Identifying and Analyzing Supply Chain Risks of Saipa Automobile Company using the Coso Model and Social Network Analysis (SNA)

This paper aimed at identifying and analyzing supply chain risks of Saipa automotive company to determine those seemly critical and the appropriate decision for each category to be made. To this end, first, according to company’s documents and interviews with experts, and using theme analysis method, the identification and categorization of supply chain risks are addressed. In the second step, by using of SNA approach, the most important risks in terms of the effects they have on emerging other risks in the risks’ relationship network are determined. The results are analyzed using the IPM matrix and the necessary decisions are made according to this matrix. According to the results, 48% of the total risks are categorized in financial-economic, suppliers, information, and transportation categories. Therefore, it seems that paying particular attention to these areas can result in significant improvement in system’s status. Introduction: The automotive industry is the second largest industry in Iran, the survival of which is of great importance for the country. Today, various factors, such as fluctuations in the foreign exchange market, have led to uncertainties in this industry. In addition, other factors, including increasing the variety of products and services, reducing product life cycle, demand fluctuations, rising costs, technological changes, political issues, financial instability, and natural disasters have also increased the uncertainty and risk in the industry’s supply chain. On the other hand, the automotive industry has faced many risks owing to its long supply chain, in which diverse companies interact with each other. Hence, the supply chain risk management of this industry to identify and evaluate the risks and reduce their adverse effects is counted as a critical issue on which many researchers have been embarked. So far, various models, such as Fault Tree Analysis (FTA) (Zhang et al., 2016) and Failure Modes and Effects Analysis (FMEA) (Liu & Zhou, 2014) have been developed as risk analysis tools. However, in these models, each risk, its significance, and its impact on the performance of the company or supply chain has been deemed as a single concept regardless of various possible relationship among different kinds of risks in the system. Regarding the promising relationships among different types of risks, some have used Analytic Hierarchical Process (ANP) method (Talebi & Iron, 2015) to evaluate and prioritize the risks. The main problem