An analytical method for investigating multi-tier sustainable supply chains: simplifying the complex

Multi-tier sustainable supply chain relationships (MSSCR) are complex with involvement of multiple organisations, practices, objectives, and interconnectivities. These complexities make it difficult to effectively study MSSCR using traditional empirical statistical correlative research. In MSSCR the relationship between the focal firm and sub-supplier may be affected by the relationship between the focal firm and direct-supplier, and the relationship between the direct-supplier and the sub-supplier. This paper introduces a research methodology, based on K-Means clustering, rough set theory, and cluster membership to investigate complex relationships across multi-tier sustainable supply chain triads. Collaborative advantage variables including knowledge-sharing routines, relation-specific investments, complementary capabilities, effective governance mechanisms, and long-term commitment are conceptually presented to evaluate relationships among MSSCR practices and sustainability performance. Insights for practitioners and researchers are provided. Research insights can be gained by analytically providing alternative explanatory and equifinality relationships amongst variables and multi-pair organisations. The methodology can mitigate the endogeneity problem, such as omitted factors (variables), measurement error, even in small sample data situations. Directions for future research are discussed.KEYWORDS: Multi-tier supply chainssuppliersustainabilitycomplexityequifinalityrough set AcknowledgmentThis study was partially supported by the TEC-LOGd Chaire sponsored by the Hauts-de-France region and the Cambrai Agglomeration Community.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe data that support the findings of this study are available from the corresponding author, [Bai, C.], upon reasonable request.Additional informationFundingThis work is supported by the National Natural Science Foundation of China Project (72072021 and 71772032). This work was also partially supported by U.S. National Science Foundation Grant 2021871.Notes on contributorsChunguang BaiChunguang Bai is a Professor in the School of Management and Economics, at the University of Electronic Science and Technology of China. Her research interests include sustainable supply chain management, smart technology, and the carbon neutralisation. She has dozens of publications with over 60 papers in journals such as Production and Operations Management, Decision Science, European Journal of Operational Research. She has over 6000 citations based on Google Scholar. She has been recognised as one of the most cited researchers in China across disciplines And World's Top 2% Scientists 2020 (by Stanford University).Joseph SarkisJoseph Sarkis is a Professor in the Business School at Worcester Polytechnic Institute. His research and teaching are in the areas of operations, supply chain, technology, and sustainability management. He has been a highly cited scholar for many years with over 500 publications. He is also an international scholar at the Hanken School of Economics and the TEC-LOGd Chaire d'excellence at the Université Polytechnique Hauts-de-France focusing on Circular Economy, Transportation, Logistics, Sustainable Supply Chains and Technology. He does his best to live sustainably.Sherwat IbrahimSherwat Elwan Ibrahim is an Associate Professor of Operations Management at The American University in Cairo (AUC). Her research and teaching are in the areas of operations, supply chain, technology, and Africa sustainable development and she has several publications in prestigious journals. She is also a Visiting Associate Professor at the School of Public Policy and International Affairs (SPIA) at Princeton University, and she serves as founding Chair of the UN Principals of Responsible Management Education (PRME) for Africa Chapter.