Development of a Causal Model and Scenario Formulation for Industrial Resilience – The Auto Parts Manufacturing Industry

The aim of the present study was to develop a causal model and formulate scenarios for industrial resilience using a thematic analysis approach and Interpretive Structural Modeling (ISM) in the auto parts manufacturing industry. In this research, key drivers affecting industrial resilience were identified and selected through thematic analysis and expert interviews. According to the research findings, the overall distribution pattern of industrial resilience drivers in the auto parts manufacturing sector indicates an unstable environmental system. The results of the interpretive structural modeling also show that the most influential components of the resilience model are the presence of multiple suppliers and contractors, as well as employee training and knowledge transfer. Furthermore, the most impacted components of the resilience model in the auto parts industry include creating a platform for inter-company collaboration, implementing activities related to sales promotion, networking and cooperation with competitors, institutions, and research and knowledge-based organizations, product introduction and advertisement, and customer engagement and feedback collection.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.61838/medda.2.1.18
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
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article

Development of a Causal Model and Scenario Formulation for Industrial Resilience – The Auto Parts Manufacturing Industry

Morteza Mahmodzadeh, H Chitsaz, Sirous Fakhimi Azar, Yaghob Alavi Matin
2 links
Supply Chain Resilience and Risk Management
article

Development of a Causal Model and Scenario Formulation for Industrial Resilience – The Auto Parts Manufacturing Industry

Morteza Mahmodzadeh, H Chitsaz, Sirous Fakhimi Azar, Yaghob Alavi Matin
article en

Abstract

The aim of the present study was to develop a causal model and formulate scenarios for industrial resilience using a thematic analysis approach and Interpretive Structural Modeling (ISM) in the auto parts manufacturing industry. In this research, key drivers affecting industrial resilience were identified and selected through thematic analysis and expert interviews. According to the research findings, the overall distribution pattern of industrial resilience drivers in the auto parts manufacturing sector indicates an unstable environmental system. The results of the interpretive structural modeling also show that the most influential components of the resilience model are the presence of multiple suppliers and contractors, as well as employee training and knowledge transfer. Furthermore, the most impacted components of the resilience model in the auto parts industry include creating a platform for inter-company collaboration, implementing activities related to sales promotion, networking and cooperation with competitors, institutions, and research and knowledge-based organizations, product introduction and advertisement, and customer engagement and feedback collection.

Vol. 2(1)
Openalex Percentile: Top 82%
Supply Chain Resilience and Risk Management
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