Supply chain risks and mitigation strategies in Turkey automotive industry: findings from a mixed-method approach

Abstract

This research aims to develop an assessment model to determine appropriate risk mitigation strategies for the automotive supply chain risks. A two-phased mixed-method approach is adapted, whereas a quantitative one follows qualitative research. Data were collected from 20 supply chain experts of 15 different automotive companies in Turkey. Interviews were conducted with supply chain experts to identify the risks, risk mitigation strategies, and probabilities. Then, a Bayesian network model was created to determine the probabilities of risks and risk mitigation strategies. Scenario and sensitivity analyses were performed to assess the robustness of the model. Operational risk, on the other hand, is ranked the last. Collaboration and flexible transport emerged as the most effective risk mitigation strategies to deal with supply chain risks. This study is expected to contribute significantly to the literature as it is the first to address the risks, risk factors, and risk mitigation strategies in the automotive sector using Bayesian networks.