Research Article | | Peer-Reviewed

Determinants of Agribusiness Enterprise Growth in West Shoa Zone, Ethiopia: A Multi-Factor Analysis

Received: 4 September 2026     Accepted: 17 September 2026     Published: 28 September 2026
Views:       Downloads:
Abstract

Agribusiness is pivotal for economic transformation, job creation, and poverty reduction in agrarian economies like Ethiopia. However, its growth is constrained by multidimensional factors that are not fully understood at the sub-regional level. This study investigates the determinants of agribusiness enterprise development in the West Shoa Zone of the Oromia Region, Ethiopia. A mixed-methods approach was employed, combining descriptive and explanatory research designs. Data were collected from 290 purposively selected agribusiness entrepreneurs using a structured questionnaire. Multiple regression analysis was used to assess the influence of six independent variables: Financial Access, Technological Adoption, Marketing Capabilities, Government Support, Demographic Factors, and Environmental Conditions. Results reveal that Technological Adoption (β = 0.797, p < 0.001), Financial Access (β = 0.474, p < 0.001), and Government Support (β = 0.281, p < 0.001) are the most significant positive predictors of enterprise growth. Marketing Capabilities showed a moderate positive effect, while Environmental Conditions exerted a significant negative influence. Demographic Factors were statistically insignificant. The model explained 57.1% of the variance in agribusiness development. The study concludes that a synergistic policy framework prioritizing technology diffusion, inclusive finance, and proactive public-sector support is essential for unlocking the agribusiness potential in rural Ethiopia. Recommendations are directed at policymakers, development agencies, and entrepreneurs to foster a resilient and market-oriented agribusiness ecosystem.

Published in Science Futures (Volume 2, Issue 5)
DOI 10.11648/j.scif.20260205.14
Page(s) 275-283
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2026. Published by Science Publishing Group

Keywords

Agribusiness Development, Enterprise Growth, Technological Adoption, Access to Finance, Government Policy, Ethiopia, West Shoa Zone, Rural Entrepreneurship

References
[1] Abate, G. T., Rashid, S., Boros, C., & Lemma, S. (2016). Rural finance and agricultural technology adoption in Ethiopia. IFPRI Discussion Paper 01524. International Food Policy Research Institute (IFPRI).
[2] African Agribusiness Report. (2013). Agribusiness: Africa's overlooked asset. African Development Bank.
[3] Andersen, P., & Shimokawa, S. (2007). Rural infrastructure and agricultural development. In Annual World Bank Conference on Development Economics. The World Bank.
[4] Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120.
[5] Barrett, C. B. (2008). Smallholder market participation: Concepts and evidence from eastern and southern Africa. Food Policy, 33(4), 299–317.
[6] Beck, T., & Cull, R. (2014). Banking in Africa. World Bank Policy Research Working Paper, (6684).
[7] Birthal, P. S., Joshi, P. K., Roy, D., & Thorat, A. (2015). Innovations in financing of agri-food value chains in China and India: Lessons and policies for inclusive financing. China Agricultural Economic Review, 7(4), 616–634.
[8] Central Statistical Agency (CSA). (2002). Ethiopia agricultural sample survey. Addis Ababa, Ethiopia.
[9] Chamberlin, J., & Jayne, T. S. (2013). Unpacking the meaning of "market access": Evidence from rural Kenya. World Development, 41, 245–264.
[10] Demirgüç-Kunt, A., & Klapper, L. (2013). Measuring financial inclusion: Explaining variation in use of financial services across and within countries. Brookings Papers on Economic Activity, 2013(1), 279–340.
[11] Desalegn, G. (2008). Agricultural development-led industrialization in Ethiopia: A review. Ethiopian Economic Association.
[12] Dorward, A., Kirsten, J. F., Omamo, S. W., Poulton, C., & Vink, N. (2009). Institutions and the agricultural development challenge in Africa. In J. F. Kirsten, A. R. Dorward, C. Poulton, & N. Vink (Eds.), Institutional economics perspectives on African agricultural development (pp. 3–34). International Food Policy Research Institute (IFPRI).
[13] Edessa, N. (2005). Survey of honey production systems in West Shewa Zone. Ethiopian Journal of Animal Production, 5(1), 23-40.
[14] Feder, G., Murgai, R., & Quizon, J. B. (2010). Sending farmers back to school: The impact of farmer field schools in Indonesia. In Agricultural Extension and Rural Development (pp. 147–162). Routledge.
[15] Food and Agriculture Organization. (2021). FAO in Ethiopia: Country programming framework / Ethiopia at a glance. Food and Agriculture Organization of the United Nations.
[16] Haggblade, S., & Hazell, P. B. R. (2010). Successes in African agriculture: Lessons for the future. IFPRI Issue Brief. International Food Policy Research Institute.
[17] Igbaria, M., & Shayo, C. (2007). The impact of demographic variables on technology adoption. Information & Management, 44(2), 150-163.
[18] International Food Policy Research Institute. (2018). Global food policy report 2018. International Food Policy Research Institute (IFPRI).
[19] IPCC. (2014). Climate Change 2014: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press.
[20] Isubikalu, P. (2007). Stepping-stones to improve upon functioning of participatory agricultural extension programmes. Wageningen Academic Publishers.
[21] Jayne, T. S., Mather, D., & Mghenyi, E. (2010). Principal challenges confronting smallholder agriculture in Sub-Saharan Africa. World Development, 38(10), 1384–1398.
[22] Joseph, B. (2017). The challenges for artificial intelligence in agriculture. AgFunder News.
[23] Kelly, S. (2012). Smallholder business models for agribusiness-led development. Food and Agriculture Organization of the United Nations.
[24] Ministry of Finance and Economic Development (MoFED). (1999). Ethiopia: Development and poverty profile. Addis Ababa, Ethiopia.
[25] Möller, K. (2006). The marketing mix revisited: Towards the 21st century marketing. Journal of Marketing Management, 22(3), 439-450.
[26] Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill.
[27] Onwumere, J., Okoro, G., & Ibezim, G. (2000). Financing agriculture in Nigeria: Problems and prospects. Journal of Agricultural and Social Research, 1(1), 55-62.
[28] Pingali, P. L. (2012). Agricultural modernization: Challenge and opportunities for the 21st century. Agricultural Economics, 43(s1), 1–12.
[29] Tefera, T. (2004). The role of microfinance in agricultural development: Evidence from Ethiopia. Journal of African Economies, 13(1), 78-115.
[30] World Bank. (2006). Enhancing agricultural innovation: How to go beyond the strengthening of research systems. The World Bank.
[31] World Bank. (2009). Awakening Africa’s sleeping giant: Prospects for commercial agriculture in the Guinea Savannah Zone and beyond. The World Bank.
[32] World Bank. (2022). Ethiopia economic update: Strengthening agricultural commercialization and market integration. World Bank Group.
[33] Yamane, T. (1967). Statistics: An introductory analysis (2nd ed.). Harper & Row.
[34] Yumkella, K. K., Kormawa, P. M., Roepstorff, T. M., & Hawkins, A. M. (Eds.). (2011). Agribusiness for Africa’s prosperity. United Nations Industrial Development Organization.
Cite This Article
  • APA Style

    Techan, A., Bayessa, G. (2026). Determinants of Agribusiness Enterprise Growth in West Shoa Zone, Ethiopia: A Multi-Factor Analysis. Science Futures, 2(5), 275-283. https://doi.org/10.11648/j.scif.20260205.14

    Copy | Download

    ACS Style

    Techan, A.; Bayessa, G. Determinants of Agribusiness Enterprise Growth in West Shoa Zone, Ethiopia: A Multi-Factor Analysis. Sci. Futures 2026, 2(5), 275-283. doi: 10.11648/j.scif.20260205.14

    Copy | Download

    AMA Style

    Techan A, Bayessa G. Determinants of Agribusiness Enterprise Growth in West Shoa Zone, Ethiopia: A Multi-Factor Analysis. Sci Futures. 2026;2(5):275-283. doi: 10.11648/j.scif.20260205.14

    Copy | Download

  • @article{10.11648/j.scif.20260205.14,
      author = {Abebe Techan and Gemechu Bayessa},
      title = {Determinants of Agribusiness Enterprise Growth in West Shoa Zone, Ethiopia: A Multi-Factor Analysis},
      journal = {Science Futures},
      volume = {2},
      number = {5},
      pages = {275-283},
      doi = {10.11648/j.scif.20260205.14},
      url = {https://doi.org/10.11648/j.scif.20260205.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.scif.20260205.14},
      abstract = {Agribusiness is pivotal for economic transformation, job creation, and poverty reduction in agrarian economies like Ethiopia. However, its growth is constrained by multidimensional factors that are not fully understood at the sub-regional level. This study investigates the determinants of agribusiness enterprise development in the West Shoa Zone of the Oromia Region, Ethiopia. A mixed-methods approach was employed, combining descriptive and explanatory research designs. Data were collected from 290 purposively selected agribusiness entrepreneurs using a structured questionnaire. Multiple regression analysis was used to assess the influence of six independent variables: Financial Access, Technological Adoption, Marketing Capabilities, Government Support, Demographic Factors, and Environmental Conditions. Results reveal that Technological Adoption (β = 0.797, p < 0.001), Financial Access (β = 0.474, p < 0.001), and Government Support (β = 0.281, p < 0.001) are the most significant positive predictors of enterprise growth. Marketing Capabilities showed a moderate positive effect, while Environmental Conditions exerted a significant negative influence. Demographic Factors were statistically insignificant. The model explained 57.1% of the variance in agribusiness development. The study concludes that a synergistic policy framework prioritizing technology diffusion, inclusive finance, and proactive public-sector support is essential for unlocking the agribusiness potential in rural Ethiopia. Recommendations are directed at policymakers, development agencies, and entrepreneurs to foster a resilient and market-oriented agribusiness ecosystem.},
     year = {2026}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Determinants of Agribusiness Enterprise Growth in West Shoa Zone, Ethiopia: A Multi-Factor Analysis
    AU  - Abebe Techan
    AU  - Gemechu Bayessa
    Y1  - 2026/09/28
    PY  - 2026
    N1  - https://doi.org/10.11648/j.scif.20260205.14
    DO  - 10.11648/j.scif.20260205.14
    T2  - Science Futures
    JF  - Science Futures
    JO  - Science Futures
    SP  - 275
    EP  - 283
    PB  - Science Publishing Group
    SN  - 3070-6289
    UR  - https://doi.org/10.11648/j.scif.20260205.14
    AB  - Agribusiness is pivotal for economic transformation, job creation, and poverty reduction in agrarian economies like Ethiopia. However, its growth is constrained by multidimensional factors that are not fully understood at the sub-regional level. This study investigates the determinants of agribusiness enterprise development in the West Shoa Zone of the Oromia Region, Ethiopia. A mixed-methods approach was employed, combining descriptive and explanatory research designs. Data were collected from 290 purposively selected agribusiness entrepreneurs using a structured questionnaire. Multiple regression analysis was used to assess the influence of six independent variables: Financial Access, Technological Adoption, Marketing Capabilities, Government Support, Demographic Factors, and Environmental Conditions. Results reveal that Technological Adoption (β = 0.797, p < 0.001), Financial Access (β = 0.474, p < 0.001), and Government Support (β = 0.281, p < 0.001) are the most significant positive predictors of enterprise growth. Marketing Capabilities showed a moderate positive effect, while Environmental Conditions exerted a significant negative influence. Demographic Factors were statistically insignificant. The model explained 57.1% of the variance in agribusiness development. The study concludes that a synergistic policy framework prioritizing technology diffusion, inclusive finance, and proactive public-sector support is essential for unlocking the agribusiness potential in rural Ethiopia. Recommendations are directed at policymakers, development agencies, and entrepreneurs to foster a resilient and market-oriented agribusiness ecosystem.
    VL  - 2
    IS  - 5
    ER  - 

    Copy | Download

Author Information
  • Department of Management, Ambo University, Ambo, Ethiopia

  • Department of Marketing Management, Ambo University, Ambo, Ethiopia

  • Sections