Multi-criteria group decision analytics for sustainable supplier relationship management in a focal manufacturing company

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.