R. Asha* and K. Umadevi1
Agricultural Economics, Acharya N. G. Ranga Agricultural University Agriculture College, Bapatla
1Agricultural Economics, Institutional Development Plan, ANGRAU, Lam, Guntur
Email: asha.rallapalli06@gmail.com
Received-12.02.2020, Revised-27.02.2020
Abstract: The study intends to analyse the impact of backward integration on technology adaptation by chilli farmers. A sample of 128 farmers has been selected purposively from four mandals of Prakasam district in Andhra Pradesh. Technology adoption index, probit regression and poisson model with endogenous regression model used to analyse the impact backward integration on technologies adoption by chilli farmers. The findings show that majority (46.87%) of the chilli farmers who are following backward integration are adopting maximum technologies with technology adoption index 80-90 and the farmers who are not following backward integration (73.43%) are adopting less than four technologies with adoption index <50. The extension service (0.11) and backward integration (0.53) had a positive significant at 10 per cent and 5 per cent levels effect on adoption of technologies.
Keywords: Backward integration, Chilli farming, Technology adoption index, Probit regression, Poisson model
Agricultural Statistics at a Glance (2017). Directorate of Economics and Statistics. Ministry of Agriculture and Cooperation. Government of India. New Delhi.
Baumgart-Getz, A., Prokopy, L. S and Floress, K. (2012). Why farmers adopt best management practices in the States, United: a meta-analysis of the adoption literature. Journal of Management Environmental. 96: 17-25.
Beshir, H. (2014). Factors affecting the adoption and intensity of use of improved forages in the north east Highlands of Ethiopia. American Journal of Experimental Agriculture. 4(1): 12-27.
Caviglia-Harris, J.L. (2003). Sustainable agricultural practices in Rondonia, Brazil: do local farmer organizations affect adoption rates? Economic Development & Cultural Change. 52(1): 23-49.
Cochran, W.G. (1963). Sampling Techniques. (2nd Ed.). New York: John Wiley and Sons.
Floyd, C., Harding, A. H., Paudel, K. C., Rasali, D. P., Subedi, K. and Subedi, P. P. (2003). Household adoption and the associated impact of multiple agricultural technologies in the Western Hills of Nepal. Agricultural Systems. 76: 715-738.
Gebremedhin, B. and Swinton, S.M. (2003). Investment in soil conservation in northern Ethiopia: the role of land tenure security and public programs. Agricultural Economics. 29(1): 69-84.
Greene, W.H. (1997). FIML estimation of sample selection models for count data. New York University, Leonard N. Stern School of Business.
Isgin, T., Bilgic, A., Forster, D.L and Batte, M.T. (2008). Using count data models to determine the factors affecting farmers’ quantity decisions of precision farming technology adoption. Computers and Electronics in Agriculture. 62(2): 231-242.
Lohr, L. and Park, T.A. (2002). Choice of insect management portfolios by organic farmers: lessons and comparative analysis. Ecological Economics. 43(1): 87-99.
Mbaga-Semgalawe, Z. and Folmer, H. (2000). Household adoption behaviour of improved soil conservation: the case of the North Pare and West Usambara Mountains of Tanzania. Land Use Policy. 17(4): 321-336.
Rahelizatovo, N.C. and Gillespie, J.M. (2004). The adoption of best-management practices by Louisiana dairy producers. Journal of Agricultural and Applied Economics. 36(1): 229-240.
Rahman, A.M. (2017). Contract farming and adoption of improved technologies in maize production in the northern region of Ghana. Ph. D Thesis. University for Development Studies.
Ramirez, O.A. and Shultz, S.D. (2000). Poisson count models to explain the adoption of agricultural and natural resource management technologies by small farmers in Central American countries. Journal of Agricultural and Applied Economics. 32(1): 21-33.
Ransom, J. K., Paudyal, K. and Adhikari, K. (2003). Adoption of improved maize varieties in the Hills of Nepal. Agricultural Economics. 29: 299-305.
Sall, S., Norman, D. and Featherstone, A.M. (2000). Quantitative assessment of improved rice variety adoption: the farmer’s perspective. Agricultural Systems Journal. 66: 129-144.
Sharma, A., Bailey, A. and Fraser, I. (2011). Technology adoption and pest control strategies among UK cereal farmers: evidence from parametric and non-parametric count data models. Journal of Agricultural Economics. 62(1), 73-92.
Spices Statistics (2019). Spice Board, Ministry of Commerce and Industries, Government of India, Cochin.
Wanyoike, F.G. (2003). Dissemination and adoption of improved fodder tree: the case of Calliandra calothrsus in Embu district, Kenya. M. Sc. (Ag.) Thesis. University of Nairobi. Kenya.