Ranking of Outsourcing Risks in Supply Chain of Automotive Industry Using Fuzzy AHP and Fuzzy Inference System

Competition is the driving force of today's economy and it is vital for organizations to gain competitive advantages. In recent years, outsourcing has been the focus of managers as a tool for developing organizations and improving productivity. This study deals to analyze the outsourcing risks of the supply chain in the automotive industry using fuzzy inference systems. For this purpose, in the first stage, outsourcing risk identified using research literature, then to summarize, a questionnaire is designed and provided to the experts of the automotive industry. Some of the factors were eliminated by experts’ opinion and finally, nine main criteria (preparedness, selectivity, implementation, organizational output, supply, production, distribution and environment risk) and 43 sub-criteria were identified. Then, for each risk, three components of severity, probability and seriousness were measured and performance analysis criteria were identified and weighted by experts in the fuzzy hierarchical process. Research results after prioritizing, show that "inappropriate planning" with the weight of 0.029921 is in the first priority and "production capacity" and "the danger of war" risks with the weight of 0.02964 jointly were in the second priority.  Finally, using a fuzzy inference system, the outsourcing risks in the supply chain of Saipa automotive company is analyzed to get the performance evaluation.