Identification of Evaluation indicators in Automotive Industry LARG Supply Chain via Fuzzy Best-Worst Method: The Case of Saipa Yadak Company

Abstract

The current study was undertaken to identify evaluation indicators of LARG supply chain in Saipa Yadak Company initially through fuzzy screening and further to weight and prioritize them through fuzzy best-worst method. The research population comprised 20 senior managers at Saipa Yadak Company with at least 10 years of administrative experience within the supply chain management sector. The enquiry started with an extensive review of existing literature on the theoretical foundations and interviewing experts to identify indicators of LARG supply chain via fuzzy screening procedure. Having screened the indicators, we designed a paired comparison questionnaire which was piloted and distributed among the experts. The data obtained from the questionnaires were weighted and ranked using fuzzy best-worst method. The findings identified accountability, environmental function, speed of knowledge and technology, participation and support, human resource management, relation with suppliers and customers, competency, flexibility, and, cost and operation control as the most important indicator of the LARG supply chain, respectively. In addition, each indicator was weighted and prioritized to provide support for managers of at automotive industry through LARG supply chain evaluation and assist them in selecting effective solutions to reduce supply chain risks, and thereby, to facilitate decision making.

Keywords

• automotive industry
• fuzzy best-worst method (fbwm)
• fuzzy screening procedure
• larg supply chain