Abstract

The objective of this study was to evaluate the effects of adopting enhanced beehive technology on the welfare of rural households engaged in beekeeping activities in Ethiopia. We examined the impact of adopting enhanced beehive technology on welfare outcomes in the Wonchi districts using a two-stage random selection process and propensity score matching (PSM) methodology. This research offers novel perspectives on the adoption of enhanced beehive technology and its influence on household welfare outcomes in the field of beekeeping. It employs a comprehensive analysis that takes into account several dimensions, such as income, welfare, and spending. Our research findings indicate that several characteristics have a favorable impact on the adoption of enhanced beehive technology. These factors include the gender of the household head, the size of the land, the marital status of the household head, as well as the availability of extension services, input and credit services, and the total number of animals owned. On the other hand, age, dependency ratio, and proximity to farmer training facilities negatively impact the adoption of technology. The analysis using Propensity Score Matching (PSM) methodology demonstrated that the adoption of technology had a favorable influence on the income, wealth, non-food expenditure, and food expenditure of households. However, it is important to acknowledge some limitations. As the study relied on cross-sectional data from a specific region, its findings may not be generalizable to other locations or time periods. Additionally, self-reported data is subject to biases. Other potential limitations are the omission of other factors that could influence welfare outcomes and limited assessment of long-term sustainability. Based on our research results, policymakers should prioritize efforts to understand the determinants that facilitate the acceptance and utilization of enhanced beehive technologies in order to enhance the overall well-being of rural households. Further research is needed to address the study limitations.

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