Document Type : Research Paper

Authors

• sima zinalpour ¹
• Saeed Yaghoubi ²
• Tahmomoures Sohrabi ³

¹ PhD student of Industrial Management, Faculty of Management, Islamic Azad University, Central Tehran Branch, Tehran, Iran

² Associate Professor, Department of Logistics and Supply Chain Engineering, School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

³ Assistant Professor, Department of Industrial Management, Faculty of Management, Islamic Azad University, Central Tehran Branch, Tehran, Iran

Abstract

The high accuracy difference of nonlinear Bayesian averaging models compared to classical models indicates the failure of classical models. Classical models do not have the ability to determine the optimal model and always follow a predetermined pattern. Accordingly, to improve this gap, a hybrid of nonlinear Bayesian averaging models and panel time-varying parameters has been used to model the risk of the automotive industry. The time period of the present study was from 2011to2023, and in this study, information from 57 companies active in the automotive industry on the Tehran Stock Exchange was used. 119 risks affecting the automotive industry supply chain were identified. Based on nonlinear Bayesian averaging approaches, 15 unsystematic risk indicators and 13 systematic risks were identified as the most important risks to the supply chain. After identifying the factors, an attempt was made to examine these factors over time in the automotive industry supply chain based on the TVP-PFAVR approach. Given that the significant proportion of systematic risk in the supply chain is higher than unsystematic risk, the stability of the economic and business environment, good governance, and political environment should be on the agenda over management stability. In fact, stabilization policies in the form of demand-side policies, including monetary-fiscal policies, should be included in the Central Bank's mandate to reduce the economic-financial risks of the automotive industry supply chain. Given the significance of financing constraint indicators in creating systematic risk, ranking automotive industry companies is strongly recommended to optimally allocate financial resources to these companies.

Keywords

• Supply Chain
• Systematic and Unsystematic Risk؛ Automotive Industry
• Bayesian Approach
• Panel Time Variable Parameter

Main Subjects

• supply chain management