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dc.contributor.advisorRam, Sudhaen_US
dc.contributor.authorLee, Changheon
dc.creatorLee, Changheonen_US
dc.date.accessioned2012-09-11T18:38:17Zen
dc.date.available2012-09-11T18:38:17Zen
dc.date.issued2012en
dc.identifier.urihttp://hdl.handle.net/10150/243117en
dc.description.abstractOnline communities have become an increasingly popular channel for social interaction, enabling knowledge and opinion sharing across a board range of topics and contexts. Their viability and sustainability depends largely on contributions from community members in terms of time, resources, and knowledge. However, how individuals' knowledge contribution behavior changes over time and what network structural characteristics influence individuals' contribution behavior is not well understood. This study investigates "co-evolution" of social networks (i.e. advice network) and knowledge contribution behavior thorough a lens of social selection and social influence mechanism. This study are particularly interested in examining the dynamics of the advice network ties and the knowledge contribution behavior in the context of virtual financial communities in which people voluntarily participate to exchanges investing-related information. Unlike popular friendship-based online social networks, virtual financial communities in this study enables members to construct their own advice network by adding, maintaining, or terminating advice ties. Changes in network ties are referred to as social selection, while changes in individuals' behavior in response to the current network position are referred to as social influence. Dynamic network modeling is applied to investigate effects of social selection and influence separately and then examine the interplay between social selection and behavioral influence. Examination of such effects both separately and simultaneously requires a longitudinal data that capture dynamic changes in both the advice ties and the behavior under study.
dc.language.isoenen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectManagement Information Systemsen_US
dc.subjectSocial Networken_US
dc.subjectVirtual Financial Communityen_US
dc.titleDynamics of Advice Network and Knowledge Contribution: A Longitudinal Social Network Analysisen_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.contributor.committeememberPingry, Daviden_US
dc.contributor.committeememberLin, Mingfengen_US
dc.contributor.committeememberRam, Sudhaen_US
dc.description.releaseRelease after 09-Aug-2014en_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineManagement Information Systemsen_US
thesis.degree.namePh.D.en_US
dc.description.admin-noteOriginally embargoed until 09-Aug-2014; further restricted on 22-Jan-2016 per author request / KCen_US
refterms.dateFOA2016-08-09T00:00:00Z
html.description.abstractOnline communities have become an increasingly popular channel for social interaction, enabling knowledge and opinion sharing across a board range of topics and contexts. Their viability and sustainability depends largely on contributions from community members in terms of time, resources, and knowledge. However, how individuals' knowledge contribution behavior changes over time and what network structural characteristics influence individuals' contribution behavior is not well understood. This study investigates "co-evolution" of social networks (i.e. advice network) and knowledge contribution behavior thorough a lens of social selection and social influence mechanism. This study are particularly interested in examining the dynamics of the advice network ties and the knowledge contribution behavior in the context of virtual financial communities in which people voluntarily participate to exchanges investing-related information. Unlike popular friendship-based online social networks, virtual financial communities in this study enables members to construct their own advice network by adding, maintaining, or terminating advice ties. Changes in network ties are referred to as social selection, while changes in individuals' behavior in response to the current network position are referred to as social influence. Dynamic network modeling is applied to investigate effects of social selection and influence separately and then examine the interplay between social selection and behavioral influence. Examination of such effects both separately and simultaneously requires a longitudinal data that capture dynamic changes in both the advice ties and the behavior under study.


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