Abstract

A network analysis can quantify the depth and breadth of a farmer’s relationships with other local farmers, buyers and sellers, or other groups and organizations. Such an analysis can potentially also reveal farmers’ incentives, situations, and behaviors, and it may explain their economic success more generally. This study examines small and minority farmers’ networks using a primary survey in three farming communities. We emphasize networks related to production, marketing, and resource-sharing activities of 127 farmers (nodes) in Tennessee, 46 in Maryland, and 23 in Delaware, and compute three different measures of network importance or “centrality” for each farmer. We then use generalized least squares analysis relating farmer’s age, gender, race, educational attainment, labor use on the farm, and farm location to the farmer’s centrality position or importance in the network, defined by number and strength of links or connections. In additional regression analyses, we find significantly positive effects of the centrality position on farm sales of specialty crops: our model predicts that a farmer who adds one additional link or connection can expect a 19% to 25% increase in sales, all else equal. Our results can potentially be used not only to disseminate information more efficiently, but also to identify farm­ers who would benefit the most from more targeted extension services. See the press release for this article.

Highlights

  • Knowledge about new agricultural practices and technology is often diffused through human interactions, whereby network structures as well as informant characteristics are critical

  • We find significantly positive effects of the centrality position on farm sales of specialty crops: our model predicts that a farmer who adds one additional link or connection can expect a 19% to 25% increase in sales, all else equal

  • The trust that is represented by social capital may be most valuable when it is used to address local problems involving the provision of public goods (Coleman, 1990; Flora & Flora, 2008; Rupasingha & Goetz, 2007)

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Summary

Introduction

Knowledge about new agricultural practices and technology is often diffused through human interactions, whereby network structures as well as informant characteristics are critical. Individual and community cooperation and interactions among farmers and between groups can help build their capacity in new entrepreneurial opportunities (Beratan et al, 2014) and local agri-food systems (Dunning et al, 2012). It can mitigate problems such as food insecurity in urban agriculture settings (Meenar & Hoover, 2012)

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