Viol J, Durst C (2014)
Publication Type: Book chapter / Article in edited volumes
Publication year: 2014
Publisher: Springer Verlag
Edited Volumes: Social Networks: A Framework of Computational Intelligence
Series: Studies in Computational Intelligence
Book Volume: 0
Pages Range: 259-285
ISBN: 978-3-319-02992-4
DOI: 10.1007/978-3-319-02993-1-12
Organizations introduce Enterprise Social Networks to support knowledge management and in particular to facilitate knowledge transfer. However, to reap the full benefit of Enterprise Social Networks it is necessary to understand the relations and the interactions between employees within these networks. This book chapter provides a literature-based theoretical framework that enables the analysis of the relationships between an employee's embeddedness in an Enterprise Social Network, their access to social capital, their individual knowledge transfer process and the achieved knowledge transfer in an organization. We develop network-based measures that can be extracted for each framework element using data mining techniques and discuss the relationships among the framework elements. Additionally, suggestions on how to process the network measures using Computational Intelligence methods, e.g., fuzzy logic, are presented. Establishing a strong theoretical groundwork, this book chapter encourages future research crossing the boundaries between information systems, Computational Intelligence, organizational science, and knowledge management. © 2014 Springer International Publishing Switzerland.
APA:
Viol, J., & Durst, C. (2014). A Framework to Investigate the Relationship between Employee Embeddedness in Enterprise Social Networks and Knowledge Transfer. In Pedrycz, W., Chen, S.-M. (Eds.), Social Networks: A Framework of Computational Intelligence. (pp. 259-285). Springer Verlag.
MLA:
Viol, Janine, and Carolin Durst. "A Framework to Investigate the Relationship between Employee Embeddedness in Enterprise Social Networks and Knowledge Transfer." Social Networks: A Framework of Computational Intelligence. Ed. Pedrycz, W., Chen, S.-M., Springer Verlag, 2014. 259-285.
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