion engine vehicles (ICEVs) with new and one of the most well-known green energy vehicles, that is, electric vehicles (EVs) looks to be a feasible step towards sustainable growth. EVs are those alternative fuel vehicles (AFVs) that have gained prominence in recent years and are viewed as one of the most promising options for sustainable transportation (Zhuge & Shao, 2019). They are expected to reduce adverse effects on the environment and save finite fossil fuel resources over the course of their entire lifespan (Lieven et al., 2011). Additionally, EVs provide ways to promote climate change and can help communities become more sustainable by providing emission-free mobility options (Raugei & Winfield, 2019). Even though there hasn’t been much research on the topic, it’s important to raise awareness because current EV buyers can be categorised as early adopters who have a higher level of technical knowledge and familiarity with EVs, suggesting that they may vigorously adopt EVs (Axsen et al., 2016). Due to the lack of familiarity with EVs, the market’s present preference is ICEVs. Most customers have less confidence or trust in tins new energy vehicle which may hurt EV purchase decisions. The key drivers of prospective purchase intentions for EVs ¨ were shown awareness about them by various studies (Bruckmann, 2022; Dash, 2021; De Rubens et al., 2018). In addition to assisting in raising consumer acceptance of EVs, enhancing consumer understanding of this green technology is essential in reducing customers’ concerns and perceived risk associated with EVs. Since the reduction in local pollution and dependence on oil are co-benefits of decarbonising transportation, public perceptions are crucial. But we notice that the communities of transport and energy research frequently regard the general population statically and view them as either troublesome or insignificant to the issues at hand (Kester et al., 2019). Thus, to dig deeper into the subject, some earlier relevant studies will be discussed in the next section.

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Background Literature The burgeoning body of literature on electric mobility frequently uncovers a variety of grim obstacles to acceptance and usage in the future. For instance, numerous studies have indicated that consumer barriers to quicker adoption of EVs include the higher cost and shorter range of EVs roughly equivalent to ICEVs, a dearth of charging facilities, a lack of EV models and erratic government aid (Egbue & Long, 2012; Lane & Potter, 2007). According to some research, consumers’ lack of interest in EVs is correlated to their level of awareness of EVs, and consumers’ psychological perception of EVs has a big influence on public acceptance (Wang et al., 2018; Wu et al., 2019; Xu et al., 2019; Zhang et al., 2017; Zhu et al., 2019). However, these studies have thus far focused mostly on the relevance of customer behaviour, beliefs, values, customs and norms about their EV adoption intention (Huang et al., 2021). There is a need to conduct a more thorough characterisation of the variable ‘EV knowledge’ in the studies so that a better understanding could be achieved of the link between knowledge and the decision to adopt EV (Rotaris et al., 2021). Hence, the following research questions will be attempted to be answered by this study: (1) How extensive is the body of knowledge regarding EV awareness research; (2) To what extent does ‘knowledge and awareness’ encourage the adoption of EVs; (3) What aspect of the subject deserves more study? ‘Knowledge’ is defined by Rogers et al. (2014) in his ‘Innovation-Decision Process’ as ‘Knowledge is acquired when a person is exposed to an innovation and learns how it functions.’ EV acceptability and EV knowledge are key factors in accelerating the adoption of more environmentally friendly passenger transportation and e-mobility. Few studies have looked at how to explore the effects of consumer technical knowledge about EVs on their desire to adopt them. A technological knowledge-based viewpoint is lacking in earlier studies; therefore, ¨ to address this knowledge gap, more research is necessary (Bruckmann, 2022). We are proposing a fresh set of research priorities based on a novel reviewing approach, i.e. systematic literature review (SLR) (Liberati et al., 2009; Paul & Criado, 2020). The essential characteristic of this review is that it is apparent and consistent and all of its steps need to be noted (Page et al., 2021). Previous studies (Coffman et al., 2017; Kumar & Alok, 2020; Liao et al., 2017) employs a systematic literature review to identify factors affecting EV adoption, while other researchers (Biresselioglu et al., 2018; Rezvani et al., 2015) restrict their review effort to motivators and obstacles to the adoption of EVs. This review of the literature differs from previous reviews as it emphasises the impact of awareness on the uptake. Here, the three facets of awareness that influence customer intentions to adopt EVs are identified that will be discussed separately in the result section. The following section will talk about the methodology that has been used and that is best suited for the review process.

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Methodology To find pertinent material and resolve the questions raised, an SLR was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach (Liberati et al., 2009; Page et al., 2021). This approach seeks to evaluate essential data and conduct a methodical search for literature relevant to the issue of interest (Kitchenham, 2004). A Scopus database search took place using the terms ‘Electric vehicle’ OR ‘EVs’ ‘BEVs’ OR ‘PHEVs’ OR ‘HEVs’ OR ‘green vehicles’ OR ‘clean vehicles’ OR ‘electric mobility’ OR ‘emobility’ AND ‘adoption’ OR ‘EV adoption’ OR ‘adoption intention’ AND ‘awareness’ OR ‘knowledge’. The survey had no set time limit and was carried out in September 2022. The search methodology, keywords, strategy, database, publication type, language and time frame are shown in Table 21.1. It’s noteworthy that 272 documents were found between the years 2003 and 2022. Then, the subject area was made limited to ‘energy’, ‘social science’, ‘environment, business’, ‘management and accounting’, ‘econometrics’ and ‘multidisciplinary’ which helped to filter out 202 studies. PRISMA flowchart (Fig. 21.1), broken down into three key phases: I. Identification: (a) Creating a keyword tree from the ‘EV adoption’ and ‘Awareness’ (b) Outlining the research protocol (search strategy, subject area, publication type and language); II. Screening: (a) reading study titles and abstracts to locate those that do not meet the papers’ aims and should be deleted from the collection; (b) reviewing complete article to filter out publications that do not address the function of EV awareness in the adoption of EVs; III. Included: Description of the final portfolio of 40 articles after adding four articles acquired from the reference list and manual search. Hence, these final 40 articles including the three dimensions of awareness are covered in detail in the next section.

Results According to the 40 articles evaluated in Table 21.A1 (Appendix), consumer knowledge appears to have a considerable impact on their intention to adopt EVs.

Table 21.1. Research Protocol. Search Term (Title, Abstract ‘Electric vehicle’ OR ‘green vehicles’ OR ‘clean or Keywords) vehicles ‘ OR ‘electric mobility’ OR ‘emobility’ AND ‘adoption’ OR ‘EV adoption’ OR ‘adoption intention’ AND ‘awareness’ OR ‘knowledge’. Search Strategy ‘Energy’, ‘social science’, ‘environment, business’, ‘management and accounting’, ‘econometrics’ and ‘multidisciplinary’. Publication Type Articles and Review papers Language English Search Period Not Specified

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Search terms used within TITLE-ABS-KEY in Scopus database

Screening

Identification

"electric vehicle" OR “green vehicles” OR "clean vehicles " OR "electric mobility" OR "emobility" AND "adoption" OR "EV adoption" OR "adoption intention" AND "awareness” OR "knowledge”

Studies identified from Database (n = 272)

Studies screened (n = 202)

Studies excluded after limiting subject areas (n = 70)

Studies retrieved (n = 151)

Studies excluded after limiting to articles and reviews only (n = 51)

Included

Studies evaluated for eligibility (n = 36)

Studies excluded after title review (n = 48) Studies excluded after abstract review (n = 67)

New studies included in review (n = 4)

Sample studies included in systematic review (n = 40)

Fig. 21.1.

PRISMA Flowchart Showing the Identification Process of Relevant Studies Included in a Systematic Review.

However, very few studies have looked at ways to analyse how this awareness about EVs affects consumers’ desire to embrace them. After a thorough examination of all the studies, three facets of awareness that influence customer intentions to adopt EVs are identified: awareness about EVs and its technology; awareness of government aid or support in the form of policies and incentives; and environmental knowledge including benefits of using EVs and consequences of driving ICEVs (gasoline vehicles). Each of these facets is presented in Fig. 21.2 and discussed in detail later.

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EV Adoption Intention

Awareness of Government Assistance

Awareness of EVs & its technology

Environmental knowledge

Fig. 21.2.

Three Dimensions of Awareness Impacting Consumers’ EV Adoption Intention.

Awareness of EVs and Its Technology Various studies have shown that people’s perceptions and willingness to adopt pro-environmental goods are greatly influenced by their awareness of this product (Huang et al., 2021; Jaiswal et al., 2021; Krause et al., 2013; Lane & Potter, 2007; Rotaris et al., 2021; Sierzchula et al., 2014). EV’s technical knowledge includes its performance, battery, charging, etc. Graham-Rowe et al. (2012) particularly indicated that EV adoption may be influenced by how much the general public begins to recognise them as ‘ready for market’ rather than ‘works in progress’. Vuichard (2021) found lack of information is a severe challenge in the adoption of EVs. Further, it was determined that individuals know little about the performance characteristics, charging interval, operating and maintenance costs of EVs (Zhang et al., 2011). The uncertainty around EV battery technology has been discovered as a big potential impediment that has been observed to mainstream EV adoption. This uncertainty may be partially ascribed to a lack of experience with EV technology, but it may also be the result of certain members’ scepticism that EVs are a superior choice than some already available ICEVs (Egbue & Long, 2012). Noel’s findings also demonstrate the close connections between these kinds of obstacles and customer knowledge and experience (Noel et al., 2020). Abbasi’s result also suggests that increased consumer awareness and knowledge of EV features can have a positive impact on consumer motivation. Edgue and

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Long’s findings demonstrate that awareness and knowledge about EVs vary by gender, age and educational level. Regarding modifications to personal traits, the knowledge varies. The younger generation may understand it differently from the elder ones. The studies reveal a favourable correlation between probable EV adoption and younger men, higher income earners, having more children, EV experiencers and typically sustainability-minded individuals (Chen et al., 2020; Egbue & Long, 2012). The findings of Huang revealed a favourable and substantial relationship between consumer technology expertise and consumers’ perceptions of EV utility, ease of use and enjoyment as well as their intention to adopt EVs (Huang et al., 2021). Fry had proven in his research that respondents know little about EVs, and their misconceptions have given rise to unfavourable and negative sentiments. Whereas, Bruckmann examined whether familiarity with and exposure to EVs ¨ can change consumers’ understanding and buying inclinations (Bruckmann, 2022; Fry et al., 2018). To stay up-to-date on automotive news, Broadbent et al. (2021) asserted that EV owners predominantly used textual materials, focusing on online sources, including digital platforms and media sources. When the government in New Zealand developed EV policies to encourage customers to purchase EVs, many media outlets subsequently covered these activities. It was discovered by Pradeep et al. in 2021 that maintenance knowledge related to EVs had no direct impact on the decision to buy them. It demonstrated strong indirect effects on purchase intention, particularly for consumers who had sufficient maintenance expertise and were aware of the benefits of a battery electric vehicle (BEV). The paper of S. Wang et al. (2018) revealed that consumers will perceive less risk when they are informed about EVs, on the other hand, customers are more inclined to feel that EVs are sustainable and can improve the environment if they are aware of their benefits. They hence proved that EV knowledge negatively affects the perceived risk and positively affects the perceived value associated with EV.

Awareness of Government Assistance in the Form of Policies and Incentives Government policies and regulations can have an impact on the adoption behaviour of consumers. Some aim to increase demand for technology by decreasing its price or providing charging facilities (a ‘supply push’ approach); others work to increase a technology’s acceptability or affordability (a ‘demand pull’ method) (Du et al., 2018; Krause et al., 2013). He and Zhan (2018) also emphasised the significance of policy coordination and offer concrete recommendations by showing the connections between EV policies and its adoption. Their findings have significant ramifications for comprehending EV marketing in the context of diverse consumer segments and efficient policy coordination tactics. Policies promoting environmental awareness, buying incentives, infrastructure investment and also informing customers about EVs and their benefits have been viewed as a legitimate tactic to raise consumer acceptance of EVs. All ¨ might play a vital role in achieving a large shift to EVs (Bruckmann, 2022;

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Rosales-Tristancho et al., 2022; Wang et al., 2017). Moreover, well-designed regulations for the electrification of corporate fleets would result in a notable expansion of the market for EVs, given that fleet exposure to EVs serves as a benefit for private acquisition (Di Foggia, 2021). Based on earlier research, it is clear that financial incentive policies may cut the cost and lower the price of adopting EVs, sparking consumer interest in doing so (Wang et al., 2017). Most studies had proved that consumers’ intention to adopt EVs is positively impacted by financial incentive policies and they would be more likely to embrace EVs if more financial incentives were offered (Carley et al., 2013; Kester et al., 2018; Mersky et al., 2016; Wang et al., 2018, 2021). Though few research questions are still unanswered or unexplored: • Are the public aware of the incentives or variety of financial aids offered by the

government, either local, state or national? If yes, then what is the level of awareness among the public? • Do the potential consumers have in-depth knowledge about the various financial policies so that they can enjoy full tax benefits and subsidies while purchasing EVs? • What will be the impact of widespread awareness regarding government assistance on EV adoption?

Environmental Knowledge (Benefits and Consequences) The degree of environmental awareness (EA) of a person has been extensively looked at in connection to that person’s plans to acquire an EV. However, there has been relatively little prior macroeconomic analysis of this subject. According to the research (Simsekoglu & Nayum, 2019), drivers are more receptive to knowing about BEVs’ economic and environmental advantages than their mechanical ones. Moreover, one research proposes a novel and original technique in this field of study termed a Twitter keyword analysis to examine the influence of EA on the EV sector in 27 member states of the European Union (EU) and two states of the European Free Trade Association (EFTA). Although the investigation’s findings demonstrated that EA had little impact on the adoption of EVs than other variables, this study added a new factor to the current body of literature (Austmann & Vigne, 2021). In the study of Abbasi, a strong and favourable relationship between perceived environmental knowledge and consumer intention was established (Abbasi et al., 2021). Han et al. (2019) claimed that product knowledge is crucial to boosting people’s perceptions of electric aeroplanes as trustworthy, which in turn influences people’s adoption and purchasing intentions. According to other works (Lane & Potter, 2007; Okada et al., 2019), factors like cost and performance rank higher than EV sustainability and environmental advantages and also have the biggest influence on EV adoption. Given that some individuals in this group are worried about how sustainable and environmentally friendly EVs are compared to ICE automobiles, those people with high levels of

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environmental consciousness or values might not see buying an EV as being good for the environment. Several studies have shown that the environmental awareness variable is less disputed and frequently used in the study on transportation choice (Abbasi et al., 2021; Fry et al., 2018). Moreover, Mohiuddin et al. (2018) confirmed that customers’ favourable views about green vehicles are significantly influenced by environmental education and awareness. Therefore, a concerted effort is required to promote these types of studies which consider this variable. • Are people aware of the disadvantages of driving ICE vehicles and the benefits

of driving EVs? • What is the effect of EA on EV adoption?

Dealer Knowledge De Rubens et al. (2018) studied various attributes of EV dealers such as the salesman’s perceived competence, outlook, passion and skill to make sales and provide customer service, as well as their technology orientation in addition to their understanding of EVs. This study found that due to customers’ lack of familiarity with EVs, they are more dependent on the information which dealer provides them. Hence, customer experiences at auto dealerships may have a big influence on EV purchase decisions and to speed up the adoption of EVs, corporate and policy initiatives that eliminate hurdles at the point of sale are required.

Most Common Theories Utilised in the Literature Theory of planned behaviour (TPB): Several studies (Adnan et al., 2018; Austmann & Vigne, 2021; Egbue & Long, 2012; Lane & Potter, 2007; Mohiuddin et al., 2018; Pradeep et al., 2021; Simsekoglu & Nayum, 2019) confirms that the TPB was useful in predicting consumers’ intention to purchase EVs and had a strong predictive power. This construct primarily incorporates consumer awareness of the environmental effects of driving EVs, particularly in the consumer EV adoption study. Diffusion of Innovations (DOI): By applying the innovative and unique theory of Rogers, Fry et al. (2018) investigate the impact of ‘knowledge and persuasion’ on the choice to accept or reject alternative fuel vehicles. Since DOI theory is adaptable and has a wide variety of applications in several study disciplines, it is suitable to use in EV investigations. The theory is especially intriguing for figuring out what influences EV adoption since it believes that the attributes of the technology, the user and the social system are all significant in the innovation diffusion process and that is the very reason behind its wide application in EV researches (Broadbent et al., 2021; Chen et al., 2020; Fry et al., 2018; Okada et al., 2019). Technology acceptance model (TAM): The TAM framework places more emphasis on employees’ individual choices to adopt new technologies than on

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management’s earlier decision to acquire and implement the technologies into the company, which is widely utilised by many researchers (Huang et al., 2021; Jaiswal et al., 2021; Vuichard, 2021; Wang et al., 2018). Unified Theory of Acceptance and Usage of Technology (UTAUT): Some studies back up the UTAUT applicability in encouraging and pushing consumers to buy EVs (Venkatesh et al., 2003). Several studies demonstrated the model’s relevance in the context of EV motivation. By adding perceived environmental knowledge to the UTAUT model in the context of motivating variables, this study adds to the body of literature (Abbasi et al., 2021; Jain et al., 2022; Wolf & Seebauer, 2014). Additionally, this theory is a synthesis of eight different theories regularly utilised in technology acceptance research, e.g. TPB, TRA, DOI, etc. Hence, this theory possesses wide applicability to EV studies and guarantees the researchers for the best outcome. Studies also link self-image/identity with EV purchasing intentions using the self-image congruency theory (Higueras-Castillo et al., 2019). According to this theory, a product’s appearance matching a consumer’s self-image favourably affects the consumer’s purchasing inclinations. Another model based on norm-activation theory (NAT) is being employed to explain pro-environmental behaviour (He & Zhan, 2018). Some significant study implications will be presented in the part that follows to assist in future research.

Implications and Future Scope Theoretical implications: This study will make it easier for young researchers in particular to comprehend the concepts and methods that have been employed in past studies. Researchers and academicians may find study gaps in terms of methodology, theories and constructs based on the gathered data. Furthermore, it is highly recommended to quantitatively test and validate the model developed in this study to analyse the total influence of awareness on electric mobility (i.e. all three facets mentioned in the study). In addition, new theories or concepts of awareness must be incorporated in future works rather than depending just on one idea or body of literature. Thus, there is adequate room for exploration given the relative dearth of studies that offer quantitative evidence for describing the significance of awareness and knowledge in the adoption of EVs. Policy and managerial implications: The major ways to get beyond these obstacles and accelerate the adoption of EVs include, raising consumer awareness of emissions through government and business promotional activities. With the help of this study, government and companies could plan the best EV-promoting policies and strategies that may benefit greatly from faster EV adoption. Many people worry that some of the practical characteristics of EVs, such as their short driving distance and shortage of charging stations, may provide an unfavourable impression of their usefulness. It is necessary to inform more people about the EV charging infrastructure that is already in place in a certain area. To avoid an excessive flurry at charging points during peak hours, this is especially crucial.

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Government agencies also need to concentrate on developing leasing groups so that consumers can obtain first-hand experience. Local businesses that are ready to invest in an EV repair facility must receive subsidies, much like the current rules that subsidise land for EV manufacturing. Findings help policymakers and managers develop strategies for optimal value creation at a time when customers in emerging nations are becoming more environmentally conscious. In the end, this strategy will support projects in clean and green technology and encourage a higher rate of sustainable vehicle adoption in emerging economies. The government could launch some kind of application that can be used by EV owners to locate EV chargers near them such as ‘EV Roam’ in New Zealand and ‘e-Amrit’ in India (Broadbent et al., 2018). Increasing awareness programmes like this could assuage concerns and lessen range anxiety. Manufacturers of EVs and the appropriate governmental bodies, for instance, may provide specific statements and case studies outlining the features, capabilities, applications and advantages of EVs. The use of other information dissemination platforms, such as news outlets, magazine articles, radio programmes, television shows and new social media, can also be used to educate the general public about the importance, utility and advantages of EVs and give consumers a better understanding of them. Additionally, manufacturers can start the Trade Show of EVs as well as several cars sharing activities including visiting an EV experience hub, taking EV test drives and renting EVs. Hence, the last and final portion will wrap up our research.

Conclusion In conclusion, this literature review underscores the importance of consumer knowledge in driving EV adoption. By understanding and addressing the specific facets of awareness, namely EV technology, government support and environmental knowledge, stakeholders can effectively promote consumer intentions to adopt EVs and accelerate the transition towards a greener and more sustainable future. To foster a smooth transition towards widespread EV adoption, policymakers, manufacturers and stakeholders should prioritise initiatives that enhance consumer knowledge in these identified areas. Promoting public awareness campaigns, disseminating accurate information and highlighting the benefits and government support associated with EVs can strengthen consumer intentions to embrace this sustainable transportation option. Moreover, the government will be able to reduce carbon emissions following the SDGs with the support of consumer encouragement and the adoption of these vehicles. Therefore, emphasising the financial and environmental advantages of EVs and highlighting the advancements in EV infrastructure and technology may help to paint a more favourable picture of the practical benefits of EVs, and thereby sufficiently motivate consumers to switch to this mode of transportation. The literature on the prospects for EV adoption and the role of awareness is lacking in most developing nations. More studies are required to investigate the impacts of consumer technology knowledge regarding EVs on their adoption

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intention. Nevertheless, this study serves as a foundation for operationalising future studies within a pre-existing framework and demonstrates how future research may enhance our understanding of the subject. Further research endeavours are undoubtedly crucial to offer decision-makers enhanced understandings of the determinants impacting EV adoption within a given nation. Such studies are essential for informing and developing strategies that effectively bolster the pursuit of EV adoption goals. It is particularly heartening for policymakers and stakeholders to recognise that fostering a positive perception of EV technology plays a pivotal role in driving its adoption. Thus, to enable a shift towards cleaner, more effective and economical transportation options for all, the authors must be nevertheless optimistic that lingering technological, legislative, cultural, behavioural and business-model obstacles may be overcome over time through widespread dissemination of knowledge and awareness related to EV.

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Appendix

Title

Abbasi et al. (2021) ‘Consumer motivation by using unified theory of acceptance and use of technology towards electric vehicles’ Adnan et al. (2018) ‘What make consumer sign up to PHEVs? Predicting Malaysian consumer behaviour in adoption of PHEVs’ Austmann and ‘Does Vigne (2021) environmental awareness fuel the electric vehicle market? A Twitter keyword analysis’ Broadbent et al. ‘Increasing electric (2021) vehicle uptake by updating public policies to shift attitudes and perceptions: Case study of New Zealand’

Journal

Sustainability (Switzerland)

Country

Malaysia

Sample Collection (n)

Method of Estimation

Theory

Factors/Constructs in the Research Model Performance expectancy, effort expectancy, social influence, techno philia and environmental knowledge Subjective norm, personal moral norm, perceived behavioural control and attitude

199 responses

PLS-SEM

Unified Theory of Acceptance and Usage of Technology (UTAUT)

Transp. Res. Malaysia Part A: Policy and Practice

403 samples

PLS-SEM

Extended TPB

Energy Economics

EU and EFTA

29 countries

Panel data regression

Theory of planned behaviour (TPB)

Energies

New Zealand

588 random samples from national panel

Pearson’s Diffusion of Chi-squared tests Innovation and ANOVAs

EV purchase intentions and environmental awareness (EA)

Perceptions, attitudes, awareness of incentives

Divya Singh and Ujjwal Kanti Paul

Author(s) (Year)

348

Table 21.A1. Summary of all the Relevant Studies Included in the Review.

¨ Bruckmann (2022)

Chen (2020)

De Rubens et al. (2018)

Energy Policy

Switzerland

Renewable and Sustainable Energy Reviews

Denmark, 4,885 through Finland, Qualtrics Paid Iceland, Panel Service Norway and Sweden

Smart and Sustainable Built Environment

India

‘Dismissive and deceptive car dealerships create barriers to electric vehicle adoption at the point of sale’

Nature Energy Denmark, 82 car dealerships Finland, Iceland, Sweden and Norway

4,149 conventional Ordinary least car holders squares (OLS) regression

Chi-square testing, hierarchical regression analysis, ANOVA

355 vehicle owners Structural of Delhi equation modelling

ANOVA and regression models

Technological knowledge and adoption intention of new energy technology

Diffusion of Innovation

Socio-demographic, technical, economic and behavioural factors

Nil

Environmental concern, knowledge of EVs and subjective norms, attitude and willingness to adopt Salesperson’s perceived professionalism, attitude, enthusiasm, ability to sell and service, EV knowledge

Nil

(Continued)

349

Nil

Adoption of Electric Vehicles

Dash (2021)

‘The effects of policies providing information and trialing on the knowledge about and the intention to adopt new energy technologies’ ‘Assessing the socio-demographic, technical, economic and behavioural factors of Nordic electric vehicle adoption and the influence of vehicle-to-grid preferences’ ‘Determinants of EVs adoption: a study on green behaviour of consumers’

Table 21.A1. (Continued)

Du et al. (2018)

‘Who buys New Energy Vehicles in China? Assessing social-psychological predictors of purchasing awareness, intention, and policy’ ‘Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions’ ‘The influence of knowledge and persuasion on the decision to adopt or reject alternative fuel vehicles’ ‘Mainstream consumers driving plug-in battery-electric and plug-in hybrid electric cars: A qualitative analysis of responses and evaluations’

Egbue and Long (2012)

Fry et al. (2018)

Graham-Rowe et al. (2012)

Journal

Country

Sample Collection (n)

Method of Estimation

Theory

Factors/Constructs in the Research Model

Transp. Res China Part F: Traffic Psychology and Behaviour

811 valid Responses

Correlation analysis and hierarchical multiple regression analyses

Theory of planned behaviour (TPB)

Attitudes, subjective norms, perceived behavioural control, personal norms, low-carbon awareness and policy

Energy Policy

The United States

481 respondents from tech. university

Chi-square test

Nil

Socio-technical barriers such as battery range, EV concern, attitude and motivation

Sustainability (Switzerland)

The United Kingdom

413 representatives Pearson’s Chi-Square test and Spearman’s rho (rs)

Diffusion of Innovation

Knowledge, persuasion and adoption

40 vehicle drivers

Grounded theory

Cost minimisation, vehicle confidence, vehicle adaptation demands, environmental beliefs, impression management and EVs as a ’work in progress

Transp. Res. The United Part A: Policy Kingdom and Practice

Semi-structured interview, Grounded theory analysis

Divya Singh and Ujjwal Kanti Paul

Title

350

Author(s) (Year)

The United States

321 respondents

Journal of Cleaner Production

China

396 responses via online survey

‘Evaluating consumer attitudes towards electromobility and the moderating effect of perceived consumer effectiveness’ Huang et al. (2021) ‘The influence of knowledge management on adoption intention of electric vehicles: perspective on technological knowledge’

Journal of Retailing and Consumer Services

Spain

404 sample via quasi-experimental questionnaire

Industrial Management and Data Systems

China

443 participants

Higueras-Castillo et al. (2019)

Structural equation modelling (SEM)

Nil

Perceived risk, new product knowledge, attitude towards electric aeroplanes, trust and adoption intention Factor analysis Norm Awareness of Path analysis Activation consequences, and Hierarchical theory (NAT) ascription of regression responsibility, perceived consumer effectiveness, personal norms and perceived risk and benefits Partial least Self-image Green self-identity, squares-SEM congruence trust, prior theory and the knowledge, uses and perceived consumer gratifications effectiveness, theory (UGT) attitudes and adoption intention

Structural equation modelling

Technology Consumer acceptance technological model (TAM) knowledge, perceived ease of use, perceived usefulness and perceived fun to use

351

Journal of Air Transport Management

Adoption of Electric Vehicles

‘An electric airplane: Assessing the effect of travelers’ perceived risk, attitude, and new product knowledge’ He and Zhan (2018) ‘How to activate moral norm to adopt EVs in China: An empirical study based on extended NAM’

Han et al. (2019)

(Continued)

352

Table 21.A1. (Continued) Title

Jaiswal et al. (2021) ‘Investigating the role of electric vehicle knowledge in consumer adoption: evidence from an emerging market’ Jenn et al. (2018) ‘Effectiveness of electric vehicle incentives in the United States’ Joshi et al. (2022) ‘Assessing adoption intention of electric vehicles in India: The mediating role of government policies’ Kester et al. (2019) ‘Public perceptions of electric vehicles and vehicle-to-grid (V2G): Insights from a Nordic focus group study’

Journal

Country

Sample Collection (n)

Method of Estimation

Benchmarking

India

565 samples

Energy Policy

The United States

All new vehicle Regression registrations across analysis all 50 states of the United States 399 responses Factor analysis, regression and Path analysis

European Jour. India of Trans & Infrastructure Res.

Transp. Res. Part D: Transport and Environment

Nordic 61 participants region from eight focus (Iceland, groups Sweden, Denmark, Finland and Norway)

SEM and path analyses

Qualitative analysis

Theory

Factors/Constructs in the Research Model

Technology EV knowledge, acceptance adoption intention, model (TAM) perceived usefulness, perceived ease of use and perceived risk Nil

Nil

Nil

Incentives, tax credits, consumer awareness and EV adoption Price, environmental concern, infrastructure requirement and knowledge of EV EV’s environmental sustainability, range, charging, price, social status, sound and acceleration

Divya Singh and Ujjwal Kanti Paul

Author(s) (Year)

21 cities of The United States

2,304 samples

Journal of Cleaner Production

The United Kingdom

‘Consumers continue to be confused about electric vehicles: comparing awareness among Canadian new car buyers in 2013 and 20170 ‘Environmental knowledge, awareness, and business school students’ intentions to purchase green vehicles in emerging countries’

Environmental Research Letter

Sustainability (Switzerland)

Long et al. (2019)

Mohiuddin et al. (2018)

Multiple regression

Consumer theory

Consumer knowledge, policy, attitude and misperception about price and savings

Samples not known Review

Theory of planned behaviour, Value-BeliefNorm theory

Canada

In 2013 (n 5 2922) Chi-square test and in 2017 (n 5 1808)

Nil

Consumer attitudes, other psychological and situational factors and the adoption of cleaner car technologies Consumer familiarity, understanding, experience and awareness of public PEV chargers

Malaysia

200 students from three universities

Theory of planned behaviour (TPB)

Structural equation modelling

Environmental knowledge, awareness of consequences, attitude, subjective norms, perceived behavioural control

(Continued)

353

Energy Policy

Adoption of Electric Vehicles

Krause et al. (2013) ‘Perception and reality: Public knowledge of plug-in electric vehicles in 21 U.S. cities’ Lane and Potter ‘The adoption of (2007) cleaner vehicles in the UK: exploring the consumer attitude-action gap’

354

Table 21.A1. (Continued) Title

Jain et al. (2022)

‘What drives adoption intention of electric vehicles in India? An integrated UTAUT model with environmental concerns, perceived risk and government support’

‘Understanding the socio-technical nexus of Nordic electric vehicle (EV) barriers: A qualitative discussion of range, price, charging and knowledge’ Okada et al. (2019) ‘Effect of environmental awareness on purchase intention and satisfaction pertaining to electric vehicles in Japan’

Noel et al. (2020)

Journal

Country

Sample Collection (n) 284 respondents using purposive sampling

Method of Estimation

Factors/Constructs in the Research Model

Unified theory of Acceptance and Usage of Technology (UTAUT)

Performance expectancy, effort expectancy, social influence, facilitating conditions, perceived risk, environmental concern, government support and adoption intention Range, price, charging and knowledge

Research in Transport Business & Management

India

Energy Policy

Denmark, 227 semi-structured Qualitative Finland, interviews from analysis using Iceland, experts cluster analysis Norway and Sweden

Nil

Transp. Res. Part D: Transport and Environment

Japan

Diffusion of Innovation (DOI)

Out of 246,642 respondents, 785 were EV owners

Hierarchical regression analysis

Theory

Structural equation modelling

Environmental awareness, evaluation of EVs and purchase intention

Divya Singh and Ujjwal Kanti Paul

Author(s) (Year)

Ireland

17 semi-structured interviews

Thematic analysis

Nil

Technical, financial, organisational and environmental themes

Transp. Res. Part D: Transport and Environment

India

385 individuals

Multiple regression and mediation analysis

Theory of planned behaviour (TPB)

‘Analysis of the barriers to the adoption of zero-emission vehicles in Spain’ Rotaris et al. (2021) ‘The slow uptake of electric cars in Italy and Slovenia. Evidence from a stated-preference survey and the role of knowledge and environmental awareness’ Ruoso and Ribeiro ‘An assessment of (2022) barriers and solutions for the deployment of electric vehicles in the Brazilian market’

Transp. Res. Spain Part A: Policy and Practice

1,474 drivers

Cluster analysis

Nil

Attitude, subjective norms, perceived behavioural control, knowledge of maintenance and instrumental attributes Knowledge of ZEV, purchase price and fuel availability and government support

Transp. Res. Italy and Part A: Policy Slovenia and Practice

Italian (N 5 996) and Slovenian (N 5 938)

Hybrid mixed logit model (HMXL)

Rational choice theory

BEV knowledge and environmental awareness

Transport Policy

31 interviewees

Qualitative analysis

Nil

Environmental, social, economic, policy, technical factors

Rosales-Tristancho et al. (2022)

Brazil

355

Case Studies on Transport Policy

Adoption of Electric Vehicles

O’Neill et al. (2019) ‘Barriers to electric vehicle uptake in Ireland: Perspectives of car-dealers and policy-makers’ Pradeep et al. ‘Does perceived (2021) technology and knowledge of maintenance influence purchase intention of BEVs’

(Continued)

356

Table 21.A1. (Continued) Title

Journal

Country

Sample Collection (n)

Method of Estimation

‘The influence of financial incentives and other socio-economic factors on electric vehicle adoption’ ‘Predictors of intention to buy a battery electric vehicle among conventional car drivers’

Energy Policy

Transp. Res. Norway Part F: Traffic Psychology and Behaviour

205 samples

Tarei et al. (2021)

‘Barriers to the adoption of electric vehicles: Evidence from India’

Journal of Cleaner Production

Vuichard (2021)

‘Electrifying the Energy company car: Research and Identifying hard and Social Science soft barriers among fleet managers in Switzerland’

10 experts from Hybrid automobile and EV two-phased industry multi-criteria decision-making (MCDM) 10 companies (field Qualitative experiment) analysis

Sierzchula et al. (2014)

Simsekoglu and Nayum (2019)

The Data collected Netherlands from 30 Countries

India

Switzerland

Ordinary least squares (OLS) regression and sensitivity analyses PCA, multiple hierarchical regression and mediation analysis

Theory

Nil

Factors/Constructs in the Research Model

Financial incentives and other socio-economic factors like charging infrastructure, model availability Theory of Perceived accident planned risk, knowledge, behaviour perceived car (TPB) attributes, environmental attributes and intention to buy a BEV Nil Technical, infrastructural, financial, behavioural and external barriers Technology Soft barriers such as acceptance lack of knowledge model (TAM) and the perceived low level of EV usability

Divya Singh and Ujjwal Kanti Paul

Author(s) (Year)

Wang et al. (2018)

Wolf and Seebauer (2014)

Zhang et al. (2011)

‘Policy implications for promoting the adoption of electric vehicles: Do consumer’s knowledge, perceived risk and financial incentive policy matter?’ ‘Technology adoption of electric bicycles: A survey among early adopters’

320 consumers

Structural equation modelling

Technology Knowledge, acceptance perceived usefulness, model (TAM) perceived risk, attitude, financial incentive and adoption intention

Transp. Res. Austria Part A: Policy and Practice

1,398 e-bike purchasers

Structural equation modelling

Unified Theory of Acceptance and Usage of Technology (UTAUT)

Energy Policy

299 participants

Logistic Nil regression model

China

Perceived usefulness, ease of use, facilitation conditions, social norms, personal norms, attitude and car availability Variables related to EV awareness and acceptance

Adoption of Electric Vehicles

‘Analysing public awareness and acceptance of alternative fuel vehicles in China: The case of EV’

Transp. Res. China Part A: Policy and Practice

357

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Index Accessibility, Availability, Accuracy and Affordability (four As), 177, 180 Accident causation hypothesis, 249 Accra economy, 202–203 Activated sludge model, 101 Adaptation, 290 Administration, 320 Adoption, 333 Advanced technologies, 134 Agriculture, 292–297 AlphaGo, 51–52 Alternative fuel vehicles (AFVs), 332 Amazon Web Services, 279–280 Amsterdam smart city, 199–200 Analytic technologies, 64 Artificial intelligence (AI), 2, 44–45, 51–53, 70, 114, 134–136, 155, 166, 197, 232, 235, 240, 258–259, 278, 291–292 advances technology, 177–178 technology in agriculture, 293 Artificial neural network (ANNs), 232–235 Augmented Reality (AR), 135, 227–228 Automation, 44, 70, 133–135 Autonomous robots, 136 Awareness, 332 of EVs and technology, 336–337 of government assistance in form of policies and incentives, 337–338 Banking, 44 Battery electric vehicle (BEV), 337 Bhuvan, 234 Bias in AI, 146

in emerging technologies, 155–157 Bibliographic coupling of documents, 5–12 Bibliometrics, 2 analysis, 2 review, 167 Big data, 114, 117, 123 Big data analytics (BDA), 45–46, 278–279 Bio-based nanomaterials, 104–105 Biofuels, 105 Biotech-Krishi Innovation Science Application Network (Biotech-KISAN), 313 Bitcoin, 217 Blockchain, 44, 114, 117, 135, 235–236 blockchain-based solutions, 214–215 for food supply chain disruption management, 322–323 for governance and administration, 324–325 in healthcare systems, 45–46 in higher education, 46–47 for human resource management, 323 for modern education and certification, 324 Blockchain technology (BCT), 103, 217, 235, 291–292, 320 in agriculture, 295–297 and current applications, 321 for healthcare management, 321–322 implications and future research recommendations, 325–326 literature review, 321 against ongoing and future pandemics, 321–325

360

Index

Blue-collar workers, 308–309 Bowtie model, 249 Business, 147, 149, 151 enabler skills, 67 innovation, 11 sector advancement, 192–193 Carbon market, 214 Cashless economy, 24 City officials, 194 Classroom learning, 228 Classroom teaching, 231 Clean Development Mission (CDM), 104–105 Climate Awareness Bond, 215 Climate change, 215 Climate-smart agricultural practices (CSAP), 290 agriculture and technology 4.0, 292–297 approach, 290–291 industry 4.0, 291–292, 297–298 technology in agriculture, 298–299 Climate-smart agriculture (CSA), 290–291 Cloud computing, 45–46, 114, 123, 135, 231–232, 279–280 Collaborations, 229–231 COMAX, 293 Communication skills, 51–52 Competency, 68 Computer-aided design (CAD), 271 Computer-aided manufacturing (CAM), 271 Conceptualisation, 257–258 Confrontation strategies, 51–52 changes in industrial structure and global trend through industry 4.0, 53–54 for employment in industry 4.0, 57–60 impact of industry 4.0 on future employment, 54–56 literature review, 52–53 policy discussion and research implications, 60

Consulting, 44 Contact tracing-Bluetooth technology, 178 Content analysis, 2, 10 Corporate green bonds, 215–216 Corporate social responsibility (CSR), 80–81 Correction methods, 60 COTFLEX, 293 COVID-19 pandemic, 80, 130, 164 Crowdsourcing, 123 Customer centricity, 291–292 Customer relationship management (CRM), 280–281 Cyber-physical systems (CPS), 134, 136–137, 243–244, 271–272 Data analytics, 44, 133–135 Data driven decisions, 231–232 Database, 235–236 Database management systems (DBMS), 235 Dealer knowledge, 339 Decentralised Financing (DeFi), 103 Decision support system, 139 Deglobalisation, 230 Department of Cooperative Governance (DCoG), 203–204 Desktop publishing (DTP), 233–234 DICOM, 178 Diffusion of Innovations (DOI), 339 Digital building block skills, 67–68 Digital competencies implications of digital competencies on future of work, 69–70 for sustainability, 68 Digital entrepreneurship, 95–100 and women, 311–312 Digital evolution, 101–102 Digital healthcare, 163–164 challenges of digital healthcare equity, 180 core services, 176 determinant during core services, 176

Index human factor, 176 keywords from previous articles, 173–175 literature review of study, 164–167 methodology, 167–168 propositions for future studies, 171 resources, 175–176 result, 168–180 study, 176–178 technology and COVID-19, 179–180 Digital image processing, 233–234 Digital inclusion, 310 Digital India, 166 Digital initiatives, 114 conceptual framework, 117–121 dynamic capabilities, 121–124 literature review, 116–117 market performance, 121–122, 124 review of studies, 118–120 Digital leaders, 69 Digital management, 54–56 Digital payments, 30 Digital space, 10 Digital technologies (DTs), 2, 64–65, 176, 205, 227, 229, 243–244, 309 bibliographic coupling of documents, 5–12 contributing countries, 3–4 implications, 14 keyword co-occurrence analysis, 4–5 methodology, 2 publications trend, 2–3 text analysis of future scope, 12 transformation skills, 67–69 Digital tokenisation, 219 Digital tools, 123 Digital transformation, 46–47, 64, 122 digital technology transformation skills, 67–69 to future of work, 64–65 implications of digital competencies on future of work, 69–70

361

importance of retooling and upskilling for sustainability, 70–71 new digital age and possible effects on sustainability, 65–66 opportunities and challenges, 71–72 retooling and upskilling for, 70 Digital twins, 276–277 Digital websites, 114 Digital-related competencies, 70 Digitalisation, 2, 14, 64, 164, 258–259 accessibility by respondents, 31 awareness of respondents, 32 frequency of usage, 34 of health, 171–172 in Increasing Women’s Workforce Participation, 308–312 methods used by respondents, 33 pre-requisite for online banking, 32 of slum dwellers, 30–34 usage by respondents, 32–33 Digitalising industrial processes, 240 Digitisation, 95–100 Dimension of digital competencies, 68–69 Directory of Open Access Journal (DOAJ), 271–272 Disruptive technological adaptation, 46–47 Disruptive technological innovation, 46–47 Disruptive technologies, 44, 276 future research directions, 47 in professional services, 45–47 Distributed Ledger Technology (DLT), 217–218 Do-it-yourself bonds (DIY bonds), 221 DuPont safety excellence principles, 249 Dynamic capabilities, 115–116, 121–124 E-commerce, 130 companies, 130–131 factors influencing carbon emission in e-commerce returns, 133

362

Index

E-health, 166 EC Electronics, 102–103 Economic growth, 150 EcoTEDA initiative, 105–106 Education, 11, 58–59, 323 Education for Sustainability (EfS), 226–227 Educational institutions, 228–230 Efficient market hypothesis (EMH), 115–116 Electric vehicles (EVs), 332 background literature, 333 common theories, 339–340 implications and future scope, 340–341 knowledge, 333 methodology, 333–334 results, 334–339 Electronic health records (EHRs), 177 Embedded sensors, 269–270 Emerging technologies, 155–157 Employees, 59–60 Employment, 51–52 Energy management, 11 Energy trading, 214 Enterprise resource planning (ERP), 271 Enterprises, 57–58 Entrepreneurship, 310–311 Environment, 101 Environment, Social and Governance Investing (ESG Investing), 146 measures, 151–152 practice and problem, 151–152 theoretical and practical implications, 152 Environmental awareness (EA), 338 Environmental deterioration, 215 Environmental justice, problem of bias and implications for, 156–157 Environmental knowledge, 338–339 Ethereum, 295–297 European Free Trade Association (EFTA), 338

European Union (EU), 338 Event study approach, 114 Evolution of employment, 51–52 Explainability, 157 Extended reality (XR), 227–228 Female labour force participation, 308 Fifth Industrial Revolution (Industry 5.0), 94, 101, 239–240, 242 Financial systems and growth, 11 Financing, 214–215 Food management, 11 Food supply chains, 320 Foundational Literacy and Numeracy (FLN), 228–229 Fourth Industrial Revolution (Industry 4.0), 45–46, 51–53, 134, 229, 231, 270 based framework for managing reverse logistics, 137–139 changes in industrial structure and global trend through, 53–54 comparison of industry 4.0 strategies of major countries, 53 confrontation strategies for employment in, 57–60 CSAP, 291–292 frameworks, 280–281 Global Electronics Industry 4.0 Solution Lead at IBM, 281–282 industrial internet of things technologies, 276–281 impact of industry 4.0 on future employment, 54–56 literature analysis, 271–273 M/s Frost & Sullivan, 282–283 technologies in logistics, 133–137 theoretical background, 273–276 Future employment, impact of industry 4.0 on, 54–56 Future Internet (FI), 269–270 Future of work connecting digital transformation to, 64–65

Index implications of digital competencies on, 69–70 Fuzzy Logic (FL), 293 Gamification, 235–236 Gender, skills and responsibility, 11 Geospatial technologies, 229–231 Global Electronics Industry 4.0 Solution Lead at IBM, 280–282 Global Hunger Index, 290 Global Positioning System (GPS), 137 GoDaddy, 279–280 Google Cloud Platform (GCP), 279–280 Google Maps, 230 Governance, 320 Government, 57 Government of India (GOI), 80 Green bonds, 214 objective and methodology, 215–221 Green energy, 104, 216 Green finance, 214–215 Green investment funds, 214 Green technologies, 103–105 Greenease, 102–103 Greenhouse gas emissions (GHG emissions), 290–291 Greenwashing, 216 Gross Domestic Product (GDP), 304 Harvesting, 298 Health, 102 informatics, 177 Health equity, 165, 171–172 previous and recent trends in, 172–175 Healthcare, 44 Heinrich’s Law, 249 Heterophilic ties, 82–84 Higher education, 44 Higher purpose, 258, 260–261 Holland’s theory, 54–56 Homophilic ties, 82–84 Hospitality, 44

363

Human capital theory, 305 Human knowledge, 191–192 Human resource management (HRM), 323 blockchain for, 323 Human Rights (HR), 149 Human-centricity approach, 243–244 Humans, 51–52 Hybrid cloud, 279–280 Hybrid review method, 168 Hyperledger, 295–297 IBM Cloud, 279–280 IKEA, 101 Image processing, 232–235 Immersive technologies, 227–228 Indian economy, 24 Individual spirituality, 259 Industrial Internet of Things (IIoT), 271–272 technologies, 276–281 Industrial symbiosis, 105–106 Industry 1.0 evolution to industry 5.0, 247–248 Information and communication technology (ICT), 12, 54, 166, 188–189, 270–271, 308 Information Technology (IT), 123 Infrastructure as a service (IaaS), 231, 279–280 Innovation, 94, 101–102 Innovative ecosystems, 94–95 Insurance, 44 Integrated skills for digital economy, 67–68 Integration, 227 of industry 5.0 and safety 4.0, 250–251 Intelligent warehousing, 134 Interconnectedness, 258, 261 Intergovernmental Panel on Climate Change (IPCC), 290 Internal combustion engine vehicles (ICEVs), 332

364

Index

International Business Machines Corporation (IBM), 202–203 International Capital Market Association (ICMA), 214 International Monetary Fund (IMF), 147 Internet, 231–232 Internet of Services (IoS), 282–283 Internet of Things (IoT), 44, 53, 65, 135–136, 188, 205, 246, 258–259, 269–270, 278, 291–292, 321 in agriculture, 295 Internet Protocol (IP), 282–283 Internet-operated therapeutic software, 178 Investments, 214 Investors, 215 Istanbul smart city, 198–199 ITC E-Choupal, 298–299 Johannesburg, South African Smart City, 203–204 Just-In-Time (JIT), 275–276 Kaggle, 234 Keyword co-occurrence analysis, 4–5 Knowledge, 333 Kolkata Municipal Corporation (KMC), 24–25, 27 Lagos smart city context, 201–202 LaTeX, 228 Leadership, 44 competencies, 68 Lesbian, gay, bisexual and transgender queer (LGBTQ), 156 Life cycle assessment (LCA), 11, 282–283 Life Years Index, 319 Low-Middle Income Countries (LMICs), 163–164 M-Health Voice Message Service, 178 M-Pesa, 66–67

M/s. Frost & Sullivan–Framework, 280, 282–283 Machine learning (ML), 2, 45–46, 52–53, 134, 146 Machine-to-machine communication (M-2-M communication), 276 Manufacturing industry, 242 Market performance, 121–122, 124 Market reactions, 114 Market-based methods, 116–117 Massive Open Online Courses (MOOCs), 229–231 Meaningfulness, 258, 260 Metaverse, 227–228 Microsoft, 104 Microsoft Azure, 279–280 Microsoft PowerPoint, 228 Microsoft Word, 228 Millennium Development Goals (MDGs), 226 Mindfulness, 258, 262 Mission Indradhanush, 167 Mitigation of Climate Change in Agriculture programme (MICCA programme), 290–291 Mixed reality (MR), 227–228 mMitra application, 178 Mobile Alliance for Maternal Action (MAMA), 178 Mobile health (m-health), 165 MS Access, 235 MYSQL, 235 Nanoparticles, 104–105 Nanotechnology solutions, 104–105 National Sample Survey Organization (NSSO), 24–25 Nationally Determined Contribution (NDC), 214 Network collaboration, 134 Network ties scholars, 82 New digital age, 65–66 Norm-activation theory (NAT), 340

Index Notepad, 228 One Laptop per Child (OLPC), 152–153 Online shopping, 130–131 Online trade, 130–131 Open data repository, 232–235 Open Government Data Platform India (OGD Platform India), 234 OpenStreetMap, 234 Oracle, 235 Organisational spirituality, 259 Oslo smart city, 200–201 PACS, 178 Paradigm shift, 157–158 Patient transformation, 164 Performance Auditing and Review approach to Operation (POPMAR), 249 Personal protective equipment (PPE), 246, 250 Piper Alpha tragedy, 245 Plan Do Check Act (PDCA), 249–250 Platform as a Service (Paas), 279–280 POMME, 293 Post-harvesting, 298 Pre-harvesting, 297–298 Predictive maintenance, 134, 136–137 Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach (PRISMA approach), 2–3, 334 Prezi, 228 PricewaterhouseCoopers (PwC), 280 Primary account number (PAN), 217 Private cloud, 279–280 Private mobility, 332 Production worker (see Blue-collar workers) Professional services, 44 disruptive technology in, 45–47 Professional services firms (PSFs), 45 Public cloud, 279–280

365

Public services, 81 Public Services Supply Chain (PSSC), 80–81 Purchasing power parity (PPP), 148 Rackspace, 279–280 Radio Frequency Identification technology (RFID technology), 133–134, 249–250, 276, 295 Real-time data collection and analysis, 134, 136 Real-time visibility, 134 Reduce-Reuse-Recycle, 229 Reference Architecture Model Industry 4.0 model (RAMI 4.0 model), 280 Resiliency, 244 Resilient systems, 320 Resource-based view (RBV), 115–117 Resource/capabilities mechanism, 114 Reverse logistics (RL), 131 factors influencing carbon emission in e-commerce returns, 133 growth of global parcels returns, 131–132 industry 4.0 based framework for managing, 137–139 industry 4.0 technologies in logistics, 133–137 systems, 132–133 RIASEC, 54, 56 Robens Report of 1972, 249 Robotics, 52–53, 70, 278 technology, 240 Robotics process automation (RPA), 278 Robots, 44, 51–52, 276 Safety 2.0, 249 Safety 4.0, 242 drivers, 251 framework of safety management in industry 5.0, 247–251 future work, 252 implications, 251–252

366

Index

literature review, 242–247 Safety culture, 246–247 Safety intelligence (SI), 240 Safety management, 244–247 evolution, 248–250 framework of safety management in industry 5.0, 247–251 practices, 240 Scalability, 152–155 Scale-up problem, elements of, 153–155 Scholars, 82 Science, 94 Science, technology, engineering and mathematics (STEM), 257–258 Science mapping method, 168 Securities and Exchange Commission (SEC), 215–216 Security market, 221–222 Seizing, 121–122 Self-help groups (SHGs), 26 Self-image congruency theory, 340 Sensing, 121–122 Sensors, 276 Simple Storage Service (S3), 279–280 Singapore smart city, 197–198 Singapore University of Technology and Design (SUTD), 197 Skilled Through Alternative Routes (STARs), 229 Slum dwellers, 24–25 age of respondents, 28 cashless economy, 24 data analysis and findings, 27–34 demography of respondents, 27–30 digitalisation of slum dwellers, 30–34 education of respondents, 28–30 geographical location of sample, 27 household structure of respondents, 28 literature review, 25–27 objectives of study, 27 occupation of respondents, 30 research methodology, 27

SDG and women empowerment, 34–37 slum economy, 24–25 Slum economy, 24–25 Small and medium-sized enterprises (SMEs), 276 Smart cards, 269–270 Smart city, 11, 188 in African Sub-Sharan continent, 194–196 for developed countries and SubSaharan African countries, 205 framework for case-study evaluation and synthesis, 196 global development and characteristics and framework, 189–194 initiatives and features, 190 insights, 196–204 scorecard, 197 Smart commerce, 192–193 Smart contracts, 323 Smart factory, 58, 243–244, 275–276 Smart manufacturing, 52–53 Smart networking, 193–194 Smart routing, 134, 137 Smartisation, 205 Smartphone services, 193–194 SMARTSOY, 293 Social capital, 191–192 Social media, 231–232 channels, 114 technologies, 64 Social network analysis (SNA), 81 Social networking technologies (SNTs), 81 data collection and analysis, 84–87 perspective, 81–82 research study methodology, 83 theoretical foundation, 81–82 Social networks, 81–82 Social sphere, 83–84 Socio-digital technology, 193–194

Index Software as a service (SaaS), 231, 279–280 Solar power, 104–105 South African Smart Cities Framework (SCF), 203–204 Spirituality, 258, 260 Stakeholder theory, 149 Storage solutions, 276 Structured Analysis and Design Technique (SADT), 245–246 Structured Query Language (SQL), 235 Supply chain management (SCM), 280–281 Sustainability, 2, 45–46, 80–81, 102, 132, 145–146, 214, 225–226, 244 importance of retooling and upskilling for, 70–71 possible effects on, 65–66 and sustainable development, 148–149 Sustainable cities, 199 Sustainable competitive advantage, 115 Sustainable development, 2, 94–95, 146, 225–226, 305 business, 147–151 strategy, 259 techies, 258–259 technological innovation in, 95–103 Sustainable supply chain, 11 Swiss cheese model, 249 System of Rice Intensification (SRI), 105–106 Systematic literature review (SLR), 2, 168, 333 Techies, 257–258 higher purpose, 260–261 interconnectedness, 261 mindfulness, 262 sustainable development, 258–259 workplace spirituality, 259–260 Technological innovation, 44 challenges in adopting, 105–106

367

for social and environmental challenges, 101–103 in sustainable development, 95–103 Technology, 66, 94, 188, 191–192 in agriculture, 298–299 characteristics, 191 ITC E-Choupal, 298–299 literature review, 95–96, 99 recent technological advancements, 103–105 technology 4.0, 292–297 Technology acceptance model (TAM), 339–340 Technology intelligence, 270 TECHO technology, 167 Telehealth, 102 Telemedicine, 166, 178 Text analysis, 2 of future scope, 12 Text-to-speech converter (TTS converter), 293 Theory of planned behaviour (TPB), 339 Three-dimensional printers (3D printers), 58 3D printing, 276–277 Tokenisation, 214–215, 217–220 Transforming, 121–122 TreeMap, 272 Uber, 54–56 UN Food and Agriculture Organization (FAO), 290 Unified Theory of Acceptance and Usage of Technology (UTAUT), 340 United Nations (UN), 2, 66, 247, 305, 307 United Nations Environment Programme (UNEP), 65 United Nations Sustainable Development Goals (SDGs), 2, 27, 34, 37, 65, 95, 146, 165, 195–196, 214–215, 247, 290, 304–305, 332 localising, 10

368

Index

women workforce participation, 305–308 Urban slums, 40 Urbanisation, 195–196 Verizon Cloud, 279–280 Virtual and augmented reality (VRAR), 58 Virtual reality (VR), 227–228 VMware, 279–280 Vodafone Sakhi, 313 Waste reduction technologies, 103 Web GIS, 293 Web of Science (WoS), 2, 167, 271–272 Web-based self-help intervention, 178 White-collar jobs, 310 Window dressing, 216 Wireless local area networks (WLAN), 295 Wireless Sensor Network (WSN), 295 Women in agriculture and digitalisation, 309–310 in blue-collar jobs and digitalisation, 308–309

empowerment, 34–37 in entrepreneurship and digitalisation, 310–311 in white-collar jobs and digitalisation, 310 Women workforce participation, 304 barriers to, 305 digitalisation in increasing, 308–312 future research agenda, 313–314 implications, 312–313 and sustainable development goals, 305–308 theoretical background and existing literature on, 305–308 WomenReBOOT, 313 Workplace accidents, 240 spirituality, 258–260 World Bank, 147 World Commission on Environment and Development (WCED), 258–259 World Economic Forum (WEF), 65 World Health Organization (WHO), 80, 320