Future Studies on Developing University-Industry Collaboration in Iran's Automotive Sector

Abstract

This study aimed to identify key factors, develop scenarios for university-industry collaboration in Iran's automotive sector, and determine key strategies for achieving an optimal scenario by 2034. The present study adopted a future studies approach using the GBN scenario-planning method. To identify key factors, data were collected through semi-structured interviews with experts. Thematic analysis was employed to identify themes within the qualitative interview data. Data analysis was conducted using the Friedman test and MICMAC software to prioritize the drivers influencing the development of university-industry collaboration in the automotive sector. A total of 26 key factors were identified based on expert opinions in the fields of academia and the automotive industry through thematic analysis of interview texts. Two factors with the highest levels of importance and uncertainty were selected to develop the study’s scenarios: "Strengthening the innovation ecosystem in the automotive industry" and "Practical application of academic knowledge in the automotive sector." Four scenarios for the future of university-industry collaboration in the automotive sector were proposed: (1) technology transfer and localization, as well as extracting knowledge from leading countries and advancing academic knowledge with a focus on designing and producing fully electric vehicles, resulting in the creation of an "Iranian Tesla"; (2) neglecting the role of universities in the innovation system of the automotive industry, leading to technology transfer and knowledge extraction within the automotive industry; (3) utilizing research and development and supporting domestic research for the production and enhancement of a national hybrid vehicle; and (4) lack of university-industry collaboration and continuation of the current trend of producing assembled hybrid vehicles. Subsequently, key strategies for achieving the optimal scenario were presented, and the scenarios were validated.