Ranking Suppliers in FMCG Industries Using Fuzzy WASPAS: A Case Study in Arak Metropolis
Publish place: International Journal of Innovation in Management, Economics and Social Sciences، Vol: 4، Issue: 4
Publish Year: 1403
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJIMES-4-4_002
تاریخ نمایه سازی: 23 دی 1403
Abstract:
Purpose: Decision-making refers to the process of selecting an alternative from among available alternatives, including analyzing relevant information, considering potential outcomes, and evaluating the effects of each alternative. Decisions can be made in various life situations, including personal, professional, financial, and organizational issues. One of the most important organizational decisions is selecting the [most] appropriate supplier, which is a multi-criteria decision. Such decisions are usually complex and unstructured in nature. Management science today can greatly help deal with such problems. This paper aims to apply the fuzzy WASPAS technique to select the best chicken meat supplier in a city in Markazi Province to ensure maximum compliance with the specified criteria. These criteria were obtained through interviews with store managers. They employed the abovementioned criteria to evaluate and select chicken meat suppliers and related products.Methodology: The opinions of chicken meat store managers (n=۲۴ in total) were collected using tools such as questionnaires. The linguistic variables obtained from the questionnaires were transformed by the Fuzzy Likert Scale (FLS). The latest version of MATLAB software was used to analyze the data.Findings: According to the results, after applying the FWASPAS method, out of six suppliers, three were selected as the best considering the identified criteria. Herein, all analyses were conducted in Excel. The results also demonstrated that Supplier #۶ (i.e., Dorsa Morgh Co.) performed best in ۲۰۲۳.Originality/value: This research identifies the best chicken meat supplier company using the fuzzy WASPAS technique.Purpose: Decision-making refers to the process of selecting an alternative from among available alternatives, including analyzing relevant information, considering potential outcomes, and evaluating the effects of each alternative. Decisions can be made in various life situations, including personal, professional, financial, and organizational issues. One of the most important organizational decisions is selecting the [most] appropriate supplier, which is a multi-criteria decision. Such decisions are usually complex and unstructured in nature. Management science today can greatly help deal with such problems. This paper aims to apply the fuzzy WASPAS technique to select the best chicken meat supplier in a city in Markazi Province to ensure maximum compliance with the specified criteria. These criteria were obtained through interviews with store managers. They employed the abovementioned criteria to evaluate and select chicken meat suppliers and related products. Methodology: The opinions of chicken meat store managers (n=۲۴ in total) were collected using tools such as questionnaires. The linguistic variables obtained from the questionnaires were transformed by the Fuzzy Likert Scale (FLS). The latest version of MATLAB software was used to analyze the data. Findings: According to the results, after applying the FWASPAS method, out of six suppliers, three were selected as the best considering the identified criteria. Herein, all analyses were conducted in Excel. The results also demonstrated that Supplier #۶ (i.e., Dorsa Morgh Co.) performed best in ۲۰۲۳. Originality/value: This research identifies the best chicken meat supplier company using the fuzzy WASPAS technique.
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Authors
Asma Etebari
Department of Industrial Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran
Rahmat Arab *
Department of Industrial Engineering, Gorgan Faculty of Engineering, Golestan University, Gorgan, Iran.
Mohammad Amirkhan
Department of Industrial Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran
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