Social learning and the acquisition of information and knowledge—a network approach for the case of technology adoption

Abstract

Abstract The complexity of agricultural innovations and heterogeneity of circumstances of technology application, outcomes, and social network structures have often led to obstacles in social learning and suboptimal adoption. In this article, we examine technology diffusion by focusing on the roles of peer adoption decision, peer experience, and network structures, using survey data from 500 farm households in Northern Ghana to generate social network contacts. Our results reveal that learning from peer experiences matter more in the diffusion process than just peer adoption decisions alone. We also find that social learning and the likelihood of adoption are higher when peers are central nodes, and particularly when they belong to cohesive subgroups, but lower when they are in highly segregated networks. Our results shed new light on the role of central agents, since highly cohesive neighbourhoods seem to promote diffusion more in high-modularity networks than central nodes.