Determinants of tractors adoption among smallholder farmers in Makuey district, Gambella region, Ethiopia
Article Sidebar
Main Article Content
Abstract
Background and Objective: The Gambella region has significant agricultural potential. However, various obstacles have prevented the development of agriculture and limited smallholder farmers’ capabilities to increase their income. This study aimed to determine the adoption of tractors by smallholder farmers in the Makuey district.
Methodology: The study sample comprised 250 smallholder farmers from the Makuey district. A multi-stage sampling technique was used, beginning with purposive sampling to choose the district because of its low tractor adoption by smallholder farmers. Simple random sampling was used to select kebelles, followed by random sampling of farmers within each village. Data were gathered through focus group discussions, structured interviews, questionnaires, and key informant interviews. The study employed mean, standard deviation, frequency, percentage, chi-square tests, t-tests, and binary logistic regression to analyze the data.
Main Results: The findings revealed that access to credit was positively associated with farmers’ tractor adoption (χ² = 10.000, P < 0.01). The total annual income showed a statistically significant mean difference (t = -3.470, P < 0.01) and farming experience (t = 2.015, P < 0.05) between adopters and non-adopters. Furthermore, binary logistic regression revealed that educational level (P < 0.05), cultural norms (P < 0.01), total annual income (P < 0.01), and access to subsidies (P < 0.01) were the main variables that influenced farmers’ tractor adoption.
Conclusions: Increasing tractor adoption among smallholder farmers is imperative and will require policy intervention. Increasing access to credit on favorable terms, strengthening farmer training programs, and improving income diversification can each contribute to alleviating financing and knowledge constraints. Reducing cultural norms through sensitization and raising subsidies or cheap loan rates for machinery would also facilitate adoption. Harmonizing these interventions can transform agriculture and enhance farm income in the region.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
Adesida, I.M., W. Nkomoki, M. Bavorova and M.Y. Madaki. 2021. Effects of agricultural programmes and land ownership on the adoption of sustainable agricultural practices in Nigeria. Sustainability. 13(13): 7249. https://doi.org/10.3390/su13137249.
Aryal, J.P., D.B. Rahut, G. Thapa and F. Simtowe. 2021. Mechanization of small-scale farms in South Asia: Empirical evidence derived from farm households survey. Technol. Soc. 65: 101591. https://doi.org/10.1016/j.techsoc.2021.101591.
Ayele, S. 2022. The resurgence of agricultural mechanization in Ethiopia: Rhetoric or real commitment?. J. Peasant Stud. 49(1): 137–157. https://doi.org/10.1080/03066150.2020.1847091.
Barbosa, M.W. 2024. Government support mechanisms for sustainable agriculture: A systematic literature review and future research agenda. Sustainability. 16(5): 2185. https://doi.org/10.3390/su16052185.
Bor, C. and K. Deng. 2024. Challenges and opportunities of tractor adoption by smallholder farmers in Gambella region, Ethiopia. Int. J. Mech. Eng. Appl. 12(5): 129–135. https://doi.org/10.11648/j.ijmea.20241205.12.
Challa, M. and U. Tilahun. 2014. Determinants and impacts of modern agricultural technology adoption in West Wollega: The case of Gulliso District. J. Biol. Agric. Healthc. 4(20): 63–77.
Cochran, W.G. 1977. Sampling Techniques. 3rd Edition. Wiley, New York, USA.
Crudeli, L., S. Mancinelli, M. Mazzanti and R. Pitoro. 2021. Beyond individualistic behaviour: Social norms and innovation adoption in rural Mozambique. World Dev. 157: 105928. https://doi.org/10.1016/j.worlddev.2022.105928.
Dawid, I., T. Gebiso and E. Boka. 2022. Comparative advantage of tractor utilization in Southeastern Oromia, Ethiopia. IJDEE. 10(2): 75–101.
Deepa, M. and K.V. Subramanyam. 2025. Empowering rural women - Drudgery reduction through mechanized weed management in Guntur District. Bhartiya Krishi Anusandhan Patrika. 40(1): 119–122. https://doi.org/10.18805/bkap743.
Degife, A.W. and W. Mauser. 2017. Socio-economic and environmental impacts of large-scale agricultural investment in Gambella region, Ethiopia. J. US-China Public Adm. 14(4): 183–197. https://doi.org/10.17265/1548-6591/2017.04.001.
Dong, L., Y. Li, Z. Sun, L. Zhang and H. Tang. 2024. Farmers’ non-agricultural income, agricultural technological progress, and sustainable food supply security: Insights from China. Sustainability. 16: 7929. https://doi.org/10.3390/su16187929.
Fekad, M. 2020. Gender, agriculture, food and nutrition security in Ethiopia: A critical review. IJRSAS. 6(2): 14–21. https://doi.org/10.20431/2454-6224.0602003.
Gorbachev, O. and M.J. Luengo-Prado. 2019. The credit card debt puzzle: The role of preferences, credit access risk, and financial literacy. Rev. Econ. Stat. 101(2): 294–309. https://doi.org/10.1162/rest_a_00752.
Green, W.H. 2003. Econometric Analysis. 5th Edition. Pearson, New Jersey, USA.
Gujarati, D.N. 2004. Basic Econometrics. 4th Edition. McGraw-Hill, New York, USA.
Guo, J., J. Chen and Y. Xie. 2022. Determining a reasonable concession period for risky transportation BOT projects with government subsidies based on cumulative prospect theory. Eng. Constr. Archit. Manag. 29(3): 1396–1426. https://doi.org/10.1108/ECAM-11-2019-0612.
Hosmer, D.W. and S. Lemeshow. 1980. Applied Logistic Regression. Wiley, New York, USA.
Hu, Y., B. Li, Z. Zhang and J. Wang. 2022. Farm size and agricultural technology progress: Evidence from China. J. Rural Stud. 93: 417–429. https://doi.org/10.1016/j.jrurstud.2019.01.009.
Jayasekara, D.N. 2021. Can traditional farming practices explain attitudes towards scientific progress?. Econ. Model. 94: 320–339. https://doi.org/10.1016/j.econmod.2020.10.012.
Khadka, D., K. Dhakal, M.S. Teli, H. Pokhrel, P. Sharma and M. Lamichhane. 2024. Status of farm mechanization and factor affecting its adoption among the rice (Oryzae sativa) farmers in Sarlahi district, Nepal. Arch. Agric. Environ. Sci. 9(3): 414–421. https://doi.org/10.26832/24566632.2024.090302.
Khaspuria, G., A. Khandelwal, M. Agarwal, M. Bafna, R. Yadav and A. Yadav. 2024. Adoption of precision agriculture technologies among farmers: A comprehensive review. J. Sci. Res. Rep. 30(17): 671–686. https://doi.org/10.9734/jsrr/2024/v30i72180.
Koppmair, S., M. Kassie and M. Qaim. 2017. The influence of farm input subsidies on the adoption of natural resource management technologies. Aust. J. Agric. Resour. Econ. 61(4): 539–556. https://doi.org/10.1111/1467-8489.12220.
Kropf, B. and H. Mitter. 2022. Factors influencing farmers’ climate change mitigation and adaptation behavior: A systematic literature review, pp. 243–259. In: Alpine Landgesellschaften zwischen Urbanisierung und Globalisierung. Springer VS Wiesbaden, Wiesbaden, Germany.
Liu, X., Z. Wang and X. Han. 2024. The impact of digital literacy on farmers’ green production behavior: Mediating effects based on ecological cognition. Sustainability. 16(17): 7507. https://doi.org/10.3390/su16177507.
Máquina, D.A., L.P.D.M. Castiano, B.A. Máquina and A.J.V. da Silva. 2024. Analysis of determinates for the adoption of agricultural technologies by family farmers in the administrative post of OCUA, Northern Mozambique. J. Appl. Biotechnol. Bioeng. 11(3): 54–58. https://doi.org/10.15406/jabb.2024.11.00360.
Martinez, P.D., D. Tancredi, M. Pavel, L. García and H.M. Young. 2024. Technology acceptance among low-income, Asian American older adults: Cross-sectional survey analysis. J. Med. Internet Res. 26: e52498. https://doi.org/10.2196/52498.
Mazur, M. and J. Bański. 2021. Means of production in agriculture, pp. 119–128. In: Transformation of Agricultural Sector in the Central and Eastern Europe after 1989. Springer, Cham, Switzerland.
Miller, R.L. 2015. Rogers’ innovation diffusion theory (1962, 1995), pp. 261–274. In: M. Al-Suqri and A. Al-Aufi, (Eds.), Information Seeking Behavior and Technology Adoption: Theories and Trends. IGI Global Scientific Publishing, Pennsylvania, USA.
Nakano, Y., T.W. Tsusaka, T. Aida and V.O. Pede. 2018. Is farmer-to-farmer extension effective? The impact of training on technology adoption and rice farming productivity in Tanzania. World Dev. 105: 336–351. https://doi.org/10.1016/J.WORLDDEV.2017.12.013.
Naveen, R., A. Kumar, R. Kumar, H.L. Kushwaha, M. Khanna, V. Ramasubramanian and S. Poojith. 2024. Assessment of whole-body vibration and development of mitigation intervention for single-axle tractor–trailer combination. Front. Mech. Eng. 10: 1426764. https://doi.org/10.3389/fmech.2024.1426764.
Ogisi, O.D. and T. Begho. 2023. Adoption of climate-smart agricultural practices in sub-Saharan Africa: A review of the progress, barriers, gender differences, and recommendations. Farm. Syst. 1(2): 100019. https://doi.org/10.1016/j.farsys.2023.100019.
Onomu, A.R. and M. Aliber. 2021. Factors influencing smallholder farmers’ mechanization decisions in Nigeria: The case of tractor use in the Fourth Industrial Revolution era. Asian J. Agric. Rural Dev. 11(2): 199–209. https://doi.org/10.18488/journal.ajard.2021.112.199.209.
Park, D.C. and E.T. Smith. 2022. Facilitation of cognition in older adults: Traditional and non-traditional approaches to inducing change. Med. Res. Arch. 10(10). https://doi.org/10.18103/mra.v10i10.3192.
Quaye, W., J.A. Onumah, M. Boimah and A. Mohammed. 2022. Gender dimension of technology adoption: The case of technologies transferred in Ghana. Dev. Pract. 32(4): 434–447. https://doi.org/10.1080/09614524.2021.2000588.
Ruzzante, S., R. Labarta and A. Bilton. 2021. Adoption of agricultural technology in the developing world: A meta-analysis of the empirical literature. World Dev. 146: 105599. https://doi.org/10.1016/J.WORLDDEV.2021.105599.
Teklewold, H. 2021. How effective is Ethiopia’s agricultural growth program at improving the total factor productivity of smallholder farmers?. Food Sec. 13: 895–912. https://doi.org/10.1007/s12571-021-01175-7.
Thamsuwan, O., S. Milosavljevic, D. Srinivasan and C. Trask. 2020. Potential exoskeleton uses for reducing low back muscular activity during farm tasks. Am. J. Ind. Med. 63(11): 1017–1028. https://doi.org/10.1002/ajim.23180.
Wordofa, M.G., J.Y. Hassen, G.S. Endris, C.S. Aweke, D.K. Moges and D.T. Rorisa. 2021. Adoption of improved agricultural technology and its impact on household income: A propensity score matching estimation in eastern Ethiopia. Agric. Food Secur. 10: 5. https://doi.org/10.1186/s40066-020-00278-2.
Xie, H. and Y. Huang. 2021. Influencing factors of farmers’ adoption of pro-environmental agricultural technologies in China: Meta-analysis. Land Use Policy. 109: 105622. https://doi.org/10.1016/J.LANDUSEPOL.2021.105622.
Yaakobi, E. 2021. Can cultural values eliminate ostracism distress? Int. J. Intercult. Relat. 80: 231–241. https://doi.org/10.1016/j.ijintrel.2020.10.014.
Zerssa, G., D. Feyssa, D. Kim and B. Eichler-Löbermann. 2021. Challenges of smallholder farming in Ethiopia and opportunities by adopting climate-smart agriculture. Agriculture. 11(3): 192. https://doi.org/10.3390/AGRICULTURE11030192.
Zincov, A. 2025. Operation of Cars and Tractors: Control, Diagnostic and Adjustment Work: Workshop. INFRA-M Academic Publishing LLC, Moscow, Russia.
