THE SELECTION OF THE MOST SUITABLE SUPPLIER IN SUSTAINABLE SUPPLY CHAIN WITH AHP, TOPSIS AND ELECTRE METHODS

Authors

  • Tuğba ÇİÇEK Düzce Üniversitesi Sosyal Bilimler Enstitüsü
  • Mehmet Selami YILDIZ Düzce Üniversitesi İşletme Fakültesi, İşletme Bölümü
  • İsmail DURAK Düzce Üniversitesi İşletme Fakültesi, İşletme Bölümü, Sayısal Yöntemler ABD

DOI:

https://doi.org/10.17740/eas.stat.2020‐V16‐01

Keywords:

AHP, TOPSIS, ELECTRE, Sustainable Supplier Selection

Abstract

To present the right product at the right place, time, in the right way and at the lowest possible cost, in a way to achieve customer satisfaction; it is critical for businesses to take sustainability as the main criterion when carrying out these operations. The selection of the most appropriate supplier within a sustainable supply chain is the problem of this research. For this purpose, AHP, TOPSIS and ELECTRE methods, which are multi-criteria decisionmaking techniques, have been applied on a firm. The economic, social and environmental criteria, which are the criteria of sustainability, were determined as the main criteria. In addition to these 3 main criteria, 12 sub-criteria were included in the study. The AHP method was used to determine the significance of the main criteria and subcriteria, while the TOPSIS and ELECTRE methods was used to select the most appropriate supplier. The main criteria according to their importance at the end of the study; while they are listed as economic, environmental and social criteria respectively; the most important sub-criteria are quality, price, delivery performance and environmental management system respectively. “Supplier A” has been selected as the supplier with the highest score among the current suppliers of the company.

Published

2020-05-15

How to Cite

ÇİÇEK, T., YILDIZ, M. S., & DURAK, İsmail. (2020). THE SELECTION OF THE MOST SUITABLE SUPPLIER IN SUSTAINABLE SUPPLY CHAIN WITH AHP, TOPSIS AND ELECTRE METHODS. Eurasian Eononometrics, Statistics and Emprical Economics Journal, 1–18. https://doi.org/10.17740/eas.stat.2020‐V16‐01

Issue

Section

Makaleler