Effects of social network factors on information acquisition and adoption of improved groundnut varieties: the case of Uganda and Kenya
- 994 Downloads
Social networks play a significant role in learning and thus in farmers’ adoption of new agricultural technologies. This study examined the effects of social network factors on information acquisition and adoption of new seed varieties among groundnut farmers in Uganda and Kenya. The data were generated through face-to-face interviews from a random sample of 461 farmers, 232 in Uganda and 229 in Kenya. To assess these effects two alternative econometric models were used: a seemingly unrelated bivariate probit (SUBP) model and a recursive bivariate probit (RBP) model. The statistical evaluation of the SUBP shows that information acquisition and adoption decisions are interrelated while tests for the RBP do not support this latter model. Therefore, the analysis is based on the results obtained from the SUBP. These results reveal that social network factors, particularly weak ties with external support (e.g., researchers, extension agents, etc.), partially influence information acquisition, but do not influence adoption. In Uganda, external support, gender, farm size, and geographic location have an impact on information acquisition. In Kenya, external support and geographic location also have an impact on information acquisition. With regard to adoption, gender, household size, and geographic location play the most important roles for Ugandan farmers, while in Kenya information from external sources, education, and farm size affect adoption choice. The study provides insight on the importance of external weak ties in groundnut farming, and a need to understand regional differences along gender lines while developing agricultural strategies. This study further illustrates the importance of farmer participation in applied technology research and the impact of social interactions among farmers and external agents.
KeywordsSocial networks Strong and weak ties Adoption Information acquisition Kenya Uganda Groundnuts
Full information maximum likelihood
Peanut Collaborative Research Support Program
Recursive bivariate probit
Seemingly unrelated bivariate probit
The authors wish to thank Dr. Barry G. Sheckley for his review of this paper, and the researchers from Kenya Agricultural Research Institute (KARI-Kisii) and the National Semi-Arid Resources Research Institute (NaSARRI) Uganda for time spent in the fieldwork. The authors are also grateful for the comments received from two anonymous reviewers and the Editor-in-Chief, Harvey James. The study was supported by the United States Agency for International Development (USAID) under the Peanut CRSP Grant ECG-A-00-07-00001-00 2007–2012.
- Bandiera, O., and I. Rasul. 2005. Social networks and technology adoption in Northern Mozambique. Unpublished paper. London, UK: London School of Economics and CEPR.Google Scholar
- Bandura, A. 1977. Social learning theory. Englewood Cliffs, NJ: Prentice-Hall Inc.Google Scholar
- Cameron, A.C., and P.K. Trivedi. 2009. Microeconometrics using Stata, vol. 5. College Station, TX: Stata Press.Google Scholar
- Chambers, R. 2009. Foreword. In Farmer first revisited: Innovation for agricultural research and development, ed. I. Scoones, and J. Thompson, xix–xxv. Warwickshire, UK: Practical Action Publishing Ltd.Google Scholar
- Conley, T., and C. Udry. 2005. Learning about a new technology: Pineapple in Ghana. Working paper. New Haven, CT: Yale University.Google Scholar
- Genius, M., C.J. Pantzios, and V. Tzouvelekas. 2006. Information acquisition and adoption of organic farming practices. Journal of Agricultural and Resource Economics 31(1): 93–113.Google Scholar
- Greene, W.H. 2007. Econometric analysis, 6th ed. Upper Saddle River, NJ: Prentice Hall.Google Scholar
- Hartwich, F., and U. Scheidegger. 2010. Fostering innovation networks: The missing piece in rural development? Rural Development News 1: 70–75.Google Scholar
- Huth, P.K., and T.L. Allee. 2002. The democratic peace and territorial conflict in the twentieth century. New York, NY: Cambridge University Press.Google Scholar
- Katungi E., S. Edmeades, and M. Smale. 2006. Gender, social capital and information exchange in Rural Uganda. CAPRi Working Paper 59. Washington, DC: International Food Policy Research Institute.Google Scholar
- Kidula N., N. Okoko, B.E. Bravo-Ureta, M. Thuo, and L. Wasilwa. 2010. A preliminary analysis of yield differences in groundnuts between research and non-research farmers in Kenya. In Paper Presented at the 12th KARI Biennial Scientific Conference, 8–12 November 2010, Nairobi, Kenya.Google Scholar
- Kipkoech, A.K., M.A. Okiror, J.R. Okalebo, and H.K. Maritim. 2007. Production efficiency and economic potential of different soil fertility management strategies among groundnut farmers of Kenya. Science World Journal 2(1): 15–21.Google Scholar
- Li, A., B.E. Bravo-Ureta, D.K. Okello, C.M. Deom, and N. Puppala. 2013. Groundnut production and climatic variability: Evidence from Uganda. Zwick Center Working Paper 17. Storrs, CT: University of Connecticut.Google Scholar
- Matuschke, I. 2008. Evaluating the impact of social networks in rural innovation systems: An overview. IFPRI Discussion Paper, 00816. Washington, DC: International Food Policy Research Institute.Google Scholar
- Monge, M., F. Hartwich, and D. Halgin. 2008. How change agents and social capital influence the adoption of innovations among small farmers: Evidence from social networks in rural Bolivia. IFPRI Discussion Paper, 00761. Washington, DC: International Food Policy Research Institute.Google Scholar
- Moreno, G., and D.L. Sunding. 2003. Simultaneous estimation of technology adoption and land allocation. In Paper prepared at the American agricultural economics association annual meeting, 27–30 July 2003, Montreal, Canada. http://ageconsearch.umn.edu/bitstream/22134/1/sp03mo01.pdf. Accessed 15 Oct 2011.
- Ntare, B.R., A.T. Diallo, J. Ndjeunga, and F. Waliyar. 2008. Groundnut seed production manual. Andhra Pradesh, India: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT).Google Scholar
- Okello, D.K., M. Biruma, and C.M. Deom. 2010. Overview of groundnuts research in Uganda: Past, present and future. African Journal of Biotechnology 9(39): 6448–6459.Google Scholar
- Okoko, E.N.K., D.J. Rees, J.K. Kwach, and P. Ochieng. 1999. Participatory evaluation of groundnut production, Southwest Kenya. In Towards increased use of demand driven technology, ed. J.A Sutherland, 305-307. KARI/DFID NARP II PROJECT, End of Project Conference Proceedings, 23rd–26th March. KARI and DIFD, Nairobi, Kenya. Okoko, N., N. Kidula, F. Muriithi, G. O. Rachier, M. Shiluli, M. Okelo, M. Odendo, F. Simtowe and R. Kanda. 2011. Understanding the potential of groundnuts in Kenya. KARI-Kisii, Compiled Report. 54 pp.Google Scholar
- Research into Use (RIU). 2011. Poor farmers in Uganda boost their income with new groundnut varieties: Commercial incentives for groundnut production and farmer led multiplication. http://www.researchintouse.com/nrk/RIUinfo/PF/CPP03.htm#L1. Accessed 18 Sep 2011.
- Rogers, E.M. 2003. Diffusion of innovations, 5th ed. New York, NY: Simon & Schuster Inc.Google Scholar
- Scandizzo, P.L., and S. Savastano. 2010. The adoption and diffusion of GM crops in United States: A real option approach. AgBioForum 13(2): 142–157.Google Scholar
- Sustainet. 2011. Sustainable agriculture: A pathway out of poverty for East Africa’s rural poor. Sustainable Agriculture Information Network. http://www.sustainet.org/download/sustainet_publication_eafrica_part1.pdf. Accessed 20 Sep 2011.
- Wooldridge, J. 2001. Econometric analysis of cross section and panel data, 1st ed. Cambridge, MA: MIT Press Books.Google Scholar