Application of construal level theory in identifying factors affecting individual decision-making in implementing flood protection measures in rural areas of Iran

Floods are among the most frequent and destructive natural disasters globally, inflicting extensive damage on infrastructure, causing significant economic losses, displacing communities, and triggering public health crises. Developing countries are particularly vulnerable due to inadequate infrastructure, substandard housing, widespread poverty, and low adaptive capacity-challenges that are especially pronounced in rural areas. In the absence of effective mitigation systems, the impact of floods on rural communities can intensify, potentially resulting in the complete collapse of local livelihoods. Therefore, enhancing the resilience of these communities through targeted capacity-building and resilience strategies is essential. This study aims to identify the key factors influencing the adoption of flood preparedness measures in rural regions of Iran. The primary research instrument was a questionnaire, and the data were analyzed using Structural Equation Modeling (SEM). This study employed Construal Level Theory (CLT) as its theoretical framework. The findings revealed that CLT components-including geographical distance, temporal distance, social distance, hypothetical distance, belief in climate change, and flood risk perception-significantly influence the adoption of protective measures prior to flood events, collectively explaining 67.1% of the variance. Notably, this research marks the first application of CLT in the context of flood preparedness, both in Iran and globally. As such, it offers novel insights for the development of effective flood management strategies in rural communities and lays a foundation for strengthening the resilience of their livelihoods.