Multi-criteria group decision analytics for sustainable supplier relationship management in a focal manufacturing company
In the context of sustainable development, while the benefits of incorporating environmental, social, and governance (ESG) considerations into supplier management have been widely discussed in recent years, a significant gap in the literature remains. Specifically, there is a lack of a standardized...
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| Vydáno v: | Journal of cleaner production Ročník 476; s. 143690 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
15.10.2024
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| Témata: | |
| ISSN: | 0959-6526 |
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| Abstract | In the context of sustainable development, while the benefits of incorporating environmental, social, and governance (ESG) considerations into supplier management have been widely discussed in recent years, a significant gap in the literature remains. Specifically, there is a lack of a standardized decision analytics framework for ESG-oriented supplier relationship management (SRM) processes in the manufacturing sector. To address this gap, this study introduces a multi-criteria supplier analytics framework (MCSAF) towards sustainable SRM. Through referring traditional supplier evaluation criteria as well as emerging ESG criteria, a novel decision hierarchy for supplier segmentation is developed. The proposed system utilizes the Bayesian best-worst method and the Canopy-k-means clustering algorithm to formulate different supplier segments for strategic development. The proposed MCSAF has been successfully implemented in a German solar water pump manufacturer. The results show that the five highest-ranked criteria are ‘Quality’, ‘Impact and importance on product quality and business growth’, ‘Environmental policy/management’, ‘Customer and product responsibility’, and ‘Risk and crisis management’. 52 suppliers are categorized into five segments, leading to the formulation of ESG-enabled supplier development strategies are subsequently formulated. The successful implementation of the MCSAF showcases its effectiveness in advancing ESG practices in sustainable supplier management.
•ESG-driven supplier evaluation criteria system is developed.•MCDM method and clustering algorithms for supplier segmentation are integrated.•Multi-criteria group decision process for supplier evaluation is presented.•Sustainable supplier development strategies are suggested. |
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| AbstractList | In the context of sustainable development, while the benefits of incorporating environmental, social, and governance (ESG) considerations into supplier management have been widely discussed in recent years, a significant gap in the literature remains. Specifically, there is a lack of a standardized decision analytics framework for ESG-oriented supplier relationship management (SRM) processes in the manufacturing sector. To address this gap, this study introduces a multi-criteria supplier analytics framework (MCSAF) towards sustainable SRM. Through referring traditional supplier evaluation criteria as well as emerging ESG criteria, a novel decision hierarchy for supplier segmentation is developed. The proposed system utilizes the Bayesian best-worst method and the Canopy-k-means clustering algorithm to formulate different supplier segments for strategic development. The proposed MCSAF has been successfully implemented in a German solar water pump manufacturer. The results show that the five highest-ranked criteria are ‘Quality’, ‘Impact and importance on product quality and business growth’, ‘Environmental policy/management’, ‘Customer and product responsibility’, and ‘Risk and crisis management’. 52 suppliers are categorized into five segments, leading to the formulation of ESG-enabled supplier development strategies are subsequently formulated. The successful implementation of the MCSAF showcases its effectiveness in advancing ESG practices in sustainable supplier management.
•ESG-driven supplier evaluation criteria system is developed.•MCDM method and clustering algorithms for supplier segmentation are integrated.•Multi-criteria group decision process for supplier evaluation is presented.•Sustainable supplier development strategies are suggested. In the context of sustainable development, while the benefits of incorporating environmental, social, and governance (ESG) considerations into supplier management have been widely discussed in recent years, a significant gap in the literature remains. Specifically, there is a lack of a standardized decision analytics framework for ESG-oriented supplier relationship management (SRM) processes in the manufacturing sector. To address this gap, this study introduces a multi-criteria supplier analytics framework (MCSAF) towards sustainable SRM. Through referring traditional supplier evaluation criteria as well as emerging ESG criteria, a novel decision hierarchy for supplier segmentation is developed. The proposed system utilizes the Bayesian best-worst method and the Canopy-k-means clustering algorithm to formulate different supplier segments for strategic development. The proposed MCSAF has been successfully implemented in a German solar water pump manufacturer. The results show that the five highest-ranked criteria are ‘Quality’, ‘Impact and importance on product quality and business growth’, ‘Environmental policy/management’, ‘Customer and product responsibility’, and ‘Risk and crisis management’. 52 suppliers are categorized into five segments, leading to the formulation of ESG-enabled supplier development strategies are subsequently formulated. The successful implementation of the MCSAF showcases its effectiveness in advancing ESG practices in sustainable supplier management. |
| ArticleNumber | 143690 |
| Author | Li, Yanlin Tsang, Y.P. Wu, C.H. Lee, C.K.M. |
| Author_xml | – sequence: 1 givenname: Yanlin orcidid: 0000-0003-3619-9691 surname: Li fullname: Li, Yanlin organization: Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hunghom, Hong Kong Special Administrative Region – sequence: 2 givenname: Y.P. orcidid: 0000-0002-6128-345X surname: Tsang fullname: Tsang, Y.P. email: yungpo.tsang@polyu.edu.hk organization: Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hunghom, Hong Kong Special Administrative Region – sequence: 3 givenname: C.K.M. surname: Lee fullname: Lee, C.K.M. organization: Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hunghom, Hong Kong Special Administrative Region – sequence: 4 givenname: C.H. surname: Wu fullname: Wu, C.H. organization: Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Shatin, Hong Kong Special Administrative Region |
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| Keywords | ESG Canopy-K-Means clustering algorithm Bayesian best-worst method Sustainable supplier relationship management |
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