Applications of Data Envelopment Analysis in Supplier Selection

Publish Year: 1403
نوع سند: مقاله ژورنالی
زبان: English
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JR_BGS-6-4_008

تاریخ نمایه سازی: 23 آبان 1403

Abstract:

This paper delves into applying Data Envelopment Analysis (DEA) in supplier selection. DEA, a non-parametric mathematical programming technique, is employed to evaluate the relative efficiency of suppliers based on multiple input and output criteria. The study commences with a comprehensive literature review that explores the theoretical underpinnings of DEA and its application in supplier selection. Subsequently, the methodology section outlines the step-by-step process of implementing DEA in supplier evaluation, including identifying relevant input and output variables, data collection, and model formulation. The numerical results section presents a case study illustrating the application of DEA to a hypothetical supplier selection problem. The findings demonstrate the effectiveness of DEA in ranking suppliers based on their overall efficiency and identifying potential areas for improvement. The conclusion summarizes the paper's key contributions and discusses the implications of DEA for strategic supplier management. The paper concludes by highlighting potential avenues for future research in this domain.This paper delves into applying Data Envelopment Analysis (DEA) in supplier selection. DEA, a non-parametric mathematical programming technique, is employed to evaluate the relative efficiency of suppliers based on multiple input and output criteria. The study commences with a comprehensive literature review that explores the theoretical underpinnings of DEA and its application in supplier selection. Subsequently, the methodology section outlines the step-by-step process of implementing DEA in supplier evaluation, including identifying relevant input and output variables, data collection, and model formulation. The numerical results section presents a case study illustrating the application of DEA to a hypothetical supplier selection problem. The findings demonstrate the effectiveness of DEA in ranking suppliers based on their overall efficiency and identifying potential areas for improvement. The conclusion summarizes the paper's key contributions and discusses the implications of DEA for strategic supplier management. The paper concludes by highlighting potential avenues for future research in this domain.

Authors

Alireza Ataei

Department of Mathematics, Faculty of Intelligent Systems Engineering and Data Science, Persian Gulf University, Bushehr, Iran