Rural Households Agroforestry Technology Adoption in Assosa District, Benishangul Gumuz Regional State, Western Ethiopia
Data publikacji: 26 maj 2025
Zakres stron: 100 - 117
Otrzymano: 23 wrz 2024
Przyjęty: 08 kwi 2025
DOI: https://doi.org/10.2478/jlecol-2025-0022
Słowa kluczowe
© 2025 Addiselem Yasin et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Agroforestry technology is becoming increasingly important in regions where land is limited and population density is high. While it has the potential to enhance agricultural production, the sector is encountering several challenges. Farmers face various barriers in adopting agroforestry technologies, but research suggests that technology adoption plays a crucial role in overcoming these challenges and improving agricultural productivity. Thus, this study examined determinants of agroforestry technology adoption in the Assosa district, Benishangul Gumuz Regional State (BGRS), Western Ethiopia. The research used both primary and secondary data, and 173 household heads were selected using a multistage stratified random sampling technique. Descriptive statistics and inferential statistics, including ANOVA and chi-square tests, along with an ordered logit model, were employed for analysis. The findings revealed that most (61.7 %) households had a low level of agroforestry technology adoption, followed by medium (30 %) and high levels (8.3 %). Additionally, the study shows significant differences in terms of age, farm incomes and frequency of extension contact of rural households across these adoption categories at 1 % of significance level; but, livestock ownership exhibit significance difference at 10 % of significance level. The ordered logit model results indicated that factors such as the age and family size of the household head shows significant difference 10 % of significance level; off-farm income, total land holding, access to credit and extension contacts exhibit significant difference 5 % of significance level. Additionally, farm income of households significantly affects the extent of agroforestry technology adoption at 1 % of significance level. Notably, the study found that total land holding had a positive impact on agroforestry technology adoption. The implications of this study suggest the need for policies that enhance farmers’ potential for adopting agroforestry technology, including improving extension services, increasing access to off-farm and non-farm opportunities, creating a favorable environment for livestock production, and enhancing the knowledge of elder farmers.