Journal
CLIMATE AND DEVELOPMENT
Volume 13, Issue 2, Pages 152-163Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/17565529.2020.1737797
Keywords
Drought; adaptation; protection motivation theory; cognitive process; agricultural extension
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Empirical evidence shows that farmers can effectively manage the negative impact of drought by changing their farming practices, with adaptation being crucial in reducing vulnerability. Understanding farmers' responses to drought events can broaden adaptation options and enhance sector resilience. Knowledge of farmers' adaptive decision-making at the farm level is essential for designing effective public drought adaptation strategies.
Empirical evidence has revealed that farmers can manage the negative impact of drought effectively by changing and adapting their current farming practices. Adaptation is thus a focal point in reducing farmers' vulnerability. Knowledge of what farmers do in response to drought events can broaden adaptation options and improve resilience within the sector. To design effective public drought adaptation strategies, it is crucial to understand farmers' adaptive decision-making at the farm level. The aim of this study was thus to investigate farmers' ongoing adaptation measures and to identify factors influencing their choice of methods. To identify the factors influencing farmers' decisions, we used Protection Motivation. The study was designed as a cross-sectional survey. The population of interest consisted of farmers in Dehloran, in the Ilam Province of southwestern Iran. The study sample consisted of 320 farmers selected through a multistage random sampling procedure. The structural equation modelling result revealed that the response efficacy, perceived vulnerability and response cost respectively had a significant effect on the adaptive response. From the practical point of view, the present study provides a justification for using constructs of the Protection Motivation Theory in policy and decision-making aimed at encouraging farmers to reduce drought risks.
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