Knowledge Sharing in Security-Sensitive Communities

Yonit Rusho (), Daphne Ruth Raban, David Simantov and Gilad Ravid
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Yonit Rusho: Department of Industrial Engineering and Management, Ben Gurion University of the Negev, Beer Sheba 8410501, Israel
Daphne Ruth Raban: School of Business Administration, Faculty of Social Sciences, University of Haifa, Haifa 3498838, Israel
David Simantov: Institute for the Research of the Methodology of Intelligence (IRMI), Ramat Hasharon 4713401, Israel
Gilad Ravid: Department of Industrial Engineering and Management, Ben Gurion University of the Negev, Beer Sheba 8410501, Israel

Future Internet, 2025, vol. 17, issue 4, 1-22

Abstract: Collective intelligence inherently relies on knowledge sharing. In security-sensitive organizations, tension arises between the need to develop collective knowledge and organizational culture, which requires secrecy. Drawing on the effects of trust on social behavior, this study examines knowledge-sharing in security-sensitive organizations compared to non-sensitive organizations dealing with the same subject matter. Methodology—We use Social Network Analysis (SNA) to analyze data from 18 communities: 7 security-sensitive and 9 non-sensitive. This comparative analysis explores the impact of organizational culture on communication structures and knowledge-sharing patterns. Findings—(1) The communication structure of security-sensitive communities differs from the structure of non-sensitive communities; (2) Security-sensitive communities have a higher density than non-sensitive communities. (3) When two security-sensitive organizations join together, knowledge sharing decreases. (4) Characteristics of the organizational culture of security-sensitive communities affect their network structure, which in turn affects knowledge sharing. This study provides valuable insights into the complex relationship between organizational culture, trust, and knowledge sharing in security-sensitive contexts. It highlights how secrecy and trust dynamics shape communication patterns and collective intelligence, contributing to a deeper understanding of knowledge-sharing practices in environments where security concerns are paramount. The findings are particularly relevant for improving knowledge-sharing strategies in both security-sensitive and non-sensitive organizations.

Keywords: collective intelligence; knowledge sharing; social networks analysis; community structure; security-sensitive communities (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2025
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