A new fuzzy BWM approach for evaluating and selecting a sustainable supplier in supply chain management

汽车工业 供应链 模糊逻辑 供应商评价 供应链管理 持续性 计算机科学 供应商关系管理 运筹学 可持续价值 价值(数学) 领域(数学) 业务 人工智能 营销 数学 工程类 机器学习 生态学 生物 航空航天工程 纯数学
作者
M. Amiri,Mohammad Hashemi-Tabatabaei,Mohammad Ghahremanloo,Mehdi Keshavarz-Ghorabaee,Edmundas Kazimieras Zavadskas,Audrius Banaitis
出处
期刊:International Journal of Sustainable Development and World Ecology [Taylor & Francis]
卷期号:28 (2): 125-142 被引量:127
标识
DOI:10.1080/13504509.2020.1793424
摘要

Sustainability has become one of the most important issues in the field of supply chain management (SCM). In recent years, many studies have been conducted about how to select a sustainable supplier and different methods have been proposed for this purpose in fuzzy and deterministic environments. A review of the research literature reveals that decision-makers have paid more attention to the results of fuzzy-based studies because they are more accurate and precise in collecting data. The purpose of this paper is to present a new model with a triangular fuzzy approach for sustainable supplier selection (SSS) in the supply chain. The proposed fuzzy model is based on the best-worst method (BWM) and α-cut analysis in which the decision-maker (DM) can determine the alpha value between 0.1 and 0.9, depending on the level of uncertainty. A high value of alpha indicates low uncertainty and its low value indicates a high uncertainty in decision-making. To illustrate the model and demonstrate its capability, a real SSS case in Iran Khodro Company (IKCO), was examined by three experts in the automotive industry and the decision criteria were selected based on the literature review and expert opinions. The results show that the first supplier (ISACO Parts Supply Company) is the most sustainable supplier.
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