4.6 Article

Why Have Economic Incentives Failed to Convince Farmers to Adopt Drip Irrigation in Southwestern Iran?

Journal

SUSTAINABILITY
Volume 14, Issue 4, Pages -

Publisher

MDPI
DOI: 10.3390/su14042055

Keywords

water scarcity; irrigation system; social capital; socio-economic characteristics; adoption technology

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This study examines the factors influencing the adoption of improved irrigation technology in Iran, focusing on farmers' socio-economic characteristics, social capital, and technology characteristics. The findings suggest that socio-economic factors are the strongest predictor of adoption, followed by technology characteristics and social capital. The results provide valuable insights for agricultural extension agents and policy-makers to design effective strategies for increasing the adoption rate of drip irrigation.
Sustainable water usage is an important global concern and an urgent priority, especially in dryland regions such as Iran. The Iranian government is actively addressing the challenge of water scarcity by encouraging farmers to adopt new water application technology. Its main element to decrease water consumption is to encourage new irrigation systems, in particular drip irrigation. However, despite the benefits of drip irrigation technologies and the availability of generous government subsidies, adoption rates of the improved irrigation technology remain critically low among Iranian farmers. Therefore, this study seeks to determine what is limiting the uptake of improved irrigation technology in Iran. While it is well known that acceptance of new technology ultimately depends on multiple and interrelated factors, we examine those factors affecting farmers' adoption from three theoretical perspectives in the adoption literature: farmers' socio-economic characteristics, social capital, and technology characteristics. A cross-sectional survey was undertaken in Behbahan district in Khuzestan province in southwest Iran. The sample comprises 174 farmers who adopted drip irrigation in that region and 100 non-adopters who were located in the same region. Discriminant analysis reveals that a socio-economic approach is the strongest model to predict adoption of drip irrigation technology in the study area, followed by models of technical characteristics, and social capital. These results can help agricultural extension agents and policy-makers design appropriate and effective strategies that facilitate the adoption of drip irrigation at an increasing rate.

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