Integrative analysis of climate change drivers using ISM DEMATEL approach for structural decision making

This study aims to explore and structure the complex interplay of key climate change drivers using an integrated Interpretive Structural Modeling (ISM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach. By focusing on 14 variables identified through expert consensus, the study seeks to uncover the hierarchical structure and causal relationships influencing climate change, particularly within the context of developing countries such as Indonesia. Structured expert interviews were conducted to build the Structural Self-Interaction Matrix (SSIM), followed by the construction of Initial and Final Reachability Matrices (IRM and FRM). DEMATEL analysis was then applied to derive the Total Influence Matrix and identify cause-effect groupings. The findings reveal that deforestation (V1), industrial emissions (V4), and weak environmental regulations (V10) emerge as high-impact causal factors. Meanwhile, renewable energy adoption (V14) and population growth (V9) appear as highly dependent effects. ISM partitioning highlighted foundational factors at lower levels and more symptomatic outcomes at the top, offering a layered understanding of intervention priorities. This integrated framework enables the identification of leverage points that could guide more coherent and impactful climate strategies. The study’s main contribution lies in providing a methodological synthesis of ISM and DEMATEL to model climate drivers holistically. Unlike previous research that often treats these drivers in isolation, this approach unveils their interdependencies and dynamic influences. The originality of this work stems from its application in the Southeast Asian context, providing empirical insights and strategic directions for climate governance in similarly vulnerable regions.Clinical trial number: Not applicable.