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It takes two: Experimental evidence on the determinants of technology diffusion

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  • Hardy, Morgan
  • McCasland, Jamie

Abstract

This paper reports on an experiment that brings insights from the literature on demand-side determinants of technology adoption to the study of peer-to-peer diffusion. We develop a custom weaving technique and randomly seed training into a real network of garment making firm owners in Ghana. Training leads to limited adoption among trainees, but little to no diffusion to non-trainees. In a second phase, we cross-randomize demand for the technique. Demand shocks increase adoption of the technology in both groups and diffusion to untrained firms, generated by a pattern in which trained firm owners teach approximately 400% more of their peers if they are randomly assigned to the demand intervention. We find no evidence that our main effects are driven by differences in ability (learning-by-doing) or other adoption-based mechanisms. Rather, our findings are most consistent with the demand intervention generating differential willingness to diffuse among potential teachers.

Suggested Citation

  • Hardy, Morgan & McCasland, Jamie, 2021. "It takes two: Experimental evidence on the determinants of technology diffusion," Journal of Development Economics, Elsevier, vol. 149(C).
    • Handle: RePEc:eee:deveco:v:149:y:2021:i:c:s0304387820301759
    DOI: 10.1016/j.jdeveco.2020.102600
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    References listed on IDEAS

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    Cited by:

    1. Sun, Bing & Yang, Xueting & Zhong, Shen & Tian, Shengnan & Liang, Tian, 2024. "How do technology convergence and expansibility affect information technology diffusion? Evidence from the internet of things technology in China," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    2. Réka Juhász & Mara P. Squicciarini & Nico Voigtländer, 2020. "Technology Adoption and Productivity Growth: Evidence from Industrialization in France," NBER Working Papers 27503, National Bureau of Economic Research, Inc.
    3. Dalton, Patricio & Rüschenpöhler, Julius & Uras, Burak & Zia, Bilal, 2019. "Local Best Practices for Business Growth," Other publications TiSEM fc650e2f-88cf-4d75-8257-f, Tilburg University, School of Economics and Management.
    4. Mattea Stein, 2021. "Know-how and Know-who: Effects of a Randomized Training on Network Changes Among Small Urban Entrepreneurs," CSEF Working Papers 622, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    5. Has van Vlokhoven, 2023. "Diffusion of Ideas in Networks with Endogenous Search," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 49, pages 269-311, July.

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    More about this item

    Keywords

    Networks; Diffusion; Technology; Demand; Firms;
    All these keywords.

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • O17 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Formal and Informal Sectors; Shadow Economy; Institutional Arrangements
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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