Factor influencing the adoption of sustainable agricultural practices in developing countries: a review
Developing countries have seriously low adoption rates of sustainable agricultural practices (SAPs) and there is a need to understand why. This paper reviews 31 past studies focusing on the factors influencing the adoption of SAPs. Using a vote count methodology, SAPs adoption is revealed as a compl...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Technical University of Iasi. Politehnium Publishing House
2017
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| Online Access: | http://psasir.upm.edu.my/id/eprint/61842/1/Factor%20influencing%20the%20adoption%20of%20sustainable%20agricultural%20practices.pdf http://psasir.upm.edu.my/id/eprint/61842/ http://www.eemj.icpm.tuiasi.ro/pdfs/vol16/no2/9_106_Tey.pdf |
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| Summary: | Developing countries have seriously low adoption rates of sustainable agricultural practices (SAPs) and there is a need to understand why. This paper reviews 31 past studies focusing on the factors influencing the adoption of SAPs. Using a vote count methodology, SAPs adoption is revealed as a complex set of behaviors which depend on a range of socio-economic, agroecological, institutional, informational, psychological factors and perceived attributes. Identified within these six dimensions, male farmers, higher educational attainment levels, bigger farm size, steeper farms, and the presence of land right security emerge as common factors which often lead to adopt SAPs. These factors imply the general importance of economic motivations in facilitating sustainable farm management. In particular, gender, farm topography, and land tenure have a special role in the context of developing countries. These common factors, and other converged factors, lend support to drawing general policymaking guidelines by identifying the characteristics of potential adopters, promotion strategies, and effective communication channels. For effective local management, future research should consider a range of factors from multiple categories and identify the relative importance of statistically significant ones. |
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