Theory driven approaches to understand Industry 4.0 technologies in Logistics and Supply Chain Management

Call for papers for: International Journal of Physical Distribution & Logistics Management

Theory driven approaches to understand Industry 4.0 technologies in Logistics and Supply Chain Management 

Deadline for paper submission: 31 August 2021 - Call will be open in ScholarOne from 31 May 2021

Guest Editors:
Prof Michael Bourlakis ([email protected]). Cranfield School of Management
Cranfield University, UK

Dr Abhijeet Ghadge ([email protected]). Cranfield School of Management
Cranfield University, UK

Prof Nigel Caldwell ([email protected]). Guildhall School of Business and Law
London Metropolitan University, UK. 

Prof Sachin Kamble ([email protected]). EDHEC Business School, Lille, France. 

Prof Angappa Gunasekaran ([email protected]). School of Business and Public Administration, 
California State University at Bakersfield, USA. 

Industry 4.0 is viewed as an emerging phenomenon. The world of logistics and supply chains management (LSCM) is currently facing unprecedented disruptive innovation from the ‘Industry 4.0’ technologies. Although academic literature lacks a clear and universal definition of the Industry 4.0 concept (Hofmann and Rüsch, 2017; Hofmann et al., 2019), Industry 4.0 technologies may include Blockchain, Additive manufacturing (3D printing), the Internet of Things (IoT), Automation, Robotics, Big Data Analytics, Artificial Intelligence, Virtual reality, etc. Each Industry 4.0 technology, as well as synergetic combinations of several Industry 4.0 and existing technologies, can be integrated to potentially solve complex problems and achieve competitive advantage. 

Several recent calls for papers have invited research on applications of Industry 4.0’s disruptive technologies in LSCM. These calls have generated a keen research interest in Industry 4.0 within the LSCM research community. Most of the research to date has focused on describing different technologies and answer the what question, e.g., “what does this technology do?” There are some efforts to develop typologies and categorization of technologies, while others broadly examine drivers, enablers, and inhibitors (e.g. Ghadge et al., 2020; Jain and Ajmera, 2020; Veile et al., 2020). Some research jumps to the conclusion that industry 4.0 technologies can broadly bring many performance benefits, while very few cases of successful use are presented. Few studies have attempted to theorize the development and use of Industry 4.0 technologies, e.g., Treiblmaier (2018) on Blockchain, Eyers et al. (2018) on Additive Manufacturing and Stank et al. (2019) on digitalization, to name a few. There are very few attempts to develop theory to understand how logistics and supply chain managers tackle opportunities and challenges related to Industry 4.0 technologies (e.g. Falcone et al. (2019) discuss network theory and technological innovations; Oberer and Erkollar (2018) discuss leadership). 

LSCM researchers sometimes ask, why do we need more theory? What is the use of theory in such an applied subject area? Schmenner and Swink (1998) and Schmenner et al. (2009) have directly addressed these debates. Their answer as to what theory can do for a functional, process-driven area like LSCM involves not only the role of theory in explaining how the phenomena work the way that they do and how they facilitate and enable prediction, but also their role in the development and evolution of LSCM as a field. The good use of theory, testing of theory, the rejection of deficient theory and the adoption of new theory always rejuvenates the field to grapple with the latest phenomena such as industry 4.0 technologies. 'The goal is to topple a deficient theory (and all theories can be deficient) and to erect a new one that does a better job with the facts as they are known’ (ibid.p340). 

Concerning industry 4.0 technologies, logistics and supply chain managers are confronted by many important questions: How can they identify the right combinations of technologies to adopt from competing options? How can they integrate these new technologies into existing organizational structures, processes and technology platforms? Since not all these technologies are fully developed, how could they be developed, or who should be taking the risk of developing them? Is it better to be the first, second or late movers? How can managers learn about new technologies developed from other sectors? How can these technologies be implemented to realize their claimed benefits? To answer these questions, managers may begin to develop technology roadmaps, technology strategies, conduct feasibility studies and pilots, develop collaboration or strategic alliances, etc. This is where management theories can contribute.  

A significant limitation of the LSCM field facing is the reliance on existing and well-known grand theories adopted from other disciplines (e.g. Resource-based view, Transaction-cost economics, Network theory, Principle-agent theory) that can provide only a broad understanding of the world. We need theories that answer the ‘how’, ‘why’ and ‘when’ questions (Ketchen and Hult, 2011). For example, “how do managers approach the potential of a particular technology and justify its benefits?” Thus, the prominence of ‘problematization’ over ‘gaps filling’ is crucial for advancing interesting theories (Alvesson and Sandberg, 2011; Carter, 2011). To avoid the drawbacks of the sheer description of phenomena (raw empiricists) and grand, all-inclusive theory (grand theorists); we contend that Merton's (1968) middle-range theorizing is an appropriate approach for understanding clearly defined aspects of phenomena such as Industry 4.0, as it aims at integrating theory and empirical data to explain such as complex phenomenon (Hitt et al., 2007; Soltani et al., 2014). Moreover, grounded theory and inductive approaches are necessary for grounding complex behaviours and relationships in LSCM (Randall and Mello, 2012; Ghadge et al., 2013).

Theory simplifies a complex world in ways that make it understandable, communicable and can offer insights into the future through appreciating likely outcomes (Corley and Gioia, 2011). It enables the generalization of findings by creating recognized frameworks and substantial research guidance (Colquitt and Zapata-Phelan, 2007). In the words of Walker et al.-"Theories help make sense of the world around us. They can serve a function beyond descriptive, in that they allow us to predict the nature of relationships between phenomena" (2015: p1183). The theory is critical in developing a coherent explanation for findings resulting from the empirical evidence, as it provides a foundation that fosters the systematic accumulation of knowledge informing future research and practice (Flynn et al., 2020). These strengths make theory indispensable for understanding current LSCM activities, and even more so for new technologies that will bring disruptive innovation to LSCM activities. 

The primary objective of this call for papers is to disseminate work on Industry 4.0 that uses theory beyond description, that tries to make sense of the world and offers an explanation and predictive insights into the nature of relationships between LSCM professionals and Industry 4.0 technologies. This special issue of IJPDLM invites novel and connecting theory-driven research on Industry 4.0 and logistics and supply chain management. Although this special issue is open to any theoretical perspective and empirical approach, all submissions should make it clear that their contributions are relevant to logistics and supply chain management and fit the scope of IJPDLM.

Topics of Interest:
Topics of interest include, but are not limited to the following:
•    Theories that explain how Industry 4.0 technologies are adopted/implemented in logistics and supply chain management.
•    Theories that explain how LSCM managers make sense of the benefits of Industry 4.0 technologies and how they develop technology strategies to realize the benefits.
•    Theories that explain how LSCM managers interact with and learn from other technology providers and other sectors. 
•    Theories that explain immersive (augmented, virtual, and mixed reality) user experience in logistics and supply chain management.
•    Theories that explain changes in logistics and supply chain management strategies and practice following the transition to virtual or cyber-physical systems.
•    Theoretical perspectives on social and environmental impacts of Industry 4.0 adoption in logistics and supply chain management.
•    Theory-based examinations of the 'dark side' of adopting Industry 4.0 in logistics and supply chain management.
•    Theories or models for connecting the circular economy and sustainability in supply chains with Industry 4.0 technologies.
•    Theories that explain the interface between Industry 4.0 and other supply chain concepts, e.g., risk, agility, resilience, etc.
•    Theories that explain the use and development of big data analytics, AI, digital twins, Blockchain, etc. for achieving digital supply chains.
•    Studies informed by theories imported from other disciplines or that are rarely used in LSCM to offer new insight and explanation into industry 4.0 and inspire new research agenda.
Note: IJPDLM seeks strategically focused, theoretically grounded, empirical, conceptual and qualitative original research studies in logistics, physical distribution, purchasing, operations and supply chain management, and associated strategic issues. Quantitatively oriented mathematical and modelling research papers are not suitable for IJPDLM.

Review Process:
Manuscripts should comply with the scope, standards, format, and editorial policy of the International Journal of Physical Distribution & Logistics Management. All papers must be submitted through the official International Journal of Physical Distribution & Logistics Management submission system ( with clear selection indicating that the submission is for this Special Issue. Before submission, authors should carefully read over the Journal’s “Author guidelines”. The submission system will be open on 31 May 2021, and submissions are welcome up to and including 31 August 2021. Papers submitted to the Special Issue will be subjected to the normal thorough double-blind review process.
Deadline for paper submission: 31 August 2021 
Reviewer first reports: 30 October 2021
Revised paper submissions: 31 December 2021
Expected publication date: Mid 2022


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