| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w24912 |
| 来源ID | Working Paper 24912 |
| Can Network Theory-based Targeting Increase Technology Adoption? | |
| Lori Beaman; Ariel BenYishay; Jeremy Magruder; Ahmed Mushfiq Mobarak | |
| 发表日期 | 2018-08-20 |
| 出版年 | 2018 |
| 语种 | 英语 |
| 摘要 | In order to induce farmers to adopt a productive new agricultural technology, we apply simple and complex contagion diffusion models on rich social network data from 200 villages in Malawi to identify seed farmers to target and train on the new technology. A randomized controlled trial compares these theory-driven network targeting approaches to simpler strategies that either rely on a government extension worker or an easily measurable proxy for the social network (geographic distance between households) to identify seed farmers. Our results indicate that technology diffusion is characterized by a complex contagion learning environment in which most farmers need to learn from multiple people before they adopt themselves. Network theory based targeting can out-perform traditional approaches to extension, and we identify methods to realize these gains at low cost to policymakers. |
| 主题 | Development and Growth ; Development ; Innovation and R& ; D |
| URL | https://www.nber.org/papers/w24912 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/582586 |
| 推荐引用方式 GB/T 7714 | Lori Beaman,Ariel BenYishay,Jeremy Magruder,et al. Can Network Theory-based Targeting Increase Technology Adoption?. 2018. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w24912.pdf（583KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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