Cluster-based supplier segmentation: a sustainable data-driven approach

Mohammad Rahiminia, Jafar Razmi, Sareh Shahrabi Farahani and Ali Sabbaghnia

Modern Supply Chain Research and Applications, 2023, vol. 5, issue 3, 209-228

Abstract: Purpose - Supplier segmentation provides companies with suitable policies to control each segment, thereby saving time and resources. Sustainability has become a mandatory requirement in competitive business environments. This study aims to develop a clustering-based approach to sustainable supplier segmentation. Design/methodology/approach - The characteristics of the suppliers and the aspects of the purchased items were considered simultaneously. The weights of the sub-criteria were determined using the best-worst method. Then, the K-means clustering algorithm was applied to all company suppliers based on four criteria. The proposed model is applied to a real case study to test the performance of the proposed approach. Findings - The results prove that supplier segmentation is more efficient when using clustering algorithms, and the best criteria are selected for sustainable supplier segmentation and managing supplier relationships. Originality/value - This study integrates sustainability considerations into the supplier segmentation problem using a hybrid approach. The proposed sustainable supplier segmentation is a practical tool that eliminates complexity and presents the possibility of convenient execution. The proposed method helps business owners to elevate their sustainable insights.

Keywords: Supplier management; Clustering; Sustainability; Purchasing portfolio matrix; Supplier potential matrix (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eme:mscrap:mscra-05-2023-0017

DOI: 10.1108/MSCRA-05-2023-0017

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