Towards the next generation of manufacturing: implications of big data and digitalization in the context of industry 4.0

1. Introduction

Industry 4.0 has come as a consecutive and predicted outcome of the previous industrial periods, recently dubbed Industry 1.0, 2.0 and 3.0 (Pereira and Romero 2017). As an expected outcome, companies were proactively prepared for the transformational potential of this opportunity by defining in advance the most suitable manufacturing models, operational processes and targets –coming prepared for the associated challenges (Almada-Lobo 2016; Pereira and Romero 2017). From a technical perspective, the context of Industry 4.0 can be described as ‘increased digitisation and automation in addition to increased communication enabled by the creation of a digital value chain’ (Oesterreich and Teuteberg 2016, 122). While not a fully agreed term, ‘Industry 4.0’ is still a ‘slippery’ concept (Pereira and Romero 2017), however undoubtedly the term ‘Industry 4.0’ is an evolving trend and attracted increasing interest from both practitioner and academic communities (Liao et al. 2017; Fatorachian and Kazemi 2018). Industry 4.0 primarily includes the internet of things (IoT), cloud and cognitive computing, and digital manufacturing and cyber-physical systems that collect, transfer and make sense of Big Data (Zhou, Liu, and Zhou 2015) in order to develop smart industries and respond to fluctuations in the markets’ demands for high-quality products. Industry 4.0 has been used in manufacturing and in the car industry by companies such as BMW and Jaguar Land Rover, and also in the food industry by companies such as Mondelez and Nestlé to enhance their overall operational efficiency.

While literature has acknowledged the power of Big Data and the implied disruption in the product and service models (Baines et al. 2017; Papadopoulos et al. 2017; Spanaki et al. 2018; Yoo et al. 2012), Industry 4.0 implies a wave of innovation. There are potential opportunities for organisations and supply chains to innovate, to create strategic advantage and to generate new business value from the data (Gandomi and Haider 2015), but a rigorous approach of the associated disruption is still missing (Fatorachian and Kazemi 2018; Santos et al. 2017). The aim of this Special Issue is to facilitate an ongoing discussion for researchers or practitioners, to showcase their findings, and to explore the implementation of advanced and emerging technologies in the next generation of manufacturing and the wider implications of Industry 4.0 in production planning and operations management.

2. Contributions to the special issue

The response to our call for papers for this SI was tremendous. There were exceptional papers, but some were out of scope and therefore had to be rejected. The rest of the manuscripts underwent review by two reviewers at least. Based on the reviewers’ comments and our own reading of the manuscripts, authors were invited to revise and resubmit their papers. After two or three rounds of reviews, we selected twelve papers out of eighty in the SI. These were grouped in four themes:

2.1. The disruptive potential of Industry 4.0 in production processes, planning and control

These papers discuss the disruptive potential of Industry 4.0 in turbulent contexts and highlight the importance of Industry 4.0 for sustainability in turbulent times.

In the first paper Barlette and Baillette discuss the capabilities that result from the use of Big Data Analytics (BDA) which are critical in turbulent environments, in the context of the Industry 4.0 revolution, especially with regards to agility and performance. From a managerial point of view, the paper highlights the role of top management in achieving organisational changes required to embrace BDA.

Ogbuke et al. review the literature on Industry 4.0 with a focus on big data in supply chain management and discuss the benefits of BDA for organisations and society. Furthermore, they discuss the ethical, security, privacy and operational challenges of big data techniques as well as the dark side of big data that may bring potential dis-benefits to businesses. Four facets of big data were identified and analysed based on a review of the literature, that is, big data analytics, applications, ethics and privacy issues, as well as the role of big data in predicting the future of businesses and move resources and capabilities to the required direction. The authors argued for the importance of big data to transform businesses in an increasingly challenging and uncertain environment.

Hughes et al. argue that despite the plethora of new technologies, the multi-faceted nature of Industry 4.0 and new technologies needs to be balanced with the aim to remain operationally effective and sustainable. They review the literature on Industry 4.0 in relation to sustainability and contribute to the debate of the links between Industry 4.0 and sustainability by offering and discussing an innovative Industry 4.0 framework and alignment of Industry 4.0 themes with the UN Sustainability Goals.

2.2. The adoption of Industry 4.0 for operational efficiency, productivity and performance

Moradlou et al. examine issues related to the collaboration between buyers and suppliers during the adoption of emerging technologies. They adopt the relational view and study how a high-tech firm from the aerospace sector developed additive manufacturing technology. In contrast to the literature on the collaboration between buyers and suppliers in the supply chain, this paper argues that the regular interaction between buyers and suppliers does not necessarily lead to information and knowledge sharing during the development of emerging technologies. Rather, the freedom of using intellectual property in non-competing industries and guarantees of future business are key to knowledge sharing and exchange and for the success of the adoption.

Davies et al. examine the development of additive manufacturing as a supply chain solution, that allows for the management of complexity and for products and supply chains to adapt efficiently and effectively close to context of use. This is done through a single case study, drawing upon design change data and in-depth interviews with industry experts. The findings of the paper suggest that, in contrast to the view of the literature claiming that tangible products are fixed and intangible service elements adapt to absorb variety, it is that tangible products as well can absorb variety to meet emergent need.

Fosso-Wamba and Queiroz focus on Blockchain diffusion across supply chains. They offer a multi-stage model of adoption (intention, adoption, and routinisation stages) that facilitates the adoption of Blockchain, drawing on diffusion of innovations theory, the resource-based view, dynamic capability, the technology adoption model, and the institutional theory. The model is then validated using PLS-SEM applied in Indian and US organisations. The authors illustrate the different variables and their implications that need to be considered in each of the stages and highlight the role of the context (i.e. country) in the diffusion. For instance, within the intention stage Indian organisations highlighted perceived benefits, top management support, absorptive capacity, and trust as the most critical variables, whereas for US organisations it was only perceived benefits and trust.

Kucukaltan et al. argue towards the importance of Industry 4.0 for logistics service providers (LSPs). With regards to this sector, they conduct a structured survey in the Turkish logistics industry. A follow up then took place through an integrative interview survey, where the probabilities and the impacts of Industry 4.0 were discussed. The contribution of this study lies in demonstrating the role of Industry 4.0 for LSPs but also the possible changes in the logistics industry from the operational, financial, and human resources aspects.

Rahman et al. focus the role of Industry 4.0 in enhancing organisational performance in the cargo logistic business (service sector) in Bangladesh and Canada. They use the Technology-Organisation-Environment (TOE) framework, as shaped by the institutional theory. Through purposive sampling a total of 210 (105 each) survey questionnaires, as completed by employees working in logistics companies, were gathered. The paper argues no matter if the two contexts are totally different, businesses should enact Industry 4.0 to gain benefits both in short-term (day-to-day operations) and long -term strategic planning.

Robert et al. discuss the weaknesses of Industry 3.0 performance management systems with regards to its omission of the human factor when they argue that the inclusion of the human factor is sine qua non to understanding Industry 4.0 performance management systems. They used a case study of an organisation that dealt with the issues of Industry 3.0 using a grounded theory approach (Glasser and Strauss, 1967) based on a thorough and comprehensive literature review followed by practical observations of a performance management system within Schneider Electric. The contribution of this paper is twofold: firstly, it presented a model of performance management that was implemented successfully by Schneider Electric to deal with the repercussions of the organisational transition to an Industry 4.0; and secondly, it highlights the importance of human factors which are very important for sustainable Industry 4.0 performance management systems.

Wiech et al. look at the relationship between the implementation of Industry 4.0 related technologies and performance, as well as the role of the organisational structure in this relationship. Following a review of the literature, a set of hypotheses were developed, then tested with 116 participants from German-speaking countries. The findings do highlight the link between technology and performance as these technologies have distinct, partially unexpected, performance effects. Additionally, the authors found that organisational structure does not play a significant role in technology adoption.

2.3. Industry 4.0 technologies and sustainability

Felsberger et al. investigate the impact of the implementation of Industry 4.0 on the sustainability dimensions of European manufacturing industries. They propose a framework that combines the firms existing and new dynamic capabilities, competencies and market requirements to achieve sustainable competitive advantage. The authors collected and analysed data from six European Manufacturing industries including aerospace manufacturing (AM) and electronic component and systems (ECS) manufacturing. The contribution of this paper lies in revealing the relationships between Industry 4.0, the dynamic capabilities of the firm, and distinct dimensions of sustainability. The dynamic capabilities mediate the impact Industry 4.0 on economic, environmental, and social aspects.

Finally, the paper by Kayikci et al. completes our SI. This paper focuses on food supply chains and the role of Industry 4.0 in tracing the food across the whole supply chain from the farm through processing until it reaches the customer and, thus, ensure transparency. The study recognises the opportunities and challenges related to the adoption of blockchain technology in the food supply chain, based on qualitative research and semi-structured interviews with stakeholders from the food industry in India and Turkey with an interest in tracking, or who had used blockchain before. Then a semi-structured questionnaire was developed with twelve major questions which covered aspects of people, process, performance, and technology. Hence, this study contextualises PPT theory in an emerging economy to show the interaction effect of technology to strengthen the relationship between people, process, and performance.

Acknowledgements

We would like to express our sincere thanks to the Editor-in-Chief Prof Stephen J Childe for giving us an opportunity to organise the SI on this emerging theme. Furthermore, we would like to thank our reviewers who have spent their time reviewing and providing quality inputs to the articles included. Finally, we would like to thank the editorial staff of PPC and especially Mrs. Heather Childe, Assistant to the Editor of Production Planning and Control Journal along with the staff at Taylor and Francis for their continuous support and guidance during this process. Thank you All!

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Notes on contributors

Thanos Papadopoulos

Thanos Papadopoulos is a Professor of Management (Information Systems/Operations Management) at Kent Business School, University of Kent, UK and Director of the TIME research centre. His research is focusing on the problems that are at the nexus of operations management and information systems and more recently on Big Data within Supply Chains and Operations. He has participated in FP7 projects and has been awarded funding inter alia, from Marie Currie Cancer Care Research UK. He has published over 140 articles in peer reviewed journals and conferences including, inter alia, the British Journal of Management, Decision Sciences, European Journal of Operational Research, International Journal of Operations and Production Management, International Journal of Production Research, IEEE Transactions on Engineering Management, International Journal of Production Economics, Technological Forecasting and Social Change, and Production Planning and Control. He is Associate Editor for International Journal of Operations and Production Management and Benchmarking: an international journal. He also sits at the Editorial board of Technological Forecasting and Social Change, Industrial Management and Data Systems, and is Distinguished Editorial Board member of International Journal of Information Management.

Surya Prakash Singh

Surya Prakash Singh is Professor in the Department of Management Studies, IIT Delhi, India. He is also visiting fellow at NUBS, Newcastle University, UK. He holds a PhD from IIT Kanpur. He is also a postdoctoral fellow from NUS Singapore-MIT USA alliance. His research interest includes facility planning design, procurement, supplier selection, supply chain analytics, flexible and sustainable operations, big data analytics, Industry 4.0, international manufacturing network, developing heuristics and meta-heuristics approaches. His work has been published in leading international journals such as COR, DSS, CAIE, IJPR, ANOR, IJPE, LNCS, PPC, IJLM, IMDS, IJAMT, ESWA, Food Control, BIJ, GJFSM, EJM, and APMR. More than 150 papers have been published at various international journals and conference proceedings of repute. He also regularly reviews articles for many leading journals. In addition to this, he is also involved in doing research projects funded by British Council, UKIERI, DST India, UGC India, Ministry of Tribal Affairs, India, NBCC India, and RVNL India. He has been awarded Young Outstanding Faculty Fellowship from IIT Delhi. Recently, he was awarded with ASEM-DUO fellowship from Seoul, Korea.

Konstantina Spanaki

Konstantina Spanaki is a Lecturer in Information Management at Loughborough University since 2017. Prior to this appointment, she has been a Research Associate at Imperial College London, where she worked on joint EPSRC projects between the Business School and the Department of Computing. Konstantina’s main research areas lie within the intersection of Information Systems (IS) and Operations Management (OM). Recently, she is actively involved in projects related to Data and Information Management, Technology Management, Data Sharing, Cloud Computing and Disruptive Technologies. Konstantina is a member of EurOMA, of BAM, the AIS and the OR Society.

Angappa Gunasekaran

Dr. Angappa Gunasekaran is Dean and Professor at the School of Business & Public Administration, California State University, Bakersfield. Prior to this, he served as Dean of the Charlton College of Business from 2013 to 2017, Chairperson of the Department of Decision and Information Sciences from 2006-2012, and the founding Director of Business Innovation Research Center (BIRC) from 2006 to 2017 at the University of Massachusetts Dartmouth. He has over 300 articles published in peer-reviewed journals. He has presented about 50 papers, published 50 articles in conferences, and given a number of invited talks in many countries. He is on the editorial board of several journals. He has organized several international workshops and conferences in the emerging areas of operations management and information systems.

Rameshwar Dubey

Dr Rameshwar Dubey is a Reader-Operations Management at Liverpool Business School. Rameshwar is also a Senior Editor of International Journal of Physical Distribution and Logistics Management and Associate Editors of Journal of Humanitarian Logistics and Supply Chain Management, International Journal of Information Management, Benchmarking: An International Journal, Global Journal of Flexible Systems Management and Management of Environmental Quality. Before joining Liverpool Business School, Rameshwar was a full time Associate Professor-Supply Chain Management at Montpellier Business School, Montpellier, France which he is still associated as an Affiliate Professor. He also has taught at some of the leading international school which includes Indian Institute of Management, Jammu, India, the Faculty of Engineering, UNESP, Bauru, SP, Brazil, Southern University of Science and Technology of China, Stockholm School of Business, Stockholm, Sweden and Audencia Business School, Nantes, France. Rameshwar research interests include supply chain management, operations management and business analytics with strong focus on humanitarian operations management, sustainable supply chain management, supply chain design issues and application of emerging technologies in disaster relief operations. Rameshwar has published some of the most cited papers in International Journal of Operations and Production Management, International Journal of Production Economics, International Journal of Production Research, British Journal of Management, Production, Planning & Control, IEEE Transactions on Engineering Management, Journal of Business Research, Journal of Cleaner Production, Annals of Operations Research, Technological Forecasting & Social Change and Management Decision. For his academic work, Rameshwar has received several awards: outstanding reviewer award International Journal of Production Economics, Journal of Business Research, Journal of Cleaner Production, best reviewer award Journal of Humanitarian Logistics and Supply Chain Management (2014, 2016), Management Decision (2018) and received a title on 8th November 2019 at Bauru, SP, Brazil for lifetime commitment to advancing scientific knowledge on supply chain management, operations management, information systems and technology for promoting innovation, enhancing industrial competitiveness and improving quality of life, both in Brazil and worldwide. Rameshwar is an active member of several professional societies, active reviewer of over 75 leading international scientific journals, reviewer of PhD thesis and other professional bodies engaged in dissemination of grant.