Management for Digital Transformation (Management and Industrial Engineering) 3031420594, 9783031420597

Table of contents :
Preface
Contents
Editors and Contributors
Digital Transformation of Organizational and Management Controls—Review and Recommendations for the Future
1 Introduction
2 Organizational and Management Controls and Systems
3 Research Approach
3.1 Sample Selection
3.2 Overview of Technologies
4 Findings
4.1 Drivers for Utilizing Digitalization in Management and Organizational Controls
4.2 Utilizing Novel Digital Tools in Management Control Systems and Organizational Controls
4.3 Digitalization’s Effects on Decision-Making Quality and Effectiveness
4.4 Digitalization’s Effect on Performance
5 Directions for Future Research
6 Conclusions
References
Examining the Role of Technology Transfer on Digitalization: Consequences and Challenges
1 Introduction
2 Conceptual Foundations: Technology Transfer
2.1 Advantages of TT
2.2 Disadvantages of TT
3 Conceptual Foundations: Digitalization
3.1 Advantages of Digitalization
3.2 Disadvantages of Digitalization
4 The Role of Technology Transfer in Digitalization
5 Real Evidence of TT on Digitalization: The MATES Project
5.1 Methodological Approach
5.2 Practical Examples of Digitalization
5.3 Difficulties and Recommendations
6 Challenges and Implications
6.1 Technological Challenges
6.2 Organizational Challenges
7 Final Remarks
References
Talent Management in Digital Transformation
1 Introduction
2 Organizational Change in Digital Transformation
3 Human Resources Departments in Digital Transformation
4 The Contributions of HR Departments in the Digital Age
5 The Importance of Talent in Business Strategy
6 Talent Management in Digital Transformation
6.1 Talent in the Digital Age: Talent Relationship and Digital Transformation
6.2 The New Digital Culture and Talent Management
6.3 The State of Attraction, Commitment and Retention of Talent in the Digital Transformation
6.4 HR Analytics and Talent Decisions
6.5 Artificial Intelligence (AI)
6.6 The Tools of Collaborative Work
7 Discussion
7.1 Definition of Talent
7.2 Adaptation to the Digital Context
7.3 New Organizational Culture
7.4 The New Role of HR Departments in Digital Transformation
7.5 Strategies for Attracting, Retaining and Engaging Talent in Business Strategy in the Digital Age
8 Conclusions
References
Consumer’s Vulnerabilities and Potential Dignity Risks in the Context of Digital Transformation Processes
1 Introduction
2 Digital Transformation and Its Challenges
3 Consumer Vulnerability
4 Social Issues in Management
4.1 Stakeholder Theory
4.2 Humanistic Management Theory
4.3 Dignity Protection
5 Consumers Vulnerability Challenges in Digital Transformation Processes
5.1 Vulnerability Challenges Rising from Entry Barriers
5.2 Vulnerability Challenges Rising from Perceived Empowerment
6 Concluding Remarks
References
Use of Generative AIs in the Digital Communication and Marketing Sector in Spain
1 Introduction
2 Rise of Personal Assistants
2.1 Generative IAs or Synthetic Content Generation Tools: The “ChatGPT Revolution”
2.2 Risks and Ethical Considerations of Generative AIs
2.3 Marketing and Communication Field
3 Methodology
4 Results
4.1 Quantitative Results
4.2 Qualtitative Results
5 Discussion and Conclusions
References
“The New Online Normal”: Exploring Online Trends on E-commerce and Internet Use During and After COVID-19 Pandemic
1 Introduction
1.1 E-commerce Trends
1.2 The Future of E-commerce
1.3 Demand for Online Services
2 Methodology
3 Results
3.1 Online Shopping Trends
3.2 Social Media Trends
4 Discussion and Conclusion
4.1 Challenges and Opportunities
References
Virtual Teams: An Intelligent Tool on the Path to Digitalization—A Case Study
1 Introduction
2 Virtual Teams: A Case Study
2.1 The VirtualSmile Case
3 Theoretical Review
3.1 Virtual Teams: Around the Concept
3.2 Advantages and Disadvantages of Virtual Teams
3.3 Challenges in Human Resource Management Practices
4 Final Remarks
References
Collaboration as an Enabler for Digital Transformation: The Helix Paradigm
1 Introduction
2 Collaboration for Technology Transfer
2.1 The Helix Paradigm: From the Triple to the Quintuple Helix
2.2 The Network Paradigm: The Role of Collaboration Structures for Innovation
3 The Helix and Network Paradigms in Industry 4.0 Digitalization
3.1 Industry 4.0 and the Need for “Going Digital”: A Depiction of the Current Industrial Context and the Importance of Digitalization
3.2 What is the Specific Link Between Innovation and Digitalization: Some Insights on the Innovation Helix and Networks Paradigms
3.3 Insights on Each Subsystem of the Quintuple Helix and Networks Paradigms
4 Evidence
4.1 Cases of Collaboration for Technology Transfer
4.2 Conclusions
5 Final Remarks
References
Conceptualising Management Practices for Mapping Mobile Phone Waste Through Scientometric, Bibliometric and Visual Analytic Tools
1 Introduction
2 Theoretical Orientation
2.1 Overview of MPW
2.2 Composition and Management of a Mobile Phone Waste
2.3 Motivation Towards the Increased Collection of Mobile Phone Waste
3 Research Methodology
3.1 Exclusion and Inclusion Criteria
3.2 Research Source of Information
3.3 Conducting Search
3.4 Bibliometric Analysis
3.5 Scientometric Analysis
4 Results and Discussion
4.1 Analysis of Bibliometric
4.2 Mobile Phone Waste Management
4.3 Discussion
5 Conclusion
5.1 Concluding Remarks
5.2 Implication (Significance) to Practice and Management of MPW
5.3 Limitations and Future Work
References
Index

Citation preview

Management and Industrial Engineering

Carolina Machado J. Paulo Davim   Editors

Management for Digital Transformation

Management and Industrial Engineering Series Editor J. Paulo Davim, Department of Mechanical Engineering, University of Aveiro, Aveiro, Portugal

This series fosters information exchange and discussion on management and industrial engineering and related aspects, namely global management, organizational development and change, strategic management, lean production, performance management, production management, quality engineering, maintenance management, productivity improvement, materials management, human resource management, workforce behavior, innovation and change, technological and organizational flexibility, self-directed work teams, knowledge management, organizational learning, learning organizations, entrepreneurship, sustainable management, etc. The series provides discussion and the exchange of information on principles, strategies, models, techniques, methodologies and applications of management and industrial engineering in the field of the different types of organizational activities. It aims to communicate the latest developments and thinking in what concerns the latest research activity relating to new organizational challenges and changes world-wide. Contributions to this book series are welcome on all subjects related with management and industrial engineering. To submit a proposal or request further information, please contact Professor J. Paulo Davim, Book Series Editor, [email protected]

Carolina Machado · J. Paulo Davim Editors

Management for Digital Transformation

Editors Carolina Machado Department of Management School of Economics and Management University of Minho Braga, Portugal

J. Paulo Davim Department of Mechanical Engineering University of Aveiro Aveiro, Portugal

ISSN 2365-0532 ISSN 2365-0540 (electronic) Management and Industrial Engineering ISBN 978-3-031-42059-7 ISBN 978-3-031-42060-3 (eBook) https://doi.org/10.1007/978-3-031-42060-3 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Paper in this product is recyclable.

Preface

The world is increasingly digital. Over the past few years, we have been witnessing a growing evolution of digital technologies, which, in turn, implies a set of changes in the organizational context. Indeed, we are progressively witnessing the integration of these digital technologies in all areas of the organization. Acting strategically, organizations effectively and intelligently integrate, at all levels and functions, the technologies, processes and digital skills of their employees, thus leading to a wide range of changes either in culture and in the organization as an all. Changes in culture require organizations to proactively face the challenges they face, accepting in a balanced way not only the successes, but also the failures they face. This leads us to a concept that we hear more and more in the business world, such as digital transformation. Digital transformation refers to a combination of digital technologies, tools, processes and, above all, people, which together contribute to a true transformation of the way an organization works. Effectively, the culture and mentalities that prevail in the organization are essential for this combination to be really effective. A new way of thinking and acting is needed. At this level, only collaborators and all those that belong to the organization, shareholders and stakeholders, able to develop a new way of thinking, can lead the organization to success. Digital transformation implies the need to develop and implement agile practices that allow organizations to act more proactively and responsibly in the markets in which they operate. It covers a high number of processes, technological evolutions, changes, interactions, transactions, among others, that we need to have in mind. In all these challenges, the abilities and competencies of the human being are crucial to the success of the digital business transformation. However, it is important to highlight that although these challenges, in a general way, are common to different organizations all over the world, this is also true that there are many differences among organizations, activity sectors, as well as geographical areas. In other words, a particular situation that can be adequate in an organization and/or region, for instance, does not necessarily have to be in another organization or region. This is why it is important to know and understand the way how digital business transformation has been occurring in different organizations, in different regions. To what extent the organizations’ management has been leading with these changes that digital v

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transformation implies at the different levels of the organization, namely, in what concerns the business management, models, processes, activities and/or functions; the organizational culture as well as the worker and customers’ approaches. Conscious of its importance in nowadays organizations, the present book entitled Management for Digital Transformation looks to communicate the latest developments and thinking on the digital transformation subject worldwide. This is a critical issue to managers and engineers as digital transformation more than a simple concept that we frequently hear, is an opportunity to compete with organizations to an extent that it will allow them to obtain business competencies to lead and be well succeed in rapidly changing environments, that challenge organizations to be proactive, exceeding traditional business models. And this becomes much more real when we have to be present that in the context of digital transformation, we cannot look just at the technological perspective, nor just at the perspective of human resources and processes as isolated issues. On the other hand, in an environment of digital transformation all these factors, processes, functions, etc., are in constant interaction, relationship and overlapping with the others. Digital transformation implies significant changes in the way people relate, communicate, obtain and provide information, as well as in the way they work. In short, in a context where digital transformation is an increasingly present reality, organizations need to develop a more critical view of how they relate to different stakeholders, how they organize and manage their internal processes, how they manage information, etc., with a view to more efficiently and effectively exploiting the resources at their disposal. Aimed at all those interested in developing their knowledge and understanding of what concerns management for digital evolution and its implications in the organization development and performance, this book, organized in nine chapters, starts by highlighting Digital Transformation of Organizational and Management Controls— Review and Recommendations for the Future, soon followed by Examining the Role of Technology Transfer on Digitalization: Consequences and Challenges. It follows an approach to Talent Management in Digital Transformation, presenting the next chapter Consumer’s Vulnerabilities and Potential Dignity Risks in the Context of Digital Transformation Processes. The Use of Generative AIs in the Digital Communication and Marketing Sector in Spain is also a target of analysis, following a discussion about “The New Online Normal”: Exploring Online Trends on E-commerce and Internet Use During and After COVID-19 Pandemic. Focusing the next chapter on Virtual Teams: An Intelligent Tool on the Path to Digitalization—A Case Study, the book ends with an approach to Collaboration as an Enabler for Digital Transformation: The Helix Paradigm, and finally Conceptualising Management Practices for Mapping Mobile Phone Waste Through Scientometric, Bibliometric and Visual Analytic Tools. Highlighting all these challenges and changes, Management for Digital Transformation looks to be a critical tool that will allow managers, engineers, researchers, academics, and all those that belong to the different type of organizations, to more effectively lead and manage digital transformation processes, in order to most effectively face the new challenges. This book is designed to increase the knowledge and

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effectiveness of all those involved in these areas whether in the profit or non-profit sectors, or in the public or private sectors. The Editors acknowledge their gratitude to Springer for this opportunity and for their professional support. Finally, we would like to thank all chapter authors for their interest and availability to work on this project. Braga, Portugal Aveiro, Portugal

Carolina Machado J. Paulo Davim

Contents

Digital Transformation of Organizational and Management Controls—Review and Recommendations for the Future . . . . . . . . . . . . . . Sami Seppänen, Minna Saunila, and Juhani Ukko Examining the Role of Technology Transfer on Digitalization: Consequences and Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lena Bischoff, Marta Ferrer-Serrano, Andrea Ogando-Vidal, and Amaya Soto-Rey Talent Management in Digital Transformation . . . . . . . . . . . . . . . . . . . . . . . José Manuel Montero Guerra Consumer’s Vulnerabilities and Potential Dignity Risks in the Context of Digital Transformation Processes . . . . . . . . . . . . . . . . . . . Flor Morton and Mario Vázquez-Maguirre

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Use of Generative AIs in the Digital Communication and Marketing Sector in Spain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Xabier Martínez-Rolán, Juan Manuel Corbacho-Valencia, and Teresa Piñeiro-Otero “The New Online Normal”: Exploring Online Trends on E-commerce and Internet Use During and After COVID-19 Pandemic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Teresa B. Treviño Benavides Virtual Teams: An Intelligent Tool on the Path to Digitalization—A Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 Maria Inês B. Fernandes and Carolina Feliciana Machado Collaboration as an Enabler for Digital Transformation: The Helix Paradigm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 Estefanía Couñago-Blanco, Nahuel I. Depino-Besada, Marta Ferrer-Serrano, and Lucas López-Manuel

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Conceptualising Management Practices for Mapping Mobile Phone Waste Through Scientometric, Bibliometric and Visual Analytic Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 Abdulbastwa H. Athuman, Victoria Mahabi, and Ismail W. R. Taifa Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213

Editors and Contributors

About the Editors Carolina Machado received her Ph.D. degree in Management Sciences (Organizational and Policies Management area/Human Resources Management) from the University of Minho in 1999, Master’s degree in Management (Strategic Human Resource Management) from the Technical University of Lisbon in 1994, and a degree in Business Administration from University of Minho in 1989. Teaching Human Resources Management subjects since 1989 at the University of Minho, she is since 2004 Associate Professor (with Habilitation since 2022), with experience and research interest areas in the field of Human Resource Management, International Human Resource Management, Human Resource Management in SMEs, Training and Development, Emotional Intelligence, Management Change, Knowledge Management and Management/HRM in the Digital Age/Business Analytics, Sustainability and Higher Education Sustainability. She is Head of the Human Resources Management Work Group at the School of Economics and Management at University of Minho, Coordinator of Advanced Training Courses at the Interdisciplinary Centre of Social Sciences, Member of the Interdisciplinary Centre of Social Sciences (CICS.NOVA.UMinho), University of Minho, as well as Chief Editor of the International Journal of Applied Management Sciences and Engineering (IJAMSE), Guest Editor of journals, books Editor and book Series Editor, as well as reviewer in different international prestigious journals. In addition, she has also published both as editor/co-editor and as author/co-author of several books, book chapters and articles in journals and conferences. e-mail: [email protected] J. Paulo Davim is Full Professor at the University of Aveiro, Portugal. He is also distinguished as honorary professor in several universities/colleges/institutes in China, India and Spain. He received his Ph.D. degree in Mechanical Engineering in 1997, M.Sc. degree in Mechanical Engineering (materials and manufacturing processes) in 1991, Mechanical Engineering degree (5 years) in 1986, from the

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University of Porto (FEUP), the Aggregate title (Full Habilitation) from the University of Coimbra in 2005 and the D.Sc. (Higher Doctorate) from London Metropolitan University in 2013. He is Senior Chartered Engineer by the Portuguese Institution of Engineers with an MBA and Specialist titles in Engineering and Industrial Management as well as in Metrology. He is also Eur Ing by FEANI-Brussels and Fellow (FIET) of IET-London. He has more than 35 years of teaching and research experience in Manufacturing, Materials, Mechanical and Industrial Engineering, with special emphasis in Machining & Tribology. He has also interest in Management, Engineering Education and Higher Education for Sustainability. He has guided large numbers of postdoc, Ph.D. and master’s students as well as has coordinated and participated in several financed research projects. He has received several scientific awards and honors. He has worked as evaluator of projects for the European Research Council and other international research agencies as well as examiner of Ph.D. theses for many universities in different countries. He is the Editor–in-Chief of several international journals, Guest Editor of journals, books Editor, book Series Editor and Scientific Advisory for many international journals and conferences. He has been listed in the World’s Top 2% Scientists by a Stanford University study. e-mail: [email protected]

Contributors Abdulbastwa H. Athuman Department of Informatics and Information Technology, Sokoine University of Agriculture, Morogoro, Tanzania; Department of Mechanical and Industrial Engineering, College of Engineering and Technology, University of Dar es Salaam, Dar es Salaam, Tanzania Teresa B. Treviño Benavides Business School, Management Department, Universidad de Monterrey, San Pedro Garza García, Mexico Lena Bischoff Department of Business Organization and Marketing, University of Vigo, Vigo, Spain; ECOBAS Interuniversity Research Center, Vigo, Spain Juan Manuel Corbacho-Valencia Universidade de Vigo, Vigo, Spain Estefanía Couñago-Blanco Department of Business Organisation and Marketing, ECOBAS, University of Vigo, Vigo, Spain Nahuel I. Depino-Besada Department of Business Organisation and Marketing, ECOBAS, University of Vigo, Vigo, Spain Maria Inês B. Fernandes School of Economics and Management, University of Minho, Braga, Portugal Marta Ferrer-Serrano Department of Business Management, University of La Rioja, Logroño, Spain

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José Manuel Montero Guerra Departamento de Organización de Empresas, Facultad de Comercio y Turismo, Universidad Complutense de Madrid, Madrid, Spain Lucas López-Manuel Department of Business Organisation and Marketing, ECOBAS, University of Vigo, Vigo, Spain Carolina Feliciana Machado School of Economics and Management, University of Minho, Braga, Portugal; Interdisciplinary Centre of Social Sciences (CICS.NOVA.UMinho), University of Minho, Braga, Portugal Victoria Mahabi Department of Mechanical and Industrial Engineering, College of Engineering and Technology, University of Dar es Salaam, Dar es Salaam, Tanzania Xabier Martínez-Rolán Universidade de Vigo, Vigo, Spain Flor Morton Department of Management, Universidad de Monterrey, Monterrey, Mexico Andrea Ogando-Vidal Department of Business Organization and Marketing, University of Vigo, Vigo, Spain; ECOBAS Interuniversity Research Center, Vigo, Spain Teresa Piñeiro-Otero Universidade de Vigo, Vigo, Spain Minna Saunila LUT University, Lappeenranta, Finland Sami Seppänen LUT University, Lappeenranta, Finland Amaya Soto-Rey Training Department, Centro Tecnológico del Mar, Fundación CETMAR, Vigo, Spain Ismail W. R. Taifa Department of Mechanical and Industrial Engineering, College of Engineering and Technology, University of Dar es Salaam, Dar es Salaam, Tanzania Juhani Ukko LUT University, Lappeenranta, Finland Mario Vázquez-Maguirre Department Monterrey, Monterrey, Mexico

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Digital Transformation of Organizational and Management Controls—Review and Recommendations for the Future Sami Seppänen, Minna Saunila, and Juhani Ukko

Abstract The digital transformation underlying the fourth industrial revolution— Industry 4.0—is making headway at an increasing pace. The way we work and live is changing fundamentally, and the opportunities that digitalization brings to our lives and the ways it reshapes our work at all levels are innumerable. This study aimed to explain how the utilization of emerging digital technologies for organizational and management controls has been studied and what kind of performance improvements can be achieved. A systematic review of the current literature was conducted to this end. The analysis revealed four main themes in the literature and future research directions to fill research gaps. The identified gaps were related to: (1) the internal and external drivers for utilizing digitalization in management and organizational controls, (2) the impacts of digitalization on management control systems, and prerequisites for using digital tools in management control, (3) the effects of digital tools in decision-making, and related challenges, and (4) digitalization’s effect on performance. Another possible future research direction would be to investigate the possibilities of specific techniques, such as artificial intelligence, machine learning, big data, business intelligence, and Internet of Things, in organizational and management control and decision-making. Keywords Digital transformation · Digital tools · Management control · Management control system · Organizational control · Organizational control system

1 Introduction Emerging production techniques and technological operations combined with intelligent management control systems and decision-making support can be collected under the umbrella term of “digitalization”. More broadly, they are considered part of the fourth industrial revolution—Industry 4.0. The possibilities that emerging S. Seppänen · M. Saunila · J. Ukko (B) LUT University, Lappeenranta, Finland e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 C. Machado and J. P. Davim (eds.), Management for Digital Transformation, Management and Industrial Engineering, https://doi.org/10.1007/978-3-031-42060-3_1

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digital technologies can open for developing organizational and management control systems, operations, and decision-making are interminable. However, it is crucial to understand the underlying variables that affect the effectiveness of utilizing novel technologies in them. Research done in this area is growing in the Industry 4.0 era. However, the relationship between using digital technologies and their effects on organizational and management control systems, as well as the technologies’ impact on decision-making effectiveness, is less known (Bredmar, 2017; Ukko et al., 2022). There are a few key concerns in research on organizational and management control systems. The first is to understand how and why they are effective in specific settings and how they could be improved to achieve better performance in organizations (Merchant & Otley, 2007a, 2007b). Digital transformation changes practices in different industries. At the organizational level, companies look for new ways to operate and generate value by utilizing digital technology (Matt et al., 2015). This ongoing phenomenon—also named digital transformation—has been defined as “a process that aims to improve an entity by triggering significant changes to its properties through combinations of information, computing, communication, and connectivity technologies” (Vial, 2019). It is crucial to examine more deeply the drivers and underlying factors of implementing novel technologies in organizational and management control systems, as well as the principles and ways the technologies and tools are used in different types of organizations. The speed of development is increasing both in the trend of “Industry 4.0” with full automation of the production flow (Zelinski, 2016) and in “artificial intelligence” where robots tend to make autonomous decisions and develop self-awareness and self-maintenance (Lee et al., 2014). Referring to the effects of digitalization on decision-making, the latter trend will completely change how decisions are made. Flexibility and transformability will be key attributes of successful organizations in the future and drive them on the road of digitalization (Bauer et al., 2015). Digitalization will have an effect on customer structure, increase the efficiency of operations, and finally change the entire business model (Westerman et al., 2014). Thus, when flexibility and resilience are key factors in the success of organizations, it should be examined precisely and empirically whether digitally made decisions are effective and whether there is room for human factors in decision processes for enabling decision-making flexibility, the organization’s transformability, and a positive effect on sustainable performance. As presented above, emerging technologies will be widely related to both the control and goals of the entire organization, as well as management control and people’s behavior. This study presents a systematic literature review that aims to explain how the utilization of emerging digital technologies for organizational and management controls has been studied and what kind of performance improvements can be achieved. The findings reveal research themes derived from the analysis as well as future research directions and questions.

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2 Organizational and Management Controls and Systems Before focusing on the research approach and findings, it is necessary to define the terms management control (MC), management control system (MCS), organizational control (OC), and organizational control system (OCS) and their mutual hierarchy. Referring to OC, Flamholtz et al. (1985) see control as a means to achieving goal uniformity. They defined OCs as “attempts by the organization to increase the probability that individuals and groups will behave in ways that lead to the attainment of organizational goals” (p. 36). OC is also noted to be a term used to refer to builtin controls in processes like just-in-time management and statistical quality control (Chenhall, 2003, p. 129). Considering OCSs, Flamholtz et al. (1985) define these as “techniques and processes to achieve goal congruence which may be designed for all levels of behavioral influence: individuals, small groups, formal subunits and the organization as a whole” (p. 36). It is worth mentioning that OCs and OCSs differ. An OCS is concentrated only in systems that aim for goal uniformity, while OCs include multiple types of controls like rules and process descriptions. The same train of thought is shared by Abernethy and Chua (1996), who argue that an OCS is “a combination of control mechanisms designed and implemented by management to increase the probability that organizational actors will behave in ways consistent with the objectives of the dominant organizational coalition” (p. 573). Regarding MC, Merchant and Van der Stede (2007) separate strategic control from MC and state that MC is an instrument that deals with employee behavior. According to them, MCs exist to prevent and guard against employees doing something that the organization does not want them to do. So, there would be no need for MCSs if employees could always be relied on to do what is best for the organization. An MCS, in turn, has been defined in many ways over the years; definitions contain overlaps and differences (Alvesson & Karreman, 2004; Langfield-Smith, 1997; Simons, 1995). A broad definition of an MCS includes the notions of management accounting, which is defined as a collection of practices (such as budgeting or product costing), and the management accounting system, which means the systematic use of management accounting to achieve a predetermined goal. Chenhall (2003) states that, in this definition, MCS is a term that includes management accounting systems and other control elements, such as personal control and clan control. An even broader definition of the control system is presented by Merchant and Otley (2007a, 2007b), who state that control systems include elements of learning processes, strategic development, and strategic control. Since almost everything in the organization is included in the overall control system in this conceptualization, Malmi and Brown (2008) clarify its difference from an MCS. They suggest that “to clarify these issues is to start with the managerial problem of directing employee behavior”. “Those systems, rules, practices, values and other activities management put in place in order to direct employee behavior should be called management controls” and “If these are complete systems, as opposed to a simple rule (for example not to travel in business class), then they should be called MCSs. Accounting systems that are designed to support decision-making at any organizational level, but leave the use of those

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systems unmonitored, should not be called MCSs and instead termed management accounting systems”. There are many ways to advocate distinctions between these systems, but Zimmerman (1997, 2001) states that one useful way to differentiate them is between decision-making and control. Some systems are there to provide information to support decision-making, while others function to direct and control employee activities. This means that systems can be used to support decision-making at the managerial level, for example, to optimize cash flow or production efficiency. Managers can also use the systems to support the decision-making processes of their subordinates. Thus, if there is no process or instrument to monitor manager-level goal congruence, the system is more a decision-support system or an information system than a control system. In summary, OC means controls that are built into processes. They can be policies, process descriptions, quality management practices, etc. An OCS is focused on achieving pre-set goals at a more general level. An OCS is for controlling the entirety of controls from the strategic level to the shop floor. The concept of MC is intended to describe controls that concern direct control of employee behavior and actions. If the controls are more systematic and include formal elements such as preplanned processes for completing work tasks, the entirety should be called an MCS. The concepts and their hierarchy as well as affected levels are described in Fig. 1.

Fig. 1 Concept hierarchy

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3 Research Approach 3.1 Sample Selection Keywords were extracted from a preliminary review of literature from the field as presented in the previous section where the theme was introduced. Search terms were selected to limit the findings to literature that concerns digital technologies used in decision-making, MC, OC, performance measurement, and performance management. The technologies that were included in the search were artificial intelligence (AI), machine learning (ML), big data (BD), Internet of things (IoT), and the stand-alone term “virtual”. Functions that these technology terms were combined with were “decision-making”, “management control”, “organizational control”, and “performance measurement”. The search terms applied in query strings are pictured in Table 1. This makes a total of 4 × 5 = 20 independent search terms that were inserted in the Scopus database search engine with limitations by type, language, and subject area. The subject areas that the search was limited to were business management and accounting, decision sciences, and social sciences. The language was limited to English, and the publication type was limited to search only article publications. In all, 315 unique hits were identified in the first search round. The first round usually produces a large number of hits in literature reviews, so this number was brought down systematically by restricting the acceptance criteria to three rounds. The process of trimming the quantity of articles and extracting irrelevant ones is depicted in Fig. 2. It was clear that a systematic textual analysis of 315 papers was not feasible, so the relevant papers were selected by the authors’ judgment by first ranking the papers’ relevance by their titles. This brought the number down to 124 papers. The next step was to skim the abstracts of the remaining 124 papers, which reduced the number of relevant papers to 74. In the third round, the abstracts were read through thoroughly, and a decision was made on whether the contents might match the scope of this study. The final number of papers was 63. There was a problem with the online availability of full versions of some articles; therefore, the final number of articles included is 47. After conducting a manual online search for suitable material and following reference information from originally found papers, six more publications were included. This snowballing was done with the same selection criteria previously Table 1 Search terms

Technologies

Functions

Machine learning

Decision-making

Big data

Management control

Internet of things (IoT)

Organizational control

Virtual

Performance measurement Performance management

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Fig. 2 Process of selecting relevant literature

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Fig. 3 New articles by year from 1971 to 2022

mentioned. They were read thoroughly, and their potential for meeting the formal criteria was considered before including them in the pool of relevant works. The final number of works after snowballing was 53. After reading all the selected material and collecting relevant information, the number of sources was increased to 87. Only 20 studies from the original sample were included. This indicates that the current state of research in this field and scope is still imperfect, and gaps exist; propositions for future research directions are also needed. The selected query string brought hits from 1971 to 2022. The yearly distribution of new literature by year started to increase dramatically from 2016, and the amount started to increase exponentially in 2017–2018. The number of yearly publications with the selected search terms is depicted in Fig. 3. This number includes all the matches. After cleaning the material and selecting relevant literature, the yearly numbers followed a similar progression (Fig. 4). The formal criteria for selecting the papers were the following. 1. Studies that included new theory or good novel insights about the subject were selected. The older and proven theory was also accepted in order to be able to build as precise an understanding as possible on the current state of using digital technologies in MC, OC, decision-making in organizations, and performance management, as well as the drivers for implementing digital technologies in this field of topics. 2. Due to this research topic’s technological nature, papers that were focused on using the technologies in settings of, for example, tourism and a service business environment were excluded. In other words, works in the contexts of MC, OC, performance management, and decision-making were included if the research was done in an environment that focuses on technology or the subject of the study was in the context of business and accounting, business management, or some other suitable for the study’s scope.

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Fig. 4 Articles by year after selecting relevant material

3. To ensure a sufficient degree of quality among the included papers, they were selected from peer-reviewed journals. In the final step, the 53 works were read through more closely, and recurring themes were identified. The recurring themes were quite obvious due to the selected search strings, so the focus was on finding themes that were relevant but that had gaps and divergences that needed more attention. The following themes were identified; their recurrence in the sample of 53 works was as follows. – Drivers for utilizing digitalization in MC—17 papers addressed this topic to some extent – Implementing and integrating digitalization MC—16 papers – Digitalization in MC—16 papers – Digitalization in OC—20 papers – Digitalization and its effect on decision-making on operational level—36 papers – Digital decision quality and effectiveness—30 papers – Digitalization’s effect on performance—26 papers The following questions and topics were derived from the identified recurring themes to describe what has already been studied and how future research could contribute to tackling existing gaps. 1. What are the main drivers for utilizing digital technologies in MCSs, and what is the state of understanding of these according to the literature on the subject? 2. What are the most important factors and characteristics in the successful implementation of digital technologies in MCSs at the operational level and in decision-making according to the selected literature? 3. What are the main issues and level of understanding of digitalization in MC and OC? Technologies and how they can be applied in pursuing better business performance are discussed.

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4. What is digitalization’s impact on decision-making mechanisms, and has it been identified in the literature? 5. What is digitalization’s impact on decision-making performance—its quality and effectiveness? The effectiveness of automated digital decision-making has also been studied from a sustainability point of view, and the quality and effectiveness of decisions and their impact on operational flexibility are examined in the light of the literature. 6. What are the findings in the current literature on the relationship between implementing digital technologies in business operations and business performance? These six were boiled down to four main topics by combining the themes that have content of the same nature. The content of the following chapters follows the previously described question setting. By doing this, it was possible to present a review with a clear structure. The main topics of the review are the following: 1. 2. 3. 4.

Drivers for utilizing digital tools in MCSs and OCs Implementation of novel digital tools in MCSs and OCs Digitalization’s effects on decision-making quality and effectiveness Digitalization’s effect on performance.

3.2 Overview of Technologies This review focuses on topics and settings that have both technical and management research dimensions. However, the main focus is not on the technological solutions but on the ways that novel technologies can change industrial management. Nonetheless, it is important to understand the novel technologies and applications at a conceptual level. The technologies and applications referred to in this review and their main characteristics are described in Table 2.

4 Findings 4.1 Drivers for Utilizing Digitalization in Management and Organizational Controls The first topic in research on digitalization’s effects on MC, OC, and decisionmaking at the operational level is in defining the drivers for companies utilizing digital technologies and tools in their MCSs in the Industry 4.0 era. The internal drivers for utilizing digital technologies and tools in current literature are derived from company and organization needs to keep up with the competition and stay in the markets. Remaining competitive means that products and services and the ways they are designed, marketed, produced, and distributed need to be redesigned to be able to answer increasing demands from markets and customers

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Table 2 Descriptions of technologies and applications Technologies application

Abbreviation

Description

Internet of things

IoT

The internet of things describes physical objects with sensors, processing ability, software and other technologies that connect and exchange data with other devices and system over the internet or other communications networks

Artificial intelligence

AI

Artificial intelligence is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by non-human animals and humans

Machine learning

ML

Machine learning is a field of inquiry devoted to understanding and building methods ‘learn’, that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of intelligence

Business intelligence

BI

Business intelligence comprises the strategies and technologies used by enterprises for the data analysis and management of business information

Big data/big data analysis

BD/BDA

Big data primarily refers to data sets that are too larger or complex to be dealt with by traditional data-processing application software. Data with many fields offer greater statistical power, while data with higher complexity may lead to a higher false discovery rate

and to obtain financial benefits. The key driver for change in organizations and their business is the phenomenon of digitalization and Industry 4.0. It affects everything from production to the supply chain as well as customer behavior and market structure. Digitalization enables and drives redesigning of products, production, supply chain, and the business itself (Hoßfeld, 2017). To be able to change and evolve along with novel market paradigms, firms must push to design and build new competencies quickly. In recent years, digital market intelligence tools have gained favor for being seen as sources of significant business value (Fan et al., 2015). The world is becoming increasingly quantified, and to survive this change companies and organizations must build their business strategies on a new basis of BD and business analytics. This new basis and the rise of its challenges and importance is seen as the most important feature of contemporary economies and societies (Davenport et al., 2017). Customers and markets require more targeted products and services, and responding to this is a big challenge for companies. The evolving dynamic and competitive markets also require more flexibility in processes and better coordination of supply chain and cost management. Operational, financial, and strategic concerns also need to be integrated with non-financial information to make efficient decisions possible (Bhimani & Willcocks, 2014; Mundy, 2010). There are technical differences among different digital tools such as AI systems. However, they generally serve the same purpose of creating useful outcomes, decisions, and insights by facilitating transformation using large volumes of data (Tabesh, 2022).

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Sustainability performance is another prominent driver for companies to redesign their operations and services. Industry 4.0 practices can be seen as an enabler in pursuing more sustainable business, so the main external driver for implementing digital technologies in business practices can be condensed to ESG goals. Industry 4.0 is not merely a technology roadmap but an enabler for more sustainable business. Alkaraan et al. (2022) state that by pursuing more sustainable operations, companies can also strengthen the relationship between their financial performance and Industry 4.0 practices. Recognizing the external drivers for companies to invest in digital tools to improve their business performance is a multi-dimensional question. According to Venkatesh et al. (2021), the potential drivers for implementing Industry 4.0 practices are collective dynamics that set an imperative for corporate governance and sustainability to converge by considering stakeholder views and attributes in their standard-setting. A comprehensive understanding of stakeholders’ goals, expectations, and interests is required for successful Industry 4.0 practice implementation (Awan et al., 2021). The benefits that a supply chain gains from investing and implementing BD analysis technology vary in different positions of the supply chain, and coordination of implementation has a crucial role when making changes in tools and technologies. According to Liu and Yi (2018c), the benefits can significantly vary between the component manufacturer, main company, and retailer. For the component manufacturer, it can be more beneficial to invest the amount that was allocated for implementing digital technologies in other productivity and efficiency improvement activities. This can also be beneficial for the main company. While the main company gains benefits from component manufacturer efforts in increasing its production efficiency, it can also gain more benefits from, for example, implementing digital technologies in improving the accuracy of its consumer preference information to enable gaining more revenues. These investments will also bring benefits for the retailer downstream in the supply chain. So, utilizing digitalization’s possibilities can improve operations in the whole supply chain. Ideally, this change should be coordinated by the main company. However, when a supply chain member invests in BD alone, it can generate a “spillover effect” because other members of the supply chain will benefit from a single part’s improvement (Liu and Yi‚ 2018c).

4.2 Utilizing Novel Digital Tools in Management Control Systems and Organizational Controls The second topic in research on digitalization’s effects on MC, OC, and decisionmaking at the operational level involves defining what digitalization means in MC operations and OC and identifying the most important factors in the successful implementation of digital technologies in MC activities. The questions to be answered regarding the definition of digitalization in MC and OC are: What are the main

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issues and level of understanding of digitalization in management control and organizational control? Warren et al. (2015) say that digitalization and the tools it brings to our disposal are drivers that can change the concept of MCSs drastically. For example, data-driven approaches and business analytics are currently used in management support systems in organizations. These approaches have been defined as business intelligence (BI) systems, and they can be a good means to familiarize managers and executives with data-driven approaches and analytics. Even this can be seen as a good base for building a data-driven organizational culture, but it can also have the disadvantage of “the unlearning challenge,” which is one of the most important issues to tackle in moving toward a data-driven organizational culture (Pugna et al., 2019). However, the terms “data-driven organizational model” and “data-driven decision-making” have emerged simultaneously with the rise of BD (Tabesh, 2022). BD enables the use of predictive BI that can suggest different potential actions for better chances of success in uncertain circumstances (Pugna et al., 2019). These tools have various impacts on MCSs. Managerial decision-making processes will be affected (and improved) by implementing BD in MCS processes (McAfee & Brynjolfsson, 2012), and BD is assumed to have a positive impact on processes regarding operational planning (Wang et al., 2016a, 2016b). According to a study by Vitale et al. (2020), the impact was mainly on decision-making processes and operational planning activities that BD supported; formal documents and models in the MCS were not noticeably affected. For example, models in budgeting and accounting remained unchanged. This conclusion is in line with and adds to the findings of Busco and Scapens (2011), where they demonstrate that in implementing and utilizing BD practices and tools, the significant effects were changes in purely non-financial practices; for example, accounting models were not affected at all. MCS dimensions can be divided into formal and informal dimensions. According to the studies, the impact has been mostly on informal activities by making them more rational and structured, or formalized, while formal activities have not changed much or at all. According to the conclusions presented in the previous section, the formal dimension was only partially affected by BD, since it changed (for example) budgeting, but concrete items did not change. The informal dimension of MCS was rationalized and strengthened, so it was in some sense formalized (Vitale et al., 2020). AI is also one of the key technologies supporting OCs since it is expected to offer solutions and support for organizations that constantly deal with large amounts of information that need to be processed for making effective strategic decisions that lead to desired outcomes (Trunk et al., 2020). Implementing AI will increase the need for human responsibility when the needed capabilities are different from those needed for traditional tools, which also calls for training and education for employees. (The effects of using digital tools in decision-making are described in Sect. 4.3). The literature also presents various prerequisites for utilizing novel digital tools in MCSs and OCs. There is a close link between organizational structures and decisionmaking since both are limited to human processing capacity. Challenges in both dimensions can be overcome by systems that can process information and decisions

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across roles and in different settings (Von Krogh, 2018). After all, the quality of an organization and its outcomes depend on the decisions it makes. All actions that an organization makes precede a point of decision. The decisions in OC can concern almost anything imaginable that has a strategic meaning. It can be a decision on hiring a new employee, responding to a competitor’s move, investing in a new production line, entering a new market, kicking off a new business model, or something else, but it always includes a decision (Trunk et al., 2020). Regarding specific technologies, von Krogh (2018), Bienhaus and Abubaker (2018), Paschen et al. (2019), and Butner and Ho (2019) argue that the reasons for starting to use AI are in relation to an organization’s strategies and goals. Trunk et al. (2020) conclude that the foundation for successful organizational structuring is AI, and vice versa; an organization needs to have sufficient structures for implementing AI and other digital technologies. As an example of prerequisites, Asadi et al. (2022) present three dimensions for the criteria for successful IoT adoption. The first is the technological dimension, which includes factors such as technology infrastructure, complexity, technology integration, technology competence, technology compatibility, technology integration, perceived benefits, and security concerns. The second dimension is the organizational dimension, which consists of top management support, technical knowledge, organization size, perceived cost, organizational readiness, executive support, financial resources, and earlier experiences with information technology. The environmental dimension is the third, and it includes factors that are not solely environmental attributes but that are external to the company itself. These factors are competitive pressure, government policy, government support, ICT support, and pressure from trading partners. These dimensions have reciprocal effects. However, the organizational dimension has the strongest influence together with the technological dimension. Factors in the organizational dimension have a higher influence than those of the other two dimensions, and the organizational dimension has a strong mutual influence with the technological dimension. Other studies have suggested that the main limiting factors for the adoption of BD are the organization’s knowledge and awareness. Fear of change can hinder the adoption of new technologies. Managers struggling with older technologies can be suspicious about new solutions, which can bring more challenges in adopting them (Yousuf & Zainal, 2020). Isaksson et al. (2018) state that changes in digital systems will be a long process as companies are tied to their existing systems, and it will take time to give them clear indications of potential benefits that can be gained by modernizing the systems. Perceived personal well-being and development can be seen as preceding factors as well. These are the factors that influence the attitude and behavior toward new information technologies and systems (Breward et al., 2017). Managerial and leadership skills, the soft skills needed for training employees’ capabilities, judgment, and creativity as well as collaboration skills, become more important while implementing AI in organizational decision-making (Kolbjørnsrud et al., 2017). To build trust in the technology, experience and understanding are needed. Therefore, the introduction of the technology should be done step-by-step to make employees familiar with the technology by doing things that were formerly done by more conventional machines

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(Kolbjørnsrud et al., 2017; Watson, 2017). This highlights that employees need guidance from executives throughout the implementation process. Executives need to have sufficient understanding and literacy of the technology to do this successfully (Kolbjørnsrud et al., 2017; Watson, 2017).

4.3 Digitalization’s Effects on Decision-Making Quality and Effectiveness The third topic pertains to the effects of digitalization on decision-making in the context of MC, OC, and business performance management and on the settings of digital decision quality and effectiveness in MC, OC, and decision-making. The questions to be answered are as follows: What is digitalization’s impact on decision-making mechanisms, and has it been identified in the literature? and What is digitalization’s impact on decision-making performance—its quality and effectiveness—according to the current literature? According to Blenko et al. (2010), quality and effectiveness in decision-making are building blocks of organizational success, and organizations that make effective decisions and execute them well have a strategic advantage over their competitors. Analytical decision-making requires a planned and ordered procedure for the collection of internal and external data and analysis for making a choice over different alternatives and comparing it to goals and objectives that are defined beforehand, before making the actual selection of the course of action (Fredrickson, 1984). An analytic decision-making approach works best when there is a sufficient amount of data available on the phenomenon or task. In the case of large and complex data sets, this data collection analysis can become onerous for humans due to their lack of cognitive capacity (Provost & Fawcett, 2013). ML tools have the capabilities to make analytical decision-making faster and more accurate. They can enhance decision-making in the future by learning from past data. However, they are bound and limited by data quality. The data can be irrelevant and inaccurate, and it can be misrepresented. The effectiveness of digital decisions made by AI and ML is determined by the quality of available data (Tabesh, 2022). Digitalization has a strong connection to decision-making activities in the context of MC and OC. Wang et al. (2016a, 2016b) suggest that the following achievements will result from implementing BD. First, the processing of BD will become more intelligent with technological development, and this will eventually lead to more intelligent and effective decisions, and it will also enrich decision science. Second, in social science, there are analytical and computational approaches to decisions, and computational approaches in particular will become more effective. The revolutionary tool to transform BI for more efficient decision-making is believed to be big data analytics (BDA) (Fan et al., 2015). Classifications of AI’s roles have been done in multiple ways. Generally, an AI system can be used to replace human decision-makers or to assist and support them (Edwards et al., 2000). Bader

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et al. (1988) identified six roles for a knowledge-based system in their early paper. The suggested roles are tutor, assistant, critic, expert consultant, second opinion, and automation. According to Edwards et al. (2000), the roles and findings of using AI (an expert system) in three decision-making levels (strategic, operational, and tactical) in an organization were as follows: – At all three levels, expert systems helped users make better decisions; however, the effectiveness was dependent on the users themselves. – At tactical and operational levels, expert systems were effective in a replacement role, but at the strategic level, they have limitations. – An expert system in a replacement role improved decision-making efficiency, but when it was in a supportive role it was not likely to save user time in decisionmaking. – The users of expert systems in a supportive role did not think they learned from using the system. In a more contemporary publication, Mahroof (2019) states that the capabilities of AI to undertake tasks that require more cognitive skills and that have seemed impossible, such as sensing emotion, making tacit judgments, and handling processes, will be enabled as AI technology progresses and researchers develop more advanced machines. According to Złotowski et al. (2017), this will result in increasing jobs where AI is performing autonomously without human supervision and control. This might seem rather threatening for our current way of working, but according to Wilson and Daugherty (2018), many benefits of AI in decision-making have been reported because it helps an organization’s employees make better decisions, increases creativity, and boost analytic abilities. AI’s better analytical capabilities and greater information processing capacity are undeniable, but it can be seen as an aid that extends human cognition when handling more complex situations. Humans have the capability for a more holistic and intuitive approach when dealing with ambiguity and uncertain settings in organizational decision-making. Based on this, Jarrahi (2018) present an idea of designing AI systems intended for intelligence augmentation rather than replacing human contributions. At its best, AI develops the best possible strategies and decisions according to relevant algorithms, limited data, and other input. There is, however, uncertainty in the technology, and data is often incomplete. The decisions that AI makes lack human emotions and judgment, and therefore, they may significantly alter human decisions. They are also subject to ineffectiveness or obvious decision errors. These flaws can result in ethical risks such as risk to human life, undermining social justice, and privacy breaches (Guan et al., 2022). Also, Yan (2018) state that the two major causes of ethical risks in AI decision-making are human-limited rationality and uncertainty. According to Marabelli et al. (2021), the specific sources of ethical risks are program design, intelligent algorithms, and the technologies combined with AI. Data importation and the programming in digital decision-making involve human decisions; therefore, the main source of risks is human-limited rationality (Arkin, 2008). From a technological perspective, the most significant sources of risks are misuse,

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the abuse of technology, and loss of control (Turing, 2007). Nature, humans, technology, society, and their complicated interaction are the main origin of risks in AI decision-making. Clearly, AI can reduce flaws in decision-making since it does not have the cognitive constraints of humans in handling large amounts of information. This also works the other way around, as humans can consider ethical factors, consider interpersonal effects, and adjust their actions according to changing situations with limited data through intuition. Analytical and intuitive decision-making (human vs. digital) can, therefore, maximize the effectiveness of decisions by minimizing weaknesses reciprocally. “Throughout history, human intuition has had an extraordinary impact on innovation and advancement, including too on the creation and development of AI. Therefore, rather than attempting to replace this unique human skill with advanced technology, organizations will greatly benefit from the integration of intuition and AI to improve organizational decision-making” (Vincent, 2021). The same view is supported by Duan et al. (2019) in their proposition that even if AI can have many different roles in decision-making, it will not replace humans entirely. It will rather be a support or augmentation tool. Combining human decision-making with AI might reduce the problems that AI has with being bound to data and its quality. However, there are a few studies that argue the contrary. For example, Hoßfeld (2017) concludes that digitalized decisionmaking will make decision-making more effective because human emotions will not affect the process. McAfee and Brynjolfsson (2012) and Arunachalam et al. (2018) have stated a similar proposition—that data-driven decisions are better decisions since they reduce uncertainty by better forecasting. This is, however, a somewhat confined view since forecasting always relies on historical data and experience. As was noted earlier, the flaws in historical data or missing data together with lack of experience are significant factors in the poor quality of digital decisions. It is likely that AI will be able to, for example, write programming code at some point in the future, but, as stated earlier, there will always be room for human abilities to cope with uncertainty and risk. For example, programming is a creative process that requires significant understanding of the problem at hand. Currently, AI is not capable of understanding the complete nature of all problems and applying a process to solve them by designing a solution and then implementing it so that the outcome is efficient and correct with consideration of external variables that may be linked to the outcome. AI may be able to work as an assistant on some tasks where human capabilities are not sufficient or not efficient enough, but it is unlikely to replace the human element entirely.

4.4 Digitalization’s Effect on Performance The fourth and last topic in research on digitalization’s effects on MC, OC, and decision-making at the operational level is business performance. The question to be

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answered is: What are the findings in the current literature on the relationship between implementing digital technologies in business operations and its performance? Performance management is said to be probably the most important business process in an organization seeking to achieve pre-set goals. The foundation for managing a business is making effective and good-quality decisions efficiently. Current literature agrees consistently that BD, BDA, and other digital information management tools enable better insights for performance management by enabling real-time analysis of data and feedback, predicting impacts, and providing a general overview of business performance at a given moment in time. “The ability to manage, analyze, and act constitutes a ‘data-driven’ decision system, characterized as a significant resource for competitiveness, performance, and innovation” (Tabesh et al., 2019). Ghasemaghaei and Calic (2020) conclude that more than 80% of firms think that the competitive landscape will be changed by BD and that it is a crucial aid for companies to gain market share. This phenomenon’s enablers, such as service precision, production standardization, and operation network are believed to be revamped by BD and BDA (Wolfert et al., 2017). Pham and Stack (2018) state that the phenomenon has led to a growing number of companies deploying BDA to gain more insight into strategic advantage. Despite this, Ghasemaghaei and Calic (2020) find that only 25% of companies confirm that using BDA has increased their business’s outcomes and that investments in processing BD have not provided them with unique insights that improve their business performance. Wamba et al. (2017) suggest that the reason for this failure is that many organizations still do not have sufficient understanding of BDA and are not necessarily aware of the conditions required for generating insights from BDA. However, digitalization will affect operations and supply chains now and in the future. For example, BD and BDA will make obtaining market information faster, which will reduce response time to changes. In addition, BD can be used for managing operational costs from many aspects—for example, monitoring inventory levels to reduce them, creating precise marketing strategies to lower marketing costs, and optimizing distribution routes to minimize transportation costs (Liu & Yi, 2018a, 2018b, 2018c). In their study, Awan et al. (2021) state that decision-making is an important factor in performance management. According to their findings, BI and business analytics applications enhance data-driven decision-making and performance, especially in circular economy businesses. Pugna et al. (2019) conclude in their study that one of the first areas where BD and BDA can be implemented successfully is performance management. This conclusion is based on two judgments. First, performance management is a familiar activity for business managers, and therefore, they can easily make use of new technologies to gain insights into their current performance management activities. Second, BD and BDA can be integrated moderately easily in existing system infrastructures that are based on BI. Brinch (2018) and Barbosa et al. (2018) share the same conclusion that using BD in supply chain management enhances its performance by improving business processes and decision-making. Other positive effects can be found in price breakdowns and decreasing delivery costs (Wang et al., 2016a, 2016b) and in strategic sourcing (Jain et al., 2017). In

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addition, BDA can advance supply chain agility and thereby increase its competitive advantage (Dubey et al., 2019). Lozada et al. (2019) also note that beyond the supply chain, BD can create more agile service and product innovations as well.

5 Directions for Future Research Research gaps and possible future research directions are addressed in the following and summarized in Table 3. Drivers for utilizing digitalization in management and organizational controls. First, the internal drivers for utilizing novel technologies in MCSs and OCs should be investigated more thoroughly because the current literature does not cover this subject well. The drivers are suspected to be different at different levels since the needs and uses for OCs and MCSs are reported to be very different. The difference is (supposedly) in the resolution and nature of measured qualities at different levels. Second, the meaning of implementing novel digital tools at different positions in the supply chain is supposedly different, and, therefore, the drivers are different. Companies at different positions in the supply chain have different roles and operations. Therefore, it is not certain that all roles can gain similar benefits from utilizing novel technologies in their management. Utilizing novel digital tools in MCSs and OCs. First, the transition from conventional ways of operating with MCSs and OCs to digitizing them is not advancing evenly in manufacturing industries. The prerequisites that organizations need to possess in order to successfully utilize MC require further investigation. Second, digitalization will affect management roles. For example, the roles of decision-makers will change drastically from making intuitive and experience-based decisions to making digitally assisted ones. How will the novel technologies change the roles of management, and how should the implementation be commenced and completed to get the best results? Also, the extent to which different types of control mechanisms have different impacts requires research. Digitalization’s effects on decision-making quality and effectiveness. First, when decision-making mechanisms change when novel tools are utilized, the effects of extending the amount of digitalization in decision-making at different MCS levels should be examined. In particular, operational-level decision-making requires more research. Second, this question concerns the dimension of examining if novel digital tools should be utilized as augmentation tools for human reasoning capabilities rather than for the automatization of shop floor-level decisions. This leads to another theme: is the current quality and effectiveness of digitally made decisions at a level that makes it possible to exclude human reasoning from the decision-making process in human-centered processes? Digitalization’s effect on performance. Finally, using tools more interactively will change the entire meaning of the novel digital tools in performance management. More research on the effects of specific performance dimensions is needed. For example, digital transformation is a phenomenon that can dramatically influence

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Table 3 Research themes derived from the literature and future research directions Themes derived from analysis

References

Future research directions

Drivers for utilizing digitalization in management and organizational controls Internal drivers

Need to handle large volumes of data Process improvement Need for enhanced sustainability

E.g., Davenport et al. (2017), Alkaraan et al. (2022), Tabesh (2022)

What are the attributes of decision-makers that influence the strategic choices in implementing digital tools? What are the most significant internal drivers of SMEs to start implementing digital tools and digitizing their management operations? How can sustainability information be included in a control system’s scope, with unquantifiable factors such as social sustainability?

External drivers

Market and customer demands Supply chain coordination

E.g., Liu and Yi (2018c), Awan et al. (2021), Venkatesh et al. (2021)

How do drivers change according to position in the supply chain? What is the meaning of digital tools in differently sized companies that have different positions and statuses in the supply chain?

Utilizing novel digital tools in management control systems and organizational controls Impacts on MCS

Non-financial practices formalized Decision-making processes Operational planning activities Support the analysis of large amounts of information

E.g., McAfee and Brynjolfsson (2012), Wang et al. (2016a, 2016b), Trunk et al. (2020), Vitale et al. (2020)

Why are financial and/or formal practices not affected to the same extent as informal practices? What are the limiting factors in delaying the use of digital tools in MC? What kind of process model would facilitate the implementation of new practices in management so that hindering factors can be considered? (continued)

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Table 3 (continued)

Prerequisites for using digital tools in MC

Themes derived from analysis

References

Future research directions

System readiness systems (ability to process information across different settings) Supporting strategy and goals Sufficient structures Knowledge of and experience with technologies Managerial skills

E.g., Kolbjørnsrud et al. (2017), Von Krogh (2018), Butner and Ho (2019), Trunk et al. (2020), Asadi et al. (2022)

What are the main mechanisms in operational and strategic decision-making processes that digitalization will have an effect on? What series of micro-mechanisms are required to enable the change? What needs for changes in strategy will come with the need for changes as the business environment changes? How can fear of new systems and unlearning from older systems be overcome? How will human resources practices be altered when requirements for capabilities in performing work tasks change along the way?

Digitalization’s effects on decision-making quality and effectiveness Effects of digital tools

Reduce flaws in decision-making Faster and more accurate analytical decisions More intelligent decisions Replacement of human decision-makers or supporting them Increase in decision creativity Boost analytic abilities

E.g., Blenko et al. (2010), Wang et al. (2016a, 2016b), Wilson and Daugherty (2018); Vincent (2021)

What effects do digitizing functions have in decision-making at the operational level? What are the current purposes of AI in human-centered processes as well as the possibilities that are expected to be within reach in the near future? Which indicators for AI’s impacts on decision quality and effectiveness can be utilized?

Challenges in using digital tools

Irrelevant or inaccurate data Misrepresented data causing decision errors Lack of human emotions and rationality Ethical risks such as risk to human life, undermining social justice, and privacy Risks are misuse, abuse of technology, and loss of control

E.g., Turing (2007), Arkin (2008), Yan (2018); Guan et al. (2022), Tabesh (2022)

What are the circumstances and settings where adding digital aids in decision-making can be hindering factors for manual workers? Is digitalization really enhancing performance at the operational level, and can benefits and disadvantages be quantified?

(continued)

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Table 3 (continued) Themes derived from analysis

References

Future research directions

E.g., Wang et al. (2016a, 2016b), Brinch (2018); Barbosa et al. (2018), Pham and Stack (2018), Dubey et al. (2019), Lozada et al. (2019), Awan et al. (2021)

What are the trends in the future development of performance management aided by digital tools, and what is the need for predicting BI and BDA changes? Does using digital tools change the setting to a more interactive use of data and the MCS? What are the effects of different digital tools on specific performance dimensions? What effects do digital tools have on sustainability while new technologies enable higher production efficiency?

Digitalization’s effect on performance Strategic advantage Decrease in response time Improvement of business processes Optimization of distribution routes Optimization of costs (operational costs, delivery costs, price breakdowns) Circular economy performance Supply chain agility

sustainable development, so the question is: How have digitalization and novel digital technologies affected sustainability performance in industrial companies in different positions and roles in the supply chain?

6 Conclusions This study aimed to explain how the utilization of emerging digital technologies for organizational and management controls has been studied and what kind of performance improvements can be achieved. To do so, an integrated overview of the current literature was carried out. The findings reveal research themes derived from the analysis as well as future research directions and questions. The authors’ attempt was to draw attention to topics that were recurring in the current literature but that still had gaps to be filled. Four themes were identified: drivers for utilizing digitalization in management and organizational controls; utilizing novel digital tools in management control systems and organizational controls; digitalization’s effects on decision-making quality and effectiveness; and digitalization’s effect on performance. Key themes and current debates in each theme were noted, the current state of research on each theme was compiled, and gaps in the research were identified. This study’s query string was limited to articles concerning business management and accounting, social sciences, and decision sciences, and for this reason, the study has a limitation that should be noted. The nature of the subject’s foundation is highly technological, but it was compulsory to stay at a general level to be able to identify

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the topics and the gaps they presumably include. Therefore, this review provides a broad overview of the technologies rather than a detailed explanation of how they really work in this context. After noting this, the authors suggest that one possible future research direction would be to see the possibilities of each technology indepth in the context of the topics presented in this study. In addition, the studies have contributed an extensive amount of theory and frameworks, but the examples were from very limited settings, and, therefore, the results require further backup. This reinforces the authors’ opinion that there is a need for more focused research on the effects of implementing and integrating digitalization in MC, digitalization in MCSs and OC, digitalization’s effects on decision-making, digital decision quality and effectiveness, and digitalization’s effect on performance.

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Examining the Role of Technology Transfer on Digitalization: Consequences and Challenges Lena Bischoff , Marta Ferrer-Serrano , Andrea Ogando-Vidal, and Amaya Soto-Rey

Abstract Digitalization has become critical in today’s economies as it allows individuals access to resources and capabilities that could not have been accessed without it. However, the development of digital infrastructures is not easy. The digital transition has been recognized as a global challenge in today’s societies that need collaboration to get valuable technological assets. This idea has been defined as “technology transfer”(TT) and has been identified as one of the most critical determinants for digitalization achievement. Although there is consensus on the positive side of TT and digitalization, there is anecdotal evidence of the negative part and the challenges that this new paradigm brings. To offer a holistic understanding of the consequences and the impact of TT in a digitalized economy, this chapter provides a conceptualization of TT and digitalization, investigates its advantages and disadvantages; shows some applied evidence through the lenses of real cases; identifies the main challenges and implications that TT and digitalization have on today’s society and organizations. Keywords Technology transfer · Digitalization · Conceptualization · Knowledge · Advantages · Disadvantages · Project · Collaboration · Skills · Consequences · Challenges · Implications · Innovation · Industry 4.0 · Transition · Digital transformation · Training · Digital skills

L. Bischoff · A. Ogando-Vidal Department of Business Organization and Marketing, University of Vigo, Vigo, Spain ECOBAS Interuniversity Research Center, Vigo, Spain M. Ferrer-Serrano (B) Department of Business Management, University of La Rioja, Logroño, Spain e-mail: [email protected] A. Soto-Rey Training Department, Centro Tecnológico del Mar, Fundación CETMAR, Vigo, Spain © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 C. Machado and J. P. Davim (eds.), Management for Digital Transformation, Management and Industrial Engineering, https://doi.org/10.1007/978-3-031-42060-3_2

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1 Introduction Digitalization has become critical in today’s economies. Globalization has driven to more competitive environments, where digital performance and infrastructures are needed to resist ecosystem changes (López-Manuel et al., 2022). In this sense, digitalization allows individuals access to resources and capabilities that could not have been accessed without it (Adebanjo et al., 2021; Del Giudice et al., 2021). Proof of this can be seen in the COVIID-19 pandemic, where the necessity of individuals to be connected was completely noticeable under the lockdown (Ferrer-Serrano et al. 2020; World Economic Forum, 2021). But digitalization is not only a must for individuals under extreme events but also for companies (both local and internationalized), who need to compete in global and complex contexts where being well-connected is often a driver to survival (Denicolai et al., 2021). However, the development of digital infrastructures is not an easy task (Block et al., 2022; Tortorella et al., 2020). The digital transition has been recognized as a global challenge in today’s societies that need collaboration to get valuable technological assets (Fini et al., 2023). This idea has been defined as “technology transfer”(TT), and it has been identified as one of the most critical determinants for digitalization achievement (Johnson et al., 2023; Sengupta & Rossi, 2023). Therefore, academics, managers, and policymakers have focused on the elaboration of strategies that enable the promotion of digitalization through TT. Some examples can be found at the European Commission, which has established a roadmap of strategies that foster collaboration between institutions to achieve digital transformation by 2030 in the form of a Path to the Digital Decade. The latest initiative, Horizon Europe, has increased the funding of its predecessor Horizon 2020, by almost 19%. In particular, a total of 413 projects concerning digitalization1 have been funded to date, amounting to 2.5 billion euros. Countries are also becoming aware of the need to have an adequate TT agency. Germany is making headway in setting up a national TT agency to stimulate the collaboration between universities, research centers and industry, especially for digitalization projects.2 Also, managers have shown interest in TT as an enabler strategy that fosters the digital transition. For instance, in March 2023, Amazon and Iberdrola announced a new global collaboration to support the development of large-scale renewable energy projects and leverage cloud computing technology to enhance digitalization in the energy transition,3 Another example can be found in the Netherlands, where The Digital Europe Programme with a planned overall budget of e7.5 billion (in current prices) will provide strategic funding to answer these challenges, supporting projects in five key capacity areas: in supercomputing, artificial intelligence, cybersecurity, advanced digital skills, and ensuring a wide use of digital technologies across the economy and society, including through Digital Innovation Hubs. In press: https://digital-strategy.ec.europa.eu/en/activities/digital-programme. 2 In press: https://sciencebusiness.net/news/germany-making-headway-setting-national-techno logy-transfer-agency. 3 In press: https://nawindpower.com/iberdrola-amazon-partner-to-accelerate-a-cleaner-and-sma rter-energy-system. 1

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TNO4 works as an independent research organization that provides infrastructures for potential collaborations for innovation projects. The thematic areas in which they focus include digitalization, as they consider it to be one of the main pillars and challenges for today’s society. Although there is consensus on the positive side of TT and digitalization, there is anecdotal evidence of the negative part, as well as the challenges that this new paradigm brings. To offer a holistic understanding of the consequences and impact of TT in a digitalized economy, this chapter aims to (1) conceptualize TT and digitalization terms, (2) investigate its advantages and disadvantages; (3) show some applied evidence through the lenses of real cases; (4) to identify the main challenges and implications that TT and digitalization have on today’s society and organizations. To accomplish these objectives, we have first reviewed TT and digitalization literature to outline the most up-to-date frame. Second, we have explored a collaborative European-funded project developed from 2018 to 2022 (MATES5 ). Various of the pilot experiences of this project offer key empirical evidence of TT dynamics that allow the exchange of technological resources in order to foster digitalization in the maritime industry. Finally, we have elaborated a list of the main challenges identified in the previous sections, offering both academic and practical evidence and implications for policymakers and managers. Therefore, this study contributes to the previous literature offering a better understanding of the TT strategy to foster the digital transition in nowadays complex ecosystems. It also contributes by offering evidence of the consequences and current implications of the real impact of TT on digitalization through the exploration of a European collaborative project based on collaboration dynamics. This double perspective, the theoretical and practical understanding of the phenomenon, has allowed us to finally offer a critical reflection of real challenges and implications to be considered in future research. This chapter is structured as follows. First, Sects. 2, 3 and 4 present a review of the main advantages and disadvantages of TT and digitalization. Second, Sect. 5 takes this academic knowledge into reality through the presentation of applied evidence. Finally, Sect. 4 finds some challenges and implications that TT and digitalization drive for today’s society and organizations.

2 Conceptual Foundations: Technology Transfer According to Bengoa et al. (2021), TT refers to the process of transferring knowledge, discoveries, inventions, and other intellectual property from one agent to another agent for the purpose of further development, commercialization, and/or public use. This can involve the transfer of patents, copyrights, trademarks, expertise, skills, and

4 5

Corporative website: https://www.tno.nl/en/about-tno/mission-strategy/. Project website: https://www.projectmates.eu/.

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know-how, as well as the establishment of new ventures. TT is a great driver for innovation and economic growth by making scientific and technological advancements available to a wider audience. It is often facilitated through partnerships between academic institutions, government agencies, and private industry and can take many different forms, including licensing agreements, joint ventures, and spinoff companies. The origins of TT can be traced back to the industrial revolution when knowledge and technology were first codified and systematized. In the scientific literature, TT finds its beginnings in the 1970s (Bengoa et al., 2021). TT encompasses a range of activities and mechanisms through which knowledge, skills, and technological innovations are shared and disseminated across various entities, including universities, research institutions, industries, and nations. This process is pivotal in promoting technological advancements, enhancing industrial competitiveness, and fostering economic growth (Bengoa et al., 2021). In the following paragraphs, the individual concepts of TT, including university TT, international TT, intra-firm TT, inter-firm TT, absorptive capacity, and public innovation policies, will be explained while highlighting their interconnectedness. An overview including summaries of all concepts can be found in Table 1. University TT, the most exhaustive and oldest research field, is a critical component of the innovation ecosystem, as it facilitates the commercialization of research Table 1 TT conceptualization Concepts of TT

Description

University technology transfer (University TT)

The process of transferring academic research outputs to the commercial sector fosters innovation and industry–academia collaboration (Bengoa et al., 2021)

International technology transfer (International TT)

The cross-border exchange of technology, knowledge, and skills promotes global technological advancements and economic growth (Aitken & Harrison, 1999)

Intra-firm technology transfer (Intra-firm TT)

The sharing of knowledge, technology, and skills within an organization enhances internal efficiency and innovation capacity (Lin et al., 2002)

Inter-firm technology transfer (Inter-firm TT)

Collaborative efforts between companies facilitate knowledge exchange and foster the development of novel technologies and products (Kotabe et al., 2003)

Absorptive capacity

The ability of an organization or country to recognize, assimilate, and utilize external knowledge and technology effectively (Zahra & George, 2002)

Public innovation policies

Government-driven initiatives that encourage and support innovation, research, and TT to foster economic growth and technological advancements (Grimaldi et al., 2011)

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outputs generated by academic institutions (Bengoa et al., 2021). This process encompasses various mechanisms such as academic entrepreneurship (Schmitz et al., 2017), licensing (Balconi et al., 2004), spinoffs (Pirnay et al., 2003), research collaborations, consulting, and training services (Siegel & Wright, 2015) or use of TT offices (Siegel et al., 2004). University TT not only propels the adoption of cutting-edge technologies in the market but also fosters relationships between academia and industry, promoting knowledge exchange and enhancing the overall innovation landscape (Bengoa et al., 2021; Ferrer-Serrano et al., 2021a, 2021b). International TT refers to the cross-border exchange of technological know-how, expertise, and intellectual property. This process can occur through trade, foreign direct investment, licensing, joint ventures, and collaborative research endeavors, with the need for adaptation to local conditions (Aitken & Harrison, 1999). International TT enables countries and organizations to access novel technologies and practices, fostering technological advancements and promoting global economic growth. As sub-categories, transfer at the international level can take place in both intra- and inter-firm contexts (Kotabe et al., 2003). However, these two concepts are not limited to the international context. Intra-firm and inter-firm TTs refer to the sharing of knowledge, skills, and technology within and between organizations, respectively. Intra-firm TT encompasses the diffusion of best practices, knowledge sharing among departments or teams, and internal training initiatives, which collectively enhance organizational efficiency and innovation capacity (Ferrer-Serrano et al., 2021a, 2021b; Lin et al., 2002). The dissemination of knowledge is promoted by organizational culture, formal and informal communication, or infrastructure (Lin et al., 2002). On the other hand, inter-firm TT involves collaborative efforts between companies, such as joint ventures, research partnerships, and licensing agreements, which facilitate knowledge exchange and foster the development of novel technologies and products (Kotabe et al., 2003). A vital role in the effectiveness of all types of TT processes is the concept of absorptive capacity. It refers to the ability of an organization or a country to identify, assimilate, and utilize new knowledge and technology from external sources (Zahra & George, 2002). A strong absorptive capacity is contingent upon several factors, including organizational structure, human capital, and prior knowledge. Enhancing absorptive capacity can bolster an entity’s capability to adopt and capitalize on novel technologies and innovations, thereby strengthening its competitive advantage (Zahra & George, 2002). Public innovation policies also span across a wide range of TT approaches, as they encompass government-driven initiatives aimed at encouraging and supporting innovation, research, and TT (Grimaldi et al., 2011). These policies may include research and development funding, tax incentives, intellectual property protection, and support for industry–academia collaboration. Effective public innovation policies can create a conducive environment for TT and innovation, driving economic growth and fostering technological advancements. These multifaceted concepts of TT and their interactions contribute to the overall innovation ecosystem, while specific contexts and circumstances of TT

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vary depending on a number of factors, including the type of technology being transferred, the industry or sector involved, the stage of development of the technology, and the nature of the collaboration between agents (Kirchberger & Pohl, 2016). Hence, the effective and appropriate implementation of TT mechanisms, coupled with strong absorptive capacity and supportive public innovation policies, can significantly enhance technological progress, stimulate economic growth, and promote global sustainability. However, TT can also encompass disadvantages which must be weighed against its advantages. By understanding the different concepts, approaches, and challenges, it is possible to develop a more nuanced and comprehensive understanding of the role of TT in digitalization.

2.1 Advantages of TT Technology transfer offers numerous advantages that contribute to the growth and development of various sectors while propelling digitalization forward (see Table 2). As companies leverage new technologies and expertise gained through TT, they enhance their competitiveness within their respective industries (João et al., 2020). In this context, TT plays a critical role in bridging the gap between academia and industry by facilitating information transfer (Schmitz et al., 2017). By accelerating commercialization, TT speeds up the process of bringing new products and services to the market. This acceleration, in turn, stimulates economic growth by fostering innovation and entrepreneurship, ultimately driving economic expansion and job creation (João et al., 2020). One of the key aspects of TT is the encouragement of collaboration. By fostering knowledge-sharing and cooperation among researchers, institutions, and industries, TT creates a synergistic environment where ideas can be exchanged, and innovative solutions can be developed. This collaborative atmosphere also enhances educational opportunities, as students and researchers gain access to cutting-edge technologies and knowledge from various fields, thereby broadening their horizons and improving the overall quality of research and education (Audretsch et al., 2014). Fostering entrepreneurship is another significant advantage of TT. The adoption of new technologies often leads to the creation of start-ups and the development of innovative products and services, which, in turn, further drives economic growth and diversification (Schmitz et al., 2017). This entrepreneurial spirit is closely connected to the reduction of global inequalities, as TT provides developing countries with access to advanced technologies, narrowing the gap between developed and developing nations (Audretsch et al., 2014). TT also enables technology localization, which involves the adaptation of imported technologies to suit the unique needs and conditions of the recipient country. This process not only improves the overall effectiveness of TT efforts but also contributes to the development of more context-appropriate solutions that can address local challenges (Audretsch et al., 2014).

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Table 2 TT advantages Advantages of TT

Description

Accelerates commercialization

TT speeds up the process of bringing new products and services to the market (João et al., 2020)

Stimulates economic growth

By fostering innovation and entrepreneurship, TT drives economic expansion and job creation (João et al., 2020)

Enhances competitiveness

Companies can leverage new technologies and expertise to gain a competitive edge in their industries (João et al., 2020)

Bridges academia–industry gap

TT facilitates the transfer of knowledge and technology from research institutions to the private sector (Schmitz et al., 2017)

Encourages collaboration

TT fosters knowledge sharing and cooperation among researchers, institutions, and industries (Audretsch et al., 2014)

Enhances educational opportunities

Students and researchers gain access to cutting-edge technologies and knowledge from various fields (Audretsch et al., 2014)

Fosters entrepreneurship

The adoption of new technologies often leads to the creation of start-ups and innovative products/services (Schmitz et al., 2017)

Reduces global inequalities

TT provides developing countries with access to advanced technologies, fostering economic growth (Audretsch et al., 2014)

Enables technology localization

TT facilitates the adaptation of imported technologies to suit the unique needs of the recipient country (Audretsch et al., 2014)

Contributes to global problem-solving

TT enables the pooling of resources and expertise to address pressing global issues like climate change (Kedia & Bhagat, 1988)

Lastly, TT plays a crucial role in contributing to global problem-solving. By enabling the pooling of resources and expertise from various sources, TT allows for collaborative efforts to address pressing global issues, such as climate change. Through the combination of these interconnected advantages, TT emerges as a driving force for innovation, global collaboration, and sustainable development, ultimately shaping a more equitable and prosperous world (Kedia & Bhagat, 1988).

2.2 Disadvantages of TT Despite its numerous benefits, technology transfer also presents certain drawbacks that warrant consideration (see Table 3). One significant disadvantage of TT is the

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risk of becoming dependent on foreign entities for access to key technologies and expertise (Grimes & Sun, 2014). This dependence can be problematic if the foreign entity decides to withdraw its support or increase its fees. Moreover, the reliance on TT may stifle local innovation and hinder the development of homegrown solutions, leading to reduced incentives for local research and development (Millar & Choi, 2009). Table 3 TT disadvantages Disadvantages of TT

Description

Dependence on foreign entities

TT can lead to reliance on foreign entities for key technologies and expertise, stifling local innovation ( Grimes & Sun, 2014)

Cultural differences and barriers

Differences in language, work practices, and management styles can limit absorptive capacity and create misunderstandings (Choi, 2009; Millar & Choi, 2009)

Misalignment of goals and objectives

Different goals and objectives between transferring and receiving entities may lead to conflicts and inefficiencies (Choi, 2009)

Intellectual property leakage

TT can result in the unintended sharing of intellectual property, allowing competitors to benefit from the innovation (Ockwell et al., 2010)

Loss of control over key technologies

Transferring entities may lose control over key technologies and knowledge if they do not retain sufficient intellectual property rights (Ockwell et al., 2010)

Reverse TT

Recipients may develop superior technology and transfer it back to the original entity, diminishing its competitive advantage (Millar & Choi, 2009)

Legal and regulatory issues

Complex legal and regulatory compliance challenges can increase costs and delays in TT (Kaushik et al., 2014; Ockwell et al., 2010)

Unequal distribution of benefits

Benefits from TT may not be equitably distributed among stakeholders, leading to disparities and tensions (Millar & Choi, 2009)

Environmental, societal, and ethical implications

TT can lead to environmental degradation, negative societal impacts, and ethical concerns if not properly managed, regulated, or used for controversial purposes (Siegel et al., 2003; Das & Jedlicka, 1993; Phan & Siegel, 2006)

The exploitation of academic research

TT in academia can lead to the exploitation of research for commercial gain without proper compensation (Karnani, 2013)

Overemphasis on commercial viability

TT may result in an overemphasis on commercial viability, overshadowing scientific merit or societal impact (Karnani, 2013)

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Cultural differences and barriers between the transferring and receiving entities can limit absorptive capacity and make the TT process costly and time-consuming (Choi, 2009). Differences in language, work practices, and management styles can create misunderstandings and delays (Millar & Choi, 2009). Furthermore, the misalignment of goals and objectives between the entities may lead to potential conflicts and inefficiencies, impeding the success of TT initiatives (Choi, 2009). Intellectual property (IP) leakage is another concern, as TT can lead to unintended sharing of IP, allowing competitors to benefit from the innovation (Ockwell et al., 2010). This issue is closely related to the potential loss of control over key technologies and knowledge, which can occur if the transferring entity does not retain sufficient intellectual property rights or if the receiving entity develops the technology further and becomes a competitor (Ockwell et al., 2010). Reverse TT, wherein the recipient develops superior technology and transfers it back to the original entity, may also diminish the transferring entity’s competitive advantage (Millar & Choi, 2009). Legal and regulatory issues involving complex compliance challenges can further increase costs and delays, exacerbating the overall effectiveness of TT (Kaushik et al., 2014; Ockwell et al., 2010). Additionally, the benefits from TT may not be equitably distributed among stakeholders, leading to disparities and tensions (Millar & Choi, 2009). Environmental and societal impacts must be considered in the context of TT. Transferred technology may contribute to environmental degradation if not properly managed and regulated, while negative societal consequences may arise from the adoption of certain technologies in the recipient’s society and culture (Das & Jedlicka, 1993; Siegel et al., 2003). Ethical concerns, such as the use of technology for potentially harmful or controversial purposes like nuclear or chemical technologies, must also be taken into account (Phan & Siegel, 2006). In the academic field, TT can lead to the exploitation of academic research for commercial gain without proper compensation to the academic institution or researchers (Karnani, 2013). This can result in an overemphasis on the commercial viability of research, potentially overshadowing scientific merit or societal impact and narrowing the research focus to commercially viable areas at the expense of more exploratory or basic research (Karnani, 2013). In conclusion, it is essential to address these potential disadvantages when planning and implementing TT initiatives. By doing so, it may be possible to ensure responsible and ethical TT, maximizing its benefits while minimizing risks and adverse effects.

3 Conceptual Foundations: Digitalization Digitalization has emerged as a pervasive force that has fundamentally transformed society, economy, and business over recent decades. As a defining trend of the twenty-first century, it has facilitated the development of new business models, such

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as e-commerce and the sharing economy, while also enabling previously unimaginable products and services. The influence of this megatrend extends to diverse areas, including entertainment, security features of smart homes, e-healthcare, smart mobility, and smart cities. This paradigm shift began in the 1990s and 2000s with the rise of the Internet and mobile computing, driving businesses and organizations to adopt digital technologies, transform their operations, and deliver new value to customers (Ritter & Pedersen, 2020). However, the term “digitalization” is often used inconsistently, resulting in unclear and unfocused definitions (Hellsten & Paunu, 2020). While some descriptions simply refer to the shift from analog to digital (Hagberg et al., 2016), this fails to capture the full scope of digitalization, particularly from a managerial perspective. In the business world, digitalization involves using digital technologies and data to create new revenue opportunities, enhance competitiveness, transform business processes, and enable new digital business models centered around digital information (Gobble, 2018). This comprehensive integration leads to fundamental changes in business operations, customer interactions, and employee engagement (Ritter & Pedersen, 2020). A wide range of concepts falls under the umbrella of digitalization, with digital transformation and digital disruption being the two significant overarching terms (Matt et al., 2015; Vial, 2019). Digital transformation encompasses the use of digital technologies to improve existing processes and create new ones, while digital disruption involves fundamentally changing industry practices through the creation of new digital business models (Matt et al., 2015; Vial, 2019). All other concepts in the realm of digitalization can be seen as contributing to transformation and/or disruption. For instance, Industry 4.0, or the fourth industrial revolution, has shaped the business landscape by incorporating digital technologies into manufacturing value chains and processes, thereby enhancing productivity and efficiency (Lasi et al., 2014). This shift aligns with the broader trend of digital transformation. Similarly, digital ecosystems, which represent interconnected networks of digital platforms, products, and services (Barykin et al., 2020), enable companies and individuals to create, share, and consume information and resources. The Internet of Things (IoT) fuels these ecosystems by allowing everyday objects and devices to connect and exchange data through the Internet (Barykin et al., 2020), further driving digital transformation and disruption. The interconnected nature of digital ecosystems and IoT devices generates vast amounts of structured and unstructured data, known as Big Data (Roy & Roy, 2019). The analysis and management of Big Data, which leads to insights and informed decision-making, is a crucial aspect of digital transformation. Artificial Intelligence (AI) and Machine Learning, as a subset of AI, play vital roles in processing this data and automating decision-making processes across industries (Cubric, 2020). Augmented Reality (AR) and Virtual Reality (VR) are immersive technologies that enhance user experiences and interactions, enabling businesses to create new products and services that merge digital and physical worlds (Ribaupierre & Eagleson, 2017). These technologies can contribute to both digital transformation and digital disruption. Blockchain technology, a decentralized and distributed

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ledger system, has the potential to revolutionize industries by securely recording and verifying transactions across multiple computers (Reyna et al., 2018). This innovation disrupts traditional transaction models and promotes more transparent and secure processes. Lastly, cybersecurity is essential for protecting computer systems, networks, and data from theft, damage, or unauthorized access in the increasingly digital world (Ten et al., 2010). Each of these digitalization concepts offers unique insights into how digital technologies are transforming the economy, society, and individual lives (see Table 4). It is crucial to assess their potential for promoting innovation, productivity, and competitiveness, as well as their relationship to TT. Simultaneously, we must consider the challenges and benefits associated with their implementation to develop a more nuanced understanding of digitalization’s potential (see Tables 5 and 6).

3.1 Advantages of Digitalization First and foremost, digitalization has significantly increased efficiency and productivity for businesses by enabling the automation of numerous processes (Parviainen et al., 2017). Through automation, tasks that previously required substantial time and effort can be completed more quickly, leading to cost savings and improved productivity. This increased efficiency often translates into reduced costs for both businesses and consumers, as physical infrastructure and paper-based processes are rendered obsolete (Parviainen et al., 2017). The enhanced efficiency brought about by digitalization also impacts collaboration and communication within organizations, allowing employees to work together effectively across geographical distances and time zones (Parviainen et al., 2017). This interconnectedness fosters increased productivity and the sharing of ideas, which in turn drives innovation. As a result, businesses can develop new products, services, and business models that set them apart from competitors while simultaneously improving customer experiences (Parviainen et al., 2017). Improved access to information and services is another notable advantage of digitalization in a business context (Parviainen et al., 2017). By making resources more readily available, digitalization promotes greater participation in the economy and society, leading to increased employment opportunities in fields such as software development, data analysis, and digital marketing (Bresciani et al., 2021). The interconnected nature of digitalization is further exemplified by its impact on data management. With the ability to collect, store, and analyze large volumes of data, businesses can make more informed decisions and identify new opportunities for growth (Raptis et al., 2019). This advantage feeds into the broader theme of increased economic growth, as digitalization drives productivity, efficiency, and innovation within organizations (Parviainen et al., 2017). Greater agility and flexibility are other benefits derived from digitalization, allowing businesses to adapt quickly to changing market conditions and customer

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Table 4 Digitalization conceptualization Concepts of digitalization

Description

Digital transformation

The process of using digital technologies to improve existing business processes and create new ones (Matt et al., 2015; Vial, 2019)

Digital disruption

The fundamental change in how business is conducted within an industry through the creation of new digital models (Vial, 2019; Matt et al., 2015

Industry 4.0

The incorporation of digital technologies into manufacturing value chains and processes to enhance productivity (Lasi et al., 2014)

Digital ecosystems

Interconnected networks of digital platforms, products, and services enable information and resource sharing (Barykin et al., 2020)

Internet of things (IoT)

The interconnection of everyday objects and devices through the internet enables them to send and receive data (Barykin et al., 2020)

Big data

The analysis and management of vast amounts of structured and unstructured data to derive insights and make informed decisions (Roy & Roy, 2019)

Artificial intelligence (AI) and machine learning

The development of computer systems capable of performing tasks that would typically require human intelligence and the teaching of computers to learn, adapt, and make decisions based on data inputs (Cubric, 2020)

Augmented reality (AR) and Virtual reality (VR)

The overlay of digital content onto the physical world and immersive, simulated environments created by computer-generated graphics allow users to experience and interact with virtual and enhanced worlds (Ribaupierre & Eagleson, 2017)

Blockchain

A decentralized, distributed ledger technology that securely records and verifies transactions across multiple computers (Reyna et al., 2018)

Cybersecurity

The practice of protecting computer systems, networks, and data from theft, damage, or unauthorized access (Ten et al., 2010)

needs (Parviainen et al., 2017). This responsiveness is crucial for maintaining relevance in an ever-evolving business landscape. Furthermore, digitalization contributes to a reduced environmental impact by minimizing paper-based processes, enabling sustainable business models and remote work, which helps businesses lower their carbon footprint (Gensch et al., 2017) (Table 5).

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Table 5 Digitalization advantages Advantages of digitalization

Description

Increased efficiency and productivity

Automation of processes enables faster task completion, leading to cost savings and improved productivity for businesses (Parviainen et al., 2017)

Enhanced collaboration and communication Digitalization allows employees to work together effectively across distances and time zones, fostering innovation and productivity (Parviainen et al., 2017) Improved access to information and services Digitalization promotes greater participation in the economy and society, creating new employment opportunities in various fields (Parviainen et al., 2017) Increased employment opportunities

Digitalization creates new job opportunities in fields like software development, data analysis, and digital marketing (Bresciani et al., 2021)

Impact on data management and growth opportunities

The ability to collect, store, and analyze large volumes of data helps businesses make informed decisions and identify new growth opportunities (Parviainen et al., 2017; Raptis et al., 2019)

Greater agility and flexibility

Digitalization enables businesses to adapt quickly to changing market conditions and customer needs, maintaining their relevance in an ever-evolving landscape (Parviainen et al., 2017)

Reduced environmental impact

Digitalization minimizes paper-based processes and enables remote work, helping businesses lower their carbon footprint (Gensch et al., 2017)

3.2 Disadvantages of Digitalization One significant disadvantage is the increased reliance on technology, which can create vulnerabilities and expose businesses to the risk of cyber-attacks and other security threats. As organizations become more dependent on digital systems, the potential consequences of technological failures and security breaches can have severe financial and reputational implications (Dalcher, 2007). Technological obsolescence presents another challenge for businesses in the rapidly evolving digital landscape. Companies that have invested heavily in nowobsolete technologies may face financial difficulties and struggle to keep up with competitors who have adopted more advanced systems (Mellal, 2020). This issue is compounded by the disruption of traditional industries and the displacement of jobs resulting from automation and artificial intelligence (Skog et al., 2018). While digitalization can lead to increased efficiency and productivity, it may also cause job losses within a company, leading to workforce-related challenges and potential negative public perception (Braxton & Taska, 2023).

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Digitalization can also introduce complexity and confusion, particularly for employees who are not familiar with the technology or lack the necessary digital skills. This can hinder the adoption of new technologies within an organization, resulting in inefficiencies and an inability to fully capitalize on the potential benefits of digitalization. Consequently, companies may face challenges in addressing the digital divide among their workforce, which can exacerbate existing inequalities and hamper overall productivity (Cullen, 2001). Privacy concerns represent another significant drawback of digitalization for businesses. As companies collect and use personal data, they face risks if sensitive information is compromised (Elmaghraby & Losavio, 2014). While improved data management can lead to better decision-making, it can also raise concerns about data privacy and security, which can result in legal and reputational consequences (Elmaghraby & Losavio, 2014). While digitalization can contribute to reduced environmental impact in some respects, such as by minimizing paper-based processes and enabling remote work, it also has negative consequences for the environment (Romero et al., 2018). Digitalization can lead to increased energy consumption and electronic waste production, which can negatively impact a company’s corporate social responsibility efforts and affect its public image (Romero et al., 2018). Lastly, digitalization can contribute to the dissemination of disinformation and misinformation, particularly through social media platforms (Ciampaglia, 2018). For businesses, this can have negative effects on brand reputation and trust, ultimately undermining the potential benefits of improved customer experiences and communication (Table 6). By examining the conflicting aspects of digitalization and acknowledging the interconnectivity of its advantages and disadvantages, businesses can develop strategies and policies that maximize the benefits of digitalization while minimizing its drawbacks.

4 The Role of Technology Transfer in Digitalization TT plays a crucial role in the digitalization process by facilitating access to innovative technologies and expertise. Therefore, TT accelerates the pace of digitalization, not only for companies but for education and research centers, as well as administration and governments—basically—the whole society. One primary domain where TT significantly contributes to digitalization is the expansion of digital infrastructure and connectivity. For example, the dissemination of mobile technologies from developed to developing countries has increased access to digital services, such as e-commerce, e-government, and e-health (Audretsch et al., 2014). In addition to infrastructure, TT fosters the growth of digital skills and knowledge. The exchange of training programs and best practices in fields such as data analytics, cybersecurity, and digital marketing enables companies to develop the expertise

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Table 6 Digitalization disadvantages Disadvantaged of digitalization

Description

Increased reliance on technology

Greater reliance on technology exposes businesses to vulnerabilities, such as cyber-attacks and security threats, which can have financial and reputational implications (Dalcher, 2007)

Technological obsolescence

Rapid advancements can render existing technologies obsolete, challenging businesses that have invested in them and affecting competitiveness (Mellal, 2020)

Disruption of industries and job displacement

Digitalization can lead to job losses within companies, resulting in workforce challenges and potential negative public perception (Braxton & Taska, 2023; Skog et al., 2018)

Complexity and confusion

The proliferation of digital technologies can create complexity and confusion for employees, hindering technology adoption and hampering overall productivity (Cullen, 2001)

Privacy concerns

Digitalization raises privacy concerns as businesses collect and use personal data, potentially resulting in legal and reputational consequences (Elmaghraby & Losavio, 2014)

Environmental impact

Digitalization can contribute to increased energy consumption and electronic waste, negatively impacting corporate social responsibility and public image (Romero et al., 2018)

Disinformation and misinformation

Digitalization can contribute to the spread of disinformation and misinformation, negatively affecting brand reputation and trust (Ciampaglia, 2018)

required to excel in the digital economy. Therefore, TT can also counterbalance disadvantages like complexity and confusion inherent in digitalization (Audretsch et al., 2014). Moreover, TT can catalyze the development and adoption of cutting-edge digital technologies, such as artificial intelligence (AI) and blockchain. Through TT, companies gain access to the latest research, breakthroughs, and best practices from leading institutions and experts in these rapidly evolving fields. This access enables them to incorporate advanced technological solutions into their operations and product offerings, thereby maintaining a competitive edge in the market (João et al., 2020). However, as mentioned in Sects. 2.2 and 3.2, both TT and digitalization entail difficulties. TT in the context of digitalization presents potential challenges, such as substantial cultural and language barriers (Choi, 2009; Millar & Choi, 2009), discrepancies in regulatory frameworks (Kaushik et al., 2014; Ockwell et al., 2010), and

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intellectual property rights (Ockwell et al., 2010). Additionally, concerns regarding data privacy and security may arise when transferring digital technologies across borders (Elmaghraby & Losavio, 2014). Despite these challenges, TT remains an essential driving force for digitalization. By encouraging the development and adoption of new digital technologies, enabling the exchange of digital infrastructure and skills, and bolstering the expansion of digital ecosystems, TT can help unlock the full potential of the digital economy while attending to the advantages and disadvantages associated with digitalization.

5 Real Evidence of TT on Digitalization: The MATES Project Previous sections have shown how collaborative projects are a pathway to foster TT in key industry sectors. The formulation of strategies that address the main drivers of change and which includes practical experiences enables the development of the technical and transversal skills required by the labor market. The identification of needs and challenges from which specific action lines can be drawn up paves the way for testing the resulting innovative actions. Processing and analysis of this test, their results, and their impacts give a solid basis for robust recommendations that can be widely disseminated, thus contributing to the enhancement of industrial processes and technologies. The labor market in the maritime sector, in common with many other relevant European sectors, faces several current and future challenges, such as the digitalization of industrial processes, geopolitical and socioeconomic changes, and a fair and inclusive transition for climate neutrality, among others. In this context, the European-funded project MATES (“Maritime Alliance for fostering the European Blue Economy through a Marine Technology Skilling Strategy”), implemented from January 2018 to April 2022, provides genuine practical evidence as to how the technology knowledge transfer can boost digitalization and green practices. The project was developed within the framework of the European Commission’s Blueprint6 for sectoral cooperation on skills, an instrument to tackle skills shortages and deliver specific skills solutions through sectoral partnerships. Since the beginning of this program in 2018, 28 projects have been funded from different strategic sectors, including automotive, additive manufacturing, tourism, health, and cybersecurity, among others. In this particular scenario, the MATES project brought together a wide network of multidisciplinary experts encompassing the quadruple helix, coming from industry, public administration, education and training institutions, and trade unions. The ensuing sharing of knowledge and expertise between these different actors enabled the MATES project to create flourishing collaborations, which facilitated the introduction of innovative practices, aiming for a more interconnected and dynamic Blue Economy. Whereas the MATES project 6

Blueprint for sectoral cooperation on skills: https://ec.europa.eu/social/main.jsp?catId=1415&lan gId=en.

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tackled a wide variety of aspects, reskilling and upskilling of the workforce in the use of digital technologies was understood to be one of the main pillars driving progress toward a more efficient, safe, and sustainable maritime industry. Leveraging technology and promoting its transference was a critical part of this effort. The effective introduction of technologies throughout the value-chain requires trained human resources, but there is nevertheless often a mismatch between the industry needs and the available training. With the aim of bridging this gap, the project designed a marine technologies skills strategy dealing with challenges such as the lack of qualified staff or generational replacement.

5.1 Methodological Approach The methodological approach of the project applied the Deming cycle,7 which is based on four steps for continuous improvement, Plan-Do-Check-Act, and was articulated through agile management methodologies as defined by Rasnacis and Berzisa (2017) (Table 7). Overall, this approach was applied to enhance knowledge, visibility, scalability, and transference, aiming for the development of the technical skills required by the European maritime industry that ultimately promote employability and economic growth. After analyzing the skills supply and demand in Europe for the two sectors addressed, i.e., shipbuilding and offshore renewable energy, the main lines of action were selected. This served as the basis upon which 11 Pilot Experiences were planned and implemented to help the acquisition and/or improvement of the skills most in demand in these industries. Each Pilot Experience worked as a project itself, with a specific design to match training to the needs of technical disciplines. Following this course of action, the transfer of technological knowledge was achieved by: • Delivering training courses and materials where technological knowledge was transferred through case studies and lessons learned on artificial intelligence, mechatronics, 3D printing, IoT, cloud computing, and big data. • Promoting cooperation between education, research centers, and companies to simulate industrial spaces and create materials and equipment for quality and practical learning. Virtual reality, robotics, and other immersive technologies were developed to provide realistic training experiences to both students and maritime professionals (work-based learning, life-long learning).

7

Deming cycle: https://deming.org/explore/pdsa/.

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Table 7 Pilot Experiences developed in the MATES project. detailed information can be found on the project website compilation of Layman reports Type of experience

Pilot experience

Participants

Online training materials

Education and training for data-driven maritime industry

Industry and higher education (HE) students

Two massive online open courses industry, HE, and vocational on industry 4.0 and the naval education training (VET) sector students Simulation of industrial spaces

Training programs enhancing collaboration between academia and industry

Blended transversal learning

Building an offshore wind jacket VET students in order to promote industry-led techniques Fitting out a shipyard replica for workshop training: design, construction, painting, and equipment

VET students

Specialization course on innovation management for Shipbuilding

Recently graduated university students

Additive manufacturing and risk Industry, HE, and VET students management in shipbuilding and ship repair: upskilling and reskilling on green technologies Training on marine renewable energy (wave and tide) and training of trainers in offshore wind energy

Industry, HE students, and VET teachers

Training and audiovisual material in the framework of a competition environment. Engagement with educational centers

Secondary Education (SE) and VET students and teachers

Short-term course on knowledge SE and VET students, industry, exchange between workers from scientists traditional sectors and early-career youngsters. Educational challenges both “on board” and “on the pier” (continued)

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Table 7 (continued) Type of experience

Recognition of skills and emergent professions

Pilot experience

Participants

Mobility to exchange green technologies in order to develop a methodology adapted to the strategic needs of the organizations

VET and HE students and teachers

Definition of new occupational profiles: update of skills and occupations in the offshore renewable energy and the shipbuilding sectors, following ESCOa taxonomy

Industry, VET, and HE teachers

MATES Project website. Compilation of the Pilot Experience Layman Reports. https://www.projec tmates.eu/wp-content/uploads/2022/06/D4.2-COMPILATION-OF-LAYMANS-REPORTS.pdf a European Skills/Competencies, qualifications and Occupations (ESCO). European Commission website: https://ec.europa.eu/social/main.jsp?catId=1326&langId=en

5.2 Practical Examples of Digitalization Although technological development and its transfer to different areas of the maritime industry played an important role in all Pilot Experiences, three of these were more focused on digitalization. Greater detail is provided below to explain the objectives and impact of these Experiences.

5.2.1

Education and Training for Data-Driven Maritime Industry-ED2MIT

Innovative technologies, machinery, and services require digital applications and data management at various stages of the processes. This experience identified a set of digital and data competences to develop training materials based on European recommendations DigiComp8 and EntreComp.9 Next, four training modules were prepared in line with the Data Management Body of Knowledge10 and delivered online. 117 participants from nine different countries learned about: • Data-related competencies and technologies, • Cloud services and cloud economics, 8

DigiComp—Digital Competence Framework for Citizens. European Commission website: https:// joint-research-centre.ec.europa.eu/digcomp_en. 9 EntreComp—Entrepreneurship Competence Framework. European Commission website: https:// joint-research-centre.ec.europa.eu/entrecomp-entrepreneurship-competence-framework_en. 10 Data Management Body of Knowledge—DMBOK, provides a basis for training on industrial Data Management and Governance and corresponding certification program https://www.datave rsity.net/what-is-the-data-management-body-of-knowledge-dmbok/.

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• Digital content creation, access, and management, and • Data Science and Big Data Analytics. The 43 h of training demonstrated how these concepts could be applied in the Blue Sector throughout the technology’s lifecycle from data collection, input/ingest, preparation, processing/analysis to visualization, and finally, data-driven decisionmaking. The course provides attractive content that, at that time, was not easily accessible to the maritime sector (because either they were not free or had not been adapted to the audience).

5.2.2

Two Massive Online Open Courses on Industry 4.0 and the Naval Sector

Bridging the existing gap between what is taught in centers of education and the real needs of the companies themselves motivated the development of this Pilot Experience. It focused on the analysis of new learning tools for reskilling and upskilling the engineering employees of the shipbuilding industry. Two Massive Open Courses (MOOCs) were prepared from the academic and industry perspective and delivered to engineering staff and VET students from five different countries. 1. Integration of Industry 4.0 with Shipbuilding: 20 h of training where 392 participants learned about the application to Shipbuilding of 4.0 technologies (Internet of Things, Big Data, Data Analytics, and Data Mining, Augmented Reality or Mixed Reality systems, Additive Manufacturing or 3D Printing, Cybersecurity, Collaborative Robots, and Simulation). 2. Integrated Logistic Support (ILS): 10 h of training when 40 participants analyzed how ILS is being updated through existing and emerging technologies. In terms of technology development, an Augmented Reality application that enables remote maintenance training was developed. Stakeholders were invited to collaborate in the design of the training; all involved indicated that they found it relevant to get up-to-date information regarding the latest developments or to refresh engineers’ and experts’ skills. This Pilot Experience made a significant contribution to the better alignment of industry needs and occupational profiles, showing by means of the validation of training and education, new pathways for effectively increasing employability and career opportunities.

5.2.3

Building an Offshore Wind Jacket in Order to Promote Industry-Led Techniques

The objective of this Pilot Experience was the simulation of industry spaces in VET centers and the construction of innovative devices for training purposes. Sixty students involved in the training constructed a small-scale offshore wind jacket,

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similar to those installed in actual wind farms, using industry standards, cutting-edge automated robot welding, and innovative non-destructive testing. The project-based learning method used impacted on the increase of the attractiveness of teaching and learning activities. The collaboration between the education center and six local adjacent companies generated positive mutual effects: the industrial partners were kept informed of up-to-date procedures and technological standards and the education center trained competent potential future employees. This was identified as a good practice and is useful for other centers seeking to replicate the experience. In this case, digitalization was key to the creation of a virtual reality tool capable of use in painting processes for real-scale jackets. This is a cost-effective solution for providing real industrial situations to train skills in painting, welding, and boiler-making, among others. Outputs of all the Pilot Experiences were made publicly available on the MATES website11 and the Marine Training Platform12 and were disseminated at conferences, fairs, visits, and by means of direct communications to marine professional companies and associations, the research community, and education centers.

5.3 Difficulties and Recommendations All things considered, some difficulties were detected that, as noted in Sect. 2.2, should be carefully addressed when transferring technology: • Low knowledge concerning general computer technologies or experience in working with data applied to management or technological processes (e.g., 50% of the participants in the ED2MIT courses). A minimum entry level should be set for trainings, which would enable participants to successfully follow the courses and acquire the sectoral demanded skills. • A lack of teachers and professionals with a mastery of both digital and sectoral knowledge can lead to knowledge-transfer constraints. • The COVID-19 pandemic exposed with more intensity the existing gap between those who have easy, fast, affordable, and quality access to knowledge and technology and those who do not. • Failure to reach the expected participation rates and motivation for upskillingreskilling to use digital and data technologies with a reasonable degree of competence. • The current lack of official recognition for the effort of updating content and skills in curricula can discourage teachers and educational professionals. • Drawbacks related to IP rights (i.e., confidential engineering drawings, training material, etc.) can complicate the collaboration between education centers and companies. 11

MATES Project website. Compilation of Pilot Experience Results and Impact. https://www.pro jectmates.eu/wp-content/uploads/2022/06/D6.5-Compilation-of-PE-results-and-impact.pdf. 12 Marine Training website: https://www.marinetraining.eu/home.

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The MATES project delivered 32 core recommendations (see the adaptation for this chapter in Table 8) addressed to the principal groups of sectoral stakeholders: Policymakers (P), Standardization bodies (S), Social Partners (SP), and Professional Bodies, Education and Training providers (T), and Employers (E). Recommendations were organized in eight strategic areas to reinforce the maritime technologies with the necessary capacities and skill-sets that can enable adaptation to an increasingly digital, green, and knowledge-driven economic context: • • • • • • • •

Boost Cooperation, Attract Talent, Promote Skills Intelligence, Improve Training Offer, Offshore Renewable Energy, Multipurpose Skills, Active Learning and Mobility, and Digitalization.

The use and exploitation of the project outputs and strategic recommendations were outlined in the MATES Sustainability and Long-term Action Plan. As part of this blueprint of actionable steps, partners formally engaged their involvement for Table 8 Recommendations of the MATES project strategy for digitalization. Adapted for this chapter Recommendations

Stakeholders

Providing training in digitalization for companies: • Using up-to-date digitalization technologies

SP T E

• Adapting content and training formats to SMEs’ needs

SP T E

• Considering online training provisions, MOOCs, and blended learning

E

Promoting ICT (Information and Communication Technologies) adapted for the maritime sector • Enhancing knowledge and skills transferability

P SP

• Boosting education, training, and reskilling inclusive programs that assemble ICT and maritime sectoral experts

P SP

• Organizing awareness campaigns on the benefits of common ICT methods and tools for different sectors

P SP

Developing Digital and Data competence frameworks for the maritime industry • Based on European instruments e.g., EntreComp or DigComp, to provide a common language for describing competences, skills, knowledge, and occupations

P S SP T

• Recommending that company HR departments use EU VET and capacity standards in working with job vacancies, candidate assessments, and career management

P SP

• Furthering the revision of existing curricula and courses to ensure the inclusion SP of Digital and Data skills for specialized courses, professional qualifications, or workplace courses

Examining the Role of Technology Transfer on Digitalization … Table 9 Challenges of adopting new digital technologies

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Technological challenges

Organizational challenges

Technical compatibility

Resistance to change

Cybersecurity and data privacy

Human capital

Digital divide

Environment

the rollout and the practical application of the results. The expert network which had been created also contributed to the maximum uptake and impact of the strategy. Direct outreach and well-targeted transference of the project results were carried out at national, regional and European levels. One of the most important mechanisms articulated for achieving this ambitious goal was the building of a large and sound partnership to join the European initiative, the Pact for Skills.13 In summary, these kinds of projects and instruments are powerful tools to promote a fair and resilient green and digital transition by knowledge and TT.

6 Challenges and Implications As mentioned in previous sections, the transference of new digital technologies from academia to society and organizations has transformed the way people live, work, learn, and interact with each other (Vial, 2019). The adoption of digital technologies creates new economic perspectives, increases innovation and opportunities, and influences individuals, industries, and society. Their implementation has increased efficiency and productivity in processes and business operations (Brynjolfsson & McAfee, 2014). Digital transformation has been studied extensively, showing that it has also enabled new business models, enhanced communication and collaboration, the collection and analysis of large amounts of data in real-time, expanded access to education and healthcare, and provided new forms of entertainment and leisure (Verhoerf et al., 2021). However, the increasing use of digital technologies has also raised concerns about their impact on productivity, privacy, security, society, and the environment. The impact of digital transformation on business has been examined by practitioners and academics due to the challenge of succeeding in a constantly evolving and competitive environment (Sartal et al., 2022). As such, it is essential to balance the benefits and challenges of digital technologies and ensure they are used responsibly and sustainably. The significant concerns related to the adoption of digital technologies and their implications have been categorized into two main challenges, namely Technological and Organizational challenges (Table 9).

13

Pact for Skills. European Commission website: https://pact-for-skills.ec.europa.eu/about_en.

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6.1 Technological Challenges 6.1.1

Technical Compatibility

The continuous evolution of digital technologies makes organizations keep up with the latest advancements to remain competitive. Integrating multiple technologies with existing systems may lead to compatibility issues that jeopardize interoperability. Furthermore, insufficient connectivity may create barriers to effective communication and collaboration and lead to data silos that can undermine operational efficiency, organizational performance, and innovation (Chen et al., 2021). Hence, significant planning and investment are necessary to manage this transition. In this context, sharing digital resources can provide numerous benefits. It can contribute to overcoming the mentioned barriers by improving interoperability, and allowing different systems to communicate and work together seamlessly (Laudon & Laudon, 2018). By sharing resources such as hardware, software, and databases, organizations can reduce overall costs and optimize resource utilization instead of investing in their own separate systems and infrastructure. This approach can be particularly beneficial for small and medium-sized organizations with limited resources to invest in proprietary systems. Furthermore, sharing resources can enhance the flexibility and scalability of digital infrastructure, enabling organizations to adapt to changing needs and demands (Zhang & Fan, 2021). This kind of collaboration among organizations can enable the pooling of resources, the transference of knowledge, and the sharing of expertise to foster the development of innovative products and services (Bocken et al., 2014). Furthermore, collaboration can present new opportunities for growth and expansion to new markets, customers, and business models, which may not be possible through individual efforts in a fast-evolving digital landscape (Fobbe & Hilletofth, 2021).

6.1.2

Cybersecurity and Data Privacy

The increasing adoption of technologies such as cloud computing and artificial intelligence (AI) is transforming how organizations use, share, and store information. While these technologies offer many benefits, such as increased efficiency, improved decision-making, and reduced costs, their implementation can raise ethical concerns regarding the integrity and confidentiality of data (Rodrigues et al., 2022). For example, cloud computing allows organizations to access their data and applications from anywhere with an internet connection. However, sensitive information is often stored outside the organization’s physical location (Chen & Chen, 2021). On the other hand, AI is increasingly being used to analyze vast amounts of data and identify patterns, providing valuable insights for business decision-making. However, the lack of transparency of algorithms in data processing raises concerns about the presence of biases and errors that could lead to unfair or discriminatory applications (Davenport et al., 2019; Vinuesa et al., 2020).

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Security and privacy concerns represent some of the organization’s most significant challenges when adopting digital technologies. According to the State of Chief Information Managers (CIOs) Survey by Foundry (2023), Security management was rated as the top activity in which CIOs focus their time and expertise by 47% of the respondents. Moreover, the need for security improvements was cited as the first reason for tech budgets to increase in 2023. The integration of multiple technologies and systems can heighten the risk of cyber-attacks and data breaches, making it imperative to invest in robust cybersecurity measures to safeguard their data (Kshetri, 2018; Siponen & Vance, 2010). As mentioned before, organizations must ensure that the integration of digital technologies with their existing systems does not compromise the confidentiality, integrity, and availability of their data (Kshetri, 2018). It is paramount to ensure privacy and security, including implementing robust cybersecurity measures and complying with applicable laws and regulations. Moreover, organizations should also consider partnering with cybersecurity experts to help identify and address potential threats and vulnerabilities (Trim & Lee, 2021).

6.1.3

Digital Divide

In a globalized world, digital networks are crucial to providing an infrastructure that enables the development of strategies for enterprises and organizations for collaboration, exchange of information and knowledge, and foster development. The COVID-19 pandemic is considered a significant driver of the acceleration in the adoption of modern technologies and the transformation in lifestyle, work patterns, and business strategies (Amankwah-Amoah et al., 2021). However, according to the International Telecommunication Union (ITU) (2021), there are still almost three billion people around the world (37%) who have never used the Internet. The data from ITU confirm that the capacity to connect is severely unequal. Over 2.9 billion people worldwide still do not have internet access, 98% of whom live in developing countries. The ITU estimates that $28 billion is needed to connect the remaining unconnected to the Internet by 2030. The inequalities of certain groups without access to Information and Communication Technologies (ICTs) have been particularly evident during the pandemic, where those without stable internet connections and appropriate devices have been disadvantaged (Lai & Widmar, 2021). The unequal distribution of access to and use of digital technologies, known as the digital divide, can result in significant economic and social disadvantages hindering the ability of certain groups to fully participate in digital activities such as online education and remote work (Lythreatis et al., 2022). In this sense, four main gaps have been identified: (1) the usage gap occurs when individuals lack sufficient digital skills to use ICTs, hindering their ability to perform everyday tasks; (2) the access gap is due to specific population groups being unable to access ICTs, primarily due to socioeconomic inequalities; (3) the generation gap is characterized by older populations having low digital skills; (4) the digital gender gap

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leads to women having reduced access to ICTs and choosing fewer STEM careers (UNCTAD, 2021). The consequences of the digital divide include social isolation, difficulties accessing education and work, heightened social and geographical differences, and increased vulnerability to digital crime (WEF, 2021). International organizations, such as the OECD, UN, and UNESCO, are working to ensure equal access to digital opportunities and reduce inequalities among different groups. As it was experienced during the MATES project, bridging the digital divide requires addressing four key areas: infrastructure, affordability, institution framework, and digital literacy. Governments can reduce licensing costs and taxes and improve investment regulations to pave the way for the private sector. Research and development in the tech industry can help reduce costs and increase the efficiency of ICT services (WEF, 2021).

6.2 Organizational Challenges 6.2.1

Resistance to Change

Adopting new and disruptive technologies involves significant changes in essential company areas, such as processes or organizational culture, which can be unsettling. In addition, when considering the future of digitalization, there is a notable controversy surrounding its impact on productivity and jobs. Psychological and social factors such as fear of job loss due to automation and digitization of tasks, comfort with the old system, resistance to learning, or lack of involvement in decision-making are triggers for reluctance to change during a digital transition (Zoppelletto et al., 2023). Davenport et al. (2019) have identified five perspectives on the impact of automation. Dystopians believe this will lead to massive unemployment and economic dislocation, while utopians envision unprecedented wealth and productivity. Technology optimists predict a leap in productivity and economic growth but acknowledge that many jobs will be displaced. Productivity skeptics are pessimistic about the potential gains in national productivity levels and optimistic realists believe that productivity gains will match those of previous technology waves, but demand for middle-skill jobs may decrease. As mentioned, the COVID-19 pandemic has accelerated digital transformation and social acceptance of the transition by increasing remote work and people’s willingness to work exclusively in a digital environment. In addition, more people are willing to switch from traditional to digital jobs due to the perceived importance of digital work and its potential for secure income. However, the long-term impact of the pandemic on digital transformation remains a question (Nagel, 2020). To avoid delays in the implementation of new technologies processes and missed opportunities, it might be recommendable to develop strategies to communicate the benefits of digital transformation and the positive impact that the new technologies

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adopted will have on work performance. It is also crucial to provide training and support to help workers develop the necessary skills and confidence and involve them in decision-making, creating a sense of ownership and control that allows addressing any fears, concerns, or challenges that arise (Neves et al., 2018).

6.2.2

Human Capital

The digitalization of the industry involves the incorporation of innovations such as advanced robotics, AI, hyperconnectivity, or Big Data. These technologies involve significant changes in production processes, transforming not only the nature of employment but also how we work, performed in more interactive and cooperative environments. This fact, together with the growing demand for increasingly specialized and personalized products, directly impacts the necessary skill and competence set required of professionals (Acemoglu & Restrepo, 2019). UNESCO, in its report “Recommendation on the Ethics of Artificial Intelligence” (2021), emphasizes the necessity of assessing and addressing the impact of digitalization on labor markets, promoting collaboration agreements among governments, academic institutions, vocational education and training institutions, industry, workers’ organizations, and civil society to bridge the skill-set requirements gap and to ensure a fair transition for at-risk employees. The literature suggests that while classical professional skills, such as critical thinking, problem-solving, and decision-making, are still necessary, the robotics era has placed more emphasis on technical skills and the ability to work collaboratively with machines (Brynjolfsson & McAfee, 2014; Frey & Osborne, 2017). In fact, according to the results of the survey in “The Future of Jobs Report” of the World Economic Forum (2020), skill shortages are particularly pronounced in emerging professions, i.e., Data Analysts and Scientists, AI and Machine Learning Specialists, or Software and Application Developers. Furthermore, soft skills like emotional intelligence, adaptability, interpersonal communication, and cross-functional competencies have become more critical than ever (WEF, 2018). These skills are essential in working collaboratively with machines and handling the evolving work environments that come with the use of robotics. In this context, a “T” model is sought, where a good base of traditional professional skills and a wide range of horizontal skills are combined (Ras et al., 2017). To meet this structural change, the ability to anticipate providing and update the necessary skills and competencies is a crucial factor. Human resources play a crucial role in the transfer of new digital technologies. Organizations must ensure they have the necessary expertise and resources to implement and maintain the new technology, which may involve hiring new employees, attracting digital talent, or training existing staff on the new technology. Many employers are taking proactive measures to address skills shortages by offering access to reskilling and upskilling opportunities. On average, 62% of employers currently provide such opportunities to their workforce, and an additional 11% plan to do so by 2025 (WEF, 2020). Despite these efforts, employee engagement in reskilling and

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upskilling courses is reportedly low, with only 42% of employees taking advantage of the training programs offered by their employers. This data suggests that more needs to be done to encourage employees to participate in these opportunities and develop the skills needed to succeed in an ever-changing job market (WEF, 2020).

6.2.3

Environment

The Emissions Gap Report 2021 (UNEP, 2021) warns of the intensifying climate crisis and the need to limit global warming to 1.5 °C over pre-industrial levels. The report highlights the difference between predicted greenhouse emissions in 2030 and where they should be to avert the worst impacts of climate change. The increasing adoption of cutting-edge technologies offers significant benefits, such as increased productivity, improved communication, and greater access to information, and even helps to improve ecosystem management and habitat restoration (UNESCO, 2021). However, it also leads to a significant increase in energy consumption with negative environmental impacts. For instance, training and deploying AI models result in the consumption of energy and water and the generation of carbon emissions, whether situated in data centers, the cloud, or at the edge. Amplification in data traffic via novel “data-hungry” applications may also have an adverse impact on energy consumption patterns, culminating in unsustainability (OECD, 2022). Therefore, there is a need to develop and adopt more energy-efficient technologies, use renewable energy sources to power digital infrastructure, and promote sustainable practices in designing, manufacturing, using, and disposing of digital devices. Additionally, there is a need to raise awareness about the environmental impact of digital technologies and encourage individuals, businesses, and governments to adopt more sustainable practices. With the aim of simultaneously pursuing environmental sustainability and digital transformation, the dual approach of green and digital transition has emerged, known as the twin transition. According to the World Economic Forum (2022), the twin transition approach recognizes a huge and largely untapped opportunity for technology and data to drive sustainability goals. Indeed, digital solutions can reduce global emissions by up to 20% in the three sectors with the highest emissions: energy, materials, and mobility. However, both transitions require a political and societal push to ensure their success, and it is essential to steer and support the digital transition to become an instrument for achieving a fair and just green transition (Muench et al., 2022).

7 Final Remarks This chapter has contributed to the previous literature offering a better understanding of the TT strategy to foster the digital transition in nowadays complex ecosystems. TT plays a crucial role in the digitalization process by facilitating access to innovative technologies and expertise and accelerating digitalization. However, as evidenced

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in this study, both TT and digitalization entail difficulties. TT in the context of digitalization presents potential challenges, such as substantial cultural and language barriers, discrepancies in regulatory frameworks, and intellectual property rights. Additionally, data privacy and security concerns may arise when transferring digital technologies across borders. In addition to that, it has also contributed by offering evidence of the consequences and current implications of the real impact of TT on digitalization through the exploration of a European collaborative project based on collaboration dynamics. In this sense, TT remains an essential driving force for digitalization. By encouraging the development and adoption of new digital technologies, enabling the exchange of digital infrastructure and skills, and bolstering the expansion of digital ecosystems, TT can help unlock the full potential of the digital economy while attending to the advantages and disadvantages associated with digitalization. Therefore, we encourage policymakers, managers, and scholars to consider all the challenges identified in this study to try to advance a step further in the digital transition economy by implementing TT strategies that can be helpful for this global objective.

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Talent Management in Digital Transformation José Manuel Montero Guerra

Abstract The digital transformation is the scenario of integral change that organizations have experienced in recent years, within Industry 4.0. Organizations carry out their own internal digital transformation that involves changing organizational culture, redesigning business models and strategy. The paradigm of the new digital economy requires the creation of new talent management models through human resource practices that drive the changes inherent in digital transformation. Innovation has become a permanent factor in generating competitive advantages for companies. New digital skills and talent management models based on technologies such as HR Analytics and Artificial Intelligence (AI) are required. Companies must adopt new strategies for attracting and retaining talent, given the growing talent shortage. On the other hand, technology allows companies to personalize the job and professional offer, generating new lines of relationship between talent and the organization. Keywords Digital transformation · Talent management · HR analytics · Talent attraction · Digital maturity

1 Introduction Digital transformation is a common occurrence in the international context, which means that companies must adapt their key processes, change their business models, transform their organizational cultures and create new competitive strategies, among which HR departments must update their talent management strategies. With the onset of digital transformation, companies need to revise their current business processes to survive in an increasingly competitive environment based on ICT, AI or social media. In this environment, human resources management changes in order to attract talent to key positions (Chán & Balková, 2022). To date, there is a long J. M. M. Guerra (B) Departamento de Organización de Empresas, Facultad de Comercio y Turismo, Universidad Complutense de Madrid, Madrid, Spain e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 C. Machado and J. P. Davim (eds.), Management for Digital Transformation, Management and Industrial Engineering, https://doi.org/10.1007/978-3-031-42060-3_3

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production of books and articles on talent management, but the etymological discrepancies about talent stand out (Gallardo-Gallardo et al., 2015), there are no unified definitions of talent (Gallardo-Gallardo et al., 2017). There is great confusion in the conceptualization of talent with different points of view in scientific publications (Skuza et al., 2022; Thunnisse et al., 2013) Talent management involves creating strategies for the appropriate attraction, identification, development and retention of talent (Farndale et al., 2009). As for the possibility of meeting the demand for talent, in the processes of digital transformation, scarcity hinders its progression towards digital maturity, due to the need to add digital skills, whether literacy, instrumental or management (Ferrari et al., 2012). Therefore, the meaning of talent management acquires a very significant value in order to be competitive in the middle of the digital age, although studies on the talent shortage (Manpower Shortage survey, 2016), reveal that not enough efforts are being made in companies to solve this gap. People with above-average talent are seen as the source of competitive advantage (Srivastava & Bhatnagar, 2008), but the demand for digital skills is reaching a level where it is difficult to meet the demand for talent in the short term, which is why many managers are betting on training and development (Manpower Shortage survey, 2016). According to global talent surveys, the lack of appropriate policies for attracting, developing and retaining talent can negatively affect a company’s ability to meet market challenges. It is important to verify whether the traditional techniques of attracting and retaining talent are valid in a digital context that encompasses not only the way of doing business but also impacts social, political, economic, etc. A line of research may be aimed at verifying whether the new HR policies regarding talent address these internal and external contextual factors (Thunnissen, 2016). It is important to verify whether the traditional techniques of attracting and retaining talent are valid in a digital context that encompasses not only the way of doing business but also impacts social, political, economic, etc. A line of research may be aimed at verifying whether the new HR policies regarding talent address these internal and external contextual factors (Bustamante, 2014). The relationship between these factors, such as culture and talent, within the process of digital transformation, can be sources of competitive advantage for companies. In the report “Plan Digital 2020” (CEOE, 2016), both traditional culture that is very different from digital, as well as talent and its training to obtain new professional profiles, can be digital inhibitors. Many traditional talent management processes have not been designed for today’s increasingly digital world, so a new approach is needed (Kane et al., 2017). The study and research project “Digital Businesses” (Deloitte, 2016) indicated for 70% of the more than 3,700 executives, managers and analysts surveyed that their organizations needed a new or different talent management in order to compete effectively in a digital world. Digital transformation goes beyond the digitization of processes and requires deeper transformations involving new products, services and business models (Matt et al., 2015). Regarding the process of digital maturity, several factors are considered

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to be able to measure it, in the model proposed by Azhari (2014), there are 8 dimensions: strategy, leadership, product, operations, culture, people, governance and technology. Within the digital transformation, it is necessary to make changes in factors such as the effective integration of business processes, the management of professional knowledge, the adaptation of organizational culture and the rapid integration of information and communication technology (ICT) of the company (Schuman & Tittman, 2014). DeLong and Trautman (2011), these authors highlighted that organizational culture can be used to drive talent management because it is an important factor in determining the success of projects and programs. Hatum (2011) considers that aligning talent management strategies with those of the organization as a whole is a key factor in generating competitive advantage.

2 Organizational Change in Digital Transformation Digital transformation involves changes in the very conception of the business model, organizational culture and ultimately the value chain of the company. Considering digital transformation as an exclusive process of implementing technology in the organization does not imply transformation (Rouse, 2016). The organization must be changed relying on the potential of technologies. This shift is based on technologies that are revolutionizing the way we do business: mobility, Big Data, iCloud, social networks and IoT. As a result, business models have been completely transformed or changed (Downes & Nunes, 2013). Generating competitive advantage in digital transformation is based on how it makes it easier for companies to design new organizations (Soule et al., 2009). Digital transformation changes the relationship and connection of companies with their employees, suppliers and any actor involved at an economic, social, political and technological level of the course (Berman, 2012). Digital transformation, in order to reach the required level of maturity, means opening up to a cultural change. For organizations to achieve high levels of efficiency today, they need to equip themselves with empowered teams, managed through new leadership models and with globally diverse leaders (Wakefield et al., 2016). Digital transformation makes it easier to design new ways of managing talent (Türk, 2023). It is a process of change, which involves individual and organizational resistance (Robbins, 2008). The keys to this change could be summarized in the need for transformative leadership, which assumes agile models of people management, in order to improve the focus on the client, not only by technology but by aligning its goals with those of the organization (Cascio, 2020). From a classic perspective, changes are addressed by the need to upgrade or recycle human teams, or by changing strategy and operational processes. In the digital transformation, both perspectives are valid.

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3 Human Resources Departments in Digital Transformation The digital transformation of any type of organization brings new needs in terms of strategies to manage people. These changes include organizational culture and the creation of new business models, which is why it is essential to create new ways to maintain competitive advantage with talent (Chán & Balková, 2022). The digital transformation of companies requires a new positioning of Human Resources departments. Even if they must be the same as Human Resources or assume definitively the figure of talent management and development (Suárez-Torres et al., 2020). It seems that the concept is closer to people because we are in the “age of talent” due to the fact that the current technological development has been unprecedented and is based on knowledge, which requires innovation and talent (Mejía-Giraldo et al., 2013). This raises the question: What is the contribution that digital transformation offers to talent management? How important is it to gain competitive advantages through talent in digital transformation? Do we attract talent or rather create it from within organizations? Therefore, we see that most of the factors external to HR areas that influence talent currently have to do with digital transformation, the irruption of dizzying technological changes and the development of social networks (Pomares, 2015). With regard to HR departments, we can find different factors that influence the change of their own policies, such as those focused on attracting and retaining talent. New recruitment tools such as LinkedIn, CareerBuilder or Monster have changed the relationship between employers and employees (Lund et al., 2016). Talents can assess their potential in the labor market, which is more transparent, and they can also learn opinions about the satisfaction of employees in a particular company. The classic recruitment model has given way to what we call talent attraction and for which it is essential to have social networks such as LinkedIn or Twitter. Digital work platforms and social networks, thanks to Big Data and Artificial Intelligence, improve the performance of Human Resources departments in terms of talent management. Using this type of platform improves performance by 9% and reduces costs by 7%, thus better balancing supply and demand in the digital age (Lund et al., 2016). If organizations know how to use these new ways of attracting talent, they create competitive advantages, making it easier to have more engaged, satisfied and efficient employees as their careers progress. All these changes so focused on technological development and the requirement to possess highly technical skills such as data analytics, data mining, HR analytics, and AI will mean that despite high unemployment, companies will not be able to cover 100% of their needs in terms of talent. As a result, competition will be disproportionate and strategies for attracting and retaining talent will have to be increasingly proactive and better than those of their competitors. There is a need to design HR policies that include measures such as career development, compensation and benefits, labor flexibility, temporary recruitment according to national labor regulations, international recruitment on the same terms as above, etc. This situation is exacerbated

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by the lack of skilled workers to cope with the new technology-related challenges that now characterize the labor market (Ban et al., 2003; Cavana et al., 2007). To energize and direct these profound changes towards success, we need new HR management strategies, in which technology will be the vehicle to be able to design new talent management policies that facilitate their attraction and retention.

4 The Contributions of HR Departments in the Digital Age If one of the major changes brought about by the digital transformation of companies is the opening up to an organizational culture based on innovation, this means that HR departments should be actively involved in this process. Innovation is a source of competitive advantage (Haans et al., 2016) and facilitates the process of organizational change. Technology is at the service of the employee and not the employee serving the technology. Mobility systems such as the cloud or the IOT, AI allow this whole process of change to be disruptive. It is possible to expedite exponentially the work of HR departments that until not many years ago, collapsed due to administrative processes. HR analytics processes, which allow the collection of data to perform predictive calculations, detect trends, etc., making HR work easier, allow talent management from the present to the future, abandoning traditional reactive practices. In short, thanks to new technologies, HR tools based on Big Data and mobility, among other advantages of digital transformation, the new role of HR is increasingly influencing strategic aspects of talent management that result in profits for the business. Nowadays, in the midst of the digital age, in the same way that they have turned deeply in their strategies towards the client, it is necessary to maintain a new relationship with the employee, which is called “employee centricity” (Ortega, 2017). According to the Incipy (2017) study, the 8 h challenges in the digital transformation are summarized in. 1. 2. 3. 4. 5. 6. 7. 8.

Transformative role, Digital skills training and new job profiles, Corporate Social Networks, Digital Employer Branding, Corporate Employment Websites, Relationship with candidates, Social & Mobile Recruitment, Digital & Big Data.

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5 The Importance of Talent in Business Strategy The capabilities of an organization are based on the specialization of its resources. In the case of integrating into this theory the value provided by HRM (Dao et al., 2011), it implies that the more competencies these resources possess, the greater the possibility of generating new competitive advantages. Ultimately, acquiring and knowing how to retain the right talent for the organization will mean that these competitive advantages will be sustainable. But these capabilities will also give the organization greater capacity to deal with abrupt changes, as is the case with digital transformation (Vivas-Lopez et al., 2013). Even more so if we understand that digital transformation is not only an opportunity for change, but rather an imperative change within the digital ecosystem. Based on the annual CEO survey, more than 40% of executives surveyed believe that in order to survive the next 10 years, they should make radical changes to their organizations. There are new challenges for HR departments arising from the current process of globalization and digitalization, such as the absence of barriers in the talent market. Market analysis shows that most employers are finding it difficult to find the talent they need to meet their needs. This implies reinventing oneself in a way to attract and generate greater organizational commitment. The logic could involve making decisions such as wage increases above the market, but it would put the sustainability of the company at risk. In addition, unemployment data do not match the need for skilled personnel. The differences in success between companies are marked by talent, and it is the responsibility of leaders to know how to create more competent teams to achieve success. Times of crisis are precisely when large companies are more concerned with retaining talent and take advantage of the recession to review their processes, attract the best and take advantage to grow at the slightest sign of recovery (Russo, 2016).

6 Talent Management in Digital Transformation 6.1 Talent in the Digital Age: Talent Relationship and Digital Transformation The relationship between smart systems and talent has evolved over the years. In addition to installing technological applications to take over part of the production process, workers’ own skills have been improved. Since the dawn of digital transformation, HR practices have been significantly improved through the application of technology to mainstream practices in these areas. As we can see from Deloitte’s “Global Trends in Human Capital” report 2021 (Kamen et al., 2021), these practices

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have focused and focused on creating a shared culture, designing work environments to engage people, building a new leadership model and developing new career models. Technology has not come to replace the human factor, but to improve it. In the study on “Employer branding” (Blasco-López et al., 2013), four key concepts have been introduced to analyze the employer brand: (a) (b) (c) (d)

The transmission of the company’s securities. The transfer of company advantages. The internal communication employed by the company. A sense of belonging to the employer’s brand.

Especially the answer to this question becomes key when the increase in labor mobility has become one of the main problems for companies (Rodriguez & Mearns, 2012). For example, nowadays it is increasingly clear that the process of personnel selection is bidirectional, they are both the ones who choose, both the company and the worker (Alles, 2006). From the perspective of employer branding, the goal of the brand is to attract talent to the organization and engage it (Gavilán & Fernández, 2013). At the same time, the use and exploitation of digital tools (People Analytics or AI, among others) incorporated into the recruitment process have changed the relationship between the company and talent as well as the value proposition as an employer. HR departments have become strategic business partners, as a result of the dependence between technology and the Human Factor within organizations. The growing use of AI, both in attracting talent (algorithms such as LinkedIn) and in retaining talent (Analytics for better talent management in the organization). The new digital channels are a two-way variable, on the one hand they offer new points of contact with talent, but on the other hand the same talent has more opportunities to contact and be contacted by the competition, making it increasingly clear that the war for talent today is a real reality in a truly global market. This means that companies need to know what their value is as an attractive company to work with. The organizational structure of companies undergoing digital transformation should change to adapt to the new requirements of the internal and external markets. An increasingly simplified but challenging and challenging working environment must be achieved, and intrinsic motivation must be enhanced (Herzberg, 1987). Both the design of the structure (organization charts) and the microstructure (workstations), redesigning processes to promote higher levels of job satisfaction, which will favor the positive perception of the company image that their own employees have. This competition for talent, through employer branding strategies, means improving and optimizing the channels of contact with potential candidates. This requires strengthening differentiating attributes as employers (Niubó, 2017), having very clear profiles of candidates interested in attracting and defining the appropriate communication channels. The level of digital activation of the company marks its ability to attract talent through its image on social media, especially when the number of employees engaged with the company is significantly low at 13% (Gallup, 2013).

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It is important to indicate how the use of collaborative tools is influencing the work. Tools from Google, Microsoft or examples like Trello, have changed the relationship between leaders and their teams and between collaborators themselves, especially when it comes to organizing, sharing information and improving their self-management skills.

6.2 The New Digital Culture and Talent Management Companies immersed in the digital transformation are aware that this new environment requires an extra effort to adapt their organizational culture to the digital age. If Big Data or Cloud Computing allows significant changes in the way we interact with customers and employees, it goes from analyzing behavioral trends to reliable predictions, requires organizations to be up to the change, they should address a cultural transformation promoted by the CEOs of the companies, showing their commitment along with the creation of new business models (Montero et al., 2023). Attracting the right kind of talent is now the biggest challenge companies face today, according to the 2072 Top Five Rewards Priorities Survey by Deloitte and the International Society of Employee Benefits Specialists (ISCEBS). Among the different factors that attract talent is organizational culture. This may be an obstacle or a catalyst for the change required for successful digital transformation. New production systems based on improved business processes facilitated by ICT need to overcome the rigid structures of the past. Therefore, before embarking on the digital transformation process, all companies must design their roadmap for change. This process of change must be measured through the digital maturity index, which includes in its different modalities the organizational culture factor. This concept of digital maturity, which needs to be measured, does not have a framework approach, but there are different proposals without being born from a basic theoretical core. We can find different models such as those proposed by Lorenzo (2016). Other authors have also analyzed: DREAMY (Digital Readiness Assessment Maturity model), SMSRL (Smart manufacturing readiness level), and MOM (Manufacturing Operations Management) Capability Maturity Model (De Carolis et al., 2017). But we find that this process of transformation depends not only on variables of incorporation of technology but also on other factors such as the centralization or decentralization of the decision-making process, the more centralized the process, the greater the difficulty of cultural change (McConell, 2015). Other factors that favor or hinder this transformation are the greater or lesser openness to the outside of the organization, again the more closed a company is, the more difficult it will be to change, especially when a digital culture should be more transparent internally and externally. Organizational culture is “the set of principles, values, norms, perceptions of life, knowledge of production processes” (Montesinos, 1995). Organizational culture is also “the system of meanings shared by the members of the organization that distinguishes it from other organizations” (Robbins, 2008). This differentiation is one of the main functions of the organizational culture, but it also serves to give

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identity to its members or generates a strong commitment from the members of the organization. Above all, cultures need people, who are the ones who found them, drive them according to their performance leading them to success or failure (Chiavenato, 2009). But for results to be favorable and for people to act results-oriented with significant benefits, they need an extremely favorable organizational context, which has to do with organization and mentality (Chiavenato, 2009).

6.3 The State of Attraction, Commitment and Retention of Talent in the Digital Transformation The state of talent management in the midst of digital transformation becomes a challenge associated with this profound organizational change. The talent cycle in the organization begins with the process of attracting talent (based on employer branding strategies), followed by its development in the company and the interest in generating greater engagement. Organizations rely on communication and information management (ICT) systems. All this leads to a substantial improvement in talent management, with projective tools, collaborative work tools or metrics management (Analytics). To be efficient in attracting talent, we need to start by understanding what digital companies need, since successful digital businesses share common features: they are business-centric, operate quickly, are agile and perform appropriate knowledge management (Behns, et al, 2016). Among the different benefits generated by the use of ICT in talent management, we can summarize them in the following aspects: 1. The interrelation between people and business is carried out in a more agile and direct way. We have already commented on the benefits of collaborative tools such as Trello or Teams, among others. 2. Decision-making is based on the analysis of data linked to the business plan. 3. Gains flexibility for management, thanks to the multiple possibilities to manage information from different sources. The 8th study in Spain on the Digital Transformation in HR, carried out by Incipy (2023) reveals data on the evolution of talent management policies related to the general change of the organizational model that is being undertaken in the digital age. 1. 2. 3. 4. 5. 6.

Typology of digital initiatives, Digital Workplace, Corporate Social Networks, Digital Internal Communication, Flex Work and Remote Work, Digital Employer Branding,

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Social Media in HR, Technology and Analytics, Digital training, Change Management.

In conclusion, there is progressive progress in accompanying the digital transformation process by incorporating ICT tools into talent management, but the pace of adaptation to the digital environment, as required by the digital reality, which is transforming society and the entire business environment, still seems insufficient. For this reason, companies must change their business models and culture if they do not want to stay off the hook and lose competitiveness. In the study on “Global Trends in Human Capital” (Deloitte University press, 2023), they highlight the need for companies to radically redefine their leadership, talent and HR strategies. There are risks for the digital transformation process to flow through talents, such as inherited attitudes and practices. Job design must move from the compilation of responsibilities and tasks to the computation of competencies needed for good performance. The whole process of digitization, the era 4.0 or digital transformation of the company, entails significant changes in the employee–company relationship. The irruption of new technologies, both in the search for talent and in the ability that talent has to learn about the reputation of a given company, is generating major changes in the relationship between talent and employer. Talent management policies start by identifying key positions in the organization, identifying people with potential talent to fill those key positions, attracting outside people to fill potential gaps that the organization has or will have in certain positions, and developing HR policies aimed at developing, motivating and engaging talent in order to meet the organization’s talent needs. Having a pool of key people to prepare them for more important roles (Cunningham, 2007). In the study Global Talent Trends (Mercer, 2023), these can be summarized as follows: 1. Empower employer branding strategies with actions such as linking ASG practices to the company’s purpose or encouraging teleworking. 2. 72% of companies have included collaborative work tools. 3. Within the welfare policies, 81% provide mental health assistance. 4. Improve the employability of talent by promoting training plans tailored to their needs. 5. Strengthen team spirit to avoid problems of staff exhaustion, integrating them better into the collective energy. In the study “The new role of the employer’s brand (Manpower, 2015)”, the reputation and value of the employer’s brand are considered essential for making professional decisions. 33% of respondents consider the brand as a key factor when choosing a company to get a job. 86% use the web as a gateway to the company and 30% use social networks, and 73% prefer a personal interview with HR. All strategies to improve the employer brand place the candidate at the center of the process. In addition, employer branding strategies not only serve to attract talent, but

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also affect the retention and commitment of the same. The most successful companies have aligned their marketing and HR areas to create powerful and efficient employer brands (Manpower, 2015). The international study “Talent Insight Series” by Universum (2016) analyzes the preferences of 18,000 high-achieving young people from the 200 most recognized universities in the world according to the “Times Higher Education World University Rankings 2015–16”. When asked the young people surveyed (high achievers), who come from 10 different countries, about which are the most valued attributes of the employer where they work, they prioritized the following: 1. 2. 3. 4. 5.

Prestige, Leaders who support them, The dynamic and creative working environment, Leadership opportunities, Professional development.

However, there are still circumstances in companies that undermine the ability to achieve these attributes, such as temporary hiring, the gender pay gap or senior management and the rest of the workforce. Talent is looking for more collaborative workspaces, valuing more the possibilities of reconciliation over aspects such as job security. Achieving more decentralized and autonomous work units, personalizing talent management or improving relationships between manager and employee are factors that can help to improve engagement rates.

6.4 HR Analytics and Talent Decisions According to the study by “Global Trends in Human Capital” (Deloitte University press, 2023), the vast majority of business leaders (83%), acknowledge that data processing benefits the employee and the organization. But only 19% believe they are ready to do so. It is a fact that HR metrics have evolved considerably since the publication of the book: How to Measure HR Management (Fitz-enz, 1984). In fact, today HR Analytics is considered a strategic function of the business (ÁlvarezGutiérrez et al., 2022; Minbaeva, 2018). Perhaps the main problem for this decisive step in the role of HR departments towards the strategic echelon will not occur until their members acquire the ability to use HR Analytics metrics (Álvarez-Gutiérrez, et al., 2022; Ulrich & Dulebohn, 2015). The incorporation of HR Analytics allows HR departments to adopt a much more predictive than reactive role. They will not only facilitate decision-making processes from a predictive perspective, but also allow the organization to understand the impact of its processes, the management of people and the results obtained. HR Analytics, uses any data from people management systems. It allows the determination of causal or correlational relationships. Aspects that translate into talent decisions allow the organization to:

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1. Finding and personally addressing the most qualified applicants for a specific position. 2. Predict staffing requirements and determine how best to fill vacancies. 3. Link the use of workforce with strategic and financial goals to improve business performance. 4. Identify factors that enhance employee satisfaction and productivity. 5. Find out the underlying reasons for employee abandonment and identify highvalue employees at risk of abandonment. 6. Establish efficient training and career development initiatives (IBM, 2017). The role of HR departments in today’s company, especially in the wake of the advance of digital transformation, no longer entails the traditional responsibilities of these departments, such as recruitment and selection or compensation and benefits systems, digital disruption incorporates Big Data and HR Analytics into their business. Now it matters what your employees or their employees say on social networks, analyze behavioral trends to know who may be in a position to leave the company or what value their company has as “employer branding” (Hebrero, 2016). Big Data can be applied to the entire employee lifecycle, from the pre-inclusion phase through the fingerprint, especially on social networks such as during your stay at the company by analyzing the employee experience. In today’s “cognitive” era (IBM, 2016), the use of data by talent will allow them to discover new career and growth opportunities, flexibly analyzing huge amounts of data from all types and sources, while HR managers will find improved ways to attract and retain talent. For companies in the knowledge-based economy, people are the most important thing, and the new key to sustainable competitive advantage is to become a decoded company: talent-focused, data-driven, flexible and fast. Big Data provides a set of new tools to help leaders transform their organizations into centers of gravity for talent (Segal et al., 2014). By way of conclusion, we can highlight the applications of HR Analytics, in topics such as reducing unseen turnover (Álvarez-Gutiérrez et al., 2022), and improving performance evaluation systems (Marler & Boudreau, 2017).

6.5 Artificial Intelligence (AI) AI has had a major impact in many fields, including Human Resources (HR). In today’s world of work, AI is redefining the way organizations manage talent and optimize their processes. A number of experts have expressed their views in this regard. Some authors argue that artificial intelligence can increase the efficiency of human resources. According to her, the automation of repetitive administrative tasks allows HR professionals to focus on higher value-added tasks, such as talent strategy and employee experience.

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Human Resources (HR) is just one of many areas, where AI has had a significant impact. AI is redefining the way organizations manage talent and optimize their processes in today’s world of work. A number of experts have given their views on this matter. Some authors argue that artificial intelligence can increase the efficiency of human resources. According to her, the automation of repetitive administrative tasks allows HR professionals to focus on higher value-added tasks, such as talent strategy and employee experience. However, how AI interacts with employees is still debated. Some experts suggest that it is important to maintain a balance. AI has changed the way companies attract and select talent. In a highly competitive world of work, companies are turning to AI to optimize their recruitment strategies and find the best talent available (Villasano et al., 2021). This essay will examine the effects of AI on attracting talent and how AI is changing the world of work. AI offers numerous advantages in the process of attracting talent. Using algorithms and data analytics, organizations can identify and evaluate potential candidates more efficiently and accurately. Thanks to AI, which can recognize patterns and process large amounts of data, recruiters can quickly identify ideal candidates for positions (Matute-Pinos & Bojorque-Chasi, 2021). AI has also expanded recruitment sources. Smart algorithms used by online platforms and social networks help find suitable candidates for specific positions. This allows companies to reach a more diverse talent pool and leverage distinctive skills and profiles. AI can also reduce unconscious bias in the selection process. By focusing on objective criteria and data to avoid bias based on gender, race or other discriminatory factors, AI can improve equity and diversity in recruitment. It is important to note that AI should not completely replace the human factor in attracting talent. Although algorithms can analyze data and profiles, the final decision-making will be human.

6.6 The Tools of Collaborative Work Digital transformation requires the implementation of software solutions for companies that allow companies to automate processes, save time and effort, and optimize the ability of professionals to work as a team (Flores, 2010). Collaborative tools are IT services that enhance teamwork and communication by allowing a workgroup to work together on the same project in real time or communicate without having to be in the same place. The first services for this purpose were emails and instant messaging services. However, over time, new products and services have emerged that have complicated the situation. We present those that are most common today (González et al., 2016). Proper use of online collaboration tools can have a significant impact on the quality of teamwork. Some examples to help you understand what they are and what they are for:

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1. Slack: For good reason, Slack is the preferred platform for many creators to work together. If you’re an architect or designer, you know you never have more than one project at a time. With a large number of clients and a wide range of deadlines, the situation can quickly become chaotic. Slack allows you to communicate with your team members through project-specific channels, which is very useful for managing your time and managing multiple projects at once. 2. Trello: Another free workplace is Trello. For those of you with a visual inclination and will love the customizable design that allows you to drag projects and images in the order that is most useful to the team, this is a collaborative site for project management. 3. Zoom: Use Zoom for video conferencing and virtual meetings. offers messages for images, documents and texts. In addition, there is a paid version and a free one. As expected, the free version limits some features. However, video calls with up to 100 participants can be made in this version. 4. Drive: Google Drive. It is the most popular collaborative tool to store files online. Just have a Google account. Its main functions are to point out, comment on and modify documents in real time. 5. Dropbox: It offers services very similar to Google Drive. You can save several types of files per folder. These folders can be shared with other team members. In addition, it provides added services such as Chat box. 6. Trello: It is one of the most used for team organization and project management. It is based on the Kanban methodology that enhances the visuality of the workflow. It allows you to guide projects through boards, columns and cards.

7 Discussion After reviewing different bibliographic sources that have researched talent management in different contexts, it seems that there has not been a deep interest in relating the impact of contextual factors, as well as the role of actors in a specific context (Gallardo-Gallardo & Thunnissen, 2016). There is also no general consensus on the concept of talent or a talent management model (Gallardo-Gallardo et al., 2017). But today, there is one factor in the global context that is crucial to meeting the needs of talent: digital transformation, which affects all types of companies and sectors. The situation after the successive economic recessions experienced in recent years and with the high level of unemployment in many countries, especially in the Euro area, it seemed that there would be no problem in maintaining an appropriate balance between the needs of talent for companies, however, this process of digital disruption, is provoking the real “war for talent” (McKinsey, 1998), because of its scarcity. For us, it is important to open a line of research that seeks correlations between the external context and the internal organizational context, where talent management cannot be isolated from the processes of digital transformation or from global external ones at the economic, social, political and technological levels.

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We can point out different factors that the context of corporate and social digitization in general, are conditioning the proper management of the talent shortage.

7.1 Definition of Talent There are multiple studies on the conceptualization of talent and talent management (Gallardo-Gallardo et al., 2015), but there is little about the impact that the context of the digital economy has. Therefore, the dispersion of HR policies aimed at attracting, retaining and committing talent is very wide. Digital transformation brings changes that are particularly important in terms of business models, organizational culture and operational processes, but talent management stands out because in the knowledge age people reach a critical level of leadership for the success of organizations as a whole. So it would be important to know what talent is and adjust talent management strategies accordingly. Much emphasis is being placed on recruiting digital tools technicians, neglecting the need to adjust them to the culture of the organization and its future development within the company. This dispersion of the concept leads to reactive, non-proactive actions, very focused on meeting short-term needs, such as specialists in Big Data or analytics tools in general. Although it is true that there is an etymological uncertainty about the concept of talent, there are studies that already define the competencies that professionals must have in order to be successful in the digital age. 8 of the competencies that a professional must develop to face the process of digital transformation: digital knowledge, information management, digital communication, networking, continuous learning, strategic vision, network leadership and client orientation (Magro & Salvatella, 2014). Irrespective of the debate as to whether or not talent originates from genetics, there seems to be unanimity that talent can be developed. Another study that collects the management competencies for the digital ecosystem groups 20 competencies into 4 broad categories: Technological and digital innovation competencies, Competencies related to digital business management and strategy, Competencies related to customers and markets, Competencies related to work organization and people in digital ecosystems (Lombradero, 2015).

7.2 Adaptation to the Digital Context Digital transformation involves changing traditional business models, which improve the relationship with the client, with the members of the organization being the best ambassadors to achieve this goal, but at the same time it is necessary to adopt talent management processes to the new environment, as many were designed for a non-digital world (Kane et al., 2017). Digital transformation is not only the digitization of processes (Rouse, 2016) but also involves transformation and it is people

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who can carry it out successfully, obviously relying on the new information and communication technologies.

7.3 New Organizational Culture It has already been pointed out that digital transformation involves profound changes such as evolving organizational culture, new leadership styles and a new employee experience (Wakefield et al., 2016). Talent shortages generally force companies to redesign their strategies to attract and retain talent, but also in a hyper-connected society, with the mass flow of information, any potential employee can gain real information about business practices with their employees, which can weaken the image of the employer and lose competitive advantage. The new organizational culture, which is born as a result of the digitization process, requires more decentralized structures, so that this transformation and specifically the change of culture is not slowed down by centralized decision-making processes (McConell, 2015).

7.4 The New Role of HR Departments in Digital Transformation It seems that definitely in the era of knowledge HR departments occupy a more strategic role, not just a function of supporting the operations of organizations. In turn, new technologies offer a wide opportunity to redesign your processes, from internal communication with the employee, recruitment techniques or applying analytics techniques on the employee’s behavior, among others, favoring the work of attraction and retention. But not all companies have already embarked on this digital journey, there is even no clear line on where to start and invest in talent management in the new context. There is also a lack of research on what we might call e-HRHR. Another key factor that HR departments must address is the promotion of a leadership style adapted to new organizational needs. It seems that the transformational leadership model best covers these needs (Collins & Schuman, 2015). To meet the challenges and opportunities presented by this new emerging environment, HR needs to modify its processes to become a strategic partner of the business and as they become aware of their new role in the digital age, they become “brokers” of in-house services (Forbes insight, 2016).

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7.5 Strategies for Attracting, Retaining and Engaging Talent in Business Strategy in the Digital Age In an era marked by technological innovation that permeates society, the economy, businesses, customers, etc., it has meant a necessary change in the way companies relate to their employees even before they are hired. As for the strategies of attraction and retention, the strategy of employer branding is key to success in this war for talent (Mckensey, 1998) especially in a situation where the selection process is bidirectional (Alles, 2006). It is necessary to use marketing tools that allow the promotion of differentiating attributes as employers (Niubó, 2017). The shortage of digital talent is one of the biggest obstacles to progressing digital transformation. Talent shortages in general are recognized by most managers worldwide (Strack et al., 2008). In the ManpowerGroup study on “Talent Shortage in 2017”, 25% of managers surveyed worldwide (40,000 h managers) say they have difficulties hiring staff. In Capgemini and MIT’s research “The digital talent gap” (Spitzer et al., 2013), although 87% of executives acknowledge that digital transformation is a competitive opportunity, only 46% are investing in digital skills development. This talent shortage now affects all types of companies (Pollit, 2007), so in an increasingly competitive environment, the need for talent requires solutions that differ from traditional recruitment and selection models. The application of Big Data tools, HR analytics allows us to be more efficient in this process, moving from a reactive role based on historical data to a more proactive and prospective role. Knowing what their employees say or what they say about them on the networks becomes a strategic factor to anticipate the employee’s behavior, especially if they plan to leave the company (Hebrero, 2016). The use of Big Data is enabling a significant shift in HR strategies, transforming organizations into “centers of gravity for talent” (Segal et al., 2014). This highly competitive environment, which is being created by talent shortages, may lead to more talent development activities within HR strategies. Studies have shown that it is positive for the organization that all employees benefit from these development activities (Caligiuri & Tarique, 2009). On the other hand, there are organizations that choose to evaluate who would benefit most from this type of development (Caligiuri, 2006). Organizations need to identify which characteristics are appropriate to decide who has them and incorporate them into development programmes. There are organizations that excel in talent management that have made leadership development part of their organizational culture and to achieve success involve the most senior leaders of the organization (Novicevic & Harvey, 2004).

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8 Conclusions Digital transformation is a new context that forces companies to redesign their business models, transform their organizational cultures, develop new leadership styles and reform their strategies for attracting, retaining and engaging talent to maintain their competitive edge. This context concerns external factors such as the digital economy, and knowledge society and internal factors inherent to the digital transformation such as the change in culture, business model, leadership style and employee experience. The new demands of the market have accelerated the search for a talent that allows to introduce these changes, causing a progressive shortage of talent in the market. However, the lack of clarity on basic concepts such as talent and talent management distorts the effectiveness of these strategies, which should go in unison with business strategies. Public and private organizations are making enormous efforts to attract talent with digital competencies, but paradoxically it is shared by researchers, consultants or HR experts that digital transformation involves organizational culture change and leaders are needed who are able to mobilize change, it is in this competition that there seems to be less organizational effort. Digital transformation in companies is being driven primarily by CIOs, for whom their focus is on technological innovation and having enough talent to be efficient. In this digital context, HR departments must definitely assume their role as strategic business partners, because even the smartest technological system loses value without people, so their processes must be adapted to the new paradigm. In our proposal on how the digital context or ecosystem is influencing talent management in organizations that are carrying out their own digital transformation process, we believe it is necessary to look for the correlations between change or transformation of organizational culture, redesign of the business model, new leadership style, client experience and its impact on strategies to attract and retain talent. The new HR analytics tools facilitate the change of HR processes, being able to anticipate the behavior of your employees and better understand what image the “talent market” has on its employer branding potential. To improve this value or brand reputation, it is important to know what really values the talent of the companies where they want to work, so the presence on social networks and the use of Big Data tools can facilitate more proactive strategies. The current internal and external contingencies of organizations are conditioned by digital disruption, which cannot be ignored so much because of the changes it is causing in the global context (Economy 4.0, knowledge society, cognitive age, etc.) and the need to adapt that all public or private organizations are making in order to adapt and take advantage of the competitive advantages offered by digital transformation.

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Consumer’s Vulnerabilities and Potential Dignity Risks in the Context of Digital Transformation Processes Flor Morton and Mario Vázquez-Maguirre

Abstract In today’s business landscape, managers are confronted with two relevant trends that present considerable managerial challenges. Firstly, the integration of technologies such as the Internet of Things (IoT), Machine Learning, Artificial Intelligence (AI) applications, and others, opens up new possibilities for digital transformation processes. Secondly, the diverse range of social issues has prompted a critical examination of companies’ decision-making processes and their active role in addressing these issues. While existing analyses primarily focus on the challenges faced by companies in successfully undergoing digital transformation, there is limited discussion in the literature regarding the vulnerabilities and potential risks to consumer dignity that arise during this process. As a result, this chapter aims to contribute to the exploration of these crucial issues by drawing upon the growing body of the literature on humanistic management and human dignity protection. Keywords Digital transformation · Consumer vulnerability · Stakeholder theory · Humanistic management · Dignity

1 Introduction Nowadays, managers are confronted with two big business trends that represent major managerial challenges. First, the integration of technologies such as the Internet of Things (IoT), Machine Learning, Artificial Intelligence (AI) applications, and others, present new horizons to digital transformation processes. Second, they are under careful examination of their decision-making process and their novel role in business and society: previously incentivized to focus on one-dimensional success metrics such as income, share price, or profits, they are now adding multi-dimensional variables that include social and environmental dimensions (Dierksmeier, 2016). The combination of both trends generates new value-creation opportunities and threats for F. Morton (B) · M. Vázquez-Maguirre Department of Management, Universidad de Monterrey, Monterrey, Mexico e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 C. Machado and J. P. Davim (eds.), Management for Digital Transformation, Management and Industrial Engineering, https://doi.org/10.1007/978-3-031-42060-3_4

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different stakeholders. Therefore, exploring those management issues that include both trends is necessary and urgent. This chapter focuses on exploring the challenges posed by a process of digital transformation when it considers customer vulnerability and potential dignity violations (a social dimension). Specifically, how can a process of digital transformation affect or be affected by a social dimension? Can a process of digital transformation be a source of social justice and empowerment of previously marginalized stakeholders? Can such processes be reparative with respect to the ongoing structural inequalities and discrimination? Most of the articles that examine digital transformation focus on the challenges the company may encounter: internal resistance to change, budget constraints, lack of expertise, cyber security, or reimagining customer service (Hyseni, 2022; Orlov, 2022). However, few articles analyze the customers’ perspective and the potential threats they may face, especially, when minority groups are involved or individuals that permanently face inclusion barriers. To this end, this chapter is organized as follows: first, the literature review section examines the following topics: challenges of digital transformation processes, consumer vulnerability, and social issues in management (stakeholder theory, humanistic management, dignity protection). Then, consumer vulnerability challenges in digital transformation processes are explored. Finally, concluding remarks summarize the findings of the chapter.

2 Digital Transformation and Its Challenges According to Heavin and Power (2018), organizations have been undergoing digitization and digital transformation since the 1950s. However, the progress made during this early period was modest due to technological limitations and constraints. It was not until the 1980s that the adoption of computing technology gained momentum and brought about a revolution in management and decision-making processes. Other researchers consider that the digitalization of business began with the democratization of technology, coupled with the integration of the Internet as a tool for everyday use (Fernández-Rovira et al., 2021) and in recent years, we have witnessed exponential growth in digital data storage and computing capabilities which have accelerated the digital transformation of numerous companies. Today, enterprise applications, the Internet of Things (IoT), Machine Learning, Artificial Intelligence (AI) applications, analytics, 3D printing, virtual and augmented reality, among other technologies have taken digital transformation to new heights. In fact, AI is considered the greatest technological transformation of the Information Society and a precursor of the Fourth Industrial Revolution and digital transformation has become a synonym for competitive advantage and differentiation (FernándezRovira et al., 2021). The rapid evolution of technological advancements provides a range of benefits, such as real-time monitoring, predictive analysis, digital assistants, personalization, and distributed decision support, which have fundamentally changed the way organizations operate and make strategic decisions (Heavin &

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Power, 2018; Stalmachova et al., 2022). The growing body of literature on digital innovation has provided insights into the distinct characteristics of digital technologies. Existing studies have recognized that unique features of digital technologies create novel possibilities for developing new infrastructures, products, and business models (Nasiri et al., 2022; Schneider & Kokshagina, 2021). Digitalization fundamentally shapes the new dynamics between companies and their clients. As more aspects of daily life increasingly converge towards the digital realm, customer relations present significant growth opportunities in the digital world with organizations having a considerably broader scope to engage and interact with consumers. According to Fernández-Rovira et al. (2021) with the advent of Artificial Intelligence, Big Data analytics, programming, and other emerging technologies, companies’ marketing efforts have been empowered by the possibility of targeting both the broader market with cost-effective strategies and specific segments with offerings of higher value and price, based on their distinctiveness and uniqueness. The authors highlight that the use of Big Data to foster customer loyalty and leveraging user-generated data to predict customer behavior is a rapidly growing trend in the realm of business, and the combination of Big Data and AI in marketing allows for infinite possibilities of personalization (i.e., companies can tailor their offerings to the minutest details), significantly increasing customer satisfaction and fostering long-term loyalty. Despite the numerous advantages offered by technology, previous literature has identified several challenges associated with digital transformation processes in companies. For some companies, the challenge is clearly defining the implications of digital transformation for their organization, understanding the areas it impacts, and determining how to align it with their overall strategy and operations (Schneider & Kokshagina, 2021). For instance, Drechsler et al. (2020) emphasize that digital transformation is characterized by the integration of physical and digital elements, as well as the combination of old and new technology and organizational aspects. Hence, companies are faced with the challenge of deciding whether to retain, discard, or adapt old elements to the new digital context. This transformative process can have a profound impact on organizations, requiring them to adapt their existing capabilities and structures to enable the adoption of new approaches, as well as fundamental changes in various aspects, including enterprise technology, organizational structure and identity, value proposition, and business strategy. However, socio-technical inertia in digital transformation processes can create substantial tensions between old and new elements of organization and technology. Hence, firms must strike the right balance between leveraging existing resources and embracing new approaches to evolve and adapt to the digitized environment. This process requires navigating the tensions between the past and the present to effectively address changes in environmental conditions, such as customer preferences, competition, technology advancements, and regulatory frameworks, all driven by digital innovation. Moreover, the authors point out that the rapidly evolving competitive landscape with reduced entry barriers and the proliferation of startups, which often have significant venture capital resources, imposes a challenge for incumbent companies. Amid this context, platform business models, previously associated with born-digital companies (e.g. Google,

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Facebook, Uber), have become a source of inspiration for transformation leaders in more traditional firms looking to reinvent or expand their business. However, implementing platform business models requires understanding and adapting to new paradigms, which incumbent firms are still struggling to fully comprehend and address. Additionally, Heavin and Power (2018) highlight the complex decisions organizations face when managing technology, data, and customer relationships in a digital context. These authors identify the following dilemmas: (1) Prioritizing efficiency versus customer needs: focusing on efficiency may have a negative impact on customer satisfaction and loyalty; (2) Aggregate data versus personalization: a greater emphasis on identifying patterns and stereotypes can lead to depersonalization, despite the fact that meeting customer needs often requires personalization; (3) Resources for IT staff versus self-service analytics: assessing the comparative value between increasing the number of data scientists and IT staff versus investing in training and resources for managers and staff in functional areas is challenging; (4) Storing all data versus selecting data with purpose: storing all data incurs costs, however assessing data quality and finding opportunities through the combination of data resources pose additional challenges; (5) Human workforce versus computing machines: the increasing use of computing machines and AI can displace employees at various skill levels; (6) Security versus accessibility: balancing data security, sensitivity, and accessibility is crucial. Managers face the challenge of ensuring data is easy to use while safeguarding its importance and sensitivity, particularly in some industries such as healthcare and banking; (7) Privacy versus understanding of individuals: digital transformation provides an opportunity for organizations to innovate and redefine their business processes through a comprehensive understanding of individuals’ preferences and behaviors, however, this raises privacy concerns. Furthermore, other challenges identified in the literature regarding digital transformation initiatives include measuring the success and performance of such initiatives, developing relevant skills and capabilities for the digital era, and engaging employees in innovative tools, among others (Schneider & Kokshagina, 2021). While existing analyses predominantly focus on the challenges faced by companies in successfully undergoing digital transformation, there is limited discussion in the literature regarding the vulnerabilities and potential risks to consumer dignity during this process. Therefore, this chapter aims to contribute to the reflection on these important issues.

3 Consumer Vulnerability Vulnerability is a concept that broadly refers to the human condition of living with the inevitability of death, which inherently includes the possibility of being injured or physically damaged (Kottow, 2004). Yet, vulnerability extends beyond the mere potential for physical harm and encompasses the possibility of damages arising from

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actions or inactions that jeopardize an individual’s well-being or interests (Brenkert, 1998). Marketing literature lacks consensus about the definition of consumer vulnerability and there are two general perspectives regarding the degree of vulnerability of an individual (Hill & Sharma, 2020; Khare & Jain, 2022; Riedel et al., 2021). One of these perspectives sustains there is a relative disadvantage among subpopulations, meaning that certain individuals are deemed “vulnerable” because they possess unique characteristics, which render them susceptible to significant harm inflicted by another agent within a specific consumption context (Goodin, 1985). From this standpoint, consumer vulnerability is conceptualized as being contingent upon individual characteristics, implying that individuals with specific attributes are consistently considered vulnerable (Morton & Treviño, 2021). For instance, Brenkert (1998) defines a subgroup of consumers known as “specially vulnerable” individuals who exhibit a heightened susceptibility to potential harm to their interests. This group can be characterized by three conditions: First, due to their unique characteristics such as experiences, conditions, or limitations, they face challenges in engaging in typical adult market activities. As a result, they experience one or more of the following vulnerabilities: physical vulnerability, cognitive vulnerability, motivational vulnerability, and social vulnerability. Secondly, their vulnerabilities are primarily influenced by factors largely beyond their control. Lastly, they possess significantly reduced capacity to safeguard their own interests, rendering them particularly prone to harm from marketing practices that may not have a similar impact on the average adult; these consumers may even remain unaware of their own vulnerabilities. Similarly, Smith and Cooper-Martin (1997) consider vulnerable consumers as those with demographic characteristics that limit their ability to fully benefit from economic transactions and maximize their well-being. The authors consider these individuals to be more prone to experiencing physical, psychological, or economic harm as a consequence of these transactions. Another perspective views consumer vulnerability as a transitory situation that arises from the interplay between intrinsic and external factors (Kursan, 2021). In fact, Baker et al. (2005) consider that defining vulnerability based on the individuals who experience it can lead to discrepancies between actual vulnerability (which is experienced and can only be fully understood by listening to and observing the experiences of those who are vulnerable) and perceived vulnerability (refers to the belief held by others that a person is vulnerable, which may or may not align with the individual’s own perspective). They suggest moving away from viewing vulnerability as a characteristic of a specific group of vulnerable consumers and instead propose understanding vulnerability as a transitory state that can be experienced by anyone because everyone has the potential to be vulnerable at some point, regardless of their affiliation with a consumer segment or category considered as vulnerable. These authors define consumer vulnerability as “a state of powerlessness that arises from an imbalance in marketplace interactions or from the consumption of marketing messages and products. It occurs when control is not in an individual’s hands, creating a dependence on external factors (e.g., marketers) to create fairness in the marketplace” (p. 134) and propose a conceptual model of vulnerability suggesting

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that actual vulnerability emerges from the interaction of individual states (e.g. mood, grief, motivation), individual characteristics (e.g. psychosocial and biophysical), and external conditions (such as discrimination, stigmatization, distribution of resources, and other conditions) within a consumption context where consumers’ goals may be hindered and their experience affects social and personal perceptions of self. In a similar vein Hill and Sharma (2020), who define the concept as “a state in which consumers are subject to harm because their access to and control over resources is restricted in ways that significantly inhibit their abilities to function in the marketplace” (p. 554), argue against using specific consumer designations (e.g. elderly, obese, children, lower income) interchangeably with the vulnerable consumer label. According to the authors, merely belonging to certain categories is not sufficient to establish vulnerability. Instead, vulnerability emerges when individuals are subject to harm by marketers or individuals with whom they interact during their pursuit of accessing goods and services. The authors emphasize that even disadvantaged groups (those who experience inequality and are in a worse position compared to others within a specific context) are not inherently vulnerable. While individuals experiencing disadvantage may or may not be susceptible to harm, all vulnerable consumers, by definition, face inherent exposure to potential harm. Furthermore, Commuri and Ekici (2008) propose the adoption of a perspective that combines a systemic component, where vulnerability is understood as a result of certain categories (e.g. race, age, gender), with a transitory component based on consumer status (e.g. when vulnerability occurs only during a particular consumption episode). In analyzing consumers’ vulnerability and potential dignity risks during digital transformation processes, recognizing and understanding consumer’s vulnerability as both categorical and transitory appears to be a more suitable approach because of the profound changes in social dynamics and consumption experiences resulting from these transformations. Additionally, the broad spectrum of social issues that have an impact on business and demand a more proactive approach from organizations to mitigate the negative effects of their activities call for a new perspective on management. This chapter builds upon the burgeoning body of literature concerning humanistic management and the protection of human dignity, which will be reviewed in the following section to shed light on the significance of these concepts in digital transformation processes.

4 Social Issues in Management Humanity is facing rising inequalities, unprecedented disparities of opportunity, wealth, and power, rampant unemployment, health crisis, climate change, natural resource depletion, and increasing conflict, resulting in billions of individuals living in poverty and having no prospects of a life of dignity (United Nations General Assembly, 2015). The prevailing economic paradigm based on profit maximization and the view of the employee and society as an instrument for this purpose has led to tremendous economic prosperity for some individuals at a huge social and

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environmental cost; in essence, the economic system has marginal regard for human values and virtues (Dierksmeier, 2016). The generalized disregard for moral values and ethical considerations by business practice has contributed to ongoing social and ecological issues (Ghoshal, 2005). For example, companies have contributed to social inequality by designing skewed value distribution schemes through their institutional work and influencing societal nutrition and health levels (Bapuji et al., 2018, 2020). Additionally, Guryanova et al. (2020) identify numerous ethical challenges and risks in various domains that result from the digital revolution. These include changes in ethical norms and values in professional activities and relationships between professionals and consumers due to human–machine interaction. Relying on different types of technical intermediaries affects interpersonal relations, which gives rise to social and ethical issues. Despite the advancement in the development of moral machines, ethical boundaries for its use and the level of trust in them must be established. The labor market is impacted by ethical problems resulting from the rapid reduction or even elimination of certain professions. The widespread availability of information about the activities of social, political, and commercial entities leads to changes in moral norms of behavior. Stakeholders are increasingly demanding more proactive behavior by managers to alleviate social problems and reduce the negative impacts of their organizations; in sum, create real value (Spitzeck et al., 2009). In addition, financial information is no longer enough to assure trust, but additional information such as material sustainability is now necessary towards this end (Initiative for Responsible Investment, 2012). In this scenario, managers are generating different strategies to cope with multi-purpose organizations (Dierksmeier, 2016) that are under strict scrutiny by their stakeholders. Responsible management is now mandatory to avoid the risk of compromising the future of organizations. The business case for responsible management presents broad evidence that responsible behavior pays off (e.g. Porter & Kramer, 2002). Corporate social responsibility has largely been examined by how it relates to profitability, however, scholars have also suggested that the “profitability” argument is not enough to change some managerial practices that involve indirect negative outcomes to society. Corporations should act as moral role models despite the economic costs of their decisions and there are examples of such behaviors (see Spitzeck, 2011). What kind of organizational frameworks could examine a process of digital transformation that includes social and environmental dimensions? Can a process of digital transformation be a source of social justice and empowerment of previously marginalized stakeholders?

4.1 Stakeholder Theory A search for a new conceptual framework for business and managerial decisionmaking is a primal concern for researchers and practitioners. Maybe the most known approach is stakeholder theory, which recognizes the legitimate interests of groups that affect or are affected by the firm (Freeman, 1994). This theory recommends that

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organizations include the necessities and interests of those groups in their decisionmaking process, generating conditions of fairness and notions of the common good (Freeman et al., 2010). Freeman et al. (2004) also state that business activities solely driven by the interests of shareholders could indirectly lead to the violation of the rights of other stakeholders. Stakeholder theory suggests that the relationships between a business and its stakeholders should be the main unit of analysis; this would allow managers to deal with three situations. First, the firm can shape these relationships to create as much value as possible; second, it can survive and thrive in capitalist systems; finally, it helps practitioners to avoid moral failures (Freeman et al., 2010). One useful tool to identify stakeholder’s needs and sense of urgency is a materiality matrix, which can display proposed initiatives in terms of their relevance to internal and external stakeholders (Kirby, 2014). Although one assumption of stakeholder theory is the intrinsic value of all individuals (dignity) and the possibility that business activities can result in dignity violations, this theory does not revolve around the concept of dignity like humanistic management theory.

4.2 Humanistic Management Theory Humanistic management theory recognizes the protection of human dignity as the main objective of any organization, it is mainly concerned with promoting human flourishing and avoiding the instrumentalization of individuals as a means of profit generation (Laszlo, 2019; Melé, 2016). Humanistic management assumes that dignity restoration, dignity protection, and dignity recognition are necessary conditions for well-being (Pirson, 2017). Humanistic management has its foundational roots in humanism: a system of thought centered on the human being and our capacity to improve our own life, which situates us as promoters of social causes that seek to restore dignity affronts to minority groups (Caton, 2016). Melé (2016) suggests seven propositions found in humanistic thought that serve as foundational elements of humanistic: human beings as complex, multidimensional, and unique individuals with different motivations and traits; the need to understand individuals in a holistic form; dignity as an intrinsic element of the human being that should be honored and protected; the need for organizations that provide conditions and resources for individuals to develop and flourish holistically; the search for a common good that is in balance individual freedoms; the interconnection between human beings and the environment and the role of individuals as stewards of nature; and the individual’s continuous seek for meaning and transcendence. Research in humanistic management is still in the early stages and in the process of producing a real impact on business practice (Spitzeck, 2011), but in recent years it has become a popular framework to explain new progressive enterprise models and novel management practices that show genuine concern with human dignity and welfare (Pirson et al., 2019). Sisodia and Gelb (2019) suggest a stakeholder theory

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and humanistic management are complementary. The authors believe that the focus of collaborations between companies and stakeholders should center on how they can improve well-being and dignity, alleviate suffering, and elevate the joy of every stakeholder. In this sense, dignity-centered practices and processes seem to be at the core of novel approaches to a restorative, more humane, and inclusive management.

4.3 Dignity Protection The desire for dignity is essential and predominates in every human interaction, it is difficult to develop beneficial relationships if dignity is not respected and honored (Hicks, 2011). This concept is central to modern humanism and political liberalism, which consider individuals as ends in themselves with indisputable dignity that must always be protected and cherished (Dillon, 2018). International organizations such as the United Nations (UN) have adopted dignity as a foundational principle: recognizing that the dignity of the human person is fundamental. The UN promotes universal respect for human rights and human dignity, the rule of law, justice, equality, and non-discrimination as a form to ensure individuals can fulfill their potential in dignity and in a healthy environment (United Nations General Assembly, 2015). Nussbaum (2011) mentions a capability approach to dignity where individuals need to have the abilities and the opportunities to actively thrive; therefore, organizations have the potential to promote or inhibit the development of such capabilities and opportunities. When organizations impede the flourishing of individuals, potential dignity violations may be systematically occurring, preventing economic and social development. Such dignity violations are at the core of conflicts and distrust (Hicks, 2011). Violations of dignity can take the form of affronts to people’s unconditional value as human beings, which can include compromising their autonomy, self-determination, identity, or economic security (Camargo et al., 2022). How can an organization remedy potential dignity violations? Pirson (2017) suggests three dignity thresholds to improve the human condition; organizations must consider such thresholds to create transformative strategies and practices for social change: (1) Dignity restoration which refers to remedying dignity affronts to people’s unconditional value. For example, limiting the capacity of individuals to make choices or permanently excluding a group of people from opportunities to improve their well-being can be considered a dignity violation. Dignity affronts also include violations of people’s unconditional worth, identity, freedom, autonomy, and self-determination; (2) Dignity protection, which is closely related to the safeguarding of human rights, and respect for individual identity and worth, and refers to protecting individuals’ intrinsic worth and identity; (3) Finally, dignity promotion focuses on well-being creation and human flourishing practices. Organizations going through digital transformation processes should reflect on how to remedy potential violations of consumers’ dignity during their digital transformation processes. For example, issues regarding people’s data and its manipulative use to induce certain spending decisions should be examined under the dignity

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protection threshold. Designing systems based on building human capabilities instead of value appropriation or profitability can honor the dignity promotion threshold. Overall, the central assumption is to create transformative practices that are dignitycentered, where profit is a consequence of real value generation instead of an end that subordinates everything else in the organization (Pirson et al., 2019).

5 Consumers Vulnerability Challenges in Digital Transformation Processes Customer experiences undergo fundamental transformations due to the impact of digital technologies. As many market interactions and transactions take place in a digital environment and companies actively undergo digital transformation processes, it becomes relevant to reflect on the challenges of consumer vulnerability in digital transformation and adopt a humanistic management approach to protect consumers’ dignity in this context.

5.1 Vulnerability Challenges Rising from Entry Barriers While digitalization is essential to improve customer experience nowadays, choosing the right technology is a major management concern because companies could simply be introducing more challenges into the customer ecosystem (Forbes Communications Council, 2022). Even more, a customer-centric digitalization process is focused by definition on the customer, mostly ignoring those individuals that could be interested in participating in the market if they could overcome their economic, geographic, cultural, educational, or technological barriers. A digital transformation process may maintain those same barriers if a careful examination of those potential customers’ needs is not discussed in detail. Thus, the same barriers that have prevented individuals from participating in the market will likely continue or even worsen; these digital systems could already bear an initial bias towards those groups in society that have more opportunities and leadership, maintaining historical inequalities (Marchese, 2023). From a humanistic management perspective, individuals being unable to participate in the markets to exert their freedom of choice and pursue their well-being is an affront to their dignity. For example, indigenous groups in Latin America account for almost 8% of the total population but they represent 14% of the poor (The World Bank, 2018). Traditionally, the information that is required to access health, financial, energy, telecommunication, or education services needs to be provided in the official language (mostly Spanish or Portuguese), and most of the different prerequisites do not account for their cultural worldview or needs. These elements could perpetuate historical barriers of exclusion and discrimination; thus, indigenous peoples’ full

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social and economic inclusion is still a pending issue that is being prevented by glass ceilings and structural barriers (The World Bank, 2018). The risk extends beyond the indigenous population; in Latin America, only half of the population has used a computer or has enough skills to use one and in 2018 only 68% used the Internet (OECD et al., 2020). Hence, digital transformation may increase the vulnerability of major segments of the population and amplify other inequalities in the absence of appropriate processes. Marchese (2023) mentions that designing digital systems that do not worsen prevailing social and economic inequalities is not enough, these systems should go a step further and actively contribute to restore equity in society: “Those would be systems that would take into account ways in which people are differently situated and what we can do to create a more equal playing field while maintaining procedural fairness” (Marchese, 2023: p. 1). The capability approach to dignity (Nussbaum, 2011) implies that organizations have the potential to promote or inhibit the customers’ opportunities to actively thrive. General access to products and services for the population is not a market-profitability question but an ethically driven issue that needs to be prioritized in a digital transformation process.

5.2 Vulnerability Challenges Rising from Perceived Empowerment One of the main promises of technology in the realm of consumer experiences is to provide empowerment. Empowerment refers to the perceived ability to exert control and influence over decisions that have an impact on one’s life and is composed of four key elements: meaningfulness (personal significance of an object or practice), self-efficacy (believing that we have the capability to exert control over a situation and achieve desired outcomes), self-determination (freedom to initiate, regulate, and carry out actions of one’s own choosing), and impact (a perception that our actions make a difference) (Del Bucchia et al. (2021). However, the context of technology is marked by conflicts and paradoxes. Del Bucchia et al. (2021) introduce the concept of latent vulnerability, which refers to situations where consumers may be vulnerable despite feeling empowered by online interactions with brands. The authors suggest that empowerment can conceal dependency and manipulation, and that vulnerability becomes manifest when techno-mediated interactions of consumers with brands result in a loss of control, relationship deterioration, and diminish their perception of themselves.

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Losing Control

Most studies on consumer vulnerability focus on the lack of personal control as a crucial aspect of the experience of vulnerability. In other words, individuals experience vulnerability when they feel they have no control over their cognitive processes, emotions, or behavior (Hill & Sharma, 2020). But even without realizing their lack of control, consumers may still be vulnerable. This holds particularly true when engaging with digital technology. Digital transformation implies that customers generate considerable amounts of data through self-service mechanisms to get a product or service, also companies can now automatically monitor customer feedback from various sources and use Big Data to gather extensive information about customers’ preferences, experiences, and locations; however, concerns about storage and use of data are emerging. Zuboff and Schwandt (2019) suggest potential concerns about more companies using the data they recollect from customers to propel sales. Also, companies that generate income through advertising can use this data to sell “more targeted” advertising, which means using data of individuals to find more specific individuals. The authors even describe cases where companies try to influence the mood of customers to induce sales. The company may know more about the individual’s consuming habits than the person herself. Some of these practices present important ethical concerns and constitute potential human dignity violations. Specifically, this use of data may compromise a consumer’s freedom of choice, autonomy, and right to access personal information. Such actions can result in a profound distrust of companies and suspicion when individuals try to access an app or enter personal information on a company website. In the end, some individuals may choose not to participate in the digital channels the companies may build; thus, creating a trust barrier that would prevent value creation for both the individual and the company. This is also a highly unregulated terrain (with regulations being either non-existent or far behind current needs) where inequality may increase even more as individuals who do not want companies to have their personal data may opt out of the system (Fernández-Rovira et al., 2021; Marchese, 2023). How to remedy potential data concerns? Companies that engage in digital transformation processes should address this issue with transparency and accountability. Customers should easily find information about where their data is going, who is going to have access to it, and for what purposes (even within the company). Dignity protection is tied to safeguarding an individual’s human rights, identity, worth, and autonomy. What are some potential opportunities for honoring the dignity of individuals through digital transformation processes? The potential amounts of data can help customers to make more informed decisions and achieve economic security through better use of their budget. Companies should transform this amount of data into valuable, easy-to-access information that can give individuals more efficient use of their resources and higher levels of well-being. Even if it means selling fewer products or services to customers, companies should have the moral responsibility to seek customers’ well-being before making more profits from them. In the long run, as the stakeholder theory predicts, customers may compensate for this “generous” corporate behavior in the form of loyalty, advocacy, solidarity in difficult times, etc.

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Deterioration of Relationships

Research has shown that besides the need to purchase a product, consumers engage in shopping behavior for various reasons. For consumers experiencing loneliness, offline shopping can become an effective way to alleviate this feeling (Song et al., 2018). The interaction with salespeople helps consumers establish social connections, providing them with emotional support and hedonic value that surpasses the experience of shopping online (Haridasan & Fernando, 2018). Hence, it is not surprising that consumer loneliness has a negative effect on online shopping preferences and promotes a preference for offline shopping channels (Wang, 2023). While consumers are increasingly using technology to connect with other people, techno-mediated consumption environments can also isolate them (Del Bucchia et al., 2021) or even result in hurtful interpersonal exchanges (Zolfagharian & Yazdanparast, 2017). Loneliness is not only an unpleasant experience but also a threat to life and health. It has been found to be an important risk factor for various psychological and physical diseases, as well as mortality (Cacioppo et al., 2006; Wang, 2023). Replacing human staff with AI, chatbots, and other digital technologies can be attractive for companies to improve efficiency and lower costs (Heavin & Power, 2018). However, relying solely on these technologies without offering consumers an alternative means of interacting with a human being can create vulnerabilities and jeopardize the dignity of consumers, particularly those experiencing loneliness. For example, consider elderly individuals who prefer traditional offline channels for payment and engaging with company representatives. If all their consumption transactions are shifted to online platforms, they could become more susceptible to isolation and diminished sense of connection. This poses a significant risk to their well-being. Another example is the rise of virtual traveling services that enable individuals to explore tourist destinations from the comfort of their homes. While these experiences offer convenience, if they do not allow for meaningful social interaction, it not only diminishes the overall brand experience but also has the potential to violate individuals’ dignity. In summary, while digital technologies can enhance efficiency, it is crucial for companies to strike a balance by providing alternative channels for human interaction to safeguard the dignity and well-being of consumers, especially those vulnerable to isolation and loneliness. Companies can foster the creation of consumer communities and promote interactive experiences with their brands.

5.2.3

Diminishing of the Self

Self-concept refers to people’s thoughts and emotions regarding their own identity and perceptions of themselves (Rosenberg, 1989). Zolfagharian and Yazdanparast (2017) identify that consumers have a mixed experience when it comes to feeling authentic in today’s highly calculated and hypercompetitive world. On one hand, they feel a sense of existential inauthenticity due to these factors. On the other hand, they

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genuinely value attention to detail and accurate information, especially in areas like personal finance, education, health, and fitness, where it helps them make informed decisions. According to Bartoli (2022), the digital technology and overabundance of visibility have made it easy for individuals to monitor other people’s life experiences and then draw comparisons. Hence, digital channels have become a means of self-promotion. Digital representations of individuals are considered digital selfextensions and it is known that consumers redesign enhanced identities to show to others, which increases their self-esteem. Consumers incorporate the resources offered by brands in digital settings into their personal narratives of self-expression. These resources serve as instruments for constructing a consistent narrative of the self, aiding in identity formation, and facilitating the transformation of the self into a consumable entity known as the “branded self”. This notion is problematic in terms of dignity because it reduces consumers to objects to be “consumed”, with an implicit disregard for the intrinsic value and worth of individuals. While this issue is not specific to digital contexts, a company’s digital transformation can amplify its impact exponentially. As stated earlier, through the collection and analysis of online data, companies have the ability to uncover the psychological traits and emotional states of consumers in real time (Matz & Netzer, 2017). This enables them to anticipate and meet consumers’ latent needs, as well as to engage with them more swiftly through personalized messages (Bartoli, 2022). However, although personalized messages create a sense of exclusivity and uniqueness, they also have the potential of lessening personal identities by standardizing tastes and behavior and diminishing the self as a result (Del Bucchia et al., 2021). This calls for dignity promotion actions from companies.

6 Concluding Remarks This chapter delves into some of the challenges that arise in the process of digital transformation, particularly when considering consumer vulnerability and potential threats to dignity. Unfortunately, access to the benefits of the digital revolution is not equitable, resulting in new forms of discrimination and potential social inequality. Moreover, the boundaries of confidentiality in professional and private spheres are altered, compromising privacy. Unethical use of digital advancements for commercial manipulation further exacerbates social problems, while the potential isolation and diminish of consumers’ self in digital contexts pose additional vulnerabilities in digital contexts (Del Bucchia et al., 2021; Guryanova et al., 2020; Marchese, 2023; Wang, 2023). Entry barriers can leave individuals unable to participate in the markets to exert their freedom of choice and pursue their well-being. To address this, organizations can potentially promote restorative digital systems that create an equal playing field for the consumer. Data is a source of immense power for companies, but its misuse can

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lead to negative consequences. Therefore, implementing robust security protocols for the storage and use of the growing volume of data is imperative. Additionally, well-defined and enforceable ethical guidelines are needed to ensure responsible and beneficial use of this information, safeguarding the rights and autonomy of consumers. Concerns about data may discourage individuals from participating in the market. Unethical practices such as unauthorized use of personal data (without the consumer’s consent) to drive sales, compromise a consumer’s freedom of choice, autonomy, and right to access personal information. Companies could transform this data into valuable information that empowers customers to make more informed decisions, even if it means making fewer sales. Digital technologies can enhance efficiency, however, it is crucial for companies to complement customer digital journeys and experiences with alternative channels for human interaction. This approach ensures the preservation of consumers’ dignity and well-being, particularly for those vulnerable to feelings of isolation and loneliness. Providing channels for consumer communities and promoting experiences with a human interaction component can further support this objective. This chapter addresses two gaps in the literature. While most articles focus on digital transformation from the company’s perspective, few analyze the customer’s standpoint and potential threats, especially in minority groups. Furthermore, it argues that the protection of human dignity should be a central objective in any digital transformation process. Ignoring this objective comes at the expense of perpetuating historical barriers of social exclusion, discrimination, loss of control, and manipulation, among other affronts to human dignity.

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Use of Generative AIs in the Digital Communication and Marketing Sector in Spain Xabier Martínez-Rolán, Juan Manuel Corbacho-Valencia, and Teresa Piñeiro-Otero

Abstract The rise of synthetic content generators has gained momentum over the past few years, with the increasing need for automation in content creation. These tools use artificial intelligence (AI) and machine learning (ML) algorithms to generate content, including text, images, videos, and audio. Synthetic content generators have become popular, with several platforms offering them as service, allowing users to create content with minimal effort. Despite the growing popularity of these tools, we are still in the early stages of research on how people use them and their impact on human communication. The current study analyses how professionals from communication and marketing agencies in Galicia (Spain) are beginning to use synthetic content generators and their motivations for doing so. The study will also examine the extent of use of these tools and their impact on human communication. To achieve this objective, an online form was developed and distributed among participants who have used generative AIs or synthetic content generators before in their work as advertising agencies. The online form collected both quantitative and qualitative data, allowing for a mixed-method analysis. The main results show that respondents are testing these tools, but still using them cautiously since this technological advance generates suspicions. The main uses are related to brainstorming—helping in creativity processes—and generating first drafts for texts. ChatGPT is the most known application, acting as a key for the introduction of other AI applications and assistants. Keywords Marketing and communication · Generative AI · ChatGPT · Machine learning · Algorithms · Synthetic content generation · Artificial intelligence · Language processing

X. Martínez-Rolán (B) · J. M. Corbacho-Valencia · T. Piñeiro-Otero Universidade de Vigo, Vigo, Spain e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 C. Machado and J. P. Davim (eds.), Management for Digital Transformation, Management and Industrial Engineering, https://doi.org/10.1007/978-3-031-42060-3_5

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1 Introduction Artificial Intelligence (AI) encompasses the creation of intelligent machines capable of executing tasks typically necessitating human cognition, such as visual perception, speech recognition, decision-making, and natural language processing (Russell & Norvig, 2010). The notion of constructing intelligent apparatuses can be traced to ancient myths and legends, whereas the contemporary concept of AI has its roots in the mid-20th century. For several decades, computer scientists have endeavoured to develop machines that could equal or surpass human intellectual capacity. The advent of swifter computers and more robust hardware has facilitated the design of increasingly efficient and effective AI systems. AI research has investigated an array of approaches, including machine learning and the employment of statistical methodologies. In the 21st century, advancements in machine learning techniques have been harnessed to vast data sets by both industry and academia, propelling big data research and AI applications in numerous domains. Present-day machines are capable of resolving challenges previously deemed insurmountable for them to tackle. A multitude of issues can now be confronted more expeditiously than if pursued solely by humans, as contemporary AI systems can utilise novel techniques for analyzing intricate data sets with speed and precision. The origins of AI can be traced back to the 1940s and 1950s, when researchers started to explore the possibility of creating machines that could learn and reason like humans (McCarthy et al., 2006). The development of digital computers and advances in mathematical logic and probability theory provided a theoretical foundation for AI research. One of the early successes of AI was the development of the Logic Theorist programme, which was designed to prove mathematical theorems using symbolic reasoning (Newell & Simon, 1956). Despite the early milestones of AI, the field faced significant challenges in the 1970s and 1980s, a period commonly known as the winter of AI (London, 2018; Russell & Norvig, 2010.). One of the main challenges was the difficulty of creating intelligent machines that could perform tasks that humans found simple, such as recognising faces and understanding the natural language. At the time, the existing techniques for building Al systems were limited, and progress was slow. Another challenge was the lack of computational power available for Al research: those computers were not powerful enough to process the large amounts of data needed. In addition to technical issues, AI research faced a crisis of confidence: the expectations for AI had been set too high, and many researchers had overestimated the capabilities of the existing technology. The lack of progress in AI research reduced funding and a loss of interest in the field. The field of AI experienced a “renaissance” in the 1990s, driven by the emergence of new techniques such as neural networks, genetic algorithms, and fuzzy logic (Russell & Norvig, 2010). These techniques provided more powerful and flexible tools for creating intelligent machines, and they opened new avenues for research

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in areas such as image and speech recognition, natural language processing, and robotics. Recently, the development of deep learning and reinforcement learning has further advanced the capabilities of AI, leading to breakthroughs in areas such as computer vision, game playing, and natural language understanding (Ha, 2020). Deep learning is a type of machine learning that uses artificial neural networks to learn from large datasets, while reinforcement learning is a type of machine learning that involves agent learning to make decisions based on rewards and punishments received from its environment. These techniques have been applied to various fields, including medical imaging (Dar et al., 2021), robotics (Li et al., 2022), speech recognition (Rajapakshe et al., 2020), and gaming. The combination of deep learning and reinforcement learning has enabled AI to achieve superhuman performance in many tasks, such as playing the game of Go (Igami, 2020).

2 Rise of Personal Assistants This previous and significant evolution in AI has allowed for developing of some specific areas such as personal assistants (PAs). These personal assistants can be used to perform everyday tasks like scheduling appointments, online shopping, online searches, calendar management, and much more. By using natural language processing (NLP) techniques, human–machine interaction can be performed through voice commands, a path that was opened in 2011 when Apple introduced Siri on its devices and Google debuted its Assistant. Amazon followed with Alexa in 2014, who, despite being the latest to arrive, has reached the most households (Alysis, 2019; Balcı, 2019; Dubiel et al., 2019; López et al., 2018). The rapid advancement of technology in recent times has led to an unprecedented increase in the prevalence of personal assistants in various aspects of our lives. This burgeoning technology has brought about a paradigm shift in the way we communicate and execute our everyday tasks. Personal assistants offer a plethora of advantages to users, thereby enhancing the overall user experience (McCarron et al., 2019). In fact, personal assistants, equipped with the ability to comprehend both spoken and written language, demonstrate a remarkable capacity for processing and responding to inquiries with a high degree of precision. Moreover, the progressive advancements in technology have enabled these personal assistants to undertake increasingly intricate tasks, encompassing decision-making processes founded upon the information they acquire. The development of natural language processing and speech recognition technologies has allowed personal assistants to understand and respond to human language in a more natural and intuitive way. In addition, the integration of artificial intelligence techniques such as machine learning and deep learning has enabled personal assistants to learn from large datasets and improve their performance over time. These advancements have led to breakthroughs in areas such as computer vision, game playing, and natural language understanding. Personal assistants have become an important tool for individuals and businesses

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alike, providing assistance with tasks such as scheduling, email management, and online shopping (Limsopatham et al., 2018). One of the most significant benefits of personal assistants is their ability to save users a considerable amount of time and resources. This enables individuals to effectively allocate their attention to other essential activities, resulting in a more efficient management of their personal and professional lives. Consequently, personal assistants can be considered as an invaluable tool that empowers people to maximise their time, energy, and resources, all the while fostering an increasingly seamless user experience. Therefore, the integration of personal assistants into our daily routines, facilitated by advancements in AI, has undeniably altered the landscape of human–computer interaction. These AI-driven personal assistants not only contribute to a more efficient utilisation of our time and resources but also pave the way for an optimised and increasingly user-centric experience. As we delve deeper into the realm of AI and its applications, it is crucial to explore and harness the potential of personal assistants in fostering a more productive and effective society (de Barcelos Silva et al., 2020). Technological advancements have empowered Personal Assistants (PAs) to handle various complex tasks, such as decision-making based on the information they obtain. As a result, PAs have emerged as invaluable resources for businesses and entrepreneurs, aiding in project management, client tracking, appointment scheduling, market research, and data analysis, among other responsibilities. PAs streamline these operations, leading to benefits such as improved efficiency and reduced costs. Also, the capacity of PAs to augment work efficiency and productivity has been recognised by several researchers. For example, Gartner, a prominent technology research organisation, estimated that by 2025, 50% of knowledge workers will interact with a virtual assistant daily, a considerable increase from less than 2% in 2019 (Gartner, 2021; Noy & Zhang, 2023).

2.1 Generative IAs or Synthetic Content Generation Tools: The “ChatGPT Revolution” The rising demand for PAs is transforming the way we conduct everyday tasks, providing numerous advantages to users. By allocating repetitive or time-intensive tasks to PAs, users can preserve time and resources, allowing them to concentrate on other endeavours. In addition, PAs deliver customised suggestions and immediate responses to user questions, thereby enhancing the overall user experience, but they are still part of a bigger revolution. AI-powered content generation tools have become increasingly popular recently, utilising NLP and natural language generation (NLG) models to automatically generate written content. These tools can be used for a wide range of content creation tasks such as blog posts, email subject lines, ad copies, and product pages, providing

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marketers with a valuable resource to save time and focus on more strategic aspects of content creation. Content generation tools powered by AI can also assist with idea generation by analysing audience engagement data and suggesting relevant topics for content creation (Ju & Qu, 2021). Moreover, some AI-powered tools such as Synthesia can generate digital avatars that can read scripts with realistic human-like speech and gestures, adding a new dimension to content creation. Other AI-based platforms, such as Lumen5 or Pictory.ai, can analyse text and web documents and create accompanying videos with appropriate images and music. Generative AI constitutes a subcategory of machine learning that equips systems with the capacity to produce novel, distinctive content by scrutinising and acquiring knowledge from extant data sets. In contrast to conventional rule-based chatbots, generative AI chatbots eschew reliance on predetermined responses, opting instead to generate contextually pertinent replies in real-time utilising natural language processing methodologies. This enables generative AI chatbots to yield more engaging exchanges that mimic human-like discourse. It is unequivocal that synthetic text generation tools have engendered significant interest across diverse demographics. Neural network models known as “Transformers”, possessing the capability to generate text transcending the conventional realms of analysis or classification, notably ascended in prominence in 2022. Nonetheless, the genesis and evolution of these innovative technologies have been deeply entrenched in our society for an extensive duration. GPT-3, a third-generation autoregressive language model, was released by OpenAI in 2020 (Brown et al., 2020). It has over 175 billion machine learning parameters and can perform zero-shot, few-shot, and one-shot learning. GPT-3 has been used for natural language tasks such as generation and processing in various applications, including Microsoft products for translating language into formal computer code (de Rosa & Papa, 2021) and start-ups such as Copy.ai, or Jasper.ai, both platforms using AI to automatically write content. OpenAI has also released an API for accessing new AI models developed by the company, including the GPT-3 family of models, which run with improved speed and throughput. To prevent potential negative effects such as harmful bias, OpenAI has implemented measures to regulate the API and ensure responsible use. At this juncture, it is the point where ChatGPT begins to make sense and represents a pivotal moment. ChatGPT is a chabot that employs generative AI technology to generate human-like responses to user inputs (OpenAI, 2020). Developed by OpenAI, ChatGPT has gained significant popularity recently due to its ability to mimic humanlike conversations and produce responses that are contextually relevant and often indistinguishable from those produced by a human (Brown et al., 2020). The advent of generative AI harbours the potential to profoundly influence business models and societal structures, with its applications permeating an array of sectors, including the legal and medical spheres. For example, generative AI chatbots have been employed to support legal practitioners in executing research and

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composing briefs, as well as to create medical reports and aid physicians in diagnosing patients. Furthermore, ChatGPT has demonstrated promising outcomes in language translation, summarisation, and storytelling, among other applications. Despite its clear success, some experts have expressed skepticism regarding the novelty of ChatGPT, arguing that similar techniques have already been implemented in other areas (Chen et al., 2017). Nevertheless, the potential of generative AI chatbots to revolutionise how we interact with technology and each other cannot be overstated, and ChatGPT represents an important step towards achieving this vision. This is not the first time that technology has attracted the attention of the public. What is at stake from a technological and business perspective in the world of big tech is the concept of “internet search”, which is de facto a monopoly of Google, given the volume of usage of its search engine in different countries of the world: the global average is close to 92%, and only countries with a strong local market, such as Russia (Yandex) and China (Baidu), have a market share of less than 30% (Fernández, n.d.). With its innovative use of generative artificial intelligence technology, ChatGPT can disrupt the long-standing search engine market that has been around for over two decades. Apart from ChatGPT, other relevant tools using generative AIs used in this study are: • Bing Chat: Bing Chat is an Al-powered chabot service that is integrated into the Bing search engine. Due to agreements with OpenAI, the engine in use is the most advanced model, GPT-4. It allows users to ask questions and receive answers in a conversational format, using natural language processing to understand user queries and provide relevant results. It can correct misspellings before performing the search, but there is a limit to the number of messages per day to improve search results and provide more complete answers. • You.com/chat: You.com is a search engine that puts its users first and offers more privacy than other search engines such as Google. Founded by former Salesforce employees, it emphasises comparing information to provide the best results. You.com uses a combination of search results, apps, and shortcuts to present information in a user-friendly way. But the real evolution nowadays is that, in addition to its search engine, You.com also offers an Al-powered chat assistant that can help users find answers to their questions, similar to what Bing Chat has been offering since February 2023. • DALL-E: DALL-E is an artificial intelligence program created by OpenAI, capable of generating images from textual descriptions. It leverages a neural network trained to comprehend natural language descriptions and translate these concepts into visual imagery. The model can manifest highly complex outputs and generate images of virtually any concept conceivable, prompted by a simple text input. • Stable Diffusion: Stable Diffusion is a sophisticated deep learning model employed for the purpose of text-to-image generation. The model progressively processes textual information to generate high-quality, stylised, and photorealistic images. The distinctive technique utilised by Stable Diffusion, aptly

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referred to as “diffusion”, involves an iterative process whereby an initial, highly noisy image is gradually transformed into a more defined and realistic visual representation. This transformation is achieved through the systematic addition and subsequent reduction of grainy textures, contributing to enhanced detail and realism. This model represents a collaborative achievement pioneered by researchers and engineers affiliated with CompVis, Stability AI, and LAION. Midjourney: Midjourney is an AI model engineered for the generation of images from text descriptions. Similar to DALL-E and Stable Diffusion, Midjourney employs advanced deep learning techniques to transform natural language descriptions into corresponding visual content. Capable of producing intricate outputs, Midjourney has been utilised in diverse applications, including the creation of t-shirt designs. However, compared to other models like Stable Diffusion, it may necessitate additional effort to yield the desired results. Notably, Midjourney does not offer a free version of its model and mandates usage via a specific Discord server, indicating a commercial approach to its distribution and application. Virtual assistants such as those in Craft, Notion, and others, are AI-powered text assistants that can aid users with a wide range of tasks. These tasks extend beyond project management, note-taking, and task tracking, to include features like text analysis, content transformation, language translation, and document summarisation. They can be seamlessly integrated into their respective platforms, providing personalised recommendations and suggestions tailored to user preferences. These intelligent features are often powered by advanced AI models like OpenAI’s GPT-3, offering users a robust, efficient, and sophisticated tool to optimise their workflows. Perplexity: Perplexity is an Al-powered natural language processing tool that can be used for various purposes, such as language translation, sentiment analysis, and chatbot development. It is an excellent resource for obtaining explanations about questions referred to a web searcher, despite reading texts across page results. Additionally, the generated text provides the sources used to create the answer. Elai/Synthesia: Elai and Synthesia are an Al-powered video production tool that can be used to create engaging and personalised video content. It can be used for various purposes, such as marketing campaigns, training video and product demonstrations. Elai/Synthesia is an effective tool for businesses seeking to create high-quality video content without the need for extensive video production experience. These tools are particularly relevant due to the use of realistic avatars. You choose an avatar and language, and the app creates the video from a text prompt. It is possible to clone yourself into an avatar in Sinthesia. Podcastle is an AI-driven platform specialising in the rapid and efficient creation of high-quality podcasts. The platform equips users with an array of robust features, including editing tools, sound effects, and background music, enabling the production of professionally crafted podcasts. Its sophisticated AI technology streamlines the podcast production process, making it an invaluable resource for businesses and individuals alike seeking to create engaging and informative podcasts for their respective audiences.

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2.2 Risks and Ethical Considerations of Generative AIs Despite their usefulness, it is important to acknowledge the limitations of AI-powered content generators. These tools cannot replace skilled writers or create high-quality, long-form content due to their inability to understand the intricacies of human language. Generative AI has made significant strides recently, with applications ranging from natural language processing to image synthesis. Although these advances have a wide range of potential benefits, they also raise critical ethical and risk-related questions. In this text, we will explore some of these concerns, primarily focusing on data privacy, AI-generated misinformation, and the potential for bias in generative AI systems.

2.2.1

Data Privacy

One of the primary risks associated with generative AI is the potential for data privacy violations. This is particularly relevant when considering AI models that are trained on large datasets containing personal information (Cave & ÓhÉigeartaigh, 2018). There is a risk that these models could inadvertently expose sensitive information or be used to generate synthetic data that closely resembles real individuals, leading to privacy concerns and potential legal issues. It seems that ChatGPT has been trained on a dataset from Google (Google’s C4 dataset) with 15 million websites (Schaul et al., 2023), where there may be content without consent. Particularly, a fervent debate is underway throughout Europe concerning the regulation of AI, wherein the proposition is to implement a risk categorisation system with four tiers. Each member state addresses the utilisation of these technologies in its unique way. The legal status of ChatGPT is not detached from this discussion. Italy enacted a temporary prohibition on ChatGPT at the end of March 2023, due to breaches of data protection legislation, and Spain and France have voiced analogous concerns.

2.2.2

AI-Generated Misinformation

Generative AI models can create highly realistic, yet entirely artificial, content. This can include images, audio, video, and written text. The ability to generate such content raises the risk of AI-generated misinformation, which can be used to manipulate public opinion or cause other forms of harm (Brundage et al., 2018). For example, deepfake technology can also be used for harmless purposes such as creating realistic special effects in movies or creating realistic avatars for video games. Additionally, some argue that the potential harm caused by deepfakes is overstated and that people are generally able to distinguish between real and fake content. A study conducted by researchers at the University of Warwick found that people were able to correctly

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identify deepfake videos 65% of the time (Kshetri, 2019), which suggests that the technology may not be as effective at deceiving people as some fear.

2.2.3

Bias in Generative AI Systems

Generative AI models frequently rely on large datasets to learn from and generate content. However, these datasets may contain biases that are inadvertently introduced during the data collection and curation process. These biases can then be propagated through the AI system, leading to outputs that may perpetuate stereotypes, discriminate against certain groups, or otherwise harm individuals (Kumar et al., 2020). Bias in AI models can be mitigated through various techniques such as algorithmic fairness, rational grounds for model selection, and standardising fairness assessment throughout the AI lifecycle (Vasconcelos et al., 2018). However, evidence suggests that AI models biased against sensitive classes could reinforce and even perpetuate existing inequities (Timmons et al., 2022). It is essential for AI researchers and practitioners to be fully aware of these risks and develop methods to mitigate bias in generative AI systems, although mitigating bias in generative AI systems is a multi-faceted challenge that requires concerted efforts from researchers, practitioners, and policymakers alike. Only through a keen awareness of the risks and a dedicated commitment to addressing these issues can we hope to achieve the goal of developing fair and ethical AI systems.

2.3 Marketing and Communication Field The strategic deployment of extensive data sets and automated processes has remained prevalent for more than a decade. As posited by Martínez Rolán and Piñeiro Otero (2022), the effective harnessing of data is of paramount importance in understanding the prosperity and ongoing perseverance of enterprises within a highly competitive international milieu. This necessitates the incorporation of an array of technological capabilities, culminating in a unique convergence of resources, professionals, and tools dedicated to achieving the set objectives. The influence of these burgeoning technologies has permeated various fields, including the realm of programming, as elucidated by Peng et al. (2023). Wolff et al. (2020) identified seven viable application areas where chatbots appear particularly beneficial: support (internal/external), human resources, purchase and sales, maintenance, (employee) self-service, education and training, and knowledge and information management. However, the implications of these advancements extend beyond mere coding capabilities. They manifest significantly in tasks associated with the generation and management of textual content––an integral facet of marketing and communication strategies.

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In a promising study by Noy and Zhang (2023), professionals were assigned an assortment of tasks related to text generation, such as drafting realistic memos, formulating strategy documents, and devising policies. The researchers found that the integration of advanced AI models, such as ChatGPT, into their work routines drastically improved their productivity and output quality. Specifically, task completion was expedited by 37%, and there was a marked increase in the average writing quality. An additional conclusion is the leveling power of these technologies. While the proficient improve, it is the less accomplished individuals who reap the greatest benefits from these technologies. Overall, these findings underscore the transformative potential of AI in the marketing and communication sector. By automating and enhancing aspects of text creation, AI tools like chatbots can facilitate more efficient workflow management, improve content quality, and ultimately contribute to more effective marketing and communication strategies. This not only underscores the importance of data and automation in this field but also highlights the growing relevance of AI capabilities in the modern competitive business environment.

3 Methodology The methodology adopted in this study is a mixed-method approach, using both quantitative and qualitative methods to analyse the data obtained from the online form. The use of a mixed-method approach allows for a more comprehensive and in-depth analysis of the data collected, providing a more complete understanding of how people use synthetic content generators. The online form used in this study was developed based on previous research on survey design and data collection methods. For instance, Dillman’s Tailored Design Method (TDM) was applied to design the online form, ensuring that the questions were clear, concise, and easy to understand (Dillman et al., 2014). In addition, the questions in the online form were based on a review of the literature on generative AIs and their use, ensuring that these questions were relevant and addressed the research questions. The first section of the online form collected demographic information about the participants, including age, gender, educational level, and occupation. This section of the online form was based on previous research that has used demographic information to analyse the data collected (Creswell & Creswell, 2014). The second section of the online form contained questions about the use of synthetic content generators, including the frequency of use, the types of content generated, and the platforms used. The questions in this section were designed to obtain quantitative data, which could be analysed using statistical tools such as descriptive statistics and regression analysis and were based on previous research that has used similar questions to analyse the use of technology and social media (Chen & Bryer, 2012).

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The third section of the online form contained open-ended questions about the motivations for using synthetic content generators. The questions in this section were designed to obtain qualitative data, which could be analysed using content analysis and were based on previous research that has used open-ended questions to analyse the motivations for using technology (Karahanna et al., 1999). As has been stated, the data collected from the online form were analysed using both quantitative and qualitative methods. The quantitative data were evaluated using descriptive statistics and regression analysis to identify patterns and relationships between variables. The qualitative data were interpreted using content analysis to identify themes and patterns in the data. The use of these methods for data analysis is consistent with previous research that has used similar methods to analyse survey data (Chen & Bryer, 2012; Creswell & Creswell, 2014) (Table 1). Table 1 Survey questions Question

Content block

Sex

Demographics

Age Level of education What is the size of the company you work for? (Likert scale) Do you work in digital communication/ marketing? (Yes/No) Are you familiar with any of these tools? (List of tools with likert scale)

Likert scale and open answers for quantitative data

Do you find these tools useful in your work? (Likert scale) Which one is your favourite? (open answer) Do you know of any other tool that you find interesting? (Especially if you marked “other tool” in previous questions) (open answer) Briefly describe why you use this type of tool and how it specifically helps you in your work (if applicable) (open answer)

Open-ended questions. Qualitative data

Do you miss any tool or functionality that covers any of your needs in your day-to-day work? (open answer) Would you be willing to provide your email Upcoming studies address? The survey is anonymous and the data will be pseudonymised, but we value the possibility of extracting a random sample of participants for an in-depth interview on the topic Source Prepared by the authors

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For the distribution of the survey, a limited population was chosen: the advertising and communication sector, in a regional market (Galicia) within the Spanish context. Thus, the survey was disseminated among professional contacts and associations (Creatividade Galega, about 55 advertising agencies in Galicia and 8 academic sources; and Cluster da Comunicación, 37 companies) during the month of February 2023, resulting in a total of 99 responses from the intended target population. Focus groups are a valuable qualitative research method that allows researchers to collect data on participants’ perceptions and attitudes towards a particular topic. As noted by Morgan (1996), focus groups provide an opportunity for participants to interact with each other, generate new ideas and explore their attitudes towards a particular subject in a group setting. Thus, to gain a deeper understanding of the survey results, a small focus group discussion was conducted with five randomly selected participants who had completed the open-ended questions and expressed their interest in participating.

4 Results Following a meticulous assessment of the collected data and the application of the previously established analytical methods, the results section presents a detailed and rigorous analysis of the findings obtained.

4.1 Quantitative Results Regarding knowledge of these types of applications, the study reveals that the most well-known application is ChatGPT, used at least once by 78% of the respondents. Dall-e, with 37% of users, and the Notion/Craft virtual assistant (26%) are the most used applications. Overall, there is a significant lack of knowledge of applications other than ChatGPT. More than half of the sample was not familiar with Stable Diffusion, Perplexity, Elai, Sinthesia, or Podcastle (Table 2). However, the degree of knowledge is not as low as one might suppose. Many applications have not been tested yet but are known to a small portion of the sample. 53% of respondents declare that their favourite application is ChatGPT, while 9% claim it is Dall-e and the same percentage choose MidJourney. From these results, we conclude that of the most used applications, MidJourney generates the highest loyalty, as it is closest in the declaration as a favourite application compared to its usage. 28% of respondents declare that they do not have any favourite application or formed criteria in this regard. Other applications that generate loyalty are Notion (6%), Wombo, and Playground (3%).

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Table 2 Level of knowledge of generative IA’s I do not know (%) ChatGPT

6

I know it (%)

I have tried it (%)

I use it daily (%)

16

50

28

Bing chat

44

38

13

3

You.com/chat

75

19

3

3

MidJourney

50

28

19

3

Dall-e

50

13

31

6

Stable diffusion

69

13

13

3

Asistente virtual de 47 craft/notion/otros

28

13

13

Perplexity

81

16

0

3

Elai/synthesia

81

13

6

0

Podcastle

69

25

6

0

Another synthetic TEXT generation tool

69

9

13

9

Another synthetic VIDEO generation tool

84

3

9

3

Source Prepared by the authors

Although the range of suggested applications was broad, respondents were also given the option to suggest other applications that they used for their work. These include Wombo Art, AIVA, Flexclip, Fliki, Fireflies, Sembly, Krisp, Poised, Stock AI, Browse, Sembly, Krisp, Poised, Stock AI, and Browse. Regarding the impact on the profession, the vast majority agree on the disruptive nature of these technologies. None of the respondents indicated that these technologies have made their work difficult. Only 9% admitted that they contribute nothing to their daily work. In contrast, 44% affirm that it will change everything in their profession, and with slightly less certainty, 37% agree that these technologies provide a slight help. The remaining 9% do not have a opinion on the matter by now.

4.2 Qualtitative Results After the quantitative approach, we focused on the questions that derived from the qualitative side of the study. First, we asked professionals in the sector to describe why they use this type of tool and how it specifically helps them in their work (if applicable) (Fig. 1). Approximately 28% of the participants stated that they do not use these tools. There could be several reasons why professionals might choose not to use these apps. First, the lack of knowledge regarding their existence or functions. However,

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Fig. 1 Utility of generative IAs at work. Source Prepared by the authors

some respondents stated, “I have tried them, but I do not use them in my work”, which is an important issue to explore as it raises more research questions. This lack of awareness or understanding may lead to customers not using the service to its full potential. Another reason could be a preference for human interaction. Overall, the reasons for not using these AIs are likely to vary depending on individual preferences, perceptions, needs, and experiences with the technology. We also found some skeptical points of view. They can use the apps, but they do not trust them due to the lack of reliable sources or language errors: “We are considering them at the agency in case one satisfies us when it comes to generating content, but we believe that it is not our way of working for now. What we have tried does not completely satisfy us because it is unreliable in terms of content; we have detected errors in language and in the consideration of reliable sources”. The main uses detected are brainstorming and content generation (text and image). Approximately, one-third of the interviewees point to the main use of this type of synthetic content generator for brainstorming and prototyping. They highlight the help they provide in generating content quickly and as inspiration: – The first phase of content creation is fundamental for any successful digital marketing strategy. In this stage, the objectives and themes that the content production will address, as well as the target audience it is aimed at, are defined. The basic foundations upon which to build a solid strategy are established. – Help with idea generation: Users can obtain quick and effective inspiration through simulated conversations. – Breaking the blank page barrier: A term used to describe the mental or creative block that some people experience when trying to start writing or creating content from scratch. This barrier can result from self-imposed pressure to produce something perfect from the beginning, lack of confidence in one’s own abilities, or lack of inspiration. It can be particularly problematic for content creators, writers, and other professionals who work in fields that require the regular production of ideas

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and content, such as the sector studied in this research. The use of synthetic content helps mitigate this problem according to the professionals consulted. However, even in the brainstorming function, the limitations of the tools are highlighted as follows: “Subsequently, the information needs to be curated and given the necessary touch and tone for each context”. They also distinguish the function of internal prototyping and social media publishing separately. These tools help in internal prototyping, the stage where a model or sample of the product is created to test its viability, functionality, and aesthetics. This process is focused on creative exploration, experimentation with different materials and techniques, as well as the validation of concepts and solutions before investing time and resources in the final production. Another major function covered by these types of applications is text generation, a matter that a quarter of the survey participants highlighted. Among the textual functions that professionals highlight are the different stages of text creation: – – – – – –

Drafting text Elaborating on the first versions to work on Ideation of content Expanding content Deepening content Completing texts.

Specifically, some actions that are essential in the sample are highlighted, related to specific issues in the business of communication and advertising agencies. The potential that synthetic text generators have for tasks related to copywriting and SEO positioning is stressed, as well as for expanding contexts in English and for creating final texts for different email marketing channels (“Creation of copies for automation and transactional emails”). Synthetic image generators also receive similar ratings in terms of use, as they serve to create content that supports the creative work of the professionals behind the use of this tool. “It helps me with image compositions basically to reinterpret later” or “to create graphics that I cannot generate in any other way”. In this regard, there is a certain “lateral thinking of these tools”. A content creator highlighted that they help because sometimes “creativity itself is so ‘complex that the concept does not exist as such”. Underlying the responses related to the generation of synthetic texts and images, and even in brainstorming, another advantage appears explicitly, which is cost and time savings (although we can understand time as a more valuable resource in economic terms). Specifically, these tools are referred to and their capacity to: – Save time in certain situations: • Executing multiple iterations: the use of iterations in the idea generation process allows teams to explore multiple options and solutions, which can lead to more innovative and effective ideas.

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Fig. 2 Generative IA’s adoption spectrum. Source Prepared by the authors

• Organising work: helping maintain focus and efficiency in the content creation process. • Obtaining brief answers on certain topics: cognitive load can be reduced, and the idea generation process can be accelerated. • In the idea generation processes: reducing the barrier to generating ideas. • Formulating complex questions: by asking more specific and focused questions, more useful and practical answers can be obtained for the content creation process. Additionally, open-answer questions showed some other uses such as teaching, presentations developing or very specific tasks such as meeting transcriptions, summarising and extract key points on meetings. This finding may also be related to the last question regarding missing tools or functionalities that cover any day-to-day work needs, an issue that we delved into our discussion group (Fig. 2). Half of the answers were “no”. In this sense, there is a spectrum of users who oscillate between a resounding “no” and a “no, but without opposing change”. Many people who responded negatively pointed out that their current needs were already being met, but there may be functions that are not yet known that could be covered by AI. Thus, it is an open NO to change. Half of the sample acknowledge that there are still needs that are not being met, that they are unknown, or that the current possibilities are not sufficient. From a wide spectrum that ranges from “open-mindedness” to “technological enthusiasm”, we can find different types of worker profiles: Those who recognise technology and are open to change “what comes, is debated, and if it is useful, it is adopted”, in that new ideas, technologies, or ways of working must be critically evaluated and discussed before being implemented. If a new idea or technology is considered useful and can improve performance or results, then the company or worker embraces that technology. Otherwise, it is discarded.

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This implies being willing to abandon obsolete or ineffective practices and being open to new ways of doing things. Finally, a wide spectrum of users is grouped among those who recognise current demands in their day-to-day work and seek specific improvements in the technologies used to create this type of content. One of the most demanded functionalities is the integration of voice commands, particularly in the case of spreadsheets. This would allow users to control and manipulate data in a spreadsheet through dictated prompts. Tasks such as creating and editing cells, changing cell formats, applying filters, and, above all, creating functions would be done more quickly and efficiently. Another highly demanded functionality is the use of hyper-specialised microassistants in routine tasks related to file management: automatically naming files, assigning metadata (keywords, categories), digitising a user’s private libraries—“all my books digitised and at the service of a digital assistant”, managing actions with files (tasks of exporting images and videos, ordering files and cataloging—“so that I don’t have to waste time organising and naming a large number of files that I generate daily”). In this way, in a company, a microassistant could automatically assign tags and categories to documents according to their type and content, making it easier for employees to search and access them. They could also help automate tasks such as exporting and archiving documents, allowing employees to spend more time on more important tasks. Respondents also claimed that IA-generated contents and functions “still offer limited results due to the limitations of input from the brief with text prompts”. However, the generation of synthetic images is of interest to professionals in communication and digital marketing. The generation of images is very useful for creating advertising or marketing material, as it allows images to be generated that fits perfectly with the campaign’s requirements. Not only the generation of images but also the treatment of existing images. This includes the possibility of adding special effects, modifying elements of the image, or even generating moving images. Thanks to these tools, much more dynamic and attractive content pieces can be created. From a more administrative or general perspective of the sector, another demand is linked to procedural and even administrative management. Artificial intelligence can help with time and workflow management using algorithms and data analysis to identify patterns and optimise processes. In the case of video editing, for example, artificial intelligence could analyse the workflow and editing times to identify areas where efficiency can be improved, and production times reduced. This includes the automation of repetitive tasks, the identification of areas where effects or transitions can be applied more effectively, or the optimisation of the work sequence to reduce downtime. Regarding the administration and generation of invoices, another demand of professionals, artificial intelligence could be programmed to recognise patterns in billing data and automate the generation of invoices, track pending payments, and

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send payment reminders. It could also help optimise workflow in the invoice administration, identifying areas where processing times can be reduced, and efficiency improved. In summary, artificial intelligence can help manage time and workflow by analyzing data and identifying patterns to improve efficiency and reduce production times. This can be applied in various areas, such as video editing, invoice administration, and generation, and any process that includes repetitive tasks and data processing.

5 Discussion and Conclusions The findings of this study suggest that the use of synthetic content generation tools is becoming increasingly common in the digital communication and marketing sector, even in this early stage with an incipient phase of this type of tool. Our study points out that many professionals in this field are using these tools to create high-quality content quickly and efficiently. This can save time and money, while also producing more engaging and effective content. Although initially it was believed that this technology could lead to a decline in creativity and originality, as well as a lack of diversity in the content produced, the use of this tool as brainstorming and first drafts of text debunks this idea. However, as with any early stage of technology adoption, there is a volume of sceptical professionals especially related to the human–machine interaction with prompts. Although these tools are designed to be user-friendly, some professionals indicate that human–machine interaction can be complicated and not always yield the expected results. In some cases, users may have difficulty communicating their ideas effectively, resulting in content that does not meet expectations. Another reason for skepticism is linked to the reliability of sources used in synthetic content generation. Often, these tools use algorithms to search and compile online information, which can lead to the inclusion of unreliable sources or even the spread of fake news and misinformation. Source verification is critical in the production of quality content, and a major challenge for these types of tools (Alkaissi & McFarlane, 2023; Ji et al., 2023). Finally, respondents are sceptical about the quality of the results, especially regarding the generation of images. Although these tools have made significant advancements recently, there are still limitations when it comes to the quality of the generated images. In some cases, the images may look artificial or unrealistic, which can negatively impact the brand or product’s perception. On the other hand, a clearly cyber-optimistic professional profile sees this technology as a great opportunity to improve the efficiency and quality of digital marketing and online communication. Cyber-optimists embrace technology and see it as a valuable resource to improve content production. Instead of fearing technology, these professionals see it as an opportunity to improve and optimise their work.

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In this sense, these professionals consider the reinforcement of the assistant role as a great opportunity to improve efficiency in content production. Synthetic content generation tools can help assistants perform their work more quickly and efficiently, which can be beneficial for both the professional and the company. Furthermore, the implementation of technologies such as ChatGPT is becoming the spearhead of these tools. These natural language processing systems allow users to interact with a virtual assistant, which can be a valuable tool for improving efficiency in content production. Another aspect that cyber-optimists focus on is the ability of these tools to perform well in the realm of text. Often, these tools are used to generate written content, such as long-form drafts, product descriptions, or advertising copy. In this regard, cyber-optimists highlight the effectiveness of these tools in producing quality written content. Despite the duality of opinions between skeptics and optimists, synthetic content generation tools can be a valuable resource for professionals in the digital communication and marketing sector. By allowing for creating high-quality content quickly and efficiently, these tools can help companies stand out in an increasingly crowded online marketplace. In conclusion, this study has highlighted the potential benefits and drawbacks of using synthetic content generation tools in the digital communication and marketing sector. These tools allow for creating high-quality content quickly and efficiently, which can help companies stand out in an increasingly crowded online marketplace. Although there are some concerns surrounding the ethical implications of this technology, it is evident that it can be a valuable resource for communication and marketing professionals. Therefore, it is important for companies and individuals in this field to continue exploring the potential of synthetic content generation tools while being mindful of the potential risks and challenges associated with this technology. In conclusion, despite differing opinions on the use of these tools, it is important to recognise their potential and continue exploring their use in the field of digital communication and marketing. With the constant improvement of generative AI technologies and a greater awareness of their possible limitations and risks, these tools can be an asset to help companies stand out in an increasingly competitive online marketplace.

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“The New Online Normal”: Exploring Online Trends on E-commerce and Internet Use During and After COVID-19 Pandemic Teresa B. Treviño Benavides

Abstract The COVID-19 pandemic brought a bigger and rapid adoption of digital technologies, as people needed to communicate, work, study, entertain themselves, and buy without leaving home. In fact, the pandemic serves as an accelerator for a structural change in online consumption and the digital transformation in the marketplace, organizations, and society. With this in mind, the purpose of this chapter is to review and reflect on the online trends derived from the coronavirus pandemic. Particularly, by reviewing recent literature on the topic, and presenting results of an exploratory survey, it will shed light on how people have changed and shifted some consumption patterns online with respect to (a) e-commerce, (b) Internet and social media use, and (c) demand for online services. Overall, this chapter will explore observed changes and trends around people and technology during and after the coronavirus pandemic to serve as a basis for future directions for organizations and brands. Keywords Digital technologies · E-commerce · Internet use · Social media

1 Introduction In March 2020, life began to change unexpectedly with the arrival of the Coronavirus. People around the world had to stop activities and quickly adapt to the new reality. The implementation of lockdowns and social distancing measures was practically unprecedented, which without a doubt have marked a turning point in history. Such measures and situations forced people to stay at their homes and limit their interactions with others. Therefore, consumers faced challenges in buying food and essential items, as well as to continue with their activities such as work and education. In this manner, the COVID-19 pandemic brought a bigger and rapid adoption of digital T. B. T. Benavides (B) Business School, Management Department, Universidad de Monterrey, San Pedro Garza García, Mexico e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 C. Machado and J. P. Davim (eds.), Management for Digital Transformation, Management and Industrial Engineering, https://doi.org/10.1007/978-3-031-42060-3_6

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technologies, as people needed to communicate, work, study, entertain themselves, and buy without leaving home. People had to increase their use of digital devices, or in some cases, use them for the first time, as virtual conferences, meetings, and other online activities became practically a necessity. In fact, reports have shown that the adoption of online shopping has grown faster than expected, as consumers who were not planning to buy online were practically forced to do so derived of the restriction measures (Lechuga & Hernández, 2020). Today, in June 2023, after more than 3 years and almost 7 million deaths reported worldwide, COVID-19 is no longer considered a global health emergency, as declared by the World Health Organization Chief, however, it leaves many aftermath effects throughout the world (Rigby & Satija, 2023). It can be observed that the implications of a pandemic such as Covid-19 can be classified as economic, social, political, and psychological (Lechuga & Hernández, 2020). Further, it is known from historical stressful events that the effects on people in the light of crises, occur both during the event, and some years later it ends (Zwanka & Buff, 2020). This suggests that the impact of an uncertain, difficult, or stressful event such as the coronavirus pandemic, may lead to long-term effects on consumer behavior. Therefore, it is worth discussing the idea that the consumption patterns of people modified during the pandemic, may produce some long-lasting effects in their behaviors (Guthrie et al., 2021). Some authors have reflected on the fact that the pandemic serves as an accelerator for a structural change in online consumption and the digital transformation in the marketplace (Kim, 2020). The rise of e-commerce has been accelerated by the pandemic, as consumers increasingly turn to online platforms to buy the products they need. With physical stores facing restrictions and lockdowns, individuals embraced the convenience, accessibility, and contactless nature of online shopping. This shift has reshaped traditional consumer patterns and behaviors, with more people adapting to the ease of looking for and purchasing products from the comfort of their homes. In fact, research has found that now many consumers increasingly prefer to make purchases online (Ballerini et al., 2023). As a result, businesses have been compelled to enhance their digital presence and enhance their e-commerce operations to cater to this evolving demand. Additionally, Internet use changed dramatically during the pandemic, considering that people were spending more time at their homes, they sought means of connection, information, and entertainment. There is no question that the Internet has become a vital tool for work, online learning, and socialization. Simultaneously, social media platforms have experienced an increased usage rate, with individuals relying on them for news updates, staying connected with friends and family, and consuming other online content. Moreover, online services also experienced an increased demand that has prompted businesses to innovate and adapt to meet changing consumer expectations, leading to a significant digital transformation in these industries. Overall, this heightened usage of the Internet and social media has reshaped how people communicate, seek information, and maintain relationships. With this in mind, the purpose of this chapter is to review and reflect on the online trends derived from the coronavirus pandemic. Particularly, by reviewing recent literature on the topic, and presenting results of an exploratory survey, it will shed light on how people

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have changed and shifted some consumption patterns online with respect to (a) ecommerce, (b) Internet and social media use, and (c) demand for online services. Overall, this chapter will explore observed changes and trends around consumers and technology that can be observed during and after the coronavirus pandemic to serve as a basis for future directions for organizations and brands. The following chapter is structured as follows. First, a recent literature review is presented on the topics of e-commerce trends, Internet and social media, and demand for online services. Then, the methodology of the study is presented, as well as the results from such research. Finally, findings are discussed to conclude into implications and future research directions.

1.1 E-commerce Trends E-commerce involves digital commercial transactions between and among organizations and individuals (Laudon & Traver, 2009). E-commerce as a business model has become a strategy for many organizations to obtain a competitive advantage and adapt to new circumstances. One of the first steps to succeed in e-commerce is to understand consumers and their behaviors in a way that allows companies to build experiences that exceed their expectations (Barrios et al., 2021). One of the main changes in online trends derived from the coronavirus pandemic is the notable e-commerce growth. Several factors played an important role in such growth, as most countries faced (a) an increase in Internet connections, (b) quarantine measures, and (c) governmental restrictions (Podorova-Anikina et al., 2022). In particular, when the pandemic began around March 2020, the closure of physical stores forced consumers to turn to online stores. Many companies were also forced to start operations online, so many new merchants were available for consumers. As shown in Fig. 1, in 2021, e-commerce sales growth was 17.1% compared to 2020 (eMarketer, 2022). Research suggests that online consumption during 2020 was one of the only access to informative, entertainment, cultural, and educational content (Barrios et al., 2021). There were also shifts in consumer demands, as some products were not needed when people were confined to their homes for long periods of time, such as clothing and apparel, makeup, accessories, etc. Considering that people worked and took classes online, such categories declined in importance for consumers. Furthermore, other products became the first necessities such as food, personal care, and health related items, and home improvement materials. The largest growth of the e-commerce market occurred in the United States, Great Britain, Poland, and Russia (Podorova-Anikina et al, 2022). In 2021, Brazil was the leading e-commerce market in Latin America, generating 41 billion U.S. dollars, followed by Mexico, which generated 34 billion dollars (Statista Research Department, 2023). Despite this important growth experienced from 2020 to 2021, as the coronavirus pandemic started to slow down, retailers started opening up physical stores again.

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Fig. 1 Retail e-commerce sales growth Worldwide 2017–2021. Source Own elaboration with data of eMarketer (2022)

As expected, a decrease in the unprecedented growth of e-commerce was observed, however, some product categories did maintain their pandemic customers. According to Statista, for the first time in history, e-commerce growth was negative in 2022. Some of the reasons that may impact these numbers, additionally to the reopening of physical stores, may include the economic factors such as inflation and unemployment after the pandemic. Additionally, supply chain issues make logistics expensive and affect the availability of products, and finally, the fact that all these uncertain factors may have shaken consumers’ budget and ultimately affected their confidence (Statista Digital Market Outlook, 2023). Furthermore, this decrease in online shopping was predicted and expected, as people returned to their traditional routines and consumers could go back to the physical channel. Additionally, there is a normal decrease in supplies needed at home, such as groceries and food, as people no longer work or study from home (Wang et al., 2021). The context and environment where companies are operating physical and digital stores today is not simple. On one hand, the costs for the acquisition and shipping of products have risen, and competition in online advertising is increasing as well. On the other hand, consumer expectations are even more complex, as there are now many online retailers to choose from which translates into being more selective and less accepting of slow delivery times, bad customer service, and bad quality of products (Khodzhamuratova et al., 2023). In other words, as more people actively use the Internet, their time spent on such networks is also increasing. This, in turn, increases the consumer’s experience and translates into more complex expectations and complex needs (Jasi´nska-Biliczak, 2022). For these reasons, e-commerce needs to evolve and innovate once again, and some trends around this topic will be addressed in the following sections.

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1.2 The Future of E-commerce 1.2.1

M-commerce

M-commerce can be understood as a subset of e-commerce, differentiating mainly by the commercialization process, in which a direct or indirect transaction with a monetary value is conducted through mobile devices via wireless networks (Zheng et al., 2019). In other words, m-commerce involves conducting commercial transactions that may include online shopping, but also mobile banking, mobile payments, and the use of other mobile apps or even websites that are optimized for mobile devices. The outstanding characteristics of this way of negotiation are mobility and its range of reach. In m-commerce, consumers can use their mobile devices with access to a wireless network to engage in a transaction practically anywhere (Lucas et al., 2023). Moreover, by using mobile devices for such purposes, companies can integrate mobile-specific capabilities to enhance the shopping experience. For example, location-based services, push notifications, or even mobile wallets offer personalized recommendations, alert users about specific offers close to them, or ensure easy-to-use contactless payments. The transition from e-commerce to m-commerce is increasing every year. In 2021, one in five online shoppers used a mobile device to select and order products, and today it is expected that one in two shoppers are making purchases from a mobile device (Dumanska et al., 2021). Research shows that users are moved by a hedonic motivation to use mobile devices to make purchases. This motivation refers to the fun or pleasure derived from using such technology for that purpose. In fact, when consumers have positive experiences with m-commerce apps, while considering them entertaining and enjoyable, they are more likely to reuse them in the future (Vinerean et al., 2022).

1.2.2

Social Commerce

As e-commerce refers to the purchase experience on a brand’s website or app, social commerce refers to the use of social media to sell products to consumers (Zhang & Benyoucef, 2016). In particular, social commerce, also known as s-commerce, relies on social networks such as Instagram, Facebook, Twitter, and TikTok, to promote products and generate sales (Ben-Itzhak, 2020). However, the term “social media” also includes other platforms such as message boards, blogs, and others (Zhang & Benyoucef, 2016). One of the advantages of social commerce is that the platforms offer capabilities to advertise products and allow consumers to purchase directly from the ad or account, without the need to visit another website or even talk to a person. Considering that the overall purchase process is simple and straightforward, the likelihood that the sale will take place increases. Furthermore, more and more people are spending time on social media, as they have been using it to learn about products and brands. Today, brands can complete the consumer journey by offering users the ability to purchase products directly from these platforms (Ben-Itzhak,

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2020). Today, some social network sites, such as Facebook, Instagram, Pinterest, and WhatsApp, are optimized for online commerce, where companies can create a marketplace for people to discover buy and pay for products (Rodrigues, 2023). Brands that are already successful in s-commerce understand their audience well and create appealing content for them that they find valuable and useful. In particular, research has found that millennials and Generation Z users are great segments for social commerce. Considering that 18–34 year-olds are heavy users of social networks, they are willing to make purchases while they navigate (McLachlan, 2022). Finally social commerce can also benefit from an automated consumer service, by implementing AI chatbots that can answer common questions and issues. In this manner, potential and current customers may be served 24/7 (McLachlan, 2022).

1.2.3

Live Broadcasting Commerce

Another form of social commerce is live-streaming commerce. The concept refers to conducting e-commerce activities and transactions through a live-streaming platform. In other words, during this live “event”, there is a virtual space for users to interact, consume the content, and place orders within the same system (Wang et al., 2022). Further, it provides a real-time interaction, entertainment, and social activities between the users and the streamer. By integrating live streaming into e-commerce, the shopping experience becomes more interactive and in real time. Today, this experience is intended to make a shift from a traditional product-oriented shopping environment to a more social and consumer-centered environment (Xu et al., 2020). In fact, live broadcasting commerce has been described as the future of e-commerce, and is expected to generate 35 billion dollars in sales by 2024 (Molenaa, 2023). Usually, the brand, or a brand’s spokesperson (key opinion leader, bloggers, or influencers) can create a live-streaming event in which they present or endorse products. Additionally, such product information is usually presented with the spokesperson’s personal experience and comments about the product, as well as other detailed information in the form of reviews of the quality, packaging, functions, and other tips. The nature of live streaming commerce allows users to obtain insightful information about the product, but also to engage with the spokesperson to ask questions or tips and ultimately develop relationships with streamers in real time. Further, live streaming commerce enables sellers to personalize and exchange product information based on consumers’ needs, as well as provide customer service in real time. There are many live shopping platforms that sellers can use to stream content to users. The traditional apps are embedded in popular social networking sites such as Facebook Live Shopping, Instagram Live Shopping, and YouTube Live, but other platforms such as Amazon Live, CommentSold, Grip, GoLive, Bambuster, NTWRK, among others (Molenaa, 2023). In particular and depending on the platform in which the live streaming is created, this strategy allows consumers to (a) view all products on sale when they watch the live streams, (b) send messages to streamers, (c) enter the seller’s website without leaving the live streams, (d) place orders during the live streams (Wang et al., 2022).

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Live streaming commerce is a new business model that has not been fully explored by academics or companies. However, there are few recent studies that attempt to understand the effects of such a strategy on purchase intention, engagement, and value. For example, recent studies have found that by using live-streaming commerce, consumers increase online purchase intention and also reduce psychological distance and perceived uncertainty about the product (Lu & Chen, 2021; Zheng et al., 2019). Additionally, it has been identified that live-streaming commerce provides the user with a hybrid of social, commercial hedonic scenarios that trigger more consumer participation, consumption, and social behaviors (Xu et al., 2020). Such effects can be achieved due to the fact that live-streaming commerce enhances consumer’s trust through its live interactivity, visibility, and personalization (Zhang et al., 2022). From a consumer’s perspective, research has found that users obtain four motivations while using live-streaming commerce, which are the enjoyment of interaction, substitutability of personal examination (i.e., the ability to substitute the absence of sensory inputs without touching a physical product), need for community and trend setting (Cai & Wohn, 2019). Further, all research agrees that there is a need to obtain a deeper understanding of Internet consumer behavior when interacting with live-streaming commerce, as today companies using this strategy are experiencing different levels of success (Wongkitrungrueng et al., 2020). Overall, in this new shopping environment, users are attracted and entertained by the content generated in real time, thus they can absorb product information and recommendations in a natural way.

1.2.4

E-commerce with Extended Reality (XR) Technologies

As e-commerce considers doing business using technology, it is just normal that e-commerce practices and business models evolve as technology changes. Today, Extended Reality (XR) technologies such as augmented reality (AR) and virtual reality (VR) are getting more and more attention from both companies and consumers. Such technologies are said to be able to provide enhanced consumer experiences as they mirror those experienced in physical stores. On one hand, AR introduces virtual elements into the physical world, by overlaying virtual content but does not allow users to interact with the 3D Environment. Recently, the term “Augmented Reality Marketing” has been discussed in the literature, by considering it as a novel, strategic, and potentially disruptive subdiscipline in marketing, that goes beyond being just a promotional tool for sales (Rauschnabel et al., 2022). On the other hand, VR creates an entirely new virtual world, in which users immerse themselves and interact with objects and others, this is usually achieved by using a head-mounted display (Barnes, 2016). In the e-commerce world, both technologies are being used to enhance consumer experience. For example, users can take a virtual tour around a digital store, see and manipulate online products, and even try them on virtually.

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Regarding augmented reality, there are many examples of brands that have incorporated it into their online shopping experience. For example, Ikea with its Studio app, allows users to place virtual furniture in their homes by using the smartphone camera. Bher, uses a similar approach, as customers can see how their rooms may look like with different colors of paint. Another example is Gucci, as being one of the first luxury brands to incorporate AR into their strategies. Gucci’s app allows customers to “try on” Snickers, giving them a visual representation of how the product will look on them in real life. During the pandemic, several industries suffered more than others due to the lockdown restrictions imposed by governments. For example, the tourism sector practically stopped completely for many months, and VR became relevant, particularly for this industry. The term “VR travel” refers to a mode of travel that offers tourists the virtual experience of traveling using computer technology, with immersive, realistic and participation of virtual travelers. These experiences take place through VR apps such as Oculus, Google Cardboard, or PlayStation. During the COVID-19 pandemic, VR travel became relevant, as an alternative to actual travel. Research on the topic found that during lockdowns, users were willing to use VR for “traveling purposes”, as the intent to attend in-person to such travel sites decreased significantly. Literature shows that people reported enjoyment, ease of use, usefulness, and substitutability of VR tourism during the coronavirus pandemic (Schiopu et al., 2021). Additionally, such perceptions and openness to use VR travel has been reported to continue to prevail after the COVID-19 pandemic (Sarkady et al., 2021). This was confirmed by XX, where findings of their research revealed that consumers express intentions to continue using VR travel to fulfill their travel lust even after the pandemic was over (Talwar et al., 2022). This can be capitalized, by developing unique VR experiences that offer an immersive experience. Additionally, elements of gamification can be incorporated into such experiences in a way users may become more loyal. Overall, extended reality (XR) technologies represent an opportunity for marketers to promote consumers with a more realistic experience of a service, product, or place, without necessarily being physically present.

1.3 Demand for Online Services 1.3.1

Education and Work

In the light of the pandemic, the education sector had to respond and innovate quickly. Online learning became, in many cases, the only option to continue their programs. People from all generations had to embrace online learning and adapt to the situation. Despite some of its disadvantages, like the lack of face-to-face interaction between students and teachers, online learning brought to the table some interesting advantages. One of the most important advantages is the flexibility that this method comes with. Research has shown that people engaged in online learning value the ability

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to learn from home, the freedom to learn at their own pace, collaboration, and the overall flexibility of online classes. Schools and universities around the world had to quickly adapt to the situation and in many cases invest important resources to enhance or introduce new technologies and programs to make online learning possible. Therefore, it is expected that after the pandemic the traditional education model for many educational institutions suffered some changes. Students around the world have faced a generalized change in attitudes and perceptions towards learning. In fact, a recent survey found that 68% of students are interested in a combination of in-person and online education (Forbes, 2021). Furthermore, a report on the future of learning published in 2022, identified some opportunities and changes for online learning. First, new models of education where students can get their learning in different places. Second, an approach where students can build their own program or degree by selecting courses based on their interests. Third, a continued optimization of courses for online learning and mobile devices, and finally, the application and incorporation of new digital technologies such as virtual and augmented reality, and artificial intelligence (Fran, 2022). With these changes in demand for online education, it also comes new opportunities for education providers. For example, there are many non-degree learning courses in high-demand areas that are creating a new category in the education sector. An increasing number of students prefer to obtain high-demand skills rather than a traditional degree (Diaz-Infante et al., 2022). Online education has changed dramatically because of the coronavirus pandemic and many changes in this industry are here to stay. Schools and universities around the world can rethink their traditional physical programs into a more distinctive learning and personalized experience, as well as to include cost-effective, highdemand courses to complete and compete in the online education space. Along with online learning, many jobs were also translated into the digital world during the pandemic. As expected, COVID-19 accelerated change in organizations. Remote, online, and home working became the option for organizations to continue operating during lockdowns and social distance recommendations. Today, more than three years from that moment, many workplaces have faced changes that can no longer be reversed. New ways of working have been adopted, allowing employees more flexibility and better control of their work and personal time. Research has shown that physical presence in a workplace is no longer relevant, as remote work brings several advantages to the table (Ajzen, 2021). In fact, this model of hybrid or remote work seems to increase productivity due to digital tools (Papagiannidis & Marikyan, 2020; Zapata-Cantú et al., 2023). Furthermore, when organizations provide their employees with autonomy, flexibility, and high use of digital technologies, they can improve engagement and productivity at work (Zapata-Cantú et al., 2023). For these reasons, the scenario post-pandemic envisions a workplace that can maintain a culture where most of the employees are virtually distributed. This brings opportunities but also challenges to organizations. For example, during the pandemic, the “Zoom fatigue” phenomenon, caused by spending too much time on Zoom virtual

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meetings can be evidence that there needs to be a balance in technology use. Additionally, remote work has also blurred the line between work time and personal time, increasing psychological and emotional work demands (Chan et al., 2023). Moreover, how to form and maintain a specific organizational culture, in this new virtual online environment. Research on the topic is scant and needed to understand the new context of virtual work. Particularly it has highlighted that the future of work is virtual, collaborative, autonomous, auto-motivated, and meaningful (Malhotra, 2021). In sum, changes in the way people use technology to work have prevailed since the pandemic, and organizations should rethink their physical and virtual workplaces. Research is needed to explore the impacts of different scenarios of online and physical work (Babapour Chafi et al., 2022). Other combinations of variables should be studied such as flexibility, autonomy, and work–life balance, and how they impact performance, engagement, well-being, and motivation.

1.3.2

Streaming Services

While the coronavirus pandemic kept people in their homes, the traditional movie industry suffered from the fact that cinemas and movie theaters had to temporarily close. For this reason, video streaming applications such as Netflix, Disney+, Apple TV, Hulu, Amazon Prime, HBO Max, among others, were the perfect substitutes for people at these times. Before the pandemic, streaming services were rising at an organic pace, being the early adopters and fast followers users as the main audiences, keeping them as a niche add-on for traditional TV (Luo, 2020). However, during the pandemic, many video streaming applications reported outstanding growth in terms of subscribers and number of minutes streamed. In fact, reports find that the consumption of video streaming through multiple devices rose week after week in March 2020 (Nielsen, 2020). Particularly, Netflix reported to double its projected number of new subscribers since the pandemic began in 2020, and Disney+ increased its subscribers by 22 million. On the other, streaming services on demand like Amazon Prime, also reported an increase in revenue as users can see some content for free but they also can rent or buy other types of content. Not only the number of subscribers and time spent changed during the pandemic, but also the hours in which people consumed such content. More specifically, there was an interesting increase in the early afternoon hours (1–4 P.M.), as before the pandemic, adults would normally be outside of their homes during such hours. Furthermore, the increase in consumption of content from streaming services rose for all age groups, being the younger users (age 2–17) the group that reported the largest growth (Nielsen, 2020). In 2020, these increases were looking good for popular streaming services, however, it was also expected that after lockdowns ended, people would normally decrease the time spent on TV usage. In the past, several events have prevented people from going out of their homes, such as the New Tork blizzard in 2026 and Hurricane Harvey in 2027, and research found that the total TV usage rate increased by 50%, but returned to normal when the situation ended (Luo, 2020).

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Today, now that most activities have returned to normal, streaming is still heading to a bright future. After these three years of pandemic, people are now more used to using streaming services as the main distribution platform and delivery method for content in homes (Jia, 2022). Further, now that there are so many options and less time available to be at home, price becomes more important for users. Additionally, main players are rethinking their search and recommendation algorithms, which can be the difference in the time users spent on streaming, if they receive the appropriate recommendation for the next movie, video, or song (Jia, 2022). There have been some studies that analyze the particular cases of each streaming service to understand what people like and dislike about them, and how these variables affect usage, time spent and engagement. However, it is still the right time to continue the discussion of what is happening after covid-19 pandemic in terms of usage and consumer behavior around these services. For example, understand the motivations of users who ended some subscriptions after the pandemic. Additionally, what factors impact them to choose from the numerous options available? As of 2023, numbers show that the market share is very competitive and changing by the minute. Netflix, for example, declined its US market share 6% in the first quarter of the year. Overall, the entire industry shows a downward trend from June 2022 to March 2023 (Pandey, 2023).

1.3.3

Food Delivery Apps

Food delivery apps reported an important growth and adoption during the coronavirus pandemic. These apps benefited from the contactless delivery option in times when social distancing was very important. Furthermore, the delivery apps were an opportunity for the restaurant sector to maintain operations while people could not attend physically. Today, restaurants are keeping these options as a form to increase revenue without increasing their seating capacities (Tandon et al., 2021). There was an important segment of consumers that had not tried delivery apps for several reasons, such as fear of loss of personal data, lack of knowledge, and general distrust. However, the conditions of the context made it appropriate to try them for the first time (Barrios et al., 2021). As expected, food delivery apps experienced important growth during the early stages of the pandemic, however, such growth was not expected to continue in a post-pandemic scenario (Wile, 2022). With this decline in usage now that people have returned to normal routines, it becomes important to research the topic to better understand why consumers could use such services, and what strategies work best for delivery apps. In the past, research about the use of delivery apps has been addressed in the literature. More specifically, researchers have been trying to understand what are the determinants that affect customers’ use of delivery apps. Some variables have been mentioned as important, such as the system quality and the information shared by the company and other app users. Further, both system quality and design quality of the delivery app, have been suggested to impact the perceived ease of use, which ultimately affects the attitude

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towards the use of these apps (Lee et al., 2017). Other studies have addressed the consumer’s decision-making process and intentions to use delivery apps, the role of consumer’s attitudes towards adoption, as well as intentions, usage motivations, and gratifications of delivery apps use (Kaur et al., 2021; Ray et al., 2019; Tandon et al., 2021). Particularly, the literature suggests that people use delivery apps because it is convenient and easy to use, as well as for other factors such as societal pressure, good customer and delivery experience, search for restaurants, quality control, and listing (Ray et al., 2019). Today, the adoption of technological solutions for online services as well as physical restaurants has prevailed after the pandemic. Not only the adoption of online ordering systems and delivery apps, but also contactless payments, online table reservation systems, digital menu boards for kitchen staff, access to menus online via QR codes, and others (De Souza et al., 2022). What the future holds for food delivery apps is definitely shaped by how the pandemic naturally changed how people consume products and buy food. As delivery apps focus on a convenient, easy-to-use, and safe experience they can survive this competitive and difficult market. Further, it is important to place consumer’s needs in the center of such a business model, in which delivery apps companies partner with restaurants and vendors, to innovate in service, prices, and loyalty programs or gamification strategies to increase consumer’s perceived value.

1.3.4

Social Media

Social media has kept on growing in the number of users in an unprecedented manner. In the Digital Global Statshot of 2020, DataReportal confirmed that the social media users grew 10% over the past year. This percentage means that over 3.96 billion people are active on social networks, which makes it more than half of the world’s population. The report also mentioned that an average of around 1 million people started using social media for the first time every day in 2020 which has made it an average of 12 new users per second (Kemp, 2020). Further, Statista reports show that in the U.S. users spent 65 min daily using social media during the first year of the pandemic, and the social media platform that experienced the most growth during 2020, was TikTok, followed by Facebook and Twitter (Statista, 2022). Furthermore, the exponential use of social media means that it was used as a major source of public information, which in turn influenced other behaviors and interactions. Particularly during the early stages of the coronavirus pandemic, social media was widely used to share information about the unknown virus at that time, as well as the steps or recommendations to maintain safety. In other words, social media platforms such as Facebook, Twitter, and Instagram were crucial in communicating the reasons for quarantine, providing reassurance, and sharing practical advice to address the situation (Saud et al., 2020). Additionally, research has shown that social media was used during the pandemic to seek social support, maintain communication with family and friends, obtain information for medical treatments, find innovative ways

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to stay entertained at home, and overall share experiences during the lockdown and quarantine time (Saud et al., 2020). A survey conducted in the United States in 2020 showed that socializing with friends and family virtually was one of the main reasons for using social media during the pandemic (Statista, 2022). As social media has become an important tool to obtain information and guidance, there are also negative outcomes of such increased use. One of the most important challenges faced over the pandemic is the misinformation, along with rumors and panic, shared through social media platforms. Additionally, the increased use of social media is also linked to a global crisis in mental health. In fact, there have been studies that addressed social media addiction or pathological use of social media, as well as the outcomes and consequences of such use (Treviño et al., forthcoming). Particularly, younger generations such as Gen Z and Millennials tend to be at higher risk of developing social media addiction, as most of them are high users being active on an average of five digital social media platforms every day (Williams, 2022). Today, the challenge is to better understand the advantages and disadvantages of this unprecedented social media use to increase awareness of the potential risks in order to use them in a beneficial way.

2 Methodology The present research adopts a quantitative-descriptive methodology to analyze some patterns around the digital consumer. Questions were framed to understand how consumers buy online, their devices, payment methods, and preferred shopping categories. Further, their behavior on social media was also analyzed, in order to learn about the popular social media sites, they actively use, as well as changes in their usage time. Finally, questions were included to analyze the role of social media and influencers in online shopping. In particular, an online survey was distributed through Qualtrics to 290 participants, from which 256 were complete responses. Participants were invited on a convenience and snowball basis, in a northern city in Mexico. All participants belong to medium and high socioeconomic levels and have access to the Internet and online devices. Overall, 65% of participants were female, and 35% of the participants were male. Participants’ ages ranged between 17 and 68 years old, which allowed having a wide vision of several consumer generations. The occupations of the sample were distributed as follows: 64% students, 17% employees, 11% housewives, 4% freelancers, and 4% other occupations.

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3 Results 3.1 Online Shopping Trends Participants were asked about their online shopping habits before, during, and after the pandemic, using a 10-point Likert scale to reflect on the likelihood to buy online. Overall, results show that before 2020, only 10% reported a high or very high level of online shopping (see Fig. 2). These results changed during the pandemic, as between March 2020 and March 2020, 50% of participants reported a high or very high level of online shopping patterns (see Fig. 3). Finally, 24% of participants reported a high or very high level of online shopping today. Such results are consistent with responses from participants, as 46% of them believe that their online purchases have increased in 2023 after the pandemic (see Fig. 4).

Fig. 2 Online purchases before COVID-19

Fig. 3 Online purchases during COVID-19

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Fig. 4 Online purchases after COVID-19

Further, participants were asked about their preferred devices to buy online. In this manner, 52% of respondents prefer to use a laptop or desktop computer, 44% smartphone devices, and only 4% reported using tablets for their online shopping (see Fig. 5). Considering the payment methods, most respondents (90%) prefer to use credit or debit cards directly on the websites of online retailers, and only 7% use PayPal, 3% electronic transfers, and 1% cash payments. No other payment forms were mentioned by participants. Another important data to analyze is regarding the type of purchases that consumers make online (see Fig. 6). One of the most common categories reported Fig. 5 Respondents preferred device for online shopping

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Fig. 6 Online shopping categories by participants

by respondents is clothing items (15%), as well as online content (11%) such as books, movies, music, and other streaming services. Further, participants also buy personal care products (10%) such as makeup, skincare, and others. Shoes (10%), prepared food and beverages through delivery apps (10%), and electronic devices such as computers, tablets and smartphones (8%). Other categories include supermarket items (7%), jewelry and other accessories (6%), sports equipment (6%), travel and trips, which includes hotel reservations, plane tickets, among others (5%), electronic tickets for concerts, cultural and sporting events (5%), pet products (4%), toys and items for children (2%), and finally health services such as online doctors’ appointments or therapies (2%).

3.2 Social Media Trends The second part of the survey was intended to explore trends and habits around consumers and their social media use. As expected, Instagram and WhatsApp are at the top of the list, representing two of the most used social media apps reported by participants, with 25% and 23% respectively. Next, TikTok with 15%, as well as Facebook and YouTube both with 13% each. Pinterest (7%), LinkedIn (3%) and Snapchat (1%) are the least common social media apps used by respondents (see Fig. 7). Furthermore, 100% of participants agree on the fact that their time spent actively using social media apps has increased or increased significantly from 2020 to 2023.

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Fig. 7 Most used social media accounts

More importantly, 75% of respondents in the survey mentioned that the content they see on social media has led to making an online purchase. One popular marketing strategy by brands on social media, is to rely on influencers to make recommendations of their products and gain visibility. On this topic, even though 16% of participants mentioned that they prefer not to follow influencers on their social media accounts, 42% of them agree that they are now following more influencers than before 2020. In a similar manner, participants have also mentioned that after the pandemic, they are “friends” with more brands, in other words, 45% of them are active followers of brands and their online content. With respect to online streaming services, 68% of participants agreed that their time spent on these platforms increased during the pandemic, and 44% have decreased the number of subscriptions after the pandemic was over or are expecting to do so in the near future.

4 Discussion and Conclusion There is no doubt that the COVID-19 pandemic had a profound impact on the way people use the Internet and its applications, both during and after the crisis. The pandemic forced businesses and consumers alike to rely heavily on digital platforms, leading to a significant surge in online shopping and Internet usage across various industries. As discussed earlier, during the pandemic while physical stores were closed or operating under restrictions, e-commerce emerged as a lifeline for businesses to reach their customers and continue surviving in these difficult times. For these reasons, online shopping experienced unprecedented growth as consumers turned to digital

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platforms to meet their needs. This surge in e-commerce was driven by factors such as convenience, the need for contactless transactions and social distancing, and overall safety concerns. Many people had to take advantage of such benefits of e-commerce and try it for the very first time. As discussed in this chapter, the pandemic also accelerated the adoption of new technologies and digital solutions across many industries such as tourism, entertainment, food, education, and the overall workplace. Virtual meetings, remote work, and online learning became the norm worldwide, shifting people’s behavior and openness to new innovative tools and platforms that support virtual communication. More than three years later, as the world and these industries gradually recover from the pandemic, the influence of these online trends is expected to persist in some ways. First, in terms of e-commerce as it has solidified as an important channel for organizations, and even though most businesses showed an expected decline in online sales after the pandemic, many customers are continuing to value the convenience and accessibility of purchasing online. Additionally, the experience gained during the pandemic enabled businesses to recognize the importance of incorporating this channel to reach new customers, as well as focusing on delivering a good online experience to cater to evolving customer preferences. In terms of Internet use, lessons learned from the pandemic demonstrate that there is an important potential to work from home, do remote learning, and incorporate other virtual experiences into people’s daily lives. For these reasons, many companies today are maintaining online or hybrid work models, and rethinking their work arrangements, as they recognize that people have also evolved as employees. In education, universities and other educational institutions have recognized that students now value time, flexibility, and practical skills. Therefore, there is an evolution in the program types and delivery modes, incorporating or maintaining online learning components into many curriculums. Overall, these trends in Internet and digital tools usage may indicate that they will play a central role in different aspects of people’s everyday lives, even after the pandemic is over. Based on results from both the literature review and the exploratory study from this chapter, it was possible to understand some of the impacts that these trends have had on people (see Table 1). As expected, some positive outcomes have been accomplished, such as people being more open to digital tools in general and online purchasing in particular. With these new experiences, people have increased trust in different online payment methods and marketplaces, valuing their convenience and ease of use. This shift allowed people to discover the benefits of a wide range of products and services available at their fingertips. Online shopping also provided opportunities for small businesses and entrepreneurs to reach a broader customer base, fostering economic growth and innovation. In the future, it is expected that companies will incorporate other forms of technology into their e-commerce experience, as discussed previously in this chapter, social commerce, or live streaming commerce. Moreover, new forms of entertainment emerged, such as the consumption of more online content, live streaming, and subscriptions to streaming services or apps. Additionally, increased Internet usage led to the discovery of new forms of

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Table 1 Positive and negative impacts of online trends post-pandemic Positive impacts

Negative impacts

Learn to buy online or increase online purchases Increased time on social media, streaming services, and lack of self-control New forms of entertainment • Online content • Live streaming • Streaming services or apps

Less attention and concentration on important activities

New forms to learn about products, services, and Dependency and emotional attachment to brands devices and social media • Social media • Influencers/videos • Live streaming Increased trust in online payments and marketplaces

Less in-person socialization (video calls and messages are preferred in many cases)

entertainment. Platforms such as streaming services, online gaming, and virtual events became popular alternatives to traditional sources of entertainment that were temporarily unavailable during the pandemic. These digital platforms provided individuals with diverse options for leisure and cultural experiences, contributing to a sense of connection and enjoyment even while physically distant. Because the marketplace on streaming services is complicated and very competitive, today the challenge is for companies in this industry to deliver value to consumers, as naturally time spent at home has reduced significantly now that the pandemic is over. Finally, all these practices have also brought opportunities for companies to find new ways to communicate about their products, services, and brands. Online reviews, ratings, and user feedback allowed individuals to make informed decisions and gain insights into the quality and value of various offerings. The increased Internet usage during the pandemic has also brought several negative impacts to individuals. One significant consequence of heightened Internet usage is the excessive time spent on social media platforms. With limited social interactions in person, individuals turned to social media as a means of connection and entertainment. However, prolonged exposure to social media can lead to decreased productivity, procrastination, and negative impacts on mental health. Furthermore, the rise of streaming services during the pandemic has contributed to a decrease in attention and concentration on essential activities. Binge-watching TV shows and movies for extended periods can lead to a neglect of responsibilities, such as work, studies, and personal relationships. Increased Internet usage has also fostered a dependency and emotional attachment to devices and social media platforms. The constant need to stay connected, be updated, and seek validation through likes, comments, and followers can create a cycle of reliance and addiction. This dependency can have adverse effects on mental well-being, self-esteem, and overall satisfaction with life. It can also lead to sleep disturbances, as individuals often find

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it challenging to disconnect from their devices and experience a constant stream of notifications. Overall, the negative impacts of increased Internet usage during the pandemic are evident in various aspects of individuals’ lives. Recognizing these negative consequences is crucial in promoting a healthier balance between online and offline activities and fostering a more mindful and intentional use of the Internet in the future.

4.1 Challenges and Opportunities The topics discussed in this chapter have several managerial and theoretical challenges and opportunities. First, from a practical perspective, organizations should focus on these e-commerce shifts, as they need to recognize the importance of such practices and invest in building better online platforms that deliver user-friendly and personalized experiences. Further, overall digital marketing strategies should target customers that are spending more and more time online and on social media, however, online content should always be relevant and valuable for the intended audience. Finally, the increased Internet usage provides companies with the opportunity to access important customer data and learn about their audiences. It is important to focus on understanding preferences, behavior patterns, and trends to better develop marketing strategies. From the theoretical perspective, this chapter presents several topics that are truly nascent, as society is living them now; therefore, there is a clear need to continue to be explored by researchers. In particular, this chapter presents findings of a particular sample in northern Mexico making it impossible to generalize the results in other contexts. However, it contrasts such findings with previous research in the literature. Future research can contribute to the discussion on the impacts that online trends have brought in a post-pandemic world. For example, as people are increasingly using the Internet and its tools, it would be interesting to fully capture the challenges of finding balance in this digital world and the implications in their lives. Moreover, what do consumers truly expect in terms of their relationships and exchanges with brands online? Overall, the need for research and insights on the topic represents an opportunity for companies to adapt and respond to the evolving digital landscape, capturing the different impacts of increased Internet usage on society.

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Virtual Teams: An Intelligent Tool on the Path to Digitalization—A Case Study Maria Inês B. Fernandes and Carolina Feliciana Machado

Abstract In a world characterized by deep changes, where concepts such as globalization, internationalization, digitalization, and diversity are gaining more and more strength, contributing to the promotion of high levels of competitiveness, organizations find themselves in need of introducing significant changes in their ways of functioning. Often geographically dispersed, these organizations nevertheless need to ensure their connection. At this level, operating through digital means and information and communication technologies, virtual teams assume themselves as working groups that can be adopted by organizations. Effectively, with the increasing levels of digitalization that have been observed in the different sectors of activity, the option to use virtual teams has become an increasingly common reality within organizations that promote distance work. The path towards the effectiveness of digitalization has, in this way, contributed to these teams being created more efficiently, overcoming temporal and spatial barriers, and making it possible to collaborate and share information and ideas in real time. However, the effectiveness of these teams and, consequently, of these new ways of working, imply adequate management of the organization’s time and resources, as well as the creation of a collaborative and inclusive culture. Based on this reality and these challenges, this chapter, through a case study, seeks to analyze the management practices adopted (in particular, in terms of human resources management), which facilitate the implementation of work in virtual teams, as well as a brief analysis of the literature supporting this issue. Keywords Virtual teams · Digitalization · Information and communication technologies · Working groups · Distance work · Human resource management

M. I. B. Fernandes · C. F. Machado (B) School of Economics and Management, University of Minho, Braga, Portugal e-mail: [email protected] C. F. Machado Interdisciplinary Centre of Social Sciences (CICS.NOVA.UMinho), University of Minho, Braga, Portugal © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 C. Machado and J. P. Davim (eds.), Management for Digital Transformation, Management and Industrial Engineering, https://doi.org/10.1007/978-3-031-42060-3_7

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1 Introduction In the context of diversity, globalization and internationalization, there is often discussion about challenges for human resource management. When revisiting some company cases, it seemed interesting to us to study a company that, although still small, has been growing and hiring people of different nationalities, who speak different languages and with different previous experiences—not because of their sociodemographic characteristics but because of their skills and talent—allowing them to work from home. A large part of its members chose to work remotely, which makes this company, as will be discussed in the literature review that follows, a virtual team. Now, this entails some challenges for management, not only in terms of the organization of work, time or compensation, but also in terms of managing diversity. What we propose is, therefore, to investigate, together with the referred company, the human resources management practices adopted, facilitators of virtual teamwork, and compare with what the literature review refers or suggests. To carry out this work, we opted for the case study methodology, using a structured interview to obtain information regarding the human resources and diversity management practices used by the company. This interview was conducted remotely, using the Google Drive shared documents tool. Some additional information was obtained through later informal contact in order to complement the interview. In this chapter, during the presentation of the case, we will make use of some words of the interviewee, highlighted throughout the narrative. Thus, in the first phase, we will present the case of the company VirtualSmile,1 exposing the practices of informal human resources management, referred to by the interviewee, a partner of the company, collaborating from Portugal, whose identity will remain anonymous. Then we make a brief review of the literature, starting by exploring the various definitions and characterizations of virtual teams, the advantages and disadvantages associated with this form of organization and work, with a subsequent exploration of the challenges and practices of human resource management, namely in with regard to the recruitment and selection of members of virtual teams, communication management, diversity management, training and development, performance evaluation and compensation policies. To conclude, we will discuss the differences and similarities between the performance of VirtualSmile and that suggested by the literature, making some proposals.

1

This is a fictitious name to guarantee anonymity.

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2 Virtual Teams: A Case Study 2.1 The VirtualSmile Case VirtualSmile provides design and development services for pages and web applications and is headquartered in Stockholm, Sweden. It is a micro-enterprise, with 9 effective collaborators—designers and programmers—from seven different nationalities: Sweden, Portugal, Greece, Bulgaria, Slovakia, Dominican Republic and Lithuania. Of these collaborators, three are owner partners with a distribution of 45–45–10%. One of the partners, who was interviewed, works from Portugal in a remote work and home office regime. They have one more employee, on a part-time basis, whose role is to manage the social networks in which the company and its customers are present. In Recruitment and Selection, VirtualSmile “gives primacy to knowledge and skills regardless of location and nationality” and can occur in two ways: (1) they look on online portfolio exposure platforms and contact the designers or programmers they consider to be able to adjust to the needs of the company; (2) place advertisements on the main recruitment platforms in the technology field. In both ways, the company is committed to attracting the best talent and presenting the characteristics that differentiate it from the competition. The possibility of working remotely is a bet by VirtualSmile, so “the entire recruitment and selection process is also done remotely”. It is important to note that this is an activity sector that is currently facing an imbalance between the supply and demand of job candidates—there is more need for hiring than available candidates with the right training and skills. Candidates whose profiles do not suit the company’s needs are eliminated, “the remaining candidates are invited to answer to a small set of questions via e-mail”. Of these, some go on to the selection interview stage, via Skype, conducted by one of the partners according to the training area, in which the characteristics of the function, the job and the remuneration policy are discussed and negotiated. After “discussion and internal determination”, among the partners, a person is selected, to whom is communicated the decision, once again, in a Skype video call. In addition to these tools, it is important to note that the language adopted for communication is English, both internally and with other stakeholders, which is why mastery of English, in terms of understanding, speaking and writing, will always be a mandatory requirement in a process of recruitment and selection. According to the interviewee, there is some concern about integrating and welcoming the new employee who, for a week, has the opportunity to “explore the company’s tools, rules and processes”. A person is appointed responsible for the reception and integration process of the new employee, who provides all the information and tools necessary for the beginning of his functions “including assisting in the configuration of the hardware and software, as well as in the creation of all the necessary accounts (e-mail, intranet , etc.). The details of these processes are also provided in a ‘manual of rules and procedures’”.

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VirtualSmile’s Salary and Remuneration Policy is very simple: “all employees are remunerated according to the remuneration standards practiced in the Swedish industry, regardless of their geographical location”. In other words, it may differ only in terms of form: employees who choose to live in Sweden receive the base salary in full, deducting and having the country’s social benefits. Employees who choose to live outside Sweden receive the tax equivalent. In addition to the base salary, all employees receive benefits and incentives such as “complements for the acquisition of IT material and software, a complement for health care and a monthly allowance for the acquisition of materials or experiences that employees consider beneficial to their professional practice (e.g. books, courses, service subscription, etc.)”. In addition to these practices, the company has been distributing profits over the years in the form of material or services beneficial to carrying out the work. In compliance with Swedish labor law, all employees are entitled to negotiate, on an annual basis, an “upward revision of their remuneration”. Regarding training and development, VirtualSmile does not have a formal training program, but it has personal and professional development practices such as the Personal Development Days: three consecutive days, every six months, in which employees have complete freedom to develop personal projects, “of full authorship and responsibility”. Employees are also “encouraged to inform management whenever they wish to improve their knowledge in a given area”, a need to which the company answers. With employees dispersed across the globe, as already mentioned, the company has to adopt the most effective communication tools possible. In this sense, the company uses remote communication software with chat, audio and video tools and software for internal, project and external management with clients. All employees master these tools after the first week in the office, allowing them to “communicate from a distance in a clear and direct way”. These communication and management tools allow employees to work efficiently and asynchronously, thus respecting different rhythms and ways of working. Employees have “complete freedom to work at the hours they consider most productive, with minor exceptions (e.g. meetings, deadlines, need for synchronous collaboration with other colleagues, etc.)”. In order to monitor performance and productivity, all employees must “properly document their work, explaining at the end of each day everything they worked on that day and clearly indicating what they intend to work on the next day”. Twice a year, the Personal Performance Reviews take place at VirtualSmile, which the interviewee describes as “informal interviews” during which employees “are invited to reflect on their performance, their position in the team, and their plans and future aspirations”. During these interviews, everyone—members, partners and other employees—has the opportunity to give feedback on the work carried out to date (similarly to the 360° feedback), including “praises, suggestions and recommendations (…) criticisms and requests”, later “compiled and evaluated internally”. According to the interviewee, all employees are encouraged to express their opinions freely and “without fear of reprisals” in order to foster mutual trust. The motivation and satisfaction of employees are also issues that the leadership focuses on

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and attaches great importance to, implementing “corrective measures whenever this satisfaction does not meet the standards that the company considers necessary for a healthy work environment” and to long-term sustainability. One of the investments that the company makes in terms of developing cohesion and trust among team members is an annual trip in which all members meet, in a country different from the countries of origin of the members, during which they carry out team-building activities.

3 Theoretical Review 3.1 Virtual Teams: Around the Concept There are, in the literature, several definitions of virtual teams. Some include features of work organization, such as dependence on information and communication technologies and geographic distance (Baptista, 2022; Garro-Abarca et al., 2021; Kauffeld et al., 2022; Hertel et al., 2005; Townsend et al., 1998; Virolainen, 2015). Others include the type of team taking into account the distribution by different time zones, the expansion of boundaries, the stage of the life cycle or the roles of the team members (Bell & Kozlowski, 2002; Morrison-Smith & Ruiz, 2020). Still, on the typology of the team, Cascio and Shurygailo (2003) characterize a virtual team by the number of workplaces and the number of managers involved (Table 1). Own elaboration, based on Cascio and Shurygailo (2003). Haywood (1998) researched with managers of virtual teams which are the main characteristics and the one that prevails is the geographic distance, but they also appeared in their answers: the fact that the members have different work schedules, the matrix structure of the organization or the organization temporary staff on projects, and teams with members from different companies or groups of companies. For Martins et al. (2004) a virtual team is a collective of individuals, interdependent in terms of tasks, who share responsibility for results. For Fisher and Fisher (1997), referred by Lee-Kelley and Sankey (2008), it is also important to take into account the attributes and essential skills of team members, identifying the following: the desire to improve personal performance, having specific technical skills, valuing teamwork, strong problem-solving and decision-making skills. These attributes differentiate members of virtual teams from members of traditional teams when applied to project Table 1 Virtual teams by the number of workplaces and the number of managers involved Number of managers involved One Number of workplaces

Multiple

One

Teleworkers

Matrix teleworkers

Multiple

Remote team

Matrix remote Team

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management, networking, appropriate use of technologies, self-regulation of work, cultural awareness and interpersonal sensitivity. Bell and Kozlowski (2002) draw attention to the fact that many companies with traditional teams, since a few decades ago, share characteristics of virtual teams insofar as their communication has become predominantly through technology. The authors refer, in this sense, that what can distinguish the two types of teams is the degree of virtuality, that is: the extent to which communication is more personal or more at a distance, what is the average geographic distance of team members and the number of different job locations. Thus, a team with “high virtuality” (Hertel et al., 2005, p. 71) is one whose members mostly communicate at a distance, meeting in various geographical points, distant or dispersed across the globe (Bell & Kozlowski, 2002; Gibson & Gibbs, 2006). As already mentioned, this is an increasingly prominent and prevalent reality for organizations around the world and a trend induced by factors such as globalization, technological evolution, the growing technical specialization of workers, changes in communication processes, the increase in acquisitions, mergers and outsourcing, migratory flows, the crises that the world is facing, among others (e.g. Garro-Abarca et al., 2021; Haywood, 1998; Kaufffeld et al., 2022; Lee-Kelley & Sankey, 2008; Townsend et al., 1998).

3.2 Advantages and Disadvantages of Virtual Teams For management, one of the strategic motivations for setting up virtual teams is to be able to combine a set of key skills and specialists that can come from various parts of the globe, without location being a limitation (Hertel et al., 2005; Makarius & Larson, 2017). The option of having one or more teams working remotely has associated advantages and disadvantages, for the individual, for the organization and for society. Hertel et al. (2005) and, more recently, Simpson (2017) gathered an overview of the following advantages: (1) At an individual level, this form of work has the advantages of flexibility (also shared by Großer and Baumöl (2017)), greater motivation and greater power in managing time and responsibilities; (2) At an organizational level, companies have the possibility of producing 24 h a day because they have members in different time zones working at different, and complementary, times, which also allows for greater speed in responding to market demands, the possibility of attracting, and greater connection with suppliers and customers from locations other than the company’s headquarters and reduced expenses with offices and travel; (3) Society also benefits from this way of working, as members of virtual teams can contribute to less prosperous local economies, as there is a greater possibility

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of integrating people with low mobility or other limiting health problems and also insofar as it contributes to the reduction of car traffic and pollution. In addition to these, other advantages are found in the literature associated with a lower probability of the emergence of stereotyped or political attitudes and behaviors, personality conflicts and abuse of power (Ancona & Caldwell, 1992, referred by Kirkman et al. (2002)) and even greater quality in decision-making supported by electronic systems (Gallupe et al., 1991, referred by Kirkman et al. (2002), Acai et al. (2018), Davidaviciene et al. (2020)). Another and no less important advantage is the greater possibility of participation and integration of minorities (McLeod et al., 1997, referred by Kirkman et al. (2002), Lauring and Jonasson (2023)). Hertel et al. (2005), as well as Simpson (2017), also bring together the disadvantages of virtual teams, at three levels: (1) At the individual level, the decrease in social interaction can result in a feeling of isolation and breaks in motivation, long-distance communication increases the probability of interference and misunderstandings and the scalability of conflicts, as well as the probability of ambiguity in the interpretation of papers; (2) At an organizational level, monitoring and supervision are limited to opportunities for virtual interaction, it may take longer to detect failures in productivity, communication and information technology costs may be high and data security may be limited; (3) Society can also suffer losses as working from home reduces social interaction, limiting the concept of community.

3.3 Challenges in Human Resource Management Practices These characteristics are at the same time challenges for management and even when there is no formalized Human Resources Management, it is Human Resources that are involved, being necessary to manage at various levels. For Kirkman et al. (2002) some of the fundamental practices in managing virtual teams relate to clarifying the roles of team members, ensuring the effective use of communication and information technologies and early development of mutual agreements related to forms of teamwork, namely with the creation of a manual containing norms, the mission and the goals to be achieved in a given period. With regard to Recruitment and Selection, for Neuman and Wright (1999) it should be a mandatory requirement that future members of these teams have general task-oriented attributes, such as conscientiousness and integrity, and socio-emotional skills related to teamwork, such as emotional stability, extroversion and agreeableness. Blackburn et al. (2003) added that virtual teams require members who master communication and information technologies, individuals with self-management skills and characteristics such as autonomy, empathy, cultural sensitivity, with selfconfidence and the ability to develop trust in others. Hertel et al. (2005) reinforced the importance of intercultural sensitivity in teams with greater representation of

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nationalities, cultures and languages. Another issue to consider in a recruitment and selection process is the balance between technical skills and interpersonal skills (Ndubuisi et al., 2022; Taras et al., 2022), an issue already addressed by Kirkman et al. (2002), when they highlighted the importance of evaluating each other during the process, for example, through behavioral interviews or “scenario-based questions” (Kirkman et al., 2002, p. 74). One of the authors’ suggestions for recruitment and selection is that the members of the virtual team be involved in the interviews of the new members, initiating the process of socialization and integration, thus making it possible to assess the interpersonal skills of each other and with the secondary effect of reinforcing the importance of everyone’s participation and team cohesion (Kirkman et al., 2002). Communication also plays a central role in the activity and performance of virtual teams (Marlow et al., 2017). Companies with virtual teams use information and communication technologies, such as e-mail, chat rooms or video conferences, as their main communication vehicle (Bell & Kozlowski, 2002). Lee-Kelley and Sankey (2008) speak of a third generation of technology used in these contexts, which represents shared spaces for online work, on the companies’ intranet. Pitts et al. (2012) draw attention to the gaps that can arise in distance communication through technology, namely with regard to non-verbal communication (e.g. facial and body expression), a very important part of human communication and to implicit cues in verbal communication (e.g. tone, hesitations or voice volume), which give us cues and social information. According to Martins et al. (2004), these gaps reduce the quality of communication, which in turn reduces the team’s efficiency (Jarvenpaa & Leidner, 1999), because, in addition to the possibility of misunderstandings or misinterpretations of the shared information, the development of relationships between team members is much slower. One of the ways of managing communication in virtual teams, with a view to its effectiveness and quality, proposed by Pitts et al. (2012) and Chaudhary et al (2022), is to ensure that team members are endowed with Emotional Intelligence. If all members are able to recognize and efficiently express emotions, communication is greatly facilitated and team performance improves. This characteristic can be evaluated and sought in recruitment and selection processes, but also be an integral part of training and development programs, as it is a trainable competence, which allows increasing the knowledge and awareness of individuals and the capacity for self-management, as well as the social and interpersonal awareness within the team. The authors reinforce that, in this way, members of virtual teams will be better able to deal with the challenges that naturally arise in the virtual environment (Pitts et al., 2012). This issue of communication is also related to cultural diversity (Hertel et al., 2005). The aforementioned restrictions can reduce the advantage associated with multicultural teams and those with different backgrounds—a greater probability of creative and innovative results—making it no longer constructive to create virtual teams with these characteristics. Hertel et al. (2005) refer that, when managing teams with great cultural diversity, one should consider the characteristics of each culture that may represent advantages or disadvantages for teamwork, such as the differences

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they identified between more individualistic and more collectivist cultures. On the one hand, individuals from more individualistic cultures are more resistant to isolation, have more confidence and deal better with ambiguous messages. On the other hand, individuals from more collectivist cultures are more predisposed to identify with a group and, despite showing less resistance to isolation, make a greater search for connections within the group to compensate for it. The need for socialization should, according to Kirkman et al. (2002), be evaluated during the recruitment and selection process, for example, through psychological tests. The same authors suggest that in the process of integration and welcoming realistic predictions should be made of expectations related to remote work and in virtual teams. There are also some practices that make it possible to overcome feelings of isolation such as increased contact with clients, and proactive contact with members through leadership and team-building activities. Jarvenpaa and Leidner (1999) were already of the opinion that, in order to manage these differences, specific functions should be established within the team, one of them being cultural interpreter (Gafeire, 1996, referred to by Hertel et al. (2005))— someone explicitly responsible for bridging or filling gaps when difficulties arise in communication between members. The authors state that, as a rule, this happens naturally, but that, if it is not an explicitly assigned task, it can generate misunderstandings, resentments and conflicts between members. Another way of managing cultural diversity in virtual teams is to preventively ensure that all members are endowed with cultural sensitivity, this characteristic being a criterion in the recruitment and selection of new members (Hertel et al., 2005). Differences in the time zones in which members of virtual teams work have their advantages, but one must bear in mind that lags between sharing information, queries and answers between individuals with interdependent tasks can generate stress and misunderstandings, especially if working with strict and short deadlines (Lee-Kelley & Sankey, 2008). Cultural differences also have an impact on each individual’s perception of time and sense of urgency (Velez-Calle et al., 2020). For example, Eastern cultures have a temporal perception based on cyclical events, while the Buddhist conception of time is that it is unlimited and individuals end up tending to demonstrate different rhythms of work. This can generate lags in the way deadlines are faced and have an impact on performance evaluations in which times, rhythms or meeting deadlines are evaluation criteria (Saunders et al., 2008). The authors suggest some ways of managing these differences: creating awareness of them so that everyone understands the rhythms and senses of urgency of colleagues, developing team norms, creating intersubjective views about times, using technology to inform, consult and manage deadlines, ensuring knowledge and understanding of the use of verb tenses in order to reduce uncertainty and increase the sharing of temporal perceptions and adapt the Performance Assessment measures to these possible differences. With regard to Training and Development, what Kirkman et al. (2002), in a study carried out with 65 virtual teams, concluded was that most of them have online training programs for developing skills related to managing meetings with customers,

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problem-solving, decision-making and other processes related to teamwork. Blackburn et al. (2003) suggest that virtual teams have programs available that include training on communication technology and information sharing, group processes and cultural differences. As for technology, it is important that members learn to exploit the potential of technology that allows them to carry out the tasks at hand, manage the team and collaborate virtually, for example through coaching (Blackburn et al., 2003; Edsall & Conrad, 2021). With regard to group processes, the authors suggest that virtual teams receive training on effectively holding meetings in a virtual environment, on problem-solving and decision-making, and refer that consulting firms include modules on challenges and best practices, on building relationships and trust and working in matrix organizations (Blackburn et al., 2003). With regard to culture, the authors reinforce the importance of developing awareness of differences in cultural norms, language and values to overcome cultural barriers, requiring training programs on daily and work habits, communication preferences, as well as such as reducing to writing manuals on roles, cultural issues and potential conflict resolution (Blackburn et al., 2003). They add the importance that some of the training is done face-to-face and in interaction, for better development of more positive and trusting relationships (Blackburn et al., 2003). Evaluating the performance of virtual teams and their members may seem daunting at first, given the distance, but monitoring the work done, individual contributions and the effectiveness of communication is extremely important and advantageous, having an impact not only on compensation but also on planning training and development programs (e.g. Ahenchian & McCormick, 2009; Blackburn et al., 2003). Still at the level of performance management, Topaloglu and Anac (2021), seeking to identify the main factors that affect the performance of the virtual team, concluded that factors such as leadership, knowledge sharing, empowerment, among others, play a fundamental role. With regard to Compensation and Benefits Policies, Lawler (2003) recommends that rewards should be contingent on the achievement of goals, task interdependence, demonstrated autonomy, members’ skills, as well as collective performance since, in this way, promote cooperative behavior and ensure commitment to the company’s strategy.

4 Final Remarks Despite not having a Human Resources Department or a formal Human Resources Management function, VirtualSmile ends up corresponding to some of the practices suggested in the literature. With regard to Recruitment and Selection, the company focuses entirely on the technical skills of candidates. It would be beneficial for the team, as mentioned in the literature, if socio-emotional skills, self-management, autonomy, interpersonal skills and also intercultural sensitivity were considered. It would also be important

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for the partners to involve the other members of the team in order to start the process of integration and welcoming and to make them responsible for the development of trust and cohesion in the team. The fact that the company invests in integration training, namely on communication and information technologies, is extremely positive. We do not have this information, but it would be beneficial for all members to create an Onboarding Manual that would include, in addition to useful information for installing and using the different technological tools, the mission, vision and values that define the company and also, as mentioned in the literature, realistic information about the organization and the way of working, communicating and relating. As for development training, VirtualSmile chooses to give autonomy to its members in choosing training content according to the needs that they identify themselves. On the one hand, this can be advantageous as each member will be better aware of the difficulties they experience in carrying out their work. On the other hand, it may be insufficient as the member may not be aware of the needs of the team as a whole. In addition to the aforementioned, the literature highlights the importance of virtual team development programs including content on cultural diversity, building relationships and trust, communication management, problem solving and decision-making, and other teamwork processes. Considering the cultural and linguistic diversity existing in VirtualSmile, we are of the opinion that these issues should be considered by the partners—since the other members may not feel free to suggest it or may not even be aware of this need. Still, on diversity, the suggestion given in the literature about having a cultural interpreter and making an appeal to raise awareness of the differences between members is of interest for VirtualSmile to manage and maximize the effectiveness of communication. Finally, the fact that they make an annual trip with all the members, shows itself as a conscious effort to break down cultural and relational barriers, to foster trust and group cohesion, issues highlighted in the literature. Aware that much more would have to be done, the truth is that following the practices listed above, the company has been successful, observing a good pace of growth, being in the process of recruiting new members. Finally, it is important to highlight that despite not having a member on the team with training in human resources management or similar areas, each of the partners makes an effort to learn about the best practices, which best fit the team and its strategy, which, largely due to the cultural influence characteristic of the Nordic countries, are very humanistic, flexible and promote tolerance in all management practices.

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Collaboration as an Enabler for Digital Transformation: The Helix Paradigm Estefanía Couñago-Blanco , Nahuel I. Depino-Besada , Marta Ferrer-Serrano , and Lucas López-Manuel

Abstract This chapter illustrates and synthesizes the role inter-organizational collaborations play in industry digitalization (Industry 4.0) by hinging on two of the main theoretical frames that help to understand collaboration processes; the Helix and Networks Paradigms. It also offers empirical evidence through five cases of collaborative European and Regional innovation projects that illustrate how insights from both paradigms can foster digitalization processes. More precisely, we dive into the successes and failures of these cases to unveil not only what strategies managers and firms should engage in but also what issues need to be avoided. This chapter provides both theoretical and practical contributions. Additionally, policymakers, researchers and professionals can also hinge on the examples presented in this chapter to better understand the effects of collaborative networks on innovation and growth. Keywords Collaboration · Digitalization · Digital transformation · Triple Helix · Quadruple Helix · Quintuple Helix · Network · Technology transfer · Industry 4.0

1 Introduction The success of innovations increasingly relies on firms’ ability to go beyond their boundaries (Carayannis & Campbell, 2010; von Hippel, 2005). Collaboration has emerged as a strategic tool for achieving innovation as it allows organizations access to external and critical knowledge (Ferrer-Serrano et al., 2021a, 2021b). Given its strategic potential, academia has focused on knowledge transfer lately. Several pieces of research can be found where collaboration is identified as one of the main determinants of innovation and achieving sustainable competitive advantages (Ferrer-Serrano et al., 2021a, 2021b). E. Couñago-Blanco · N. I. Depino-Besada · L. López-Manuel Department of Business Organisation and Marketing, ECOBAS, University of Vigo, Vigo, Spain M. Ferrer-Serrano (B) Department of Business Management, University of La Rioja, La Rioja, Spain e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 C. Machado and J. P. Davim (eds.), Management for Digital Transformation, Management and Industrial Engineering, https://doi.org/10.1007/978-3-031-42060-3_8

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Such is the importance of collaboration that not only researchers have been attracted to the concept, but also public authorities and industry. Some examples can be found in the press. For example, the European Union appeals for interdisciplinary collaboration in a new funding model calling for scientists from different fields to work together on significant issues that will bring innovations such as viable hydrogen energy infrastructure to the market more quickly.1 Also, in April 2023, The Eindhoven and Tilburg universities co-organized their first start-up night as a sign of a renewed collaboration to breed innovation in the Noord-Brabant region.2 However, although the implementation of digital technologies in manufacturing processes is not different (Szücs, 2018), how the kind of knowledge transfer between the firm and other economic agents impacts digitalization has so far received limited attention. Therefore, the leitmotiv of this chapter is to precisely illustrate and synthesize the role inter-organizational collaborations play in industry digitalization by hinging on two of the main theoretical frames that help to understand collaboration processes; the Helix and Networks Paradigms. To begin with, we start by introducing the Helix (Carayannis & Campbell, 2010) and Network Paradigms (Szücs, 2018). Then, we elaborate on their origins and evolution to build a state-of-the-art literature review. Given their complementarities, we approach them together, creating an integrative perspective. To be sure, while the Helix Paradigm stresses the importance of collaboration between socio-economic agents (i.e., firms, universities, decision-makers and civil society) for innovation, the Network Paradigm brings to the front the fundamental role structure plays in the success of the collaboration network. After building our theoretical frame, we apply it to industry digitalization. For this purpose, we first introduce the concept of digitalization, emphasizing its pivotal role in developing competitive advantages in the context of Industry 4.0 (Popkova et al., 2019; Thrassou et al., 2020). We then frame digitalization as the result of interfirm collaboration by hinging on the Quintuple Helix and Networks Paradigms. This allows us to discuss not only the opportunities but also the challenges of embracing the process of digitalization from a comprehensive perspective. In the last section, we offer empirical evidence that supports the previous theoretical arguments. Specifically, the last section of this chapter presents five cases of collaborative European and regional innovation projects that illustrate how insights from both paradigms can foster digitalization processes. More precisely, we dive into the successes and failures of these cases to unveil not only what strategies managers and firms should engage in but also what issues need to be avoided. This chapter provides both theoretical and practical contributions. On the one hand, from an academic perspective, we discuss the role of inter-organizational collaborations in industry digitalization, focusing on the Innovation Helix and

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More information: https://www.nature.com/articles/d41586-023-01268-7. More information: https://innovationorigins.com/en/collaboration-between-eindhoven-and-til burg-universities-is-vital-for-incubating-innovation-in-the-region/. 2

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Networks Paradigms. Hence, we provide the theoretical foundations for understanding digitalization as the outcome of a collaboration process between organizations and academic, educational, civil or governmental institutions. On the other hand, from a managerial standpoint, we provide practical examples of how inter-organizational collaboration paves the way for successful digitalization and, more generally, economic development. Additionally, policymakers, researchers, and professionals can also hinge on these examples to better understand the effects of collaborative networks on innovation and growth.

2 Collaboration for Technology Transfer 2.1 The Helix Paradigm: From the Triple to the Quintuple Helix The role of collaboration in advancing innovation and economic development has attracted the attention of academics, firms, and public institutions during the past decades (Bogers et al., 2017; Ritala et al., 2023). Consequently, several theoretical and analytical models have been formulated to understand the complexity of innovation ecosystems. This section reviews the evolution of one of them, the helix paradigm. This model has been extended with contributions from different authors, who incorporate new helixes or actors to understand and adapt to the latest current reality more precisely.

2.1.1

The Triple Helix Model: Industry, Universities and Public Institutions

Several authors have paid special attention to the need to create collaborative networks between research centres, industry and public institutions to address the complexity of innovation and technology transfer (Farinha et al., 2016; FerrerSerrano et al., 2021a, 2021b; Li et al., 2018). The main theoretical concept emerging from this debate is the so-called Triple Helix (TH) model, initially developed by Etzkowitz and Leydesdorff, which highlights the importance of the interrelationships between universities, firms and governments, particularly in the context of the knowledge-based economy (Etzkowitz & Leydesdorff, 1995). Etzkowitz and Leydesdorff point out that a basic premise for developing innovation ecosystems is a close and reciprocal collaboration among these three actors. The relationships among them are described in their helix model of innovation, identifying the state, industry and academia as the main actors. In collaborative ecosystems, industry acts as the source of production when government provides regulations, stability and rules of play, and universities are the suppliers of new knowledge and

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technology. The following is a deeper understanding of the role of each of the actors in the generation of innovations.

2.1.2

The Industry as the Ecosystem Innovation Engine

In particular, the industry axis refers to the businesses that make up the business fabric of an ecosystem and are related to the innovation process. In this sense, interfirm cooperation for R&D activities can take different forms: vertical collaboration with customers or suppliers, which facilitates the identification of opportunities, reduces risks related to product innovation (Tsai, 2009) and can help to improve quality or reduce costs as a result of process innovation (Hagedoorn, 1993; LópezManuel et al., 2023); horizontal cooperation also known as coopetition (Khanna et al., 1998), with firms competing in the same sector (Badillo et al., 2017) that allows sharing the risks of developing technological innovations (Miotti & Sachwald, 2003). Thus, collaboration for innovation between firms can bring them mutual benefits or advantages, such as access to knowledge and technological skills, joint creation and diffusion of knowledge, greater efficiency in the use of resources or the exploration of new market opportunities (Hernández-Trasobares & Murillo-Luna, 2020).

2.1.3

Universities as Knowledge Generators

The university axis of the Triple Helix refers to the activity carried out by universities and higher education centres in innovation ecosystems. In recent years, there has been increasing pressure on them to contribute more directly to the generation of wealth, given the need to offer adequate responses in a context of growing economic competitiveness and new development models in which knowledge is a key factor (Etzkowitz & Leydesdorff, 1995). Consequently, over the past two decades, the involvement of academia with industry has grown to the point that universities and R&D centres have been widely recognized as a critical source of knowledge and innovation (Mowery & Sampat, 2004) and have become an important factor in the innovation systems of knowledge-based economies (Badillo et al., 2017). By collaborating with universities, firms can access specialized equipment and infrastructure and work with highly qualified researchers and specialists.

2.1.4

Public Institutions as Innovation Facilitators

Finally, collaboration between public institutions and innovation system actors is a key element that facilitates knowledge sharing and is the only way to enable the development of specific long-term initiatives (Ferrer-Serrano et al., 2021a, 2021b; Gerstlberger, 2004; Novelli et al., 2006). Public institutions, which can be knowledge banks or brokers (von Malmborg, 2004), can influence KT processes and, thus, the

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R&D capacity of a firm or region (Zou & Ghauri, 2008). Freitas and Von Tunzelmann (2008) point out that support to firms for the adoption of innovations can be provided in two ways. On the one hand, by providing financial support (training and research). On the other hand, by developing appropriate structures to provide technological consulting, advice or information to support the diffusion of innovation. These authors also insist that good coordination of the different lines of action of public investment is necessary to achieve the alignment of objectives and knowledge flows between the different actors and, consequently, increase the adoption of innovations by companies.

2.1.5

The Quadruple Helix Model: The Civil Society Role

Arguing that the Triple Helix model is not sufficient for a long-term understanding of innovation systems and wishing to emphasize the importance of integrating the media-based and culture-based perspective of citizens, Carayannis and Campbell (2009) proposed the Quadruple Helix models that added a fourth helix to the innovation system: Civil Society. Park (2014) explained that the “quadruple helix focuses on both top-down government, university, and industry policies and practices as well as bottom-up and mid-level civil society grassroots initiatives and other actions that help to better shape, refine, and make more effective and efficient government, university, and industry policies and practices.” (2014: 204). Thus, a helpful relationship should be created between the user and the company (Arnkil et al., 2010). This proposed interaction allows the industry to become the best interlocutor to understand the real needs of society. Companies can exploit this knowledge to determine whether they can offer solutions to advanced user problems in the same way or even better than those present in the market (Carayannis & Campbell, 2011; Colapinto & Porlezza, 2012). Even at a given time, there will be an interaction between the company and potential users who are not willing to establish a long-term relationship; due to changes in their psychological, sociological and economic status, as well as technological evolution. Therefore, in international and inter-industry markets, the relationships between companies and users must be continuously monitored and cared for, as they are unstable and sensitive to changes. Knowledge of these changes enables companies to develop strategies, find new solutions, and, in short, follow the entire evolutionary process of users’ needs. The basis of this evolution is the company’s ability to respond immediately and take advantage of the potential for change. In short, to manage the development of science and technology and ensure the competitiveness of the environment in which companies operate, there must be compatibility between user needs and the environment itself (Nicotra et al., 2014).

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The Quintuple Helix Model: The Environment Role

The Quintuple Helix visualizes the collective interaction and exchange of knowledge in an innovation ecosystem through five subsystems or helixes: (1) Universities, (2) Industry, (3) Public Institutions, (4) Civil Society and (5) Natural Environment. The Quintuple Helix, the Environment, has referred to the quality of democracy, including innovation systems; international cooperation; bioeconomics; energy platforms; regional ecosystems; smart specialization and living laboratories; climate change, and sustainable development innovation diplomacy. The Quintuple Helix is a model that captures and specializes in the sum of social (societal) interactions and academic exchanges in a state (nation-state) to promote and visualize a system of cooperation of knowledge, know-how and innovation for more sustainable development (Carayannis & Campbell, 2010). Thus, “The Quintuple Helix Model is interdisciplinary and transdisciplinary at the same time: the complexity of the five-helix structure implies that a full analytical understanding of all helixes requires the continuous involvement of the entire disciplinary spectrum, from the natural sciences (for the natural environment) to the social sciences and humanities (for society, democracy and economy)” (Carayannis & Campbell, 2010, p. 62). The aim and interest of the Quintuple Helix is to include the natural environment as a new subsystem for knowledge and innovation models so that “nature” is established as a central and equivalent component of and for knowledge production and innovation. The natural environment is for the process of knowledge production, and the creation of innovation is particularly important because it serves for the preservation, survival and vitalization of humanity and the possible manufacture of new green technologies; humanity, after all, should learn more from nature. In short, it is a theoretical and practical knowledge resource-sharing model based on five social subsystems with “capital” at their disposal to generate and promote sustainable societal development (Carayannis & Campbell, 2010). The discussion on the Quintuple Helix model indicates that striving to promote knowledge as a nugget of knowledge should be considered essential (Carayannis & Formica, 2006), meaning that knowledge is the key to greater sustainability and a new quality of life. Ultimately, enhancing knowledge sharing and the pursuit of knowledge, new know-how and innovations through the Quintuple Helix model can be, or at least offer, a solution to the challenges of sustainable development under the aspect of global warming in the 21st century (Fig. 1).

2.2 The Network Paradigm: The Role of Collaboration Structures for Innovation Inter (between different organizations, institutions or entities) and intra (within an organization, institution or entity) organizational collaboration in order to carry out

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Fig. 1 The Helix paradigm

research and innovation activities have received particular attention in recent years. Several works defend that learning is the most important activity to gain competitiveness in globalized knowledge-based economies (Inkpen & Tsang, 2005; Lundvall, 1992). This is because, in the more recent academic literature, knowledge can be understood as a fundamental business resource (Cunningham & O’Reilly, 2018; Easterby-Smith et al., 2008), especially one whose knowledge sender unit (an entity that researches and creates the innovation subsequently transferring it) belongs to a source external to the knowledge receiver unit (an entity that receives the innovation thanks to collaborating with the knowledge generator) (Inkpen & Tsang, 2005) and, consequently, can generate a sustainable competitive advantage (Easterby-Smith et al., 2008; Szulanski, 1996). Furthermore, scholars have debated how a sender entity that can transfer knowledge to a receiver effectively is more productive than a similar organization with less ability to transfer knowledge flows (Baum & Ingram, 2002). Therefore, according to the arguments put forward by Inkpen and Tsang (2005), when transferred knowledge is external, it can constitute a vital stimulus to achieve organizational and social improvements. As a result of all that has been pointed out, facilitating the dissemination of the knowledge obtained by the knowledge-generating entities has become an essential mission for different institutions as it is crucial to favour national competitiveness and economic growth (Baglieri et al., 2018). This gives rise to what has come to be known as the network paradigm, which has succeeded in increasing interest in understanding the architecture of the network of relationships that is established between different agents and their influence on research and innovation processes

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(Szücs, 2018), especially concerning patterns of knowledge transfer (Bogers et al., 2017). Furthermore, the academic literature accepts the importance of networking that facilitates collaboration between entities to develop different types of innovation (von Hippel, 2005). This is because network members are more exposed to acquiring and absorbing additional knowledge that is potentially valuable in the innovation process. In line with these arguments, research on firm performance has advanced significantly through studies that analyze the networks in which organizations are embedded (Ferrer-Serrano et al., 2021a, 2021b). Specifically, it has been argued that the network occupied by actors, defined by the nature of their relationships, interactions and linkages, may be at least as important as the geographical space within which actors are located and interact (Huggins et al., 2012). Consequently, a context that facilitates and involves different actors in research and innovation activities is essential. This context should be reflected in strategic alliances and collaborative networks that favour research. In conclusion, collaborative initiatives (such as the Horizon Europe strategy) play a fundamental role in creating networks whose ultimate goal is to carry out research and innovation activities to solve challenges posed by industry, academia or governments. In addition to offering researchers the possibility of collaborating with the most brilliant minds in each field in an international context, it stimulates European competitiveness by fostering talent and innovative companies, generating employment and improving the entire population’s quality of life. In short, this strategy contributes to achieving smart, sustainable and inclusive growth.

3 The Helix and Network Paradigms in Industry 4.0 Digitalization Once we have established the theoretical foundations for innovation helix and network paradigms, we delve into how these paradigms can stimulate innovation processes within an Industry 4.0 context. In particular, we deal with the specific need for “going digital” that firms face, highlighting opportunities and challenges derived from collaboration with diverse social subsystems. The concept of Industry 4.0 has shaken the business world, across all industrial sectors (Grybauskas et al., 2022), with its promise of revolutionizing industrial practices through the integration of digital technologies into manufacturing processes (Lasi et al., 2014). The helix and networks paradigms have become increasingly relevant in such context, as they provide insights into the essentiality of substantial intra- and inter-organizational networks and how the different social subsystems contribute to innovation and sustainable development (Carayannis et al., 2012, 2022).

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3.1 Industry 4.0 and the Need for “Going Digital”: A Depiction of the Current Industrial Context and the Importance of Digitalization The fourth industrial revolution entails the integration of digital technologies into manufacturing processes (Popkova et al., 2019). In such a context, the goal is to create smart systems that can operate more autonomously, with minimal human intervention and maximum standardization and efficiency (Zheng et al., 2018). Furthermore, making firms “smarter” without automatizing MUDA––non-value-added activities– –leads to increased efficiency, reduced costs, and improved product quality (Sartal & Vázquez, 2017). Therefore, firms need to create more efficient and effective manufacturing processes by optimizing and automating value-added activities and integrating digital technologies. This allows for real-time monitoring and control of production, enabling manufacturers to make data-driven decisions (Bell & Orzen, 2016). Furthermore, the integration of new technologies and digital processes into manufacturing systems can also increase process sustainability, as it allows for reducing waste and more efficient use of resources (Du & Li, 2019). Thus, going digital has become necessary for firms to optimize their operational performance and keep up with competitors. In fact, Ross et al., (2017) suggests that digitalization that now is perceived as essential “was executed by individual heroes in a variety of creative (but not always optimal) ways”, meaning that the digitalization of processes and activities is now a generalized and valued practice that has not always been optimally applied. In essence, nowadays, digitalizing has become a must, as it allows for greater flexibility and customization in manufacturing (Matalamäki & Joensuu-Salo, 2022) and improved supply chain management (Holmström et al., 2019). Due to digitalization and data obtained, manufacturers can identify patterns and trends that can help them optimize their production processes, reduce waste and innovate in the manufacturing process. This gives manufacturers a competitive advantage by quickly responding to changing customer demands and market trends through more innovative processes (e.g., digital marketing and virtual reality). However, the need for being digital also pressures firms towards engaging with their surroundings; firms need to be eager to seize opportunities derived from constant digital innovation and reduce the risks of competitors surpassing them. Thus, on the one hand, digitalization can be a source of advantages, leading to improved productivity, quality and profitability. However, on the other hand, it can be a source of risks if firms are not prepared to (a) adopt it optimally and (b) interact with stakeholders to keep up with the pace of digital innovation.

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3.2 What is the Specific Link Between Innovation and Digitalization: Some Insights on the Innovation Helix and Networks Paradigms Innovation and digitalization are closely linked in the Industry 4.0 context. Integrating digital technologies into manufacturing processes is a form of innovation itself and creates new opportunities for second-order innovations. Nevertheless, innovation and digitalization require collaboration among different social subsystems (Oh et al., 2016), which can be challenging for organizations. On this, both the networks and helix paradigms emphasize the essentiality of collaboration among the actors that conform to the different social subsystems to stimulate innovation (Oh et al., 2016) and sustainable development. This means that organizations must proactively engage with education, economic, political, civil and natural systems to enhance innovation performance and digitalization. Furthermore, the network paradigm understands organizational phenomena as embedded within a social context (Adner, 2006), suggesting that better contexts lead to higher innovation performance. Complementary helix theorists indicate that the inputs and outputs derived from the interactions of social subsystems are fundamental drivers for innovation (Etzkowitz & Leydesdorff, 1995).

3.3 Insights on Each Subsystem of the Quintuple Helix and Networks Paradigms In the subsequent paragraphs, we provide an overview of each subsystem’s opportunities and challenges for digitalization in Industry 4.0. Finally, we approximate the analysis from a quintuple helix and network perspective, as it allows us to provide insights on inputs and outputs of the (1) education system, (2) economic system, (3) natural environment, (4) civil society (5) and the political system. First, the education system plays a crucial role in industry digitalization by conducting research and development that synergistically impulses the discovery and improvement of technologies and innovations inside and outside the firm. The education system requires inputs from several subsystems, such as public investment, cooperation with firms and human resources from civil society, and supplies from human capital to all the other subsystems. In particular, it provides firms with the necessary knowledge to generate sustainable behaviour through research and the human resources required to take such knowledge into practice. Regarding knowledge obtention, firms can finance research by academic institutions and/or establish partnerships with key academic actors for digitalization. This research can be applied to various industries, and the resulting technologies, can improve efficiency and productivity. As for future workers and innovator formation, synergies and communication channels between business and educational institutions are essential for the more stable and robust development of digitalization.

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A complementary explanation for the firm’s innovation and digitalization is its intra and inter-organizational networks. On the one hand, only if working units within the firm act coordinated and synergistically can they maximize the learning process derived from engaging with the academic in conjunct projects and maximize the benefits of having highly qualified human resources. On the other hand, they need to build bridges with the education system actively; if not, competitors may take advantage of available knowledge, learn faster and generate a competitive advantage threatening the firm. Second, the economic system allows acquiring necessary resources for innovation and sustainable development. Therefore, firms must seek to engage with suppliers, competitors and customers to improve their access to strategic resources (e.g., knowledge) to stimulate innovation. Additionally, the economic system does not work as a playground for individual transactions, but also as a driver of digitalization itself. Therefore, markets oriented toward digital development not only facilitate the creation of new business opportunities derived from digitalization (Casalet & Stezano, 2020; López-Manuel et al., 2020). On their behalf, customers can impulse digitalization processes by demanding firms for customized and virtual services. An excellent example is the renowned case of Netflix and Blockbuster, where the former encountered a competitive advantage in digitalizing well-established renting services. Partners and competitors can drive industry digitalization by constantly pushing the boundaries of what is possible and innovating to stay engaged with allies that demand digitalized processes and ahead of the competition. Two good examples are the competition between Uber and Lyft has led to the development of ride-hailing platforms that have revolutionized the transportation industry and the integration of smart supply chains that BMW partners must undertake to transact with them. However, while new opportunities for innovation are created, challenges arise for firms. They need to be prepared to transform their way of doing business, to prevent penalties and isolation from the social system. Third, the natural environment, which refers to resources, ecosystems, and environmental conditions, is intimately linked to developing and implementing digital technologies and innovation (Carayannis et al., 2012). In particular, this subsystem motivates and depends on implementing green technologies that enhance the environmental performance of firms. In this sense, digitalization can improve the sustainability of industrial processes, but can also negatively impact the natural environment if not properly managed. Therefore, the role of the natural environment subsystem in the digitalization of Industry 4.0 is to ensure that digital technologies are aligned with sustainability goals and do not negatively impact the natural environment. This system, in particular, requires collaboration and communication with and between the academic, industrial and governmental to ensure that the needs and concerns of all stakeholders are addressed. Fourth, the political system, also known as the public sector, can facilitate industry digitalization by providing funding and support for research and development. It can also stimulate good and healthy institutional networks to encourage innovation while monitoring the activities of firms (Carayannis et al., 2012). Thus, firms seek to engage with political organizations and activities to influence policymaking towards more

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favourable conditions for innovation and digitalization. For example, as referenced in the previous section, the European Union’s Horizon 2020 program funds research and development projects focusing on innovation and digital technologies. Moreover, there is a long history of technological advancements generated by governmental institutions with immense implications for the private sector, which means that the public sector is an enhancer and a producer of digital innovation in itself. For instance, the Global Positioning System (GPS) was developed by the United States Department of Defense in the 1970s as a navigation system for the military and now works as the basis of apps like Google Maps. Fifth, civil society can play a role in industry digitalization by advocating policies and practices that promote innovation and digital transformation. Society in itself works as an institutional driver of innovation across all subsystems. In basic, civil society can propagate information through media that pressures or encourages firms toward innovation and sustainable development while exerting social control over a firm’s behaviour (Carayannis & Campbell, 2010). Moreover, the source of human capital nourishes all subsystems (Carayannis et al., 2012). For example, civil society organizations can support digital literacy initiatives to ensure individuals have the skills and knowledge to take advantage of digital technologies. Furthermore, for B2C firms, it is civil society’s will to evaluate the adequacy of their digitalization in processes that are in contact with customers. For instance, the integration of virtual reality in stores and marketing campaigns. In summary, industry digitalization has become mandatory for firms to survive and to achieve sustainable development. It involves the need for synergies among subsystems as this provides fertile ground for innovation. Competitors, academia, the natural environment, the public sector, and civil society are essential in promoting innovation and driving industry digitalization forward. Therefore, considering the insights the Innovation Helix Paradigm provides is fundamental to taking advantage of the synergies that comprehend the environment. By working together and leveraging their strengths, firms and these stakeholders can create more innovative and digitally transformed productive processes (please refer to Sect. 4 of this chapter for real-life success cases).

4 Evidence Numerous examples illustrate how collaborative networks formed by the different actors that make up the Helix and Networks paradigm are fundamental to facilitating knowledge transfer in different environments. Specifically, it is possible to identify several case studies, projects, and initiatives, both public and private, that have implemented these collaborative practices in contexts marked by technology transfer and digitalization. Five of these projects and initiatives that illustrate the practical application of this type of collaboration are detailed below.

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4.1 Cases of Collaboration for Technology Transfer 4.1.1

Case 1: Triple Helix Partnership Initiative

An example of collaboration between the public, private, and academic sectors in the framework of the Triple Helix is the initiative “For an alliance in the Galician industrial sector” (CES, 2017), led by the Economic and Social Council of Galicia (CES) in collaboration with the University of Vigo. Its objective was to channel and strengthen the capacity for dialogue and cooperation between social actors in the autonomous community of Galicia (Spain) to develop a long-term industrial policy that promotes inclusive economic growth in the Galician manufacturing sector. This initiative was executed from January to December in the year 2017. The methodology used to achieve this was participatory. It involved the relevant agents in the sector, i.e., the industrial environment (business and trade union organizations), the academic environment (universities, business schools, technology centres, research institutes and Public Research Bodies) and the public administrations (i.e., Galician Agency for Innovation, CES, or the Galicia Regional Government). The project aimed to bring together all the necessary wills to consolidate the transition of the Galician industrial sector towards an adaptive ecosystem combining the material production of advanced goods and services with the generation of knowledge for innovation. To achieve this, working groups comprised representatives of all the agents who worked in the five thematic areas on which the initiative focused: regulation of framework conditions, competitiveness factors, human capital and labour relations, research and innovation and investment and capital attraction/retention. The result was the elaboration of fifty proposals for action, with their respective monitoring indicators, agreed upon by all the actors involved. These proposals were addressed to the industrial sector in general and, primarily, to the public authorities to provide them with benchmarks that would enable them to conduct their policies effectively. However, despite their careful design and the consensus reached, their successful implementation would require a sustained commitment from all the actors involved.

4.1.2

Case 2: Quadruple Helix Collaboration Project

The CÓDIGOMÁIS project,3 co-financed by the European Regional Development Fund (ERDF) through the Interreg V-A Spain-Portugal Programme (POCTEP) 2014– 2020, represents a step further in terms of stakeholder involvement by including representatives of civil society. This project was implemented between July 2015 and June 2019 to create a Cross-Border Innovation Ecosystem in Health in the GaliciaNorth Portugal Cooperation Area. In this case, the innovation ecosystem allowed the integration of all the actors in the health sector of the indicated regions. Furthermore, 3

More information: http://es.codigomais.eu/.

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it facilitated the meeting and coordination between the innovation promotion policies of the regional administrations, the supply of knowledge and technology from the technology centres and universities, its exploitation in the market by companies and the demand for services by end users. A specific case of its involvement in this project was developing a transversal pilot (covering different health services) focused on managing chronic patients that could contribute, through innovation, to improving the care of this type of pathology. The methodology used was based on principles of social innovation, using techniques such as co-creation among all the actors involved. This technique involves multiple stakeholders’ engagement and interaction to co-create solutions and initiatives, from design to implementation and evaluation (Ramaswamy & Ozcan, 2018; Vargas et al., 2022). Moreover, this technique implies involving patients in their care and treatment decisions and working with healthcare professionals to achieve better health outcomes (Keeling et al., 2021). In this sense, the cross-cutting pilot involved public health authorities (e.g. Galician Health Service, Galician Health Knowledge Agency or Portuguese National Health System), academic and research institutions (Academic Clinical Centre of Braga (2CA-Braga), the University of Vigo and the University of Porto), primary healthcare centres and residential care services (e.g. primary healthcare centres of the Health Area of Vigo or the O Lecer Seniorcare centre), healthcare professionals (doctors, nurses and orderlies), patients and caregivers. The conclusions of the working groups formed by representatives of these agents and, therefore, of the quadruple helix highlighted the need for clear information on the disease to enable health education and more frequent monitoring of patients’ evolution. As a result, two prototypes were developed: a guide for patients with type II diabetes and a scoreboard to facilitate self-management. These tools improve the care of chronic patients while offering innovative solutions in the healthcare field. In addition, the fact that they are designed through co-creation processes facilitates their acceptance by all the actors involved.

4.1.3

Case 3: Quintuple Helix Collaboration Project

Along the same lines as the previous one, but incorporating environmental factors, which place it in the framework of the quintuple helix, would be the MarRisk project,4 co-financed by the European Regional Development Fund ERDF through the Interreg V-A Spain-Portugal Programme (POCTEP) 2014–2020. This study, completed in June 2021, focused on ensuring smart and sustainable growth of the coastal areas of Galicia and Northern Portugal by assessing the most critical coastal risks in a climate change scenario. Its objective was to improve the adaptation of the action area to potential disasters by developing applications and services to ensure a coordinated response. These outputs assist in evaluating the coastal climate’s development, enhancing the accuracy of current analyses, facilitating the implementation of monitoring and surveillance systems and equipping Public Administrations, 4

For more information: https://marnaraia.org/marrisk-2/que-es/.

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the productive sector, and society with decision-making tools to enhance coastal management. One of the main themes of this study is based on the importance of knowledge in implementing effective policies to address climate change and its consequences in the coastal zone. In this sense, the project contributed to creating a set of measures focused on different stakeholders such as policymakers, economic agents, social groups and the scientific community. These measures aim to improve their adaptive capacity and encourage their participation in decision-making to address the adverse effects of climate change. Considering these criteria, one of the practical applications of MarRisk was developing a preventive tool to help the different actors in the sector make decisions on adapting ports to climate change. In this sense, note that the fivefold helix is represented transversally throughout the project insofar as it addresses the great challenge posed by climate change and proposes measures not only for improving the port’s resilience but also for its environmental sustainability. This idea materialized in developing a port resilience index in collaboration with the Outer Harbour of Punta Langosteira (A Coruña, Spain). Specifically, this index assesses operational resilience, understood as the capacity to “make the system capable of absorbing the impact of an event without losing its operational capacity” (Alderson et al., 2015). The tool was developed with the participation of all the port’s stakeholders (representatives of the secondary and tertiary sectors and the political-administrative, academic and social environment). This circumstance has facilitated the formulation and adoption of measures in the port to improve operational resilience and, using simple and easily interpreted indicators, favours their dissemination to society. Furthermore, regarding port and value chain management, the fact that stakeholders are involved in developing the resilience index seems to be a measure that will encourage greater participation of all those involved in improving resilience (León-Mateos et al., 2021).

4.1.4

Case 4: Study of Relationships in the Context of the Network Paradigm

The network paradigm is a perspective that has become very relevant in research and innovation in recent years. Its main objective is to understand the role of the relationships between the different agents involved in research and how these can influence the success of jointly developed projects. An example of the application of the networking paradigm in research can be found in the study entitled “Research in Aragon in the EU context: analysis of the H2020 ecosystem”,5 developed by the University of Zaragoza and funded by the Economic and Social Council of Aragon (CESA). This work pursued a double 5

More information: https://www.aragon.es/documents/20127/29673254/Proyecto-estudio-int egro-analisis-ecosistema-CESA.pdf/6e949d8f-764d-d488-e91a-a72b35abbfeb?t=160388444 9199.

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objective: on the one hand, to analyze the research landscape in the autonomous community of Aragon (Spain) in the European context through the analysis of the Horizon 2020 (H2020) funding strategy. On the other hand, to examine the role of the Triple Helix actors in research using the network analysis tool Kampal Research, assessing their position in the network structure based on their capacity as connectors and mediators between other actors. The results of the study, presented in September 2020 (Latorre-Martínez et al., 2020), showed that the weight of the actors in the innovation ecosystem was asymmetric in terms of their ability to attract resources in the H2020 programme. Research centres obtained the most help, followed by the private sector and higher education institutions, while public institutions received hardly any funding. However, even though the Community of Aragon presents some difficulties for business development and project implementation due to its low population density, the low population density of essential areas and population concentration around the city of Zaragoza, the Aragonese network in H2020 was found to be more cohesive than the European one. This network presented communities that collaborated intensively with each other, although with few relations with other external communities. Based on the above results, the study finds that to design a long-term strategy for research and collaboration in Aragon, five priorities should be focused on: 1. Increasing Aragon’s visibility in H2020, 2. Promoting and facilitating the participation of Aragonese companies in European research programmes, 3. Disseminating and exploiting available information, 4. Seeking opportunities for collaboration between the different agents, and 5. Developing research management policies that retain existing talent. Furthermore, as a practical recommendation, the study suggests the creation of a centralized platform to provide information, dissemination, and advice to those interested in European funding programmes. It also urges the result of a regional office coordinating funding opportunities and organizing events to connect entities interested in establishing cooperative relationships and joint training programmes. Finally, it is proposed that the Aragon European Project Office provide advisory services to companies and connect them with other agents that can complement their needs. These recommendations involve close collaboration between business, research and education organizations, the public and private sector, industry and citizens’ organizations.

4.1.5

Case 5: Collaborative Initiative in the Specific Case of I4.0

Finally, in the specific case of Industry 4.0, as an illustration of successful collaborations in terms of knowledge transfer and solutions to facilitate digitalization, we find the Competence Centres. These centres are a collaborative research initiative to unite the leading players in innovation ecosystems to support companies in implementing

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a more human-centred Industry 4.0 (Ietto et al., 2022). According to these authors, competence centres can be crucial in helping small and medium-sized enterprises (SMEs) implement Industry 4.0 technologies while providing the resources, skills and cultural mindsets necessary for a successful implementation. As an illustrative example, we could point to the MADE I4.0 Competence Centre,6 one of the eight Italian Competence Centres recognized by the European Union formed by a public–private consortium composed of universities, public entities, research facilities and manufacturing companies. It also coordinates the European Digital Innovation Hub of Lombardy, a consortium supporting the digital transformation of industry in the EU. MADE I4.0 aims to lead companies in digital and sustainable transformation (EFFRA, 2023). Accordingly, it provides knowledge, methods and technical and managerial skills in digital technologies to support manufacturing companies, mainly small and medium-sized enterprises (SMEs), in their digital transformation (MADE, 2023). For instance, this support can consist of informing and showcasing Industry 4.0 technologies, explaining them through targeted guidance and training activities and then transferring and implementing technological solutions through projects (Test before investing). To this end, it has a 2,500 m2 pilot production facility for testing, demonstrating, and realizing development projects (EFFRA, 2023). It also has a 4.0 Skills School, a training offer designed to structure training courses for those who want to update or recycle their knowledge. MADE I4.0 also participates in related product and production process innovation projects with partners and collaborative R&I projects funded by European, national, and regional programmes. It disseminates knowledge and best practices in Industry 4.0 (MADE, 2023).

4.2 Conclusions The above examples demonstrate the importance of collaboration between actors to foster technology and knowledge transfer in response to some of the current significant challenges. However, as shown, this requires the representation and implication of all actors involved in the issue to be addressed. In this way, not only will they avoid or minimize opposition to change, but the measures designed will be better tailored to the real needs of the target audiences, thus favouring stakeholder engagement (Keeys & Huemann, 2017). The reason for this is that in addition to mutual trust or clarity in communications, alignment in the objectives and expectations of the parties is a critical factor for successful collaborations (Pugh et al., 2021). Moreover, it is necessary to stress that knowledge sharing should not be limited to a static transmission of information but should be seen as an iterative and dynamic process of knowledge transformation from one actor to another (Scuotto et al., 2020). Similarly, commitment is one of the key aspects for implementing the results of these collaborative projects and initiatives (Fawcett et al., 2021). However, in 6

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many cases, they do not achieve the scope or sustainability for which they were designed. This happens because despite the successful collaboration and generating quality results, it is punctual, and the commitment is not maintained beyond the project. Finally, policy should facilitate regional collaboration to recognize regional differences and promote complementary and intercultural ideas (Barzotto et al., 2020). Within this perspective, learning is a critical mechanism for individual business success. Therefore, a broader ecosystemic perspective that promotes adaptive learning and creates a culture and a strong network of local stakeholders may be an effective approach to improving regional economies (Pugh et al., 2021).

5 Final Remarks There are no problems we cannot solve together, and very few that we can solve by ourselves (Johnson, 1964)

As highlighted by the 36th President of the United States of America, collaboration is key for the development of human activities. In particular, we explained the essentiality of collaboration for organizational activities. First, we illustrated and synthesized the role of inter-organizational collaborations in industry digitalization. Second, we explained the helix and network paradigms, which help to understand collaboration processes, providing a state-of-the-art literature review on the origins and evolution of these paradigms. Third, we emphasized the pivotal role of digitalization in developing competitive advantages in the context of Industry 4, from a helix and network perspective. Finally, we presented five cases of collaborative European and regional innovation projects that illustrate how insights from both paradigms can foster digitalization processes. We offered anecdotal evidence on multiple projects that illustrate a vivid depiction of how cooperation among different stakeholders allows for innovating and going digital in an Industry 4.0 context that asks organizations for dynamism and efficiency. The cases provided here (e.g., MarRisk project) demonstrate that successful collaboration requires the representation and involvement of all actors involved in the issue. Also highlights that mutual trust, clarity in communication, and alignment in objectives and expectations are critical factors for successful collaborations. Overall, we argued on the essentiality of creating strong collaboration networks among diverse social systems (academia, public sector, etc.) for innovation and digitalization. We hope this chapter inspires future research on the mechanisms that allow for creating and maintaining solid collaboration channels among stakeholders.

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Conceptualising Management Practices for Mapping Mobile Phone Waste Through Scientometric, Bibliometric and Visual Analytic Tools Abdulbastwa H. Athuman, Victoria Mahabi, and Ismail W. R. Taifa

Abstract The global boom in the information and communications technology (ICT) industry has exponentially accelerated the usage of mobile phones (MPs). Mobile phone consumers frequently update their MPs to meet the technology demand and keep up with new architectures, capabilities, and innovations, leading to burst volumes of MP waste (MPW). This study explores various MPW management practices. The emphasis is on MPW concepts with a particular focus on consumer knowledge and awareness level regarding MPW, MPW management motivation, consumer attitude and willingness to pay or engage the MPW management move and hindrance factors or limitations towards MPW management habits. The data collection process employed qualitative methods. This study uses visual analytic tools, scientometric and bibliometric, to classify and analyse published articles from Web of Science (WoS) and Scopus databases. R version 4.2.1 software analysed all gathered data. Selected keywords were used to search for relevant articles from Scopus and WoS databases published between January 1981 and June 2022. The results from the search came out with 26510 relevant articles, of which 93 articles were chosen for detailed review regarding e-waste management. The bibliometric results indicate that electronic waste (e-waste), including the MPW publications, started in 2008 and increased intensely from 2016 to 2021, with annual growth rates of 16.99% and 20.58% in WOS and Scopus, respectively. It was revealed that financial incentives are inevitable for the increased collection of MPW. MPs also contain different precious metals worth billions of dollars that require to go for urban mining to be cheaper than virgin mining. The MPW seems to be the current world problem, and India seems to be the leading country in the move towards research for solutions and the status quo of the global MPW. Additionally, MPW contains harmful and toxic materials which are dangerous to the environment and human health. These need special attention A. H. Athuman Department of Informatics and Information Technology, Sokoine University of Agriculture, Morogoro, Tanzania A. H. Athuman · V. Mahabi · I. W. R. Taifa (B) Department of Mechanical and Industrial Engineering, College of Engineering and Technology, University of Dar es Salaam, Dar es Salaam, Tanzania e-mail: [email protected]; [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 C. Machado and J. P. Davim (eds.), Management for Digital Transformation, Management and Industrial Engineering, https://doi.org/10.1007/978-3-031-42060-3_9

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in managing them to protect the environment, which is the focus of many studies to ensure cleaner and greener production of electronic equipment. The study concluded with the conceptualised MPW management approaches. Keywords Mobile phone waste · Obsolete mobile phone · E-waste management · Environmental management · Reverse supply chain management · Visual analytic tools · Scientometric · Bibliometric · WEEE

1 Introduction Due to the significance of information and communication technologies (ICTs) in stimulating the generation of income and economic growth in society, the electrical and electronic industries have recently emerged as the most thriving industries in developing and developed countries (Palvia et al., 2018). The Internet and advanced ICTs have boosted sustainable economic and social development in the 21st century (Zelenika & Pearce, 2013). In this regard, institutions and individuals are largely relying on mobile phones and other ICTs for their social and economic success. Moreover, ICT is treated as a requirement and driver for further innovation and competitiveness in the global economy (Matei & Savulescu, 2012). Because of such potential for individual and social development, the mobile phone industries generate huge volumes of products for consumption by the users; hence, the flow of mobile phones and other ICT products and materials from first-world countries to thirdworld countries, including Tanzania, has substantially increased (Illés & Geeraerts, 2016). Electronic waste (e-waste) is among the quickest growing global waste sources (Islam et al., 2020a). A total volume of 49.8 million metric tonnes was produced in 2018, representing a 4.5% growth rate annually (Yang et al., 2017). Globally, the quantities of mobile phones, as one of the most popular electronic devices, are exponentially increasing. Global mobile phone usage reached 7.74 billion people in 2017, with a penetration rate of more than 100% (Liu et al., 2019). Given the rapid network infrastructure development and the increased use of smartphones, the mobile phone has expanded beyond its primary use as a communication tool (Liu et al., 2019). It has become progressively involved in every part of our life (Liu et al., 2019). Given the shorter product life span and increased production volumes, mobile phones (MPs) have an overwhelmingly big presence in modern life, and the mobile phone wastes (MPWs) generation is rising drastically (in terms of units) (Liu et al., 2019; Wibowo et al., 2022). Mobile phone massive production is pushed by the fast release of gadgets having new features while given their shorter life span drives for disposal hence making the MPWs among the exponentially growing waste stream (Islam & Huda, 2019; Masud et al., 2019; Moletsane & Zuva, 2018). In contrast, many developing countries have not managed the “Waste Electrical and Electronic Equipment (WEEE)” stream; it is thus an increasing environmental

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apprehension (Moletsane & Zuva, 2018; Nnorom & Osibanjo, 2008). Also, inadequate or the absence of regulatory measures or framework on a country level, inadequate infrastructure, illegal imports and partial societal awareness have strengthened such growing apprehension (Moletsane & Zuva, 2018; Nnorom & Osibanjo, 2008). Different studies have identified that most households store their outdated (oldfashioned) mobile phones at home (in a cabin) instead of applying the best practice in managing them (Islam et al., 2020b; Liu et al., 2019; Wibowo et al., 2022). Moreover, the higher value is improved when a used good is processed. Occasionally, delaying gathering and handing out goods makes them impractical, obsolete and even totally unsalvageable. Mobile phone waste and other e-waste products are suited for “urban mining”, as it is more affordable than virgin mineral extraction (Liu et al., 2019). E-waste contains as many as 1000 different substances. Among them are toxic substances, for instance, selenium flame retardants, cadmium, hexavalent chromium, mercury, lead and arsenic, that emit dioxins once burned. In the United States of America (USA), approximately 70% of heavy metals found in landfills originates from E-waste. Also, about forty per cent of the lead found in landfills comes from consumable electronics. These toxins can cause allergic reactions, cancer and brain damage (Jaishankar et al., 2014). Statistically, mobile phone has 20% glass, 23% of metals and 40% of plastic. These metals include copper, gold, palladium and silver (Fornalczyk et al., 2013). To avoid the loss of valuable minerals and rare elements, special treatment of electronic trash (e-waste) must be addressed. Gold and palladium can be recovered more efficiently from e-waste than mining, with fewer environmental consequences. This creates attention on the better methods or strategies for better mobile phone waste management, which is the main goal of this study as well as developing the guidelines for mobile phone waste management. Some studies investigated the e-waste of mobile phones; however, most are limited to exploring potential e-waste generated from EEE or addressing gaps in e-waste legislation (NBS, 2019). Therefore, due to the rapid growth of technology, mobile phone consumers have been motivated to frequently update their mobile phones to meet the technology demand and keep up with new architectures, capabilities and innovations, leading to burst volumes of mobile phone waste. This study thus explores various publications’ current mobile phone waste (MPW) management practices. The study highlights the characteristics and material composition of MPW, the average possession life span of mobile phones and the motivation towards the increased collection of MPW. The rest parts of this study are arranged in the following order. The theoretical orientation is in Sect. 2, whereby this section provides the synopsis of the MPW, composition of MPW, management of MPW and motivation towards the increased collection of MPW. The methodology applied is in Sect. 3, whereby its discussion is based on the inclusion and exclusion criteria, research source of information, the searching process of the literature sources, bibliometric analysis and scientometric analysis. Section 4 illustrates the gathered results and discusses them, whereas the concluding remarks on the MPW, future studies and limitations are in Sect. 5.

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2 Theoretical Orientation 2.1 Overview of MPW There is a rapid growth in global mobile phone (MP) subscriptions (Ericsson, 2022; Liu et al., 2019). The advancement of science and technology contributes to this. Mobile phones have recently been used for general (basic) communication and internet services. This is due to the tremendous technological development of network infrastructure and the mobile phone itself. The MP upgrade pace and the rising penetration rate are highly influencing the rapid global increase in the MPW volume (Islam et al., 2020a). The world is experiencing a rapid penetration of mobile subscriptions of about 106% (Ericsson, 2022; Liu et al., 2019). There are now 6 billion unique mobile subscribers worldwide (Ericsson, 2022). By August 2022, the world reached a record of 8.3 billion mobile phone subscribers, an exponential increase of more than 400 million MP subscribers in just three years from 2019 (Ericsson, 2022). Meanwhile, the 4G subscription has reached 5 billion, while the number of subscribers connected with the 5G network has increased to 690 million (Ericsson, 2022). These phones will eventually be discarded, in whole or in part. On average, the original owner of a mobile phone often replaces it within two years. Compared to 2007, the number of MPWs produced annually increased by about seven times in 2020 (Islam et al., 2020a).

2.2 Composition and Management of a Mobile Phone Waste The typical weight of a mobile phone is between 75 and 100 g having its parts containing almost 40 elements in a periodic table (Islam et al., 2020b; Singh et al., 2018). No matter the manufacturer, a cell phone gadget usually consists of a printed circuit board (PCB), circuits for electronics, a liquid crystal display (LCD), a keyboard, a battery, a plastic or metal case and an antenna (Maragkos et al., 2013). Like other e-wastes, mobile phone waste comprises metals, screens, plastics, metalplastic mix, circuit boards and cables. Depending on the model, type and manufacturer, each mobile phone has a different mix and amount of these materials. Mobile phones contain different precious metals like platinum, cobalt, beryllium, gold, iron, copper, tellurium, lithium, cobalt and palladium, along with other toxic substances like mercury, arsenic, chlorine in Polyvinyl Chloride (PVC) plastics and lead and are all harmful to human and the environment (Andeobu et al., 2021; Islam et al., 2020b). However, Islam et al. (2020b) stated that over 50 earthly components are required to make one MP. According to UNEP (2019), the composition of a mobile phone includes Acrylonitrile Butadiene Styrene-polycarbonate (ABS-PC) (29%), copper and compounds (15%), ceramics (16%), epoxy (9%), iron (3%), silicon plastics (10%), other metals (10%) and other plastics (8%).

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Simultaneously, while technological innovation is moving much more quickly, the product life span is getting shorter, increasing the generation rate of MPWs. The intention and engagement of consumers in the cycle are key components of successful and productive MPW recycling (Ben Yahya et al., 2021). Due to different factors, users sometimes choose to keep obsolete or unwanted mobile phones at the office or home, given their small size, rather than properly discarding them (Ben Yahya et al., 2021; Dimitrakakis et al., 2009; Islam et al., 2020b). We can better motivate consumers to engage in recycling if we know better the factors influencing the hoarding of their mobile phones. Various factors, including technology, attitude, product characteristics, lifestyle, waste management awareness, socio-demographics and societal pressure, might impact this hoarding behaviour (Ben Yahya et al., 2021; Sabbaghi et al., 2015). Without international efforts to combat MPWs, the volume of e-waste is predicted to nearly double by 2050, reaching 120 million tons. It is now below twenty per cent of the globe’s ewaste, which is now recycled (Gill, 2022; UNEP, 2019). In contrast, in 2022, “5.3 billion mobile phones [were estimated to] be thrown away [as per] the international waste electrical and electronic equipment (WEEE) forum says” (Gill, 2022). As per the global trade data, there are predicted increase in environmental problems due to e-waste (Gill, 2022). This is because most mobile users keep old phones rather than recycle them (Gill, 2022). Mobile phones have a complex life cycle which depends on the end users’ decisions. According to Robinson (2009), mobile phones have an average lifetime of about 1–2 years, contributing largely to the total e-waste flow. Figure 1 shows the life cycle of the mobile phone. The mismanaged life cycle may result in a large amount of waste. For example, when customers purchase mobile phones and improperly dispose of outdated phones, this can cause a large amount of waste since the life span of most mobile phones is up to 2 years (Robinson, 2009). Therefore, a proper waste management approach is needed to eliminate the quantities of phone waste. Management of mobile phone waste involves recycling, remanufacturing, repair and reuse and may go beyond that to involve landfill or incineration. Mobile phone recycling involves disassembling and recovering materials (Echegaray & Hansstein, 2017). MPW management may also be termed a reverse supply chain management (RSCM), whereby mobile phone waste is collected from the consumer to the system for either repair, reuse, recycle or remanufacture. RSCM is the efficient and effective management of processes needed to acquire products from a consumer to either recover their value or discard it (Kianpour et al., 2017). RSCM may also be defined “a series of activities implemented to collect products from customers at any stage of the forward supply chain, i.e., reuse, repair, remanufacture, recycling, or disposal” (Ben Yahya et al., 2021). This involves the reverse and forward logistic processes of an electronic device. Due to the costs associated with natural resource exploitation, population increase and environmental improvement, mobile phone manufacturing industries are now forced to collect e-wastes for repair, reuse and recycling through RSCM (Ben Yahya et al., 2021).

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Fig. 1 Typical life cycle of mobile phones. Source Created by authors

2.2.1

Forward Supply Chain Against the Reverse Supply Chain of MPW

When a mobile phone is no longer useful, the production process needs the scraps to be collected and reintegrated to ensure cleaner production. The process is termed a Reverse Supply Chain (RSC). Most companies prefer to opt for RSC for their obsolete products to overcome the challenge of the scarcity of raw materials and their cost of virgin extraction, avoid waste generation and proclaim the move for a green strategy (Ben Yahya et al., 2021). Forward logistics (FL) contemplates the consumers at the end of the supply chain. On the contrary, for reverse logistics (RL), the obsolete product is considered at the customer’s beginning of the supply chain. The RL and FL processes proposed by Ben Yahya et al. (2021) are shown in Table 1. The typical FL processes involve suppliers, manufacturers, distributors (wholesalers, agents, brokers, etc.), retailers and customers (end-customers). The complete FL processes must comprise the RL to consider recycling, remanufacturing, reusing, and repairing. Customers may opt to acquire, collect, inspect and dispose of the product as willing. Similarly, in recycling and remanufacturing processes, some materials can be disposed of as well. This is contrary to the reusability and repair processes. Liu et al. (2019) highlighted three factors determining consumers’ intention to engage in waste management. Such factors for assessing the management of MPW comprise recycling attitude (RA), subjective norms (SNs) and perceived behavioural controls (PBCs). Variables RA, SN and PBCs influence behavioural intuition (BI).

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Table 1 RSC or reverse logistics (RL) processes and activities Activity

Description of the processes

Product acquisition (take-back)

The initial stage for RL activities is the acquisition of obsolete products. Due to inadequate consumer awareness of obsolete device management, this process is considered the most challenging one, as the company needs to apply strategic means to convince consumers to engage in the process by submitting their devices. It is believed that financial incentives play the best to make this possible

Collection

This includes all logistics-related operations (storage, transportation, shipping to the manufacturer, sorting and disposal). The following methods are used: (1) customer-to-manufacturer direct, (2) indirect through retailers, (3) To manufacturer via a third party

Inspection and sorting

The main goal of this stage is to classify the obsolete mobile phone’s quality and determine if they suit for recovery under the RSC method

Disposal and sales

The RSC reselling process is close to the FL process. Goods are new, whereas, in RL, products are renovated or redistributed. The product not fit for recycling will go for disposal

Design for disassembly

This process has to be accomplished via formal channels since the process of dismantling emits poisonous gases

RA is influenced by the perception of negative effects (PNE), environmental responsibility (ER) and environmental sensitivity (ES). PBCs depend on self-abilities (SAs) and recycling convenience (RC), whereby personal influence and group influence lead to SAs (Liu et al., 2019). Attitude refers to a negative or positive feeling, opinion or belief of a person to approve or disapprove of something. At the same time, a behaviour is an action or response to an internal or external stimulus. Furthermore, SNs are the conviction that a prominent person or group (parent, artists, society or peers) will applaud and encourage a specific behaviour. PBCs may be defined as peoples’ perceptions of how difficult it is to perform or enact a certain behaviour. The study concluded that only two factors, BRA and the PBC, significantly contribute to consumer behaviour on mobile phone waste recycling (Liu et al., 2019).

2.3 Motivation Towards the Increased Collection of Mobile Phone Waste Three sources contributing to the enormous MPW generation are the government, institutions, households and businesses (Islam & Huda, 2018). To be environmentally responsible, one must actively work to address environmental problems, including mobile phone waste. Solving the environmental problems is a collective effort, so each needs to be stimulated, inspired and engaged in moving towards the green movement by changing their behaviours. In light of the study’s results by Liu et al. (2019), two main factors influence MPW recycling. Consumer environmental responsibility significantly influenced mobile phone waste’s behavioural recycling attitude

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as the first factor. The second factor was that two attributes influence the perceived behavioural control of the consumer: the recycling convenience and the consumers’ self-ability to engage the MPW management. Their self-ability significantly impacted consumers’ perceived behavioural control to participate in the move and recycling convenience (convenience of the collection facilities). To improve self-ability and consumers’ responsibility, eco-environmental education should be highly considered for consumers’ motivation towards mobile phone disposal (Liu et al., 2019). Mandatory economic incentive measure is also considered an influencing factor for boosting the MPW collection process. When financial incentives are offered at the collection facility, consumers’ willingness to deliver MPW can be highly improved (Islam et al., 2021a, 2021b; Parajuly et al., 2019). Furthermore, the government should introduce mandatory measures to develop formal MPW collection centres or systems.

3 Research Methodology A qualitative methodology was typically used to gather findings from mapping mobile phone waste for conceptualising sustainable mobile phone management practices. This research adopts the five-phase approach for the conceptual paper as suggested by Wolfswinkel and Wilderom (2011) and Maganga and Taifa (2022a, 2022b, 2023). The study used scientometric, visual analytic tools and bibliometrics to categorise and assess mobile phone waste’s theoretical pedestals from Web of Science and Scopus databases. This study defines each journal article, book chapter or conference paper as the unit of analysis.

3.1 Exclusion and Inclusion Criteria To map the mobile phone waste, the research inclusion and exclusion criteria were developed (Islam et al., 2021a, 2021b; Taifa, 2021; Taifa et al., 2020). For the inclusion criteria, according to the research topic, the interval between 1981 and 2022 was chosen because a significant number of published literature related to e-waste emerged in this period. To guarantee a wide range of relevant articles for inclusion, wildcards (i.e., *) and logical operators (i.e., AND, OR) were applied with various keywords, including “waste”, “e-waste”, “e waste”, “E-waste*”, “mobile phone”, “mobile-phone”, “mobile phone waste”and “e-waste-management*”. For the exclusion criteria, this exhaustive review did not include newspapers, books, reports, articles not English, short survey, non-full articles, lecture notes and all irrelevant articles.

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3.2 Research Source of Information The foremost scientific journal databases, i.e., Scopus and WoS database, were used to collect information for mapping mobile phone waste and management practices. WoS and Scopus are believed to be the two most extensive scientific databases covering the latest scientific articles (Islam & Huda, 2018; Islam et al., 2020b).

3.3 Conducting Search We only searched for published content containing the keywords “Mobile phone waste”; however, related stuff such as waste mobile phone, e waste, e-waste management and mobile phone waste management were spotted in the search results. Furthermore, articles from all sources were screened using the same criteria to guarantee that the data and information acquired were accurate and reliable. Figure 2 describes the screening methodology (Taifa et al., 2021). Using the flow depicted in Fig. 2, the keyword e waste initially turned up with 26,516 articles in total. Then, the “e-waste”, “mobile phone”, “Mobile phone waste”and “e-waste-management” keywords were used to find the publications that only addressed MPWs, excluding the articles before 1981 and non-English articles. This reduced the search findings to 276 articles. With the final filter including the most popular publishers and preference document types, the search results ended with 93 articles.

3.4 Bibliometric Analysis The descriptive analysis looked at how papers are distributed by journals, country, year of publication and author’s contribution. This analysis thoroughly reviews the status quo and trends of MPW for the green movement. The R version 4.2.1 software analysed all gathered data.

3.5 Scientometric Analysis The articles under review underwent a content analysis regarding definitions or descriptions. We objectively depicted the study status quo for mobile phone waste.

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Fig. 2 An illustration of the screening methodology. Source Created by the authors

4 Results and Discussion 4.1 Analysis of Bibliometric The bibliometric analysis includes analysing and characterising the accessible theoretical contributions to MPW to reflect the research status quo better and identify the most vital concepts.

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Article Overview

Table 2 summarises the 93 articles reviewed. The title co-occurrence network is depicted in Figs. 3 and 4. The most pertinent sources are given in Figs. 5 and 6. Figure 7 illustrates the source dynamics; the article production country-wise is given in Fig. 8, and the most related words are shown in Figs. 9 and 10. Likewise, the field plot of trending topics is given in Fig. 11. Tree map of the most frequent words is depicted in Fig. 12, while Fig. 13 shows the co-citation network for the publications.

4.1.2

Titles Co-occurrence Network

A node represents a term in a publication’s title or abstract. The node size epitomises the number of publications it has appeared. The nodes are coloured using the legend’s colour scheme and the journal’s average year of occurrence. Nodes that are more closely spaced apart from one another are more similar. The strength of a link between two nodes reveals the possibility that they are published in the same article (Abstract or title). Figures 3 and 4 represent co-occurrence networks WoS and Scopus, respectively.

4.1.3

Most Relevant Sources

Most of the research sources included in this study were published in journals ranked the highest in the top quartile in their respective categories as ranked by CiteScore® in the Scopus database ranking system. The Journal of “Waste Management”, Journal of “Resources, Conservation and Recycling” and the “Journal of Cleaner Production” published a large number of articles relevant to this study (Figs. 5 and 6). The Emerging Sources Citation Index ranked the titles of studies from some other sources in the WoS database. Figure 5 displays the number of publications concerning mobile phone waste. Figure 7 demonstrates the source dynamics in WoS, whereby “Waste Management” and “Resources, Conservation and Recycling” journals indicate that the source dynamics began in 2009 and 2012, respectively. The “Waste Management and Recycling” journal contains articles published in 2008, but its cumulative occurrence has been stagnant. Generally, there has been a drastic increase in publications from 2017 to 2022 (Fig. 7). This is probably due to the global boom in the ICT industry, which has exponentially accelerated mobile phone use, thus resulting in more research. Despite the inclusion criterion for searching the theoretical underpinnings began January 1981–July 2022, the findings (Fig. 7) indicate that mobile phone waste’s publications increased from 2008 to date. This suggests that probably before 2008, there was no significant research performed to document mobile phone wastes.

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Table 2 Some of the key reviewed articles for mobile phone waste Sources

Description

de Jesus et al. (2022)

They assessed the eco-innovation of biodigesters technology, focusing on the implementation for the processing industries of cassava in Parana state and South Brazil

Ocicka et al. (2022)

Explored supply chain partnership for green innovations through the Poland high-tech factory

Darmandieu et al. (2022)

Demonstrated whether it is beneficial to have circular production processes. Their research showed green jobs and eco-innovativeness as mediators of a cost-efficiency benefit in the EU

Sobczak and Głuszczuk (2022)

Focused on the divergence of innovation activity and eco-innovation for SMEs in the EU

Sobczak et al. (2022)

Researched the innovation level and eco-innovation of the economy as the foundation of the EU

Mady et al. (2022)

Looked at how eco-innovation and institutional pressure are the facilitating roles of strategic environmental orientation and green absorptive capacity among SMEs manufacturing firms in Egypt

Munodawafa and Johl (2022)

Their study designed and developed an “eco-innovation management information system” to fast-track companies’ digital transformation strategy

Zheng and Iatridis (2022)

Performed a systematic theoretical background and meta-analysis to demonstrate the association between industry performance and eco-innovation

Rodríguez-González et al. (2022)

Eco-innovation and green strategies affect the automotive industry’s sustainable and financial performance. They considered sustainable supply chains as a facilitating variable in Mexico

Tomala and Urbaniec (2021)

Executed a comparative analysis focusing on eco-innovation development in Asia

Janahi et al. (2021)

Performed a systematic theoretical underpinning on the eco-innovation strategy in manufacturing firms

Tseng et al. (2021)

Investigated the controlling influences of absorptive capacity linking and eco-innovation environmental management systems and strategic orientation (continued)

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Table 2 (continued) Sources

Description

de Jesus et al. (2021)

Highlighted the future of circular innovation studies with the focus being placed on eco-innovation diversity in a circular economy

Isa and Abidin (2021)

Researched the components and drivers for adopting eco-innovation for the contractor industries

Zhang and Gu (2021)

Highlighted and suggested a framework to explore corporate growth status and path and adopt eco-innovations for achieving micro-level green growth

Maˇciulyt˙e-Šniukien˙e and Sekhniashvili (2021) Discussed the eco-innovation effect on environmental and economic performance in the EU Bierwisch et al. (2021)

Designed a workshop idea to develop eco-innovative business models for implementing eco-innovation concepts

Johl and Toha (2021)

Discussed the circular economy viewpoint focusing on the nexus between a firm financial proactive and eco-innovation performance

Arranz et al. (2021)

Explored the influences of internal, market and institutional factors on developing eco-innovation in industries

Pichlak (2021)

Explored dynamic capabilities and leadership as the drivers of technological eco-innovation

Sun and Sun (2021)

Illustrated an attention-based assessment focusing on environmental awareness and eco-innovation for executives

Curado and Mota (2021)

Performed a systematic theoretical underpinning on the sustainability of family companies

Zang et al. (2021)

Studies the influences of manufacturing specialised and expanded agglomeration on the eco-innovation efficiency through a nonlinear test from a dynamic viewpoint

Dec and Masiukiewicz (2021)

Researched socially responsible financial goods as an influence of financial organisations to achieve sustainable development

Wysocki (2021)

Illustrated innovative green inventiveness in the Poland manufacturing firms

Galera-Quiles et al. (2021)

Reviewed exports interrelationship and eco-innovations, referring to international agrifood supply chains (continued)

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Table 2 (continued) Sources

Description

Aryanto et al. (2021)

Used a case study of food SMEs to explore eco-innovation, entrepreneurship orientation, information and communications technology (ICT) learning adoption ability in Indonesia

Louˇcanová et al. (2021)

An integrated viewpoint of brand and eco-innovation mainly to achieve branding and sustainability

Naruetharadhol et al. (2021)

Suggested a model of green management practices and open innovation

Li et al. (2021)

Established drivers that enable the environmental performance in Asia

Sanchez-Planelles et al. (2021)

Established a theoretical framework for corporate sustainability

Halicioglu (2020)

Explored knowledge networks from the ANT viewpoint to establish the linkage between sustainability and eco-innovation in the construction industry

Marín-Vinuesa et al. (2020)

Explored the dynamic competencies and environmental consideration for the circular economy in industries

Maranesi and De Giovanni (2020)

Studies the corporate strategy, supply chain, and industrial symbiosis from the modern circular economy perspective

Fig. 3 Co-occurrence network WoS. Source Created by authors

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Fig. 4 Co-occurrence network scopus. Source Created by authors

Fig. 5 Most relevant sources in WoS. Source Created by the authors

4.1.4

Number of Articles Published Per Country

Figure 8 depicts the breakdown of publications production nationwide, with India leading the race with 44 articles, followed by China and Australia with 21 and 17 articles, respectively. India produces about one-third of all publications regarding

Sources

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Etnografia E Ricerca Qualitativa Ethics and Sustainability in Global Supply Chain… Energy, Ecology and Environment Energies Critical Reviews In Environmental Science And Technology Clean - Soil, Air, Water Business Strategy and The Environment Bioresources and Bioprocessing Biohydrometallurgical Recycling of Metals From… Benchmarking Asia Pacific Journal Of Marketing and Logistics Ain Shams Engineering Journal Acs Sustainable Chemistry And Engineering Acm International Conference Proceeding Series 2020 International Conference on Artificial Intelligence,… Sustainable Production and Consumption Journal of Environmental Management Resources, Conservation and Recycling Waste Management Journal of Cleaner Production Environmental Science and Pollution Research 0

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3

4

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6

7

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9

Number of articles

Fig. 6 Most relevant sources in scopus. Source Created by the authors

Fig. 7 Source dynamics in WoS. Source Created by the authors

electronic waste management. Among 21 countries researched and published globally as per Scopus and WOS, only two countries are from Africa: South Africa (6) and Nigeria (4).

Country

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Bangladesh Pakistan Mexico Colombia Canada Belgium Portugal Poland Netherlands Turkey Sri Lanka Nigeria Iran South Africa Brazil Indonesia 0

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4 Frequency

5

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Fig. 8 Country scientific production. Source Created by the authors

Fig. 9 Word clouds for trending topics. Source Created by the authors

4.1.5

Trending Topics and Most Relevant Words

Mobile phone waste management works of literature on fighting for cleaner production have been given much attention in this era of science, technology and innovation (STI) advancement. Figure 9 depicts a word cloud of the most trending words or topics in the articles published between 2008 and 2022. Four trending words are more visible than others: e-waste, recycling, waste management and waste disposal (Fig. 9). Figure 10 shows the thematic word map for trending topics in the same period. The thematic words trending as per the drawn word map include e-waste, recycling, waste management and waste disposal (Fig. 10). Their nodes illustrate so due to the size of each one. The three-field plot of the trending topics in the same period is shown in Fig. 11. At the same time, the tree map of the most frequent words is depicted in Fig. 12. In all the illustrations, the most trending keyword is electronic

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Fig. 10 Thematic word map for trending topics. Source Created by the authors

Fig. 11 Three field plots of the trending topics. Source Created by the authors

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Fig. 12 Tree map of the most frequent words. Source Created by the authors

Fig. 13 Co-citation network. Source Created by the authors

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waste (e-waste), followed by recycling, waste management, waste disposal and then mobile phone.

4.1.6

Co-citation Network

Mobile phone waste management kinds of literature on fighting for cleaner production has been given much attention in this era of advancement of science, technology and innovation. A co-citation network is a network of the frequency with which two or more articles are cited in tandem with other articles. Figure 13 shows the co-citation network of articles used in this review. From Fig. 13, Sarath et al. (2015) possess a strong co-citation network followed by Nnorom and Osibanjo (2008) and Borthakur and Govind (2019).

4.2 Mobile Phone Waste Management The concept of circular economy in MPW management was discussed in this section. The circular economy concept seeks to ‘design out’ MPW using remarkable materials, procedures and business models. The circular systems’ nature demands a joint effort from governments, businesses and consumers (Parajuly et al., 2020). According to Islam and Huda (2018), a circular economy is a restoration system that minimises resource inflow and waste, energy emission and leakage by slowing down, sealing up, and thinning the material and energy loops. This is accomplished by long-lasting design, reuse, repair, maintenance, refurbishment, recycling and remanufacturing. The graphical explanation of the conceptualised MPW management approaches is given in Fig. 14. The approaches aim to ‘design out’ mobile phone waste by optimising the cycles for products and resources by keeping their value and level of operation at their best using creative business models, cleaner and renewable technology and better policies (Parajuly et al., 2020). Considering Fig. 14, implementing the approaches to ensure sustainable mobile phone waste management is achieved with consideration of six key aspects, namely technology, management, business, users, policy and impacts, which are fully integrated into the process as adopted from a study by Islam et al. (2021a, 2021b). Islam et al. (2021a, 2021b) state that technology is related to finding new materials, being innovative and exploring modern technology-based approaches. Policies should look at WEEE in general, eco-design, Basel convection,1 circular economy and sustainable development goals in line with e-waste. For users, there is a need to study consumer demand growth, behavioural aspects and increase environmental awareness. Thus, when stakeholders can assess the general impacts on the environment and human health would find out that there could be environmental damage,

1

Basel convection meaning can be accessed from https://www.basel.int/ (accessed on 03/07/2023).

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Fig. 14 Conceptualised MPW management approaches. Source Created by the authors

exploitation of resources and the increase of toxicity, which in the long run could result in some diseases, including cancer and brain damage (Jaishankar et al., 2014).

4.3 Discussion The conceptualised theoretical background indicates the increase in MPWs globally. This is due to the global boom in the ICT industry. ICT has exponentially accelerated the usage of mobile phones (MPs). Literature indicates that mobile phone consumers frequently update their MPs to meet the technology demand and keep up with new architectures, capabilities and innovations (Palvia et al., 2018). This leads to burst volumes of mobile phone waste (MPW). A framework, roadmap, guidelines, strategies and/or model are needed to combat e-waste, especially for mobile phones. The population grows exponentially, thus contributing to the increase of mobile phone users. The solutions for the problems should incline to explore various MPW management practices. The emphasis should be tailored to MPW concepts, focusing on consumer knowledge and awareness regarding MPW, MPW management motivation, consumer attitude and willingness to pay or engage the MPW management move and hindrance factors or limitations towards MPW management habits. The commonly referred to as the 5 R’s: “Refuse, Reduce, Reuse, Repurpose, Recycle” should form the basis for the solution of eliminating e-waste. E-waste

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adversely impacts the environment and human health; management practices are thus highly recommended. Among the conventional approaches to eliminate the MPWs problem is reducing, recycling and reusing unwanted equipment. The recycling process comprises informal and formal recycling (Verschaeve, 2014). As per Verschaeve (2014), formal recycling processes are undertaken through controlled conditions where the workforce wears personal protective equipment, while informal recycling seems harmful to health and the environment. For example, informal recycling approaches include burning cables to recover copper materials and acid baths to salvage valuable accessories. It is also noted that there is a worldwide concern regarding e-waste associated with the consequences of inadequate waste management (Galeano & Rodríguez, 2021; Moletsane, 2020). In fact, the association amongst the enhanced advancement of environmental policies, market conditions, economic growth, globalisation and telecommunications, and the negative effect on the environment are of growing focus (Galeano & Rodríguez, 2021). As per Afroz et al. (2020), all countries collectively manufacture “6.1 kg per capita (kg/inch) of electronic waste (e-waste) per year in 2016, compared with 5.8 kg/inch created in 2014.” It was predicted that there would be an increase of e-waste by 2021 to 6.8 kg/inch by 2021 (Galeano & Rodríguez, 2021). Of course, around 400 million mobile phone wastes are generated yearly worldwide (Xu et al., 2016). The accessories of mobile phones and phones themselves are consumed by manufacturers, retailers and service providers. In the United States, manufacturers have some initiatives, including pre-paid postage labels or packets and manufacturer stores’ programs (Xu et al., 2016). The retailers have initiatives to provide free take back at stores, postage-paid envelopes and receive free when buying new phones. The service providers are involved in service provider stores’ programs and prepaid postage labels or envelopes. Thus, professional recycling companies handle the materials and accessories from manufacturers, retailers, and service providers. Recycling companies can refurbish and recycle so as to resale (Xu et al., 2016). The same initiatives can be adapted to the rest of the world in combating e-waste problems.

5 Conclusion 5.1 Concluding Remarks The study investigates the concepts behind contemporary mobile phone waste perceptions to sediment these emerging waste management concepts for sustainable development. This study conducted both scientometric and bibliometric reviews of the mobile phone waste concepts. The review focused on mobile phone waste management, which significantly can improve mobile phone waste management practices. Conclusively, the current mobile phone waste theoretical underpinnings were highlighted in this review. The MPW management concepts were thoroughly reviewed

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to describe mobile phone waste’s characteristics and material composition. Furthermore, the average life span of mobile phones and the motivation towards increasing MPW collection were described. This study explores various publications’ current MPW management practices. Three research issues were explored: characteristics and the material composition of MPW, the average possession life span of mobile phones and the motivation towards the increased collection of MPW. In mapping the mobile phone waste, we gathered and analysed data through the published articles in Table 2. A total of 93 articles were reviewed. The findings show that electronic waste appeared by 13% while e-waste appeared by 3% from all 93 articles reviewed. It appeared for 9% of waste management, whereas recycling is 11%. From 2017 to June 2022, there has been a drastic increase in publications regarding e-waste, mobile phone, e-waste management, MPW and MPW management. Previous reports on mobile phone waste management indicate that many developing countries have not managed well the WEEE stream (Moletsane & Zuva, 2018; Nnorom & Osibanjo, 2008). In fact, less than 20% of mobile phones are recycled, leaving at least 80% being disposed of or kept at homes (stores). WEEE management is thus a growing environmental apprehension (Moletsane & Zuva, 2018; Nnorom & Osibanjo, 2008). Some of the reasons highlighted in literature for not managing e-waste properly include the inadequate or the absence of regulatory measures or framework on a country level; inadequate infrastructure, illegal imports, and partial societal awareness have all strengthened such growing apprehension (Moletsane & Zuva, 2018; Nnorom & Osibanjo, 2008). Various research have identified that most households store their outdated (old-fashioned) mobile phones at home (in a cabin) instead of applying the best practice in managing them (Islam et al., 2020b; Liu et al., 2019; Wibowo et al., 2022). The MPW seems to be the current world problem, and India is the leading country in the move towards research for solutions and the status quo of the global MPW. It was also revealed that financial incentives are inevitable for the increased collection of MPW. Moreover, mobile phones contain different precious metals worth billions of dollars that require to go for urban mining cheaper than virgin mining. MPW also contains harmful and toxic materials that are very dangerous to human and environmental health. These need special attention in managing them to protect the environment, which is the focus of many studies to ensure cleaner and greener production of electronic equipment.

5.2 Implication (Significance) to Practice and Management of MPW In achieving proper management of MPW, priorities should be given to the environmental protection, including proper collection, handling and processing of MPW. MPW has different hazardous compounds that are mostly landfilled, so recycling

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reduces these toxic wastes from causing potential environmental effects. Furthermore, MPW urban mining preserves natural resources, the minerals required for manufacturing a new mobile phone may thus be obtained through MPW recycling rather than virgin mining. Moreover, the MPW management practices create employment opportunities for informal MPW collectors, informal recyclers, and other formal e-waste dealers. Achieving sustainable development goals is among the circular economy’s main agendas (Islam et al., 2020b). Therefore, the discussed findings in this study can contribute to establish robust strategies for MPW collection and recycling in the future.

5.3 Limitations and Future Work The following are some of the limitations of this study. Firstly, the focus of the articles searched for review in the inclusion criteria was published between January 1981 and June 2022, thus leaving other articles probably published before 1981 and after June 2022. Secondly, most of the different e-waste terms in research are used interchangeably. Furthermore, only English-written publications were considered in the review. Lastly, only some common and giant publishers were involved in the inclusion criteria. The current MPW management practices against consumer participation should be considered in future studies.

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Index

A Absorptive capacity, 30–32, 34, 35 Advantages, 27, 29, 31–35, 37, 39, 40, 42, 54, 55 After, 123–126, 130–134, 136, 137, 139, 140 AI applications, 101, 102 AI-based platforms, 105 AI chatbots, 128 AI-generated misinformation, 108 AI harbours, 105 AI lifecycle, 109 AI models, 105, 107–110 AI-powered tools, 105 AI researchers, 109 AI systems, 102, 109 Algorithms, 101, 102, 117, 118 Artificial intelligence (AI), 1, 2, 5, 10, 12–16, 20, 28, 36, 38, 39, 41, 43, 50, 53, 54, 61, 64, 65, 67, 72, 73, 83–86, 95, 101–108, 110, 113, 114, 116–118 Attracting, 61, 62, 64, 67–70, 73, 75, 77, 78 Attraction, 62, 65, 69, 76, 77 Attract talent, 61, 64, 67, 68, 70, 78 Augmented Reality (AR), 84, 129–131 Autonomy, 153, 156, 157

B Behavioral influence, 3 Behavioural Recycling Attitude (BRA), 189 Bibliometric, 183, 185, 190–192, 204 Big data, 1, 5, 63–65, 68, 72, 75, 77, 78 Big data analysis, 11 Big data analytics, 14

Bigger revolution, 104 Blended transversal learning, 44 Blockchain technology, 36 Born-digital companies, 85 Budget constraints, 84 Business, 1–3, 5, 7–13, 16, 17, 20, 21 Business intelligence, 1, 12 Business model, 61–64, 68, 70, 75, 78, 125, 129, 134 Business-performance, 8, 9, 11, 14, 16, 17 Business strategy, 66, 77, 78

C Career models, 67 Challenges, 27–29, 32, 34, 35, 37, 39–44, 49, 51, 53, 55, 83–87, 89, 92, 96, 147, 148, 153, 154, 156 ChatGPT, 101, 104–106, 108, 110, 112, 113, 119 Chat rooms, 154 Circuits for electronics, 186 Circular economy, 195, 196, 202, 206 Civil society role, 165 Cognitive era, 72 Collaboration, 27–33, 37, 39, 42, 44, 47, 49–51, 53, 55, 161–164, 166, 168, 170–178 Collaborative networks, 161, 163, 168, 172 Collaborative work, 69, 70, 73 Commitment, 66, 68, 69, 71 Communication, 101, 112, 115, 117–119 Companies’decision-making, 83 Compensation and benefits policies, 156 Competitive business environment, 110 Computing capabilities, 84

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 C. Machado and J. P. Davim (eds.), Management for Digital Transformation, Management and Industrial Engineering, https://doi.org/10.1007/978-3-031-42060-3

213

214 Conceptualising, 190 Conceptualization, 27, 30, 38 Consequences, 27, 29, 35, 39–41, 52, 55 Consumer attitude, 183, 203 Consumer-centered environment, 128 Consumer dignity, 83, 86 Consumer vulnerability, 84, 86, 87, 92, 94, 96 COVID-19 pandemic, 123, 130, 133, 139 Cultural awareness, 152 Culture, 62, 63, 67, 69, 70, 75, 76, 78 Customer-centric digitalization, 92 Customer service, 84 Cyber-optimistic, 118 Cyber security, 28, 37, 38, 40, 42, 46, 49–51, 84 D Data analytics, 40, 46 Data-driven, 72 Data-driven maritime industry, 44, 45 Data mining, 46 Data privacy, 40, 42, 49, 50, 55, 108 Data storage, 84 Decision-making, 1–5, 7–9, 11–22, 102–104 Decision-making quality, 9, 14, 18, 20, 21 Decision-making skills, 151 Deep changes, 147 Deep learning, 103, 106, 107 Degree of virtuality, 152 Delivery apps, 133, 134, 138 Democratization of technology, 84 3D environment, 129 Deterioration of relationship, 95 Digital, 1, 2, 5, 7–17, 19–21, 61, 62, 64–70, 72, 74–78 Digital age, 62, 64–66, 68, 69, 75–77 Digital communication, 111, 118, 119 Digital context, 62, 75, 78 Digital culture, 68 Digital decade, 28 Digital divide, 40, 49, 51, 52 Digital economy, 41, 42, 55 Digital ecosystems, 36, 38, 42, 55 Digital infrastructures, 27, 28, 40, 42, 50, 54, 55 Digital initiatives, 69 Digital innovation, 169, 172, 177 Digitalization, 1, 2, 8–12, 14, 16–18, 219–22, 27–29, 32, 35–42, 45, 47, 48, 52–55, 84, 85, 92, 147, 162, 163, 169–172, 176, 178

Index Digitalization processes, 161, 162, 171, 178 Digitalization projects, 28 Digital marketing, 37, 39, 40 Digital maturity, 62, 68 Digital services, 40 Digital settings, 96 Digital skills, 28, 40, 51, 61, 62, 65, 77 Digital stores, 126, 129 Digital technologies, 1, 2, 5, 7–9, 11, 13, 17, 21, 123, 124, 131, 162, 168–172, 177 Digital tools, 1, 9–12, 18–21 Digital transformation, 1, 2, 18, 28, 36, 38, 49, 52, 54, 61–70, 72–78, 83–86, 89, 92–94, 96, 97, 123, 124, 172, 177 Digital transformation processes, 83–85, 88, 91–94, 97 Digital transition, 27–29, 49, 52, 54, 55 Dignity, 84, 88, 90–97 Dignity-centered, 91, 92 Dignity promotion, 91, 92, 96 Dignity protection, 84, 90–92, 94 Dignity restoration, 90, 91 Diminishing of the self, 95 Disadvantages, 27, 29, 32–35, 39–42, 51, 55 Discrimination, 84, 88, 91, 92, 96, 97 Distance communication, 154 Distance work, 147 Distribution of resources, 88 Diversity, 147, 148, 154, 155, 157 Drivers, 1, 2, 7–12, 18, 19, 21 During, 123–125, 128, 130–136, 139–142

E Eco-environmental education, 190 E-commerce, 36, 40, 123–129, 139, 140, 142 E-commerce trends, 125 Ecosystem, 163, 164, 166, 171, 173, 175, 176 Ecosystem innovation engine, 164 Education, 32, 40, 42–49, 51–53, 123, 130, 131, 140 Effectiveness, 2, 8, 9, 14–16, 18, 20–22 Efficiency, 2, 4, 11, 15, 21 E-government, 40 E-health, 40 Electronic systems, 153 Electronic trash, 185 Electronic waste, 183, 184, 198, 202, 204, 205

Index E-mail, 149, 154 Emergent professions, 45 Emotional intelligence, 154 Emotional stability, 153 Employee-company relationship, 70 Employer brands, 67, 70, 71 Empowerment, 156 Enabler, 164, 165, 173, 174 Engaging, 70, 77, 78 Engaging employees, 86 Entry barriers, 85, 92, 96 Environment, 28, 31, 32, 38, 40, 44, 49, 52–54 Environmental dimension, 13 Environmental effects, 206 Environmental protection, 205 Environment role, 166 Ethical boundaries, 89 Ethical considerations, 108 E-waste, 183–187, 190, 191, 199, 202–206 E-waste dealers, 206 E-waste management, 183, 190, 191, 205 Extended Reality (XR), 129, 130

F Face-to-face interaction, 130 Flexibility, 2, 9, 10, 130–132, 140 Flexible, 72 Flex work, 69 Food delivery apps, 133, 134 Formal recycling process, 204 Formal subunits, 3 Future, 1, 2, 7, 8, 14, 16–22

G Generation tools, 104, 105, 113 Generative IAs, 101, 104–106, 108–110, 113, 114, 116 Generative AI systems, 108, 109 Generative AI technology, 105, 119 Glass ceilings, 93 Globalization, 147, 148, 152 Global problem-solving, 33 Going digital, 168, 169, 178 Governance, 63

H Hedonic scenarios, 129 Helix, 161–163, 165, 166, 168, 170, 172, 175, 178 Helix paradigm, 162, 163, 167, 170

215 HR analytics, 61, 64, 65, 71, 72, 77, 78 Human, 2, 12, 14–16, 18, 20 Human capital, 31, 49, 53 Human communication, 101, 154 Human dignity protection, 83 Human interaction, 91, 95, 97 Humanistic management, 83, 84, 88, 90–92 Humanistic management perspective, 92 Humanistic management theory, 90 Human-like responses, 105 Human-machine interaction, 103, 118 Human resource management, 148, 153 Human resources departments, 64 Human values, 89 I ICloud, 63 Implications, 27, 29, 34, 39, 41, 49, 55 Inclusive culture, 147 Individual level, 152, 153 Individuals, 3 Industry, 162–166, 168, 170, 171, 176–178 Industry 4.0, 1, 2, 9–11, 36, 38, 44, 46, 61, 161, 162, 168–171, 176–178 Industry 4.0 digitalization, 168 Industry digitalization, 161, 162, 170–172, 178 Industry-led techniques, 44, 46 Information and Communication Technology (ICT), 61, 63, 68–70, 76, 147, 151, 154, 183, 184, 193, 196, 203 Information sharing, 156 Innovation, 28–35, 37, 39, 44, 49, 50, 53, 61, 64, 65, 75, 77, 78, 161–168, 170–178 Innovation facilitators, 164 Innovation Helix, 162, 168, 170, 172 Innovation process, 164, 167, 168 Innovative tools, 86 Integration of minorities, 153 Integration of technologies, 83 Intellectual Property (IP), 29, 31, 34, 35, 42, 47, 55 Intelligence machines, 102 Intelligent, 154 Interconnectedness, 30, 37 Intercultural sensitivy, 153, 156 Inter-firm TT, 30, 31 International TT, 30, 31 Internet, 123–126, 129, 135, 139–142 Internet of Things (IoT), 1, 5, 13, 36, 38, 43, 46, 63, 65, 83, 84

216 Internet use, 124, 140 Inter-organizational collaborations, 161–163, 178 Inter-organizational networks, 168, 171 Interpersonal relations, 89 Interpersonal sensitivity, 152 Interpersonal skills, 154, 156 Intra-firm TT, 30, 31

J Just-in-time management, 3

K Keyboard, 186 Key skills, 152 Knowledge, 29–35, 40, 42–45, 47–51 Knowledge-generating entities, 167 Knowledge generators, 164, 167 Knowledge sharing, 156

L Lack of expertise, 84 Language processing, 102–108, 119 Leadership, 63, 67, 70, 71, 75–78, 150, 155, 156 Liquid Crystal Display (LCD), 186 Location-based services, 127 Live broadcastings commerce, 128 Loneliness, 95, 97 Long-distance communication, 153 Long-lasting effects, 124 Long-term relationship, 165 Losing control, 94

M Machine Learning (ML), 1, 5, 36, 38, 53, 83, 84, 101–103, 105 Management, 1–5, 7, 9–14, 17–19, 21, 61–63, 65, 68–71, 74, 75, 84, 88, 90–92 Management control, 1–3, 5, 11, 12, 19, 21 Management control systems, 1–3, 19, 21 Management motivation, 183, 203 Management of Big Data, 36 Management practices, 183, 185, 190, 191, 196, 203–206 Managerial challenges, 83 Managing diversity, 148 Manufacturing processes, 162, 168–170 Mapping, 190, 191, 205

Index Marketing, 101, 107, 111, 114, 115, 117–119 Marketing and communication, 109, 110 Marketing sector, 118, 119 Marketplace interactions, 87 Massive open courses, 46 MATES, 29, 42, 47, 48 MATES project, 42, 44, 45, 47, 48, 52 M-commerce, 127 Mobile apps, 127 Mobile banking, 127 Mobile devices, 127, 131 Mobile payments, 127 Mobile Phones (MPs), 183–188, 190, 191, 193, 202–206 Mobile Phone Waste (MPW), 183–194, 199, 202–206 Mobile wallets, 127 Mobility, 63, 65, 67 Moral machines, 89 MPW recycling, 187, 189, 206 N Natural language generation (NLG), 104 Natural Language Processing (NLP), 102–108, 119 Naval sector, 44, 46 Network, 162, 166–168, 170, 171, 175, 176, 178 Networking, 152 Networks, 75, 77 Networks paradigms, 161–163, 168, 170, 172 New online normal, 123 New reality, 123 Non-verbal communication, 154 Novel digital tools, 9, 11, 12, 18, 19, 21 O Obsolete mobile phone, 189 Offline shopping, 95 Online activities, 124 Online classes, 131 Online commerce, 128 Online education, 131 Online learning, 124, 130, 131, 140 Online purchases, 129, 136, 137, 139, 141 Online services, 123–125, 130, 134 Online shopping trends, 136 Online trends, 123–125, 140–142 OpenAI, 105–107 Operations, 63, 68, 76

Index Organization, 2, 3, 7, 9–18, 61–64, 66–78 Organizational, 1–3, 5, 9, 11–16, 18, 19, 21 Organizational challenges, 49, 52 Organizational change, 63, 65, 69 Organizational control, 9, 11 Organizational control systems, 3 Organizational culture, 61, 63–65, 68, 75–78 Organizational dimension, 13 Organizational level, 152, 153

P Paradigms, 161, 162, 166–168, 170, 172, 175, 178 People, 62–64, 67, 69–72, 75, 78, 123–128, 130–134, 139–142 Perceived empowerment, 93 Perception Behavioural Control (PBC), 188, 189 Performance, 1, 2, 5, 7–9, 11, 14, 16–18, 20–22 Performance assessment, 155 Personal Assistants (PAs), 103, 104 Personal performance, 150, 151 Potential dignity risks, 88 Potential risks, 83, 86 Practitioners, 105, 109 Printed Circuit Board (PCB), 186 Problem-solving, 151 Processes, 83–86, 89–94, 96 Product, 62, 63, 73 Professional profiles, 62 Profit maximization, 88 Project, 28, 29, 42–44, 47–49, 55 Psychological distance, 129 Public innovation policies, 30–32 Public institutions, 163, 164, 166, 176

Q Quadruple Helix, 165, 173, 174 Quintuple Helix, 162, 163, 166, 170, 174

R Recruitment and selection, 148, 149, 153–156 Recycling, 187–190, 193, 199, 202, 204–206 Recycling process, 204 Reinforcement learning, 103 Relationship, 61–68, 70, 71, 75 Remote work, 69

217 Resistance to change, 49, 52, 84 Resistance to isolation, 155 Responsible management, 89 Retail e-commerce sales, 126 Retaining, 75, 77, 78 Retaining talent, 61, 62, 64, 66, 67 Retention, 62, 65, 69, 71, 76, 77 Reverse supply chain, 188 Reverse Supply Chain Management (RSCM), 187 Revolution, 104 Rise, 101 Rising inequalities, 88 Risks, 108, 109, 119 S Scientometric, 183, 185, 190, 191, 204 S-commerce, 127, 128 Self-ability, 190 Self-awareness, 2 Self-efficacy, 93 Self-maintenance, 2 Self-management, 154, 156 Self-management skills, 153 Self-regulation of work, 152 Shopping environment, 128, 129 Skills, 29–31, 42, 43, 45–49, 52–55, 148, 149, 151, 155, 156 Small groups, 3 Smart growth, 174 Social commerce, 127, 128, 140 Social interaction, 153 Social issues, 83, 84, 88 Social media, 124, 125, 127, 134, 135, 138, 139, 141, 142 Social media use, 123, 125, 135, 138 Social networks, 63–65, 69, 70, 72, 73, 78 Society, 152, 153 Socio-emotional skills, 153, 156 Spain, 101, 108 Speech recognition, 102, 103 Stakeholders, 84, 89–91 Stakeholder theory, 84, 89, 90, 94 Startups, 85 Stigmatization, 88 Strategy, 61–65, 67, 69, 70, 72, 73, 75–78 Streaming commerce, 128, 129, 140 Streaming services, 132, 133, 138–141 Structural barriers, 93 Structural inequalities, 84 Supply chain, 187, 188, 194–196 Synthetic content, 101, 110, 111, 114, 115 Synthetic content generation, 104, 118, 119

218 T Talent, 61–64, 66–78, 148, 149 Talent attraction, 64 Talent decisions, 71 Talent-focused, 72 Talent management, 61–71, 74–78 Talent relationship, 66 Teambuilding activities, 155 Team members, 151–154 Team performance, 154 Teams, 147, 150–157 Teamwork, 153, 154, 156, 157 Technical compatibility, 49, 50 Technical intermediaries, 89 Technical skills, 151, 154, 156 Technological challenges, 49, 50 Technological dimension, 13 Technologies, 2, 5, 7–18, 20–22, 28, 30–55, 61, 63, 65–68, 70, 76, 123, 125, 127, 129–132, 140 Technology localization, 32, 33 Technology Transfer (TT), 27–35, 37, 40–42, 49, 54, 55, 163, 172, 173 Teleworking, 70 Tools, 64, 65, 67–70, 72–75, 77, 78, 148–150, 157, 183, 184, 190 Training, 31, 40, 42–48, 53, 54 Training and development, 148, 150, 154–156 Transformation, 1, 2, 10, 18, 62, 63, 68, 75, 76, 78 Transition, 28, 42, 50, 52–54 Triple Helix, 163–165, 173, 176 TT approaches, 31 U Universities, 162–166, 173–175, 177

Index University TT, 30, 31

V Valuing teamwork, 151 Video conferences, 154 Virtual, 5, 84, 95 Virtual communication, 140 Virtual conferences, 124 Virtual environment, 154, 156 Virtual Reality (VR), 36, 38, 43, 47, 129, 130 Virtual teams, 147–149, 151–157 Virtual teamwork, 148 Virtues, 89 Visual analytic, 183, 190 Visual perception, 102 VR apps, 130 VR experiences, 130 VR travel, 130 Vulnerabilities, 83, 84, 86–88, 93–96 Vulnerability challenges, 84, 92, 93

W Waste, 183, 184, 187, 188, 190, 191, 193, 199, 202, 204–206 Waste Electrical and Electronic Equipment (WEEE), 184, 187, 202, 205 Well-being, 87, 90, 91, 95, 97 Wireless networks, 127 Work, 123, 124, 126, 130–133, 140, 141 Work arrangements, 140 Work environments, 67 Working groups, 147 Work remotely, 148