Adoption of Agricultural Marketing Technologies by Farmers of Northern Bangladesh

A Binary Logistic Analysis to Determine the Factors Influencing Farmers' Decision


  • Md. Ziaul Haque Rajshahi University



Agricultural Marketing, Binary Logistic Regression, Marketing Technologies, Farmers' Decision


Low adoption of agricultural marketing technologies in the field of agricultural commodities marketing is one of the main reasons for profit loss of the farmers in Bangladesh. This paper examines the factors that influence farmers' decision of modern agricultural marketing technologies adoption in Northern Bangladesh. By using questionnaire survey the researcher collect data from 216 farmers in Dinajpur and Naogaon district in Northern Bangladesh and the binary logistic regression model was estimated to find out the factors influence farmers decision. Seven independent variables i.e. age of the farmer, formal education of the farmer, farm size, level of expected benefits, off-farm income generating activities, access to institutional credit and training about use of marketing technologies are statistically significant factors that influence the decision of farmers to adopt modern agricultural marketing technologies in Northern Bangladesh. So it is concluded that the farmers' decision to adopt modern agricultural marketing technologies depends on their socio-economic status and organizational effectiveness. We recommend that such policies should be made so that the positive impact factors on technologies adoption are properly utilized and negative issues are reduced.


Download data is not yet available.

Author Biography

Md. Ziaul Haque, Rajshahi University

PhD Fellow, Institute of Bangladesh Studies (IBS), Rajshahi University, Rajshahi, Bangladesh


Abara, I. O. C. & Singh, S. (1993). Ethics and biases in technology adoption: The small farm argument. Technological Forecasting and Social Change, 43, 289-300.

Adesiina, A.A. & Baidu-Forson, J. (1995). Farmers’ perceptions and adoption of new agricultural technology: Evidence from analysis in Burkina Faso and Guinea, West Africa. Journal of Agricultural Economics, 13, 1-9.

Alston, J.M., Norton, G.W. and Pardey, P.G. (1995). Science Under Scarcity: principles and Practice for Agricultural Research Evaluation and Priority Setting. Cornell University Press, Ithaca (reprinted in soft cover by CAB International 1998).

Baidu-Forson, J. (1999). Factors influencing adoption of land-enhancing technology in the Sahel: Lessons from a case study in Niger. Journal of Agricultural Economics, 20, 231-239.

Bangladesh Bureau of Statistics, Ministry of Planning, Bangladesh (2011).Community Report, Population and Housing Census, http// in March 19, 2017).

Benin, S., Mogues, T., Cudjoe, G., & Randriamamonjy, J. (2009). Public expenditures and agricultural productivity growth in Ghana. Contributed Paper for International Association of Agricultural Economists in Beijing 2009.

Boahene, K., Snijders, T.A.B. & Folmer, H. (1999). An integrated socio-economic analysis of innovation adoption: The case of Hybrid Cocoa in Ghana. Journal of Policy Modeling, 21(2), 167-184.

Caswell, M., Fuglie, K., Ingram, C., Jans S. & Kascak C. (2001). Adoption of Agricultural production practices: Lessons learned from the US. Department of Agriculture Area Studies Project. US Department of Agriculture, Resource Economics Division, Economic Research Service, Agriculture Economic Report No. 792. Washington DC.

Daku, L. (2002). Assessing farm-level and aggregate economic impacts of olive integrated pest management programs in Albania. PhD. Dissertation, Virginia Polytechnic Institute and State University, David, Lynne Riener Publishers.

Doss, C. R & Morris, M. L. (2001). How does gender affect the adoption of agricultural innovation? The case of improved maize technologies in Ghana. Journal of Agricultural Economics, 25, 27-39.

Ehler, L.E & Bottrell D.G. (2000). The illusion of integrated pest management. Issues in science and technology. Bell and Howell Information and Learning Company, pp. 61-64.

Feder, G. & Slade R. (1984). The acquisition of information and the adoption of new technology. American Journal of Agricultural Economics, 66, 312-320.

Feder, G., Just E. R. & Zilberman D. (1985). “Adoption of agricultural innovations in developing countries: A survey. Economic Development and Cultural Change, 33, 255-298.

Fernandez-Cornejo, J. (1996). The microeconomic impact of IPM adoption: Theory and application. Agricultural and Resource Economic Review, 25, 149-160.

Fernandez-Cornejo, J. (1998). Environmental and economic consequences of technology adoption: IPM in viticulture. Agricultural Economics, 18, 145-155.

Green, D.A.G., & Ng’ong’ola D.H. (1993). Factors affecting fertilizer adoption in less developed countries: An application of multivariate logistic analysis in Malawi. Journal of Agricultural Economics, 44 (1), 99-109.

Griliches, Z. (1957), Specification Bias in Estimates of Production Functions, American Journal of Agricultural Economics, 39, (1), 8-20

Harper, J. K., Rister, M. E., Mjelde, J. W., Drees, B. M. & Way, M. O. (1990). Factors influencing the adoption of insect management technology. American Journal of Agricultural Economics, 72(4), 997-1005.

Hill, L. and Kau, P. (1973). "Application of Multivariate Probit to a Threshold Model of Grain Dryer Purchasing Decisions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 55(1), pages 19-27.

Kasenge, V. (1998). Socio-economic factors influencing the level of soil management practices on fragile land. In proceedings of the 16th Conference of Soil Science Society of East Africa (Eds.: Shayo-Ngowi, A.J., G. Ley and F.B.R Rwehumbiza), 13th-19th, Tanga, Tanzania. pp. 102-112.

Kotheri, C.R. (2014). Research Methodology: Methods and techniques, 2nd ed. New Delhi: New Age International limited, pp. 179.

Lionberger, H.F. (1960), Adoption of New Ideas and Practices, Ames (Iowa): Iowa State University Press.

McNamara, K. T., Wetzstein M. E., & Douce G.K. (1991). Factors affecting peanut producer adoption of integrated pest management. Review of Agricultural Economics, 13, 129-139.

Ministry of Agriculture, Bangladesh (2009). Bangladesh Agricultural Policy, (accessed March 27, 2017)

Mugisa-Mutetikka, M., Opio., A.F. Ugen., M.A. Tukamuhabwa, P., Kayiwa, B.S., Niringiye, C. and Kikoba, E. (2000) “Logistic Regression Analysis of Adoption of New Bean Varieties in Uganda.” Unpublished.

Nkonya, E., T. Schroeder, and Norman D. (1997). Factors affecting adoption of improved maize seed and fertilizer in northern Tanzania. Journal of Agricultural Economics, 48(1), 1-12.

Pindyck, R.S. and Rubinfeld, D.L. (1998) Econometric Models and Economic Forecasts. 4th Edition, Irwin-McGraw- Hill, Boston.

Rogers, E.M. (1995). Diffusion of innovations 3rd Edition. New York: The Free Press.

Statistical Year Book 2015, Bangladesh Bureau of Statistics, Ministry of Planning, Bangladesh, (accessed March 27, 2017).

Waller, B.E., Hoy, C.W., Henderson, J.L, Stinner B., & Welty C. (1998). Matching innovations with potential users: A case study of potato IPM practices. Agriculture, Ecosystems and Environment, 70, 203- 215.

Yaron, D., Dinar A., & Voet H. (1992). Innovations on family farms: The Nazareth Region in Israel. American Journal of Agricultural Economics, 361-370.




How to Cite

Haque, M. Z. . (2019). Adoption of Agricultural Marketing Technologies by Farmers of Northern Bangladesh: A Binary Logistic Analysis to Determine the Factors Influencing Farmers’ Decision. Asian Business Review, 9(3), 113–120.