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Demystifying the Effects of Social N...

Gu, Kun.

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Demystifying the Effects of Social Networks on Agricultural Technology Adoption: Turning a Black Box into a Policy Tool.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Demystifying the Effects of Social Networks on Agricultural Technology Adoption: Turning a Black Box into a Policy Tool./
Author:	Gu, Kun.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	121 p.
Notes:	Source: Dissertations Abstracts International, Volume: 82-11, Section: B.
Contained By:	Dissertations Abstracts International82-11B.
Subject:	Public policy. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13901274
ISBN:	9798728257363

Demystifying the Effects of Social Networks on Agricultural Technology Adoption: Turning a Black Box into a Policy Tool.
Gu, Kun.

Demystifying the Effects of Social Networks on Agricultural Technology Adoption: Turning a Black Box into a Policy Tool. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 121 p.

Source: Dissertations Abstracts International, Volume: 82-11, Section: B.

Thesis (Ph.D.)--The Pardee RAND Graduate School, 2020.

This item must not be sold to any third party vendors.

The adoption of agricultural technology is a key factor for agricultural sustainability and economic development, but this technology is often adopted slowly. There is growing recognition that social networks play an important role in knowledge diffusion and technology adoption. However, the mechanisms through which information is conveyed by social networks are not well understood. Using data from a randomized experiment in rural China, this study investigates the influence of social networks on the adoption of appropriate fertilizer use and the mechanisms through which social networks operate.To quantify the network effect, the experiment provides Farmer Field School (FFS) training on fertilizer management to a random subset of farmers in 28 villages located in the Chinese province of Anhui. For untrained farmers, exposure to trained friends significantly optimizes the amount of fertilizer they use, and the optimization gets better when they have more friends who have attended the training. Moreover, the effect of social networks varies depending on the type of relationship and strength of connections. Trained farmers who are perceived to be the farming experts by their peers have the largest effect on their friends' fertilizer optimization compared to the effects exerted by other friends.To demystify the black box of the social network mechanisms, I distinguish between social learning and behavior copying. Having expert friends attending the FFS training modestly improves farmers' knowledge of the environmental benefits that accrue from appropriate fertilizer use. Long-term friends are more likely to exert a positive social network effect through behavior copying, rather than through diffusion of knowledge on fertilizer use. In addition, the social network effect is larger when farmers have friends who are more central in the network.The efficacy of social networks in shaping individual behavior in regard to the adoption of technologies highlights the potential to conduct meaningful interventions without additional monetary or labor resources. Moreover, investigation of the mechanisms through which social networks drive changes in people's adoption behavior provides a promising basis for identifying effective policy interventions. Program management, implementation, performance, and ultimately, impact can be improved by designing training programs with well-targeted participants.

ISBN: 9798728257363Subjects--Topical Terms:

532803
Public policy.
Subjects--Index Terms:

Agricultural technology

Demystifying the Effects of Social Networks on Agricultural Technology Adoption: Turning a Black Box into a Policy Tool.
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500 $a Source: Dissertations Abstracts International, Volume: 82-11, Section: B.
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506 $a This item must not be sold to any third party vendors.
506 $a This item must not be added to any third party search indexes.
520 $a The adoption of agricultural technology is a key factor for agricultural sustainability and economic development, but this technology is often adopted slowly. There is growing recognition that social networks play an important role in knowledge diffusion and technology adoption. However, the mechanisms through which information is conveyed by social networks are not well understood. Using data from a randomized experiment in rural China, this study investigates the influence of social networks on the adoption of appropriate fertilizer use and the mechanisms through which social networks operate.To quantify the network effect, the experiment provides Farmer Field School (FFS) training on fertilizer management to a random subset of farmers in 28 villages located in the Chinese province of Anhui. For untrained farmers, exposure to trained friends significantly optimizes the amount of fertilizer they use, and the optimization gets better when they have more friends who have attended the training. Moreover, the effect of social networks varies depending on the type of relationship and strength of connections. Trained farmers who are perceived to be the farming experts by their peers have the largest effect on their friends' fertilizer optimization compared to the effects exerted by other friends.To demystify the black box of the social network mechanisms, I distinguish between social learning and behavior copying. Having expert friends attending the FFS training modestly improves farmers' knowledge of the environmental benefits that accrue from appropriate fertilizer use. Long-term friends are more likely to exert a positive social network effect through behavior copying, rather than through diffusion of knowledge on fertilizer use. In addition, the social network effect is larger when farmers have friends who are more central in the network.The efficacy of social networks in shaping individual behavior in regard to the adoption of technologies highlights the potential to conduct meaningful interventions without additional monetary or labor resources. Moreover, investigation of the mechanisms through which social networks drive changes in people's adoption behavior provides a promising basis for identifying effective policy interventions. Program management, implementation, performance, and ultimately, impact can be improved by designing training programs with well-targeted participants.
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