City Research Online

Abstract

Network research shows that strong relationships, highly embedded relationships and brokered relationships may have different outcomes. While pros and cons are associated with each of these network structures, how this ambiguity translates into individuals’ actions of network change is unclear. Specifically, if network positions can be both beneficial and detrimental, how do individuals decide whether to maintain those positions? We develop a tie‐specific model of network modification that captures the positioning in the work‐related network and the level of knowledge acquired from that network for each individual in a knowledge‐intensive organization. Our analysis of tie‐level data identifies the level of acquired knowledge as an important disambiguating mechanism that determines how individuals manage their strong ties, embedded ties and brokered ties over time.

Publication Type:	Article
Additional Information:	This is the peer reviewed version of the following article: Stea, D., Pedersen, T. and Soda, G. (2022), Keep or Drop? The Origin and Evolution of Knowledge Relationships in Organizations. Brit J Manage, 33: 1517-1534, which has been published in final form at https://doi.org/10.1111/1467-8551.12521. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.
Publisher Keywords:	Network dynamics, network microfoundations, knowledge acquisition, social embeddedness, agency
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Departments:	Bayes Business School Bayes Business School > Management
SWORD Depositor:	Symplectic Administrator

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