Information Network Among Farmers: A Case Study in Ghana

Qian Yu and Patience Pokuaa Gambrah

SAGE Open, 2024, vol. 14, issue 1, 21582440241228696

Abstract: It is well established that a person’s productivity is strongly related to interactions among their network cycles. Despite this, much of the literature concerning farmers’ productivity describes only their formal relationships with extension officials, ignoring their personal relationships. This study was motivated by the need to understand how farmers can use their social networks to promote information diffusion and learning among themselves. The study assessed whether farmers’ information networks can positively influence their productivity and performance through the study of their network structure. We used survey data from 200 Ghanaian farmers. The data was then analyzed using descriptive statistics and an exponential random graph model (ERGM). The results of this study showed that farmers’ information networks had a positive effect on their performance and productivity. The study also revealed that farmers seek information from key and influential farmers while key farmers also seek information from other key farmers. A further finding of the study showed that many factors contributed to the successful diffusion of information, such as popularity, activity spread, reciprocity, multiple connections, and homophily of experience. However, on the other hand, transitivity was not significant in this network. Hence, this study clarifies the effect of the structural characteristics of farmers’ information network which influence information diffusion for higher performance and productivity. This study argues that agricultural managers should take measures to ensure that farmers understand how their information network can benefit their peers, as well as their own performance and productivity.

Keywords: farmers’ network; exponential random graph model; knowledge diffusion; farmers’ productivity (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:14:y:2024:i:1:p:21582440241228696

DOI: 10.1177/21582440241228696

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