Factors Affecting Farmers' Adoption of Flood Adaptation Strategies Using Structural Equation Modeling

Floods are a frequent disaster in Bangladesh, and farmers are the most at risk. Understanding how to improve the farmers' flood adaption is important to reduce flood effects. Protection motivation theory (PMT) has been widely used to examine flood adaptation behavior, but there is still debate regarding the quantitative effect of PMT factors on flood adaption behavior, particularly in a geographically vulnerable context. This study integrates psychological aspects based on PMT to assess farmers' flood adaptability. A cross-sectional survey was conducted to collect data from 359 farmers. We employed structural equation modeling to test a PMT model with mediation analysis. The results showed that farmers who perceive a higher flood risk and feel more fear of floods are more likely to implement flood adaptation measures. Similarly, farmers adopt more adaptive actions if they have higher self-efficacy and response efficacy. However, they are less likely to take adaptive actions if they are subject to maladaptation. Maladaptation plays a significant role as a mediating variable. These findings will act as recommendations for government agencies to design policy measures to strengthen flood risk management. The study supports the theory of protection motivation to understand farmers' flood adaptation behavior. However, further study is required to enhance and generalize the existing model.

Automated summary

Flooding is a common disaster in Bangladesh, especially affecting farmers. This study examines the factors influencing farmers' flood adaptation behavior using the Protection Motivation Theory (PMT). The results show that perceived flood risk, fear of floods, self-efficacy, and response efficacy all have significant effects on farmers' adoption of flood adaptation measures. However, maladaptation plays a mediating role, reducing the likelihood of adaptive actions. These findings have implications for government agencies in developing policies to manage flood risk.