Modeling Challenges in Low-Carbon Manufacturing Adoption Using the ISM-MICMAC Approach: A Case of Green Tech Projects of the Chinese Automotive Industry

Abstract

In addressing the issue of climate change, the Chinese government has established a definitive objective to attain its peak carbon emissions by 2030 and strive for carbon neutrality by 2060. This effort aims to progressively achieve a state of net-zero carbon dioxide (CO2) emissions. In the given scenario, this research examines challenges in promoting low-carbon manufacturing (LCM) within the Chinese automotive sector, specifically in the context of Green Tech projects. In view of greater emphasis on environmental sustainability and technological innovation, this study aims to uncover challenges restraining the adoption of LCM in one of the world’s largest automotive markets, China. A three-step methodology was adopted by incorporating a literature review, the Delphi method, Interpretive Structural Modeling (ISM), and MICMAC analysis. In the first stage, relevant articles were selected scientifically to identify the main challenges in previous studies by following the relevant keyword criteria. Further, challenges identified from the comprehensive literature review were screened through the Delphi method, and finally, challenges were modeled and clustered through ISM and MICMAC analysis. Data collected from the experts highlight that “difficulties in the transition towards energy efficient technologies”, “insufficient operational efficiency”, and “information imbalances and asymmetry” were the most critical challenges that hinder LCM initiatives in the automotive industry. This research serves as a valuable resource for academia, industry professionals, and policymakers in the quest to adopt LCM in the dynamic context of the Chinese automotive sector.