Designing assessment model of the automotive industries supply chain resistance

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Aim & Background

by increasing the occurrence of disruptions and unexpected changes in the business, the development of a resistant supply chain is a key opportunity for leading companies to gain a competitive advantage and turn threats into unique opportunities. on the other hand, in order to develop a resistant system, the need to monitor and evaluate the current position and planning of improvement route will be undeniable and inevitable. the purpose of this study is to provide a model for assessing the supply chain resistance in the automotive industries.  

Method

In terms of purpose, research is a developmental one. In terms of implementation, it is a descriptive research and from philosophical point of view, it is interpretive. to achieve the research’s goal, in the first step, the most important enablers of supply chain resistance in the automotive industry were identified. then, through interpretive - structural modeling, the causal relationships between them were explained by experts. in the next step, by the graph theory method and matrix approach, the degree of supply chain resistance in optimal, current and minimum conditions in  Pishgam part producing company was determined and the results sensitiveness was analyzed.

Findings

The supply chain resistance of this company is at the level of  %31.23. Sensitivity analysis showed that enabling the risk and income sharing, supply chain adaptability and structure are the first to third priority to improve the resistance level of the company's supply chain.

Conclusion

Enabling supply chain structure, cooperation, trust, information sharing and openness are key factors and facilitate the improvement process of other enablers. Financial strength enabler is effect and is acquired  from the improvement of other incentives and will facilitate the process of achieving a resistant supply chain. this model helps managers evaluate the consequences of their decisions to improve supply chain resistance.

Language:
Persian
Published:
Journal of Logistics Thought Scientific Publication, Volume:20 Issue: 78, 2021
Pages:
103 to 128
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