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Supplier selection and stepwise benchmarking: a new hybrid model using DEA and AHP based on cluster analysis

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  • Sung Chul Park
  • Jang Hee Lee

Abstract

This study proposes a new comprehensive methodology for supplier evaluation, selection, and improvement. A hybrid approach for evaluation and selection is presented using an expectation maximization (EM) algorithm for clustering, data envelopment analysis (DEA) for efficiency, and analytic hierarchy process (AHP) for importance. First, industrial taxonomy and EM algorithms are used to cluster the suppliers. Then, DEA is utilized to calculate internal operation efficiency. Next, AHP is applied to assess external function importance. After the weighted efficiency and importance scores are combined, the suppliers for improvement and strategic improving direction are determined based on a quadrant and diamond graph analysis. Finally, based on the supplier clusters, the effective stepwise benchmarking paths are presented with improvement strategies, and the final target indicators are obtained through DEA projection analysis. The proposed method is successfully demonstrated on 63 tier-one suppliers in the Korean automobile industry using three-year panel data from 2012 to 2014.

Suggested Citation

  • Sung Chul Park & Jang Hee Lee, 2018. "Supplier selection and stepwise benchmarking: a new hybrid model using DEA and AHP based on cluster analysis," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(3), pages 449-466, March.
    • Handle: RePEc:taf:tjorxx:v:69:y:2018:i:3:p:449-466
    DOI: 10.1057/s41274-017-0203-x
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    Cited by:

    1. Wei Song & Zhiya Chen & Aijun Liu & Qiuyun Zhu & Wei Zhao & Sang-Bing Tsai & Hui Lu, 2018. "A Study on Green Supplier Selection in Dynamic Environment," Sustainability, MDPI, vol. 10(4), pages 1-22, April.
    2. Petra Tomanová & Michal černý, 2022. "Efficiency of antiquarian bookshops in informationally complete markets," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 573-593, June.
    3. Monge, Juan F. & Ruiz, José L., 2023. "Setting closer targets based on non-dominated convex combinations of Pareto-efficient units: A bi-level linear programming approach in Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 311(3), pages 1084-1096.
    4. Pankaj Dutta & Bharath Jaikumar & Manpreet Singh Arora, 2022. "Applications of data envelopment analysis in supplier selection between 2000 and 2020: a literature review," Annals of Operations Research, Springer, vol. 315(2), pages 1399-1454, August.

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