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https://dx.doi.org/10.20372/na...
Thesis . 2024
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
https://dx.doi.org/10.20372/na...
Thesis . 2024
License: CC BY
Data sources: Datacite
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DETERMINANTS OF THE ADOPTION RATE OF IMPROVED AGRICULTURAL TECHNOLOGIES AMONG FARMERS" IN CASE OF GUBALAFTO WOREDA

Authors: SETEGN DEMLIE YIMAM;

DETERMINANTS OF THE ADOPTION RATE OF IMPROVED AGRICULTURAL TECHNOLOGIES AMONG FARMERS" IN CASE OF GUBALAFTO WOREDA

Abstract

Abstract This study analyzed the determinants of the adoption rate of improved agricultural technologies among farmers in Gubalafto woreda and the impact of adoption rate of technology on the welfare of households in the study area. The data used for the study were obtained from 343 randomly selected sample households in the study area. Multiple linear regression model was employed to analyze the determinants of farmers’ decisions to adopt modern technologies. Regression result shows that from eleven explanatory variables nine variables such as sex of HH, family size, education level, social network, income, extension service, credit service, Market distance and farm size are significant at 5%level of significance. Except Market distance all significant variables affected adoption rate positively. Based on these findings it is recommended that the zonal and the woreda leaders extension agents farm and education experts, policy makers and other development oriented organizations have to plan in such a way that the farm households in the study area will obtain sufficient education, credit accessibilities and also have to train farmers to make them understand the benefits obtained from adopting the new technologies. These bodies have also to arrange policy issues that improve farm labor participation of household members and also to arrange the ways in which farmers obtain means of income outside farming activities.

Keywords

Agriculture, Farm household, Technology Adoption rate, multiple linear regression models

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average