Design and Analysis of Automotive Supply Chain Enablers to Reduce the Bullwhip Effect Using Soft Systems Methodology, FCM, and ISM
Keywords:
Supply Chain, Bullwhip Effect, Enablers, Fuzzy Cognitive Mapping, Interpretive Structural Modeling (ISM)Abstract
The supply chain inherently possesses a high degree of complexity, which has become increasingly exacerbated due to globalization, market expansion, and the continuous evolution of customer preferences. This growing complexity may lead to asset invisibility, inefficient inventory management, or logistical mismanagement. These complications often culminate in the well-known phenomenon of the "Bullwhip Effect" (BE) within supply chains. The aim of this study is to identify the key enablers that effectively reduce the Bullwhip Effect in the automotive supply chain sector. This research is descriptive in methodology and applied in purpose. To determine the importance of critical enablers influencing the mitigation of the Bullwhip Effect, a thorough review of the literature was first conducted to identify a preliminary list of significant enablers. Subsequently, using the Fuzzy Delphi Method, the final set of influential enablers for minimizing the Bullwhip Effect in the automotive supply chain was identified. To analyze the interrelationships among the 13 foundational enablers—based on literature and data collected through questionnaires—the study employed Fuzzy Cognitive Mapping (FCM) and Interpretive Structural Modeling (ISM) to determine the most impactful enablers. FCMapper software was used for the FCM method, while Excel software facilitated the ISM approach. Based on centrality metrics within the Fuzzy Cognitive Mapping approach, five enablers were found to be critically important: information quality in the supply chain, big data, supply chain flexibility, customer relationship management, and trust in the supply chain. Additionally, business intelligence, visibility capability, supply chain agility, order volume, information sharing capability, coordination and collaboration in the supply chain, supply chain integration and transparency, and delivery time were ranked sixth to thirteenth, respectively. According to the ISM results, the following enablers were identified in order of significance as the primary factors in reducing the Bullwhip Effect in the automotive supply chain: big data, business intelligence, information sharing capability, integration and transparency, trust in the supply chain, delivery time, coordination and collaboration, visibility capability, information quality, customer relationship management, order volume, supply chain agility, and flexibility.
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Copyright (c) 2025 Sadegh Danandeh (Author); Davood Talebi (Corresponding author); Mohammad Mehdi Movahedi (Author)
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