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.
Keywords: Social Learning, Agricultural Technology Adoption, Complex Contagion, Malawi
JEL Classification Codes: O16, O13
Exploring non-residential technology adoption: an empirical analysis of factors associated with the adoption of photovoltaic systems by municipal authorities in Germany
Technology Fundamentals and False Bubble Detection: Evidence from Dot-Com and AI Episodes
Shenzhen University（深圳大学）；Xiamen University（厦门大学）；Chinese Academy of Sciences（中国科学院）；Renmin University of China（中国人民大学）；Beijing University of Chinese Medicine（北京中医药大学）；University of Wisconsin, Madison（威斯康星大学麦迪逊分校）
When a Few Misfits Trigger Digital Adoption Cascades: Network Reach, Threshold Heterogeneity, and Performance-Conditioned Complex Contagion in an Agent-Based Model of Firms
