Behavioral Drivers of Farmers’ Adaptation and Maladaptation to Natural Disasters in Coastal Odisha, India

Understanding the behavioral dimensions of climate change adaptation is critical for building resilient farming systems, particularly in regions like coastal Odisha, India, where smallholder farmers face recurring climatic threats such as cyclones, floods, and erratic rainfall. This study applied structural equation modeling (SEM) using AMOS 20 to examine the determinants of farmers’ adaptation decisions, drawing on data collected from 240 respondents across Puri and Khordha districts. The conceptual model tested eight latent constructs: risk evaluation, adaptation evaluation, maladaptation, social discourse, exact adaptive capacity, adaptation incentives, trust in national adaptation plans, and adaptation decision. Results revealed that the most influential predictor of adaptation decision was maladaptation (β = 0.650, p < 0.001), followed by adaptation evaluation (β = 0.248, p < 0.001) and risk evaluation (β = 0.155, p < 0.001). Social discourse significantly influenced adaptation evaluation (β = 0.598, p < 0.001), while risk evaluation negatively predicted maladaptation (β = -0.246, p < 0.001). Trust, adaptive capacity, and adaptation incentives were found to be statistically non-significant in the decision-making process. These findings suggest that adaptation behavior is shaped not only by rational assessments of risk and strategy efficacy, but also by deep-seated psychological constructs such as fatalism and denial. The study contributes to the climate adaptation literature by empirically validating a comprehensive behavioral model specific to high-risk agrarian systems and offers actionable insights for designing context-specific, psychologically informed interventions that support long-term adaptation in disaster-prone regions.