4.6 Article

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

出版社

TAYLOR & FRANCIS INC
DOI: 10.1080/13504509.2020.1793424

关键词

Sustainability; fuzzy best-worst method; alpha-cut analysis; supplier selection; supply chain management

向作者/读者索取更多资源

Sustainability is becoming increasingly important in supply chain management, with fuzzy methods being more accurate and precise. A new model based on triangular fuzzy approach for sustainable supplier selection has been proposed in this study. The research shows that the most sustainable supplier identified through a real case study is ISACO Parts Supply Company.
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 alpha-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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据