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‘Mobile’izing Agricultural Advice: Technology Adoption, Diffusion and Sustainability


  • Shawn A. Cole

    () (Harvard Business School, Finance Unit)

  • A. Nilesh Fernando

    () (Harvard Kennedy School)


Attempts to explain dramatic differences in agricultural productivity around the world typically focus on farm size, risk aversion, and credit constraints, with an emphasis on how they might serve to limit technology adoption. This paper takes a different tack: can managerial practices explain this variation in productivity? A randomized evaluation of a mobile phone-based agricultural consulting service, Avaaj Otalo (AO), to farmers in Gujarat, India, reveals the following. Demand for agricultural advice is substantial and farmers offered the service turn less often to traditional sources of agricultural advice. Management practices change as well: farmers invest more in recommended agricultural inputs, resulting in dramatic increases in average yield for cumin (28.0%), as well as improvements in cotton yield (8.6%) for a sub-group that received frequent reminders to use the service. Our design allows us to estimate peer effects, and we find treated farmers with more treated peers are more likely to change their cropping decisions and successfully address pest shocks. The value of the latter externality is more than twice the cost of the subsidy that would be necessary to operate the service. We estimate that each dollar spent on providing the service yields a private return of $10. These findings highlight the importance of managerial practices in facilitating technology adoption in agriculture.

Suggested Citation

  • Shawn A. Cole & A. Nilesh Fernando, 2012. "‘Mobile’izing Agricultural Advice: Technology Adoption, Diffusion and Sustainability," Harvard Business School Working Papers 13-047, Harvard Business School, revised Mar 2016.
  • Handle: RePEc:hbs:wpaper:13-047

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    Cited by:

    1. Gupta, Apoorv & Ponticelli, Jacopo & Tesei, Andrea, 2019. "Technology Adoption and Access to Credit via Mobile Phones," CEPR Discussion Papers 13956, C.E.P.R. Discussion Papers.
    2. Jean-Philippe Berrou & François Combarnous & Thomas Eekhout, 2018. "Usages du mobile et performances économiques des micro et petites entreprises informelles à Dakar. Quels profils d’usagers pour quels segments de l’informel ?," Working Papers hal-02148197, HAL.
    3. World Bank, 2020. "Sudan Agriculture Value Chain Analysis," World Bank Other Operational Studies 34103, The World Bank.
    4. repec:ilo:ilowps:487273 is not listed on IDEAS
    5. Chowdhury, Shyamal & Smits, Joeri & Sun, Qigang, 2020. "Contract structure, time preference, and technology adoption," GLO Discussion Paper Series 633, Global Labor Organization (GLO).
    6. Jean-Philippe Berrou & François Combarnous & Thomas Eekhout, 2017. "Les TIC : une réponse au défi du développement des micro et petites entreprises informelles en Afrique sub-saharienne ?," Working Papers hal-02148324, HAL.
    7. Jacopo Bonan & Harounan Kazianga & Mariapia Mendola, 2019. "Agricultural Transformation and Farmers' Expectations: Experimental Evidence from Uganda," Development Working Papers 458, Centro Studi Luca d'Agliano, University of Milano.
    8. de Janvry, Alain & Sadoulet, Elisabeth, 2020. "How experimental research in agriculture has gone from lab to field," World Development, Elsevier, vol. 127(C).
    9. Aker, Jenny C. & Ksoll, Christopher, 2016. "Can mobile phones improve agricultural outcomes? Evidence from a randomized experiment in Niger," Food Policy, Elsevier, vol. 60(C), pages 44-51.
    10. Palloni, G. & Aker, J. & Gilligan, D. & Hidrobo, M. & Ledlie, N., 2018. "Paying for Digital Information: Assessing Farmers Willingness to Pay for a Digital Agriculture and Nutrition Service in Ghana," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277451, International Association of Agricultural Economists.
    11. Camacho, Adriana & Conover, Emily, 2019. "The impact of receiving SMS price and weather information on small scale farmers in Colombia," World Development, Elsevier, vol. 123(C), pages 1-1.
    12. Global Commission on Adaptation, 2019. "Adapt Now," World Bank Publications, The World Bank, number 32362, November.
    13. Carter, Michael R. & Tjernström, Emilia & Toledo, Patricia, 2019. "Heterogeneous impact dynamics of a rural business development program in Nicaragua," Journal of Development Economics, Elsevier, vol. 138(C), pages 77-98.
    14. Chowdhury, Shyamal & Smits, Joeri & Sun, Qigang, 2020. "Contract Structure, Time Preference, and Technology Adoption," IZA Discussion Papers 13590, Institute of Labor Economics (IZA).
    15. Tamim, Abdulrazzak & Harou, Aurelie P. & Magombab, Christopher & Michelson, Hope & Palm, Cheryl, 2020. "The Long-Term Effects of Relaxing Information and Credit Constraints on Adoption, Retention, and Soil Perceptions: Evidence from a Randomized Experiment in Tanzania," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304604, Agricultural and Applied Economics Association.
    16. Cole, Shawn & Fernando, A. Nilesh & Stein, Daniel & Tobacman, Jeremy, 2020. "Field comparisons of incentive-compatible preference elicitation techniques," Journal of Economic Behavior & Organization, Elsevier, vol. 172(C), pages 33-56.
    17. Aidan R. Vining, 2016. "What Is Public Agency Strategic Analysis (PASA) and How Does It Differ from Public Policy Analysis and Firm Strategy Analysis?," Administrative Sciences, MDPI, Open Access Journal, vol. 6(4), pages 1-31, December.
    18. Apoorv Gupta & Jacopo Ponticelli & Andrea Tesei, 2020. "Information, Technology Adoption and Productivity: The Role of Mobile Phones in Agriculture," NBER Working Papers 27192, National Bureau of Economic Research, Inc.
    19. Barham, Bradford L. & Chavas, Jean-Paul & Fitz, Dylan & Schechter, Laura, 2018. "Receptiveness to advice, cognitive ability, and technology adoption," Journal of Economic Behavior & Organization, Elsevier, vol. 149(C), pages 239-268.

    More about this item


    Technology Adoption; Agricultural Extension; Informational Inefficiencies;
    All these keywords.

    JEL classification:

    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services

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