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Effects of social network factors on information acquisition and adoption of improved groundnut varieties: the case of Uganda and Kenya

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Abstract

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.

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Notes

  1. Personal communication with Okello on October 24, 2011.

Abbreviations

AT:

Appropriate technology

FIML:

Full information maximum likelihood

ML:

Maximum likelihood

NRF:

Non-research farmer

PCRSP:

Peanut Collaborative Research Support Program

RBP:

Recursive bivariate probit

RF:

Research farmer

SUBP:

Seemingly unrelated bivariate probit

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Acknowledgments

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.

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Authors and Affiliations

  1. Department of Educational Planning and Management, Wolaita Sodo University, P.O Box 138, Wolaita Sodo, Ethiopia

    Mary Thuo

  2. Department of Educational Leadership, University of Connecticut, 249 Glenbrook Road, U-2093, Storrs, CT, 06269, USA

    Alexandra A. Bell

  3. Department of Agricultural and Resource Economics, University of Connecticut, 1376 Storrs Road, Storrs, CT, 06269, USA

    Boris E. Bravo-Ureta & Michée A. Lachaud

  4. Department of Agricultural Economics, University of Talca, Talca, Chile

    Boris E. Bravo-Ureta

  5. National Semi-Arid Resources Research Institute (NaSARRI), Soroti, Uganda

    David K. Okello

  6. Kenya Agricultural Research Institute (KARI-Kisii), Box 523-40200, Kisii, Kenya

    Evelyn Nasambu Okoko & Nelson L. Kidula

  7. Department of Plant Pathology, University of Georgia, Athens, GA, 30606, USA

    Carl M. Deom

  8. Agricultural Science Center at Clovis, New Mexico State University, Clovis, NM, 88101, USA

    Naveen Puppala

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  1. Mary Thuo
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Correspondence to Boris E. Bravo-Ureta.

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Appendix 1

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Thuo, M., Bell, A.A., Bravo-Ureta, B.E. et al. Effects of social network factors on information acquisition and adoption of improved groundnut varieties: the case of Uganda and Kenya. Agric Hum Values 31, 339–353 (2014). https://doi.org/10.1007/s10460-014-9486-6

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