Determinants of the decision to apply high technologies into coffee production in central highlands
,
and
*
Article Sidebar
Full Text: 
PDF
Abstract
In this paper, Logistic models were used to estimate the impact of determinants on the decision to apply high technologies into coffee production in Central Highlands. The estimated results indicate that there are four important determinants affecting the decision to apply high technologies into coffee production, including age of famer, academic level, years of experience and institutions (access to information, extension services, and credit). Of which the institutions is the most significant factor decision to apply high technologies into coffee production. Based on the quantitative results, the empirical is foudation for some policy on access to technology information, extension services and human training; policies on high-tech human resource training. Contribute to apply high technologies into coffee production in the region. Particularly, high-tech human resource training should be a priority.
Tóm tắt
Trong nghiên cứu này, mô hình nhị phân ogistic được sử dụng để ước lượng các nhân tố tác động đến quyết định ứng dụng công nghệ cao (ƯDCNC) trong sản xuất cà phê vùng Tây Nguyên. Kết quả ước lượng chỉ ra rằng có bốn nhân tố tác động quan trọng đến quyết định ứng dụng công nghệ cao trong sản xuất cà phê, gồm: độ tuổi, trình độ học vấn, số năm kinh nghiệm và thể chế (gồm khả năng tiếp cận thông tin, dịch vụ mở rộng và tín dụng). Trong đó, nhân tố thể chế ảnh hưởng rõ nét nhất đến quyết định ƯDCNC trong sản xuất cà phê. Trên cơ sở kết quả lượng hóa, một số hàm ý chính sách về tiếp cận thông tin công nghệ, dịch vụ mở rộng và đào tạo – tập huấn; chính sách về đạo tạo nguồn nhân lực công nghệ cao được đề xuất góp phần thúc đẩy ứng dụng công nghệ cao trong sản xuất cà phê cho toàn vùng, trong đó ưu tiên đào tạo nguồn nhân lực công nghệ cao.
Article Details
References
Akudugu, M. A., Guo, E., & Dadzie, S. K. (2012). Adoption of Modern Agricultural Production Technologies by Farm Households in Ghana: What Factors Influence their Decisions? Journal of Biology, Agriculture and Healthcare, 2(3), 1-9.
Ammann, K. (2008). Integrated farming: why organic farmers should use transgenic crops. N Biotechnol, 25(2-3), 101-107. doi:10.1016/j.nbt.2008.08.012
Ammann, K. (2009). Why farming with high tech methods should integrate elements of organic agriculture. N Biotechnol, 25(6), 378-388. doi:10.1016/j.nbt.2009.06.933
Babasola, O. J., Olaoye, I. J., Alalade, O. A., Matanmi, B. M., & Olorunfemi, O. D. (2017). Factors Affecting the Use of Organic Fertilizer among Vegetable Farmers in Kwara State, Nigeria. Tanzania Journal of Agricultural Sciences, 16(1), 46-53.
Bernoulli, D. (1954). Exposition of a New Theory on the Measurement of Risk. Econometrica, 22(1), 23-36. doi:https://doi.org/10.2307/1909829
Bony, S. (2017). High-tech Agriculture or Agroecology for Tomorrrow’s Agriculture? Harvard College Review of Environment & Society, 28-34.
Challa, M. (2014). Determining Factors and Impacts of Modern Agricultural Technology Adoption in West Wollega. Journal of Biology, Agriculture and Healthcare, 4(20), 63-77.
Diiro, G. (2013). Impact of Off-farm Income on Technology Adoption Intensity and Productivity: Evidence from Rural Maize Farmers in Uganda. International Food Policy Research Institute.
(2019). New technologies and digitisation in agriculture: a crucial aspect to deliver on CAP’s objectives. News 24 May 2019 Brussels, Belgium, Agriculture and Rural Development.
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research (Vol. 6). Contemporary Sociology.
Hall, H. B., & Khan, B. (2003). Adoption of New Technology. NBER Working Paper No. 9730, May 2003, JEL No. O3, L1.
Kasirye, I. (2013). Constraints to Agricultural Technology Adoption in Uganda: Evidence from the 2005/06-2009/10 Uganda National Panel Survey. Economic Policy Research Centre - EPRC, RESEARCH SERIES No. 102.
Loevinsohn, M., Sumberg, J., & Diagne, A. (2012). Under what circumstances and conditions does adoption of technology result in increased agricultural productivity? London: EPPI Centre, Social Science Research Unit, Institute of Education, University of London.
Makokha, S., Kimani, S., Mwangi, W., Verkuijl, H., & Musembi, F. (2001). Determinants of Fertilizer and Manure Use for Maize Production in Kiambu District, Kenya. Mexico, D.F.: International Maize and Wheat Improvement Center (CIMMYT) and Kenya Agricultural ResearchInstitute (KARI).
Mauceri, M., Alwang, J., Norton, G., & Barrera, V. (2005). Adoption of integrated pest management technologies: A case study of potato farmers in Carchi, Ecuador. Selected Paper prepared for presentation at the American Agricultural Economics Association Annual Meeting, Providence, Rhode Island, July 24-27, 2005. doi:10.22004/ag.econ.19400
Meijer, S. S., Catacutan, D., Ajayi, O. C., Sileshi, G. W., & Nieuwenhuis, M. (2014). The role of knowledge, attitudes and perceptions in the uptake of agricultural and agroforestry innovations among smallholder farmers in sub-Saharan Africa. International Journal of Agricultural Sustainability, 13(1), 40-54. doi:10.1080/14735903.2014.912493
Mignouna, B., Manyong, M., Rusike, J., & Mutabazi, S. (2011). Determinants of Adopting Imazapyr-Resistant Maize Technology and its Impact on Household Income in Western Kenya. AgBioForum, 14(3), 158-163.
Miller, R. L. (2015). Rogers' Innovation Diffusion Theory (1962, 1995). Information Seeking Behavior and Technology Adoption: Theories and Trends, 261-274. doi:10.4018/978-1-4666-8156-9.ch016
Morris, M. L., & Doss, C. R. (2001). How does gender affect the adoption of agricultural innovations? The case of improved maize technology in Ghana. Agricultural Economics, 25(1), 27-39.
Mutua-Mutuku, M., Nguluu, S. N., Akuja, T., M.Lutta, & Bernard, P. (2017). Factors that influence adoption of integrated soil fertility and water management practices by smallholder farmers in the semi-arid areas of Eastern Kenya. Tropical and Subtropical Agroecosystem, 20(1), 141-153.
Okunlola, J. O., Oludare, A. O., & Akinwalere, B. O. (2011). Adoption of new technologies by fish farmers in Akure, Ondo state, Nigeria. Journal of Agricultural Technology, 7(6), 1539-1548.
Olale, E., & Henson, S. (2012). Determinants of income diversification among fishing communities in Western Kenya. Fisheries Research, 125-126, 235-242. doi:10.1016/j.fishres.2012.02.029
Raghuvanshi, R., & Amardeep. (2018). Hi tech Agriculture: A Luccrative Alternative for Indian Youth. Army Pringting Press, Lucknow, 284-288.
Runge, E. C. A., & Hons, F. M. (2015). Precision Agriculture - Development of a Hierarchy of Variables Influencing Crop Yields. American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, 143-158. doi:10.2134/1999.precisionagproc4.c13
Simtowe, F., & Zeller, M. (2006). The Impact of Access to Credit on the Adoption of hybrid maize in Malawi: An Empirical test of an Agricultural Household Model under credit market failure. 2007 Second International Conference, August 20-22, 2007, Accra, Ghana 52076, African Association of Agricultural Economists (AAAE). doi:10.22004/ag.econ.52076
Wabbi, J. B. (2002). Assessing Factors Affecting Adoption of Agricultural Technologies: The Case of Integrated Pest Management (IPM) in Kumi District, Eastern Uganda. (Msc. Thesis Eastern Uganda). Retrieved from http://hdl.handle.net/10919/36266
Wandji, D. N., Pouomogne, V., Binam, J. N., & Nouaga, R. Y. (2012). Farmer’s Perception and Adoption of New Aquaculture Technologies in the Western Highlands of Cameroon. TROPICULTURA, 30(3), 180-184.
Yaron, D., Voet, H., & Dinar, A. (1992). Innovations on Family Farms: The Nazareth Region in Israel. American Journal of Agricultural Economics, Agricultural and Applied Economics Association, 74(2), 361-370. doi:10.2307/1242490