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Gharahkhani, Marjan, Nahavandi, Nasim, AMIRI-AREF, Mehdi. (1405). Resilient Supplier Selection with a Novel Clustering Method and Improved Rank Reversal: Application in Retail Sector. , (), -. doi: 10.22059/ijms.2026.386606.677232
Marjan Gharahkhani; Nasim Nahavandi; Mehdi AMIRI-AREF. "Resilient Supplier Selection with a Novel Clustering Method and Improved Rank Reversal: Application in Retail Sector". , , , 1405, -. doi: 10.22059/ijms.2026.386606.677232
Gharahkhani, Marjan, Nahavandi, Nasim, AMIRI-AREF, Mehdi. (1405). 'Resilient Supplier Selection with a Novel Clustering Method and Improved Rank Reversal: Application in Retail Sector', , (), pp. -. doi: 10.22059/ijms.2026.386606.677232
Gharahkhani, Marjan, Nahavandi, Nasim, AMIRI-AREF, Mehdi. Resilient Supplier Selection with a Novel Clustering Method and Improved Rank Reversal: Application in Retail Sector. , 1405; (): -. doi: 10.22059/ijms.2026.386606.677232

Resilient Supplier Selection with a Novel Clustering Method and Improved Rank Reversal: Application in Retail Sector

Interdisciplinary Journal of Management Studies
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 26 خرداد 1405
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/ijms.2026.386606.677232
نویسندگان
Marjan Gharahkhani1؛ Nasim Nahavandi* 2؛ Mehdi AMIRI-AREF3
1Industrial Engineering at Tarbiat Modares University, Tehran, Iran
2Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
3KEDGE business school
چکیده
This paper proposes a novel hybrid framework for resilient supplier selection within the retail industry by integrating data mining approaches with MCDM techniques. Specifically, we present a methodological structure that effectively avoids rank reversal in supplier ordering, which has been a common issue in traditional methods. Our proposed hybrid approach comprises: (1) identify key resilience criteria for supplier selection in retail companies; (2) the Analytic Network Process (ANP) to weight these criteria and factor analysis to identify strategic resilient factors; (3) a K-medoids clustering technique to enhance the efficiency of the MCDM process; and, (4) the VIKOR method to rank the clusters. A case study involving a major retail chain is utilized to demonstrate the applicability of the proposed approach. The performance analysis is conducted in two parts. First, the results are compared with those from an ANP-VIKOR method for validation and verification, yielding a correlation coefficient of 0.856. Second, we introduce a procedure to assess the proposed method's ability to avoid rank reversal, resulting in a score of 0.83. Numerical results reveal that the proposed framework effectively addresses the complexities of resilient supplier selection in the retail industry, overcoming the limitations of traditional MCDM methods by preventing rank reversal.
کلیدواژه‌ها
Resilient Supplier Selection؛ Rank Reversal؛ Retail Industry؛ Clustering MCDM
آمار
تعداد مشاهده مقاله: 13





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