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Serving members and reaching others: The performance and social networks of a landowner cooperative
Authors:Mark Rickenbach  
Affiliation:aDepartment of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI 53706, USA
Abstract:Local forest landowner associations and broader peer-to-peer learning efforts have received attention–particularly in the United States of America–as ways to increase landowner engagement in forest planning and management. Unlike traditional technical assistance and outreach, knowledge is primarily shared among landowners as opposed to being derived from natural resource professionals. While potentially promising, few studies have investigated these approaches. Through a study of a landowner cooperative in Wisconsin, I report on a finding that considers both the effectiveness of a landowner cooperative in the Upper Midwest (USA) and the social network members rely on in decision-making. The former relies on an importance–performance analysis (IPA) of the services provided by the cooperative and the latter on an egocentric network analysis of members with an emphasis on strong and weak ties. Data were collected via a mail survey to which 146 members (81%) responded. The IPA indicates that the cooperative is providing services with which members are largely satisfied. The network analysis suggests that members, through strong ties, discuss their land with on average three others—primarily natural resource professionals (including cooperative staff), as opposed to other members, neighbors, and kin. However, by virtue of membership, they share weak ties with other members whom they see as trustworthy. The extent to which a network perspective might be applied to similar situations is discussed, as are conceptual implications and future directions. The main conclusion is that the emergence of local landowner associations and peer-to-peer learning requires research methods that better capture the social nature of these new directions.
Keywords:Landowner associations   Cooperatives   Egocentric networks   Importance–  performance analysis   Private landowners   Peer-to-peer learning
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