Dynamic Modeling of Barriers to the Localization of Emerging ‎Technologies in the Automotive Industry Using ISM–MICMAC and ‎Fuzzy SWARA

Purpose:‎The main purpose of this study is to develop an integrated model for ‎identifying, prioritizing, and structurally analyzing the barriers to the ‎localization of emerging technologies in the automotive industry using ‎multi-criteria decision-making and structural modeling methods. The study ‎seeks to identify the key barriers, determine their relative importance, and ‎examine the causal relationships among them.‎Methodology:‎This study is applied in purpose and descriptive–analytical in nature. In the ‎first stage, barriers to technology localization were identified through a ‎systematic literature review and expert opinions from specialists in ‎technology management and the automotive industry. Subsequently, the ‎Fuzzy SWARA method was employed to assign weights to and prioritize ‎the identified barriers. Interpretive Structural Modeling (ISM) was then ‎used to analyze the structural relationships and determine the causal ‎linkages among the barriers. Finally, MICMAC analysis was applied to ‎classify the barriers into four categories—driving, linkage, dependent, and ‎autonomous—based on their driving power and dependence.‎Findings:‎The findings indicated that inadequate technological infrastructure, ‎insufficient investment in research and development, and dependence on ‎foreign technologies are among the most influential barriers to technology ‎localization. The ISM results also revealed a hierarchical structure among ‎the identified barriers, in which infrastructural factors at the lower levels ‎act as the main drivers of other barriers. Furthermore, the MICMAC ‎analysis showed that certain factors play critical linkage roles within the ‎system and exert the greatest influence on the dynamics of the overall ‎structure.‎Originality/Value:‎The originality of this study lies in the integration of Fuzzy SWARA, ‎ISM, and MICMAC methods to simultaneously analyze the importance, ‎structural relationships, and systemic roles of barriers to technology ‎localization. By accounting for uncertainty in expert judgments, this ‎approach enables a network-based and multilevel analysis of the barriers ‎and improves decision-making accuracy in technology policy-making. ‎

کلیدواژه ها:

Technology localization ، strategic industries ، Fuzzy SWARA ، ISM ، MICMAC ، multi-criteria ‎decision-making ، structural analysis.‎