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Supplier Risk Assessment Based on Best-Worst Method and K-Means Clustering: A Case Study

Department of Industrial Engineering, Faculty of Engineering, Marmara University, 34722 Istanbul, Turkey
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Sustainability 2018, 10(4), 1066; https://doi.org/10.3390/su10041066
Received: 18 January 2018 / Revised: 16 March 2018 / Accepted: 28 March 2018 / Published: 4 April 2018
(This article belongs to the Section Economic, Business and Management Aspects of Sustainability)
Supplier evaluation and selection is one of the most critical strategic decisions for developing a competitive and sustainable organization. Companies have to consider supplier related risks and threats in their purchasing decisions. In today’s competitive and risky business environment, it is very important to work with reliable suppliers. This study proposes a clustering based approach to group suppliers based on their risk profile. Suppliers of a company in the heavy-machinery sector are assessed based on 17 qualitative and quantitative risk types. The weights of the criteria are determined by using the Best-Worst method. Four factors are extracted by applying Factor Analysis to the supplier risk data. Then k-means clustering algorithm is applied to group core suppliers of the company based on the four risk factors. Three clusters are created with different risk exposure levels. The interpretation of the results provides insights for risk management actions and supplier development programs to mitigate supplier risk. View Full-Text
Keywords: cluster analysis; corporate sustainability; risk assessment; supplier evaluation and selection; supply risk cluster analysis; corporate sustainability; risk assessment; supplier evaluation and selection; supply risk
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Er Kara, M.; Oktay Fırat, S.Ü. Supplier Risk Assessment Based on Best-Worst Method and K-Means Clustering: A Case Study. Sustainability 2018, 10, 1066.

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