Can Network Theory-Based Targeting Increase Technology Adoption?

• 成果类型: Article
• 署名作者: Beaman, Lori; BenYishay, Ariel; Magruder, Jeremy; Mobarak, Ahmed Mushfiq
• 署名单位: Northwestern University; William & Mary; University of California System; University of California Berkeley; Yale University
• 刊物名称: AMERICAN ECONOMIC REVIEW
• ISSN/ISSBN: 0002-8282
• DOI: 10.1257/aer.20200295
• 发表日期: 2021
• 页码: 1918-1943
• 关键词: Social networks; diffusion; INFORMATION; population; corn

摘要

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.