Determinants on the adoption of modern agricultural technology at farm household level: a case study in Dong Anh District, Hanoi city, Vietnam

Nguyen X. Dinh, Nguyen M. Dung

Abstract


This paper aims to identify the determinants on the adoption of modern agricultural technology at farm level in Dong Anh district, Hanoi city, Vietnam. A total of 300 farm households from Dong Anh district were randomly interviewed face to face for the necessary data collection. Logit regression model was used to explore the impact of different factors on the adoption of the modern agricultural technology. Findings indicated that the farmer’ education, households’ income, farm size, access to extension services and access to credit had statistically significant and positive impacts on the adoption. Meanwhile the number of land plot reflected the negative impact on the adoption. To foster the level of adoption, this study urges stimulating land accumulation for larger farm size and reduced number of land plots. In addition, demonstration models and more training courses for the farmers emphasizing on how to apply the modern agricultural technology and credit program providing loan with preferential interest rate should be provided for the farm households in the district.


Keywords


Adoption; Agricultural technology Factors; Farm households; Credit; Extension service

References


Akudugu, M. A., E. Guo and S. K. Dadzie. 2012. Adoption of modern agricultural production technologies by farm households in Ghana: what factors influence their decisions?

Ben-Akiva, M. and S. R. Lerman. 1985. Discrete choice analysis: theory and application to travel demand. Transportation Studies.

Beshir, H., E. B., K. B. and H. J. 2012. Determinants of chemical fertilizer technology adoption in North eastern highlands of Ethiopia: the double hurdle approach. Journal of Research in Economics and International Finance (JREIF), 12: 39-49.

Bonabana-Wabbi, J. 2002. Assessing factors affecting adoption of agricultural technologies: The case of Integrated Pest Management (IPM) in Kumi District, Eastern Uganda, Virginia Tech.

Carletto, C., A. Kirk, P. Winters and B. Davis. 2007. Non-Traditional Crops, Traditional Constraints : The Adoption And Diffusion Of Export Crops Among Guatemalan Smallholders. The World Bank. Place Published.

Challa, M. and U. Tilahun. 2014. Determinants and impacts of modern agricultural technology adoption in west Wollega: the case of Gulliso district. Journal of Biology, Agriculture and Healthcare, 4: 63-77.

Cochran, W. G. 1963. Sampling Techniques, 2nd Ed., New York: John Wiley and Sons, Inc. Place Published.

Doss, C. R. 2003. Understanding farm level technology adoption: lessons learned from CIMMYT's micro surveys in Eastern Africa. CIMMYT.

Doss, C. R. and M. L. Morris. 2000. How does gender affect the adoption of agricultural innovations? Agricultural Economics, 25: 27-39.

Dung, L. T., D. P. Ho, N. T. K. Hiep and P. T. Hoi. 2018. The determinants of rice farmers’ adoption of sustainable agricultural technologies in the Mekong Delta, Vietnam. Applied Economics Journal, 25: 55-69.

Franzel, S., R. Coe, P. Cooper, F. Place and S. J. Scherr. 2001. Assessing the adoption potential of agroforestry practices in sub-Saharan Africa. Agricultural Systems, 69: 37-62.

GSO. 2020. General Statitical Office of Vietnam. (2020). Statistical Yearbook 2019. Statistical Publishing House. Vietnam.

Hanoi Statistics Office. 2020. Hanoi Statistical Yearbook 2019. Statistical Publishing House. Vietnam.

Hoang, G. H. 2020. Adoption of good agricultural practices by cattle farmers in the Binh Dinh Province of Vietnam. Journal of Agricultural Extension, 24: 151-60.

Idrisa, Y. L., B. O. Ogunbameru and M. C. Madukwe. 2012. Logit and Tobit analyses of the determinants of likelihood of adoption and extent of adoption of improved soybean seed in Borno State, Nigeria. Greener Journal of Agricultural Sciences, 2: 037-45.

Jain, R., A. Arora and S. Raju. 2009. A novel adoption index of selected agricultural technologies: Linkages with infrastructure and productivity. Agricultural Economics Research Review, 22: 109-20.

Kasenge, V. 1998. Socio-economic factors influencing the level of soil management practices on fragile land. pp.102-12.

Katung, E. and K. Akankwasa. 2010. Community-based organizations and their effect on the adoption of agricultural technologies in Uganda: a study of banana (musa spp.) pest management technology. Acta Horticulturae: 719-26.

Kinyangi, A. A. 2014. Factors influencing the adoption of agricultural technology among smallholder farmers in Kakamega north sub-county, Kenya, University of Nairobi.

Le, T. Q. A., Y. Shimamura and H. Yamada. 2020. Information acquisition and the adoption of a new rice variety towards the development of sustainable agriculture in rural villages in Central Vietnam. World Development Perspectives, 20: 100262.

Loevinsohn, M., J. Sumberg, A. Diagne and S. Whitfield. 2013. Under what circumstances and conditions does adoption of technology result in increased agricultural productivity? A Systematic Review.

McNamara, K. T., M. E. Wetzstein and G. K. Douce. 1991. Factors Affecting Peanut Producer Adoption of Integrated Pest Management. Review of Agricultural Economics, 13: 129.

Mohamed, K. S. and A. E. Temu. 2008. Access to credit and its effect on the adoption of agricultural technologies: the case of Zanzibar. African Review of Money Finance and Banking: 45-89.

OECD. 2015. The agricultural policy context in Viet Nam. OECD. Place Published. pp.39-109.

Okunlola, J., A. Oludare and B. Akinwalere. 2011. Adoption of new technologies by fish farmers in Akure, Ondo state, Nigeria. Journal of Agricultural Technology, 7: 1539-48.

Place, F., R. L. Roothaert, L. Maina, S. Franzel, J. Sinja and J. Wanjiku. 2009. The impact of fodder trees on milk production and income among smallholder dairy farmers in East Africa and the role of research. ICRAF Occasional Paper No. 12. Nairobi: World Agroforestry Centre.

Reardon, T., K. Stamoulis and P. Pingali. 2007. Rural nonfarm employment in developing countries in an era of globalization. Agricultural Economics, 37: 173-83.

Salasya, B., W. Mwangi, D. Mwabu and A. Diallo. 2007. Factors influencing adoption of stress-tolerant maize hybrid (WH 502) in western Kenya.

Sezgin, A. and T. E. Kaya. 2011. Factors affecting the adoption of agricultural innovations in Erzurum Province, Turkey. African Journal of Business Management, 5: 777-82.

Sharma, A., A. Bailey and I. Fraser. 2010. Technology Adoption and Pest Control Strategies Among UK Cereal Farmers: Evidence from Parametric and Nonparametric Count Data Models. Journal of Agricultural Economics, 62: 73-92.

Simtowe, F. and M. Zeller. 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.

Tefera, S. S. 2013. Determinants of artificial insemination use by smallholder dairy farmers in Lemu-Bilbilo District, Ethiopia, Egerton University.

Uematsu, H. and A. Mishra. 2010. Can Education Be a Barrier to Technology Adoption? Selected Paper prepared for presentation at the Agricultural & Applied Economics Association 2010 AAEA, CAES, & WAEA Joint Annual Meeting, Denver, Colorado, 25–27.

Van Thanh, N. and C. Yapwattanaphun. 2015. Banana Farmers’ Adoption of Sustainable Agriculture Practices in the Vietnam Uplands: The Case of Quang Tri Province. Agriculture and Agricultural Science Procedia, 5: 67-74.

Wu, J. and B. A. Babcock. 1998. The Choice of Tillage, Rotation, and Soil Testing Practices: Economic and Environmental Implications. American Journal of Agricultural Economics, 80: 494-511.

Yaron, D., H. Voet and A. Dinar. 1992. Innovations on Family Farms: The Nazareth Region in Israel. American Journal of Agricultural Economics, 74: 361-70.


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DOI: 10.33687/ijae.009.02.3626

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