Decision-making for enhancing thermal resilience: Identifying and prioritising intervention domains across social, economic, ecological, and technological systems

The compounding effects of climate change and urbanisation have intensified heatwave frequency and the urban heat island effect, posing growing risks to thermal comfort and public health. Enhancing thermal resilience requires coordinated interventions across social, economic, ecological, and technological systems. However, existing studies remain limited in clearly identifying key intervention domains and in understanding how these domains interact within an integrated systems perspective. Therefore, the overarching aim of this research is to identify key thermal resilience interventions, examine expert-perceived interrelationships among them, and develop an expert-informed decision-support analytical framework for interpreting and prioritising interventions. Focus groups with experts from China and the UK were conducted using a modified Problem Tree Analysis approach to elicit intervention-related problems, perceived causes and effects. A subsequent web-based survey was used to assess the perceived influence relationships among the identified intervention domains. These relationships were analysed using the Decision-Making Trial and Evaluation Laboratory-based Analytic Network Process (DANP) method. The results reveal distinct expert-perceived influence structures among intervention domains across Social-Economic-Ecological-Technological (SEET) system dimensions, while also highlighting the central role of policy development and planning and economic feasibility in shaping the implementation of intervention domains. The key contribution of this study is the development of an expert-informed decision-support analytical framework that systematically captures cross-dimensional influence relationships and supports the prioritisation of thermal resilience interventions. The findings provide an expert-informed analytical basis for supporting context-sensitive decision-making in urban heat adaptation under climate change.