Can Network Theory-Based Targeting Increase Technology Adoption?

Can targeting information to network-central farmers induce more adoption of a new agricultural technology? By combining social network data and a field experiment in 200 villages in Malawi, we find that targeting central farmers is important to spur the diffusion process. We also provide evidence o...

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Publicado en:American Economic Review Vol. 111; no. 6; pp. 1918 - 1944
Autores principales: Beaman, Lori, BenYishay, Ariel, Magruder, Jeremy, Mobarak, Ahmed Mushfiq
Formato: Artículo
Publicado: American Economic Association Jun2021
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jun2021
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      pub: American Economic Association
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        10.1257/aer.20200295
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        atl: Can Network Theory-Based Targeting Increase Technology Adoption?
      aug:
        au:
          Beaman, Lori
          BenYishay, Ariel
          Magruder, Jeremy
          Mobarak, Ahmed Mushfiq
        affil:
          Department of Economics and Institute for Policy Research, Northwestern University
          Department of Economics, College of William and Mary
          Agricultural and Resource Economics, University of California-Berkeley
          Yale University
      su:
        Malawi
        Innovation adoption
        Diffusion processes
        Agricultural technology
      sug:
        subj:
          Innovation adoption
          Malawi
          Diffusion processes
          Agricultural technology
      ab: Can targeting information to network-central farmers induce more adoption of a new agricultural technology? By combining social network data and a field experiment in 200 villages in Malawi, we find that targeting central farmers is important to spur the diffusion process. We also provide evidence of one explanation for why centrality matters: a diffusion process governed by complex contagion. Our results are consistent with a model in which many farmers need to learn from multiple people before they adopt themselves. This means that without proper targeting of information, the diffusion process can stall and technology adoption remains perpetually low. (JEL O13, O18, O33, Q12, Q16)
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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