A new approach for business process reconfiguration under uncertainty using Dempster-Shafer Theory

Abstract

In an increasingly changing and uncertain market, adapting the supply chain to new changes requires reconfiguring supply chains processes to improve its performance. The decision-making process for the reconfiguration of supply chains must take into consideration the uncertainty and imprecision related to the judgments of the decision-makers. This paper deals with uncertainty in the decision-making process of supply chain reconfiguration using the Dempster-Shafer theory. An approach to reconfigure supply chain business processes under uncertainty is also proposed to improve the decision-making process for supply chain reconfiguration. The reconfiguration of the supply chain involves selecting the most appropriate configuration, process, actor and role that should be reconfigured in advance in order to optimise the reconfiguration using the Quality Function Deployment (QFD) and the Analytic Hierarchy Process (AHP) method. To reduce the imprecision and uncertainty related to the judgments and preferences of the decision-makers, the Dempster-Shafer theory is applied and, to validate the introduced approach, a case study is conducted.

KEYWORDS:

• Uncertainty
• decision-making process
• Reconfigurable Supply Chain (RSC)
• reconfiguration
• business process
• Dempster-Shafer Theory (DST)

Disclosure statement

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

Data availability statement

All data used in this paper (related to comparison matrices or sensitivity analysis) are included in this file.

Additional information

Notes on contributors

Slim Zidi

Slim Zidi is a Ph.D. student at the University of Paris 8 and a lecturer at the University of Picardie Jules Verne. He obtained his Master's degree in transport and logistics at ISGIS (Institut Supérieur de Gestion Industrielle de Sfax) in Tunisia. His research interests focus on the performance improvement of supply chains, reconfigurability measurement and disruptions management.

Tayssir Ben Soussia

Tayssir Ben Soussia obtained a Master's degree in transport and logistics at ISGIS (Institut Supérieur de Gestion Industrielle de Sfax) in Tunisia. His research interests focus on supply chain resilience.

Nadia Hamani

Nadia Hamani is an Associate Professor at the University of Picardie Jules Verne. She obtained a PhD in Industrial Engineering at Ecole Centrale de Lille. She is co-chair of international conferences or special sessions and she authored or co-authored more than 100 scientific papers. She is involved in several research networks, projects and associations. Her research interests include performance improvement, production systems and supply chain.

Mounir Benaissa

Mounir Benaissa is an Associate Professor at University of Sfax. He obtained his PhD and his habilitation in industrial engineering from University of Le Havre (France) in 2006 and 2013. He has held academic positions at Le Havre University (France), University Carthage (Tunisia) and University of Sfax (Tunisia). He is co-founder of IEEE ITS Tunisian chapter and IEEE senior member. He is the Founder and Chair or IEEE ICALT (IEEE International Conference on Advanced Logistics and Transport). He was guest editor of special issues of international journals. He has authored or co-authored more than 50 scientific papers and contributed with invited chapters to edited books. His research interests include information system, supply chain management, reverse logistics and logistics optimisation.

Lyes Kermad

Lyes Kermad is an Associate Professor at Paris 8 University. He obtained a PhD and his habilitation from the University of Technology of Lille respectively in 1996 and 2017. His current research areas cover manufacturing information systems and quantitative risks evaluation in the reconfiguration projects in industrial companies.