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Supply Chain Resilience and its Interplay with Digital Technologies


Special issue call for papers from International Journal of Physical Distribution & Logistics Management

Supply Chain Resilience and its Interplay with Digital Technologies
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Submission Deadline: January 31, 2020
(All papers should be submitted to the IJPDLM Manuscript Central website by January 31, 2020: please choose the Supply Chain Resilience and its Interplay with Digital Technologies option when submitting, refer to the IJPDLM author guidelines here before submitting)
 

Guest Editors:

Jennifer Blackhurst, Professor of Management Sciences (The University of Iowa, USA)
Ajay Das, Professor of Operations Management (Baruch College – CUNY, USA)
Dmitry Ivanov, Professor of Supply Chain Management (Berlin School of Economics and Law, GERMANY)

Resilience in supply chains is as vital for firms as immune systems are for human beings. Immune systems   continuously monitor, anticipate and adapt to   dynamic environments. Similarly, supply chains are also exposed to, and affected by changes in environmental and operational factors. One such significant and rapidly emerging change is digitalization in firms and in society (Ivanov et al. 2019c). Supply chain resilience (SCR), as a capability, is both challenged and enhanced by digitalization. Although the concept of resilience in supply chain management (SCM) is not new (Ho et al. 2015, Ambulkar et al. 2015), ongoing developments in digital technologies have been introduced fairly recently  in the field of SCR and have not yet been well explored (Papadopoulos et al. 2017, Schlüter et al. 2017, Dubey et al. 2019, Ivanov et al. 2019a,b). Innovations in digital technologies influence the development of new paradigms, principles, and models in SCM in general, and SCR in particular. We consider  digital technology as a combination of Industry 4.0, the Internet of Things (IoT), Big Data analytics,  Artificial Intelligence, Advanced tracking and tracing technologies, Wearables, and Additive Manufacturing (Büyüközkan and Göçer 2018). Accompanying such technological advances in managing SCR are similar advances in organizational practice and culture, involving  the socio-technical aspects of new technology use.
The interplay of SCR and digital technologies can be considered in light of three dimensions. The first dimension is the change in traditional SC designs, and the resulting change in SCR management. For example, additive manufacturing applications may result in redesigning global SC production and sourcing strategy. Industry 4.0 enables individualization of products and services that frequently requires supply chain re-design (Ivanov et al. 2016, Frank et al. 2019). How resilient are those new structures? Can  existing SCR management principles and methods cope with new realities? How can digitalization be used to achieve SC resileanness, i.e., a combination of resilient and lean? (Ivanov and Dolgui 2019).
The second dimension is SC visibility. Big data analytics applications to SCM have been seen in retail, procurement processes, manufacturing, omnichannel promotion actions, real-time traffic operation monitoring and proactive safety management (Schoenherr and Speier‐Pero 2016). Blockchain applications to SCs are emerging. The central objective  of data analytics is to increase visibility, response time, and efficiency in the SC. Similarly advances in sensor technology and IoT have enabled heightened awareness and visibility in the supply chain.  How can SC visibility be better utilized to increase SCR? Organizations are exploring ways  to utilize large volumes of data to both predict risks and assess vulnerability (Choi et al. 2018), and improve the resilience of SC operations (Choi et al. 2017). Das et al. (2019) and Dubey et al. (2019) provide empirical insights  on the multiple interplays between digital data technologies and SCR.
The third dimensions concerns the softer and equally important aspect of  of digitalization and supply chain resilience – relationships and technology. Organizational innovations such as supply chain towers, dynamic buyer-supplier relationships, technology investment reward sharing structures, and human-technology interface and co-management issues typify such issues. Dubey et al. (2018, 2019)  note that digital technologies may significantly influence agility, adaptability, and alignment, and their impact on performance on  supply chains. New principles and models are required to investigate potential interactions between digitalization and SCR in this dimension.

Objectives, methodologies and topics of interest

To the best of our knowledge, this is the first special issue that connects digitalization, resilience, and organizational perspectives in SCM.  The central research questions  are (1) the nature and drivers of potential inter-relationships between  digitalization  and SCR, (2) the performance implications of digitalization for  SCR; (3)  the impact of digitalization on SCR management principles and organizational and operational practices (4) the nature of digitalization technology-based extensions associated with SCR in factories of the future.
Studies shall contribute to both theory and practice, with a sharp focus on the relationship between digitalization and SCR. The special issue aims to collate and present recent, significant research initiatives  in the field of SCR, digital SCs and smart operations. Studies could look at various digitalizations and their impact on practices and performance. The special issue would also invite new ideas as to how digital technologies and associated organizational operational changes may help to increase SC and operations resilience.
Submitted papers have to comply with the philosophy of the journal. Strong, new, and insightful conceptual, modelling and applications oriented studies that add significantly to the existing body of knowledge are particularly solicited. The special issue editors are methods agnostic, and are interested in innovative new research that provides insights for academics and practitioners.
Potential topics include, but are not limited to:
•    Big Data Analytics and supply chain resilience
•    Digital supply chain and resilience
•    Ripple effect mitigation by digital technologies
•    Digital supply chain twins to manage resilience
•    Impact of supply chain visibility on resilience and the ripple effect
•    Digital technologies, resilience and sustainable manufacturing
•    Additive manufacturing and supply chain resilience
•    Blockchain and supply chain resilience
•    Digitalization impact on leadership practices and management principles to improve resilience
•    Digitalization impact on innovation and technology management to improve resilience
•    Digitalization impact on managing suppliers/customer relations in the SC to improve resilience
•    Digitalization and organizational changes to improve resilience
•    Assessment techniques for digital technology investments to improve resilience
The wider research community is invited to submit their current work in the above or closely related areas. Strong, new, and insightful conceptual and applications oriented studies that add significantly to the existing body of knowledge are particularly solicited.
Interest for academics and practitioners
Industry 4.0, additive manufacturing, and data analytics open new opportunities, but also create new challenges for SCR. While the applications of digital technologies to SCM are exemplarily spread out engineering and management journals, there is a paucity of research  that conceptualize and generalize new SCR concepts and practices that may be associated with, and  enabled by digitalization.
For example, big data analytics may reduce supply and demand risks through enhanced SC visibility and forecast accuracy, reduction in information disruption risks,  better quality of contingency plan activation. Advanced trace and tracking systems may facilitate integrated SC planning and  reduce supply and time risks through real-time coordination in activating  contingency policies. SCs are typically protected against anticipated disruptions using  means such as  risk mitigation inventory, capacity reservation, and backup sources. Such remedies are expensive and difficult to justify especially when disruptions do not happen for extended periods of time. Blockchain systems could help reduce these inefficiencies, creating  a record of activities and data needed for recovery in terms of synchronized contingency plans. Similarly, additive manufacturing can reduce the need for risk mitigation inventory and capacity reservations,  including identifying and maintaining  backup contingent suppliers. The decentralized control principles in Industry 4.0 systems make it possible to diversify  risks and reduce the need for structural SC redundancy with the help of manufacturing flexibility.SC visibility afforded by digitalization can accelerate reaction and recovery times, with quicker deployment of proactive contingency plans.  Big data analytics and advanced trace & tracking systems in general, and blockchain technology in particular, can help  trace the roots of disruptions, observe disruption propagation (i.e., the ripple effect) (Dolgui et al. 2018b, Ivanov 2018), select short-term stabilization actions based on a clear understanding of what capacities and inventories are available (emergency planning), help  develop  mid-term recovery policies,  and enable examine and analyse the long-term performance impact of  disruption ripple effects. Additive manufacturing could simplify and reduce the number of SC nodes and layers and  thus mitigating disruption propagation in the SC. These and related research concepts and relationships call for rigorous research inquiry.
Despite initial efforts to unearth new insights about the impact of digital technologies on SC risks (Tupa et al. 2017, Papadopoulos et al. 2017, Schlüter et al. 2017, Dolgui et al. 2018a, Ivanov 2018, Dubey et al. 2019), the understanding of the individual contribution and the interplay of different digital technologies on specific SC and operations resilience is not well understood.  The special issue intends to advance the body of knowledge in this regard by soliciting relevant, well-designed and rigorously executed research. 

 

References

 

Ambulkar, S., J. Blackhurst, S. Grawe (2015). Firm's resilience to supply chain disruptions: Scale development and empirical examination. Journal of Operations Management, 33(34), 111–122
Ben-Daya, M., Hassini E., & Bahroun Z. (2018). Internet of things and supply chain management: a literature review. International Journal of Production Research, DOI: 10.1080/00207543.2017.1402140
Büyüközkan, G. and Göçer, F. (2018), “Digital Supply Chain: Literature review and a proposed framework for future research”, Computers in Industry, Vol. 97, pp. 157-177.
Choi, T.M., Wallace S.W., and Wang Y. (2018). Big Data Analytics in Operations Management. Production and Operations Management, DOI: 10.1111/poms.12838
Choi TM, Lambert JH. Advances in risk analysis with big data. Risk Analysis (2017) 37, 8, 1435-1442.
Das A., Gottlieb S., Ivanov, D. (2019). Managing disruptions and the ripple effect in digital sup-ply chains: empirical case studies, in Ivanov D. et al. (Eds.) Handbook of the Ripple Effects in the Supply Chain. Springer, New York, pp. 261-285.
Dolgui A., Ivanov D., Sokolov B. (2018). Ripple effect in the supply chain: An analysis and recent literature. International Journal of Production Research, 56(1-2), 414-430.
Dubey, R., Altay, N., Gunasekaran, A., Blome, C., Papadopoulos, T., Childe SJ (2018). Supply chain agility, adaptability and alignment: empirical evidence from the Indian auto components industry. International Journal of Operations & Production Management 38 (1), 129-148.
Dubey R., Gunasekaran A., Childe, S. J. Wamba S.F., Roubaud D., Foropon C. (2019). Empirical Investigation of Data Analytics Capability and Organizational Flexibility as Complements to Supply Chain Resilience. International Journal of Production Research, https://doi.org/10.1080/00207543.2019.1582820
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Ivanov, D. (2018). Structural Dynamics and Resilience in Supply Chain Risk Management. Springer, New York
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Ivanov, D., Dolgui A., Das A., Sokolov B. (2019c). Digital supply chain twins: Managing the Ripple effect, resilience and disruption risks by data-driven optimization, simulation, and visibility, in Ivanov D. et al. (Eds.) Handbook of Ripple Effects in the Supply Chain. Springer, New York, pp. 309-332.
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