Two Heads Are Better Than One: Knowledge Sharing in Organizational Social Networks

Baksa, Máté (2023) Two Heads Are Better Than One: Knowledge Sharing in Organizational Social Networks. PhD thesis, Budapesti Corvinus Egyetem, Gazdálkodástani Doktori Iskola. DOI

PDF : (dissertation)
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In this doctoral dissertation, the author explores three research areas of organizational network theory that relate to the analysis of organizational knowledge networks. The author uses a mixed method approach, including literature reviews and qualitative and quantitative methods, to answer the research questions. This paper-based dissertation includes four papers in total. The first paper, entitled “Enterprise social media: The engine of organizational social networks,” presents the unique characteristics of enterprise social media through a comparison of the mechanisms of social networks in an online and offline context. The study found that (1) enterprise social media helped to build trust relationships in the organization through three interrelated features: (a) getting to know each other both professionally and personally, (b) making work visible, and (c) allowing orientation of new members of the organization. The study also found that (2) enterprise social media helped with knowledge sharing in the organization, as the platform's archiving function and searchability made it possible to extract information over time and to find familiar or new content. In addition, the study found that (3) enterprise social media supports the development of meta-knowledge, which is the knowledge of who knows what and who knows whom. The second paper, a literature review on negative ties in social networks, (4) draws attention to a phenomenon that had previously remained in the blind spot of scholars and managers. The author (5) places negative ties in extant models of social relationships and dyadic phenomena and proposes directions for future research. The third paper, entitled “Prerequisites of advice-seeking and knowledge sharing: Analysis of an organizational knowledge network,” explores the dynamics of advice-seeking in knowledge networks and their relational preconditions. Through a case study based on a survey and interviews at a Budapest-based management consultancy, it is found that (6) interpersonal trust and perceived competence were the most important factors in the formation of advice-seeking relationships. The study also found that (7) personal sympathy (as measured by a willingness to meet informally after work) reduced the likelihood of developing advice-seeking relationships and that the organizational culture of the consultancy was supportive of knowledge sharing. The fourth paper, entitled “The Invisible Foundations of Collaboration in the Workplace: A Multiplex Network Approach to Advice-Seeking and Knowledge Sharing,” aimed to understand the relational factors that influence advice-seeking behavior in relationships through a multiplex approach. The paper proposed that (8) a comprehensive model of relational dimensions, including feelings, judgments, and behavioral intents, can explain a significant amount of the variance in the formation of advice-seeking ties. Through the analysis of three sample knowledge networks, the paper found that (9) despite relative explanatory power of variables differ to some extent across the samples, relational prerequisites are significant in the formation of advice-seeking relationships in all examined organizations. Overall, this doctoral dissertation contributes to organizational network theory by providing a deeper understanding of the unique characteristics of enterprise social media, the significance of negative ties in social networks, and the relational preconditions of advice-seeking and knowledge sharing. The multiplex approach to advice-seeking and knowledge sharing proposed in the fourth paper also offers a new perspective on the study of organizational networks.

Item Type:Thesis (PhD thesis)
Supervisor:Branyiczki Imre, Dobák Miklós
Subjects:Knowledge economy, innovation
Business organisation
ID Code:1293
Date:29 June 2023
Deposited On:23 Mar 2023 12:59
Last Modified:23 Feb 2024 08:32

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