Modelling the measures of supply chain performance in the Indian automotive industry

Abstract

Purpose – The purpose of this paper is to investigate the interactions among the key factors of supply chain (SC) in the Indian automotive industry. These key factors are helpful to measure supply chain performance (SCP) and to improve the firm’s effectiveness. Design/methodology/approach – In this paper, an interpretive structural modeling with a fuzzy cross-impact matrix multiplication applied to classification-based approach is used to examine the interactions among the key factors of SCP measurement. Findings – The authors have identified the most dominant key factors used for measuring the performance in automotive SC. The results exhibit that the order lead-time and order entry method are the most significant key factors. These key factors have high driving power to measure SCP whereas the post-transaction measure of customer service and customer query time are highly dependent on other factors. Such relationships among the key factors can help a firm’s top management to make essential judgments in order to solve the overall SC problems and provide a better approach to proactively deal with problems. Originality/value – In this paper, the authors have explored the interactions among the key factors of the SCP in the Indian automotive industry.