Diffusion of knowledge in social media networks

Effects of Reputation Mechanisms and Distribution of Knowledge Roles

Bibliographic Data

ID7519320
AuthorsTaha Havakhor (0000-0002-4338-5970, Management Science & Information Systems Department Spears College of Business Stillwater OK USA, corresponding author), Amr Soror (0000-0002-7316-0510, California State University, Fullerton, corresponding author), Amr A Soror (Department of Information Systems and Decision Sciences, Mihaylo College of Business and Economics California State University Fullerton AR USA), Rajiv Sabherwal (0000-0002-2953-5709, Information Systems Department, Sam M. Walton College of Business University of Arkansas Fayetteville AR USA, corresponding author)
Year2016
Volume28
Issue1
Pages104-141
Publication date2016-11-29
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInformation Systems Journal (JOURNAL)
Journal identifiersISSN: 1350-1917 • E-ISSN: 1365-2575
PublisherWiley (PUBLISHER • GB)
DOI10.1111/isj.12127
OpenAlexW2558689831
LanguageEN
Citations received12
References cited146

Social media platforms serve as important tools for diffusing knowledge within organizations. The factors affecting knowledge diffusion through social media networks (SMNs) need to therefore be better understood. Accordingly, this paper focuses on two SMN‐specific characteristics – reputation mechanisms and the distribution of knowledge roles – which are argued to enhance and enable, respectively, the smooth transfer of knowledge in a SMN. To examine their effects, we distinguish between two types of reputation mechanisms – adaptive and objective – and across three distinct knowledge roles in SMNs: seekers, contributors and brokers. We argue that the extent of knowledge diffusion in the SMN depends on the type of mechanism and the relative distribution of these three roles. Using data collected through an agent‐based simulation, we find that (a) the distribution of knowledge roles affects knowledge diffusion, with distributions consisted of more brokers outperforming others and (b) objective reputation mechanisms outperform adaptive mechanisms. Furthermore, we find that reputation mechanisms and distribution of knowledge roles interact to influence knowledge diffusion. The study's implications for future research and practice are discussed in the light of its limitations. © 2016 John Wiley & Sons Ltd

Diffusion · Distribution (mathematics · Epistemology · Innovation diffusion · Knowledge management · Mechanism (biology · Physics · Reputation · Social media · Sociology · World Wide Web · Computer Science · Expert finding and Q&A systems · Knowledge Management and Sharing · Mathematics · Opinion Dynamics and Social Influence