Paper Type
ERF
Abstract
This paper examines how dormant tie reactivation serves as a coping mechanism in highly virtual R&D teams that adopt shared leadership. Drawing on affiliative coping theory, we argue that employees facing heightened stress from distributed responsibilities and limited face-to-face interaction deliberately reconnect with inactive ties. These reactivated dormant ties retain both the familiarity of strong ties and the novelty of weak ties, thereby offering fresh information and trusted collaboration. Integrating dormant tie theory and innovation literature, we develop a multilevel model positing that the combined influences of team virtuality and shared leadership prompt the reactivation of such ties, which in turn facilitates enhanced innovative performance. We propose to test these hypotheses using hierarchical linear modeling of data from R&D scientists in a multinational high-tech organization.
Paper Number
1602
Recommended Citation
Darban, Mehdi, "Reactivating Dormant Ties in Virtual Teams: An Empirical Study on Affiliative Coping and Shared Leadership" (2025). AMCIS 2025 Proceedings. 10.
https://aisel.aisnet.org/amcis2025/sig_dite/sig_dite/10
Reactivating Dormant Ties in Virtual Teams: An Empirical Study on Affiliative Coping and Shared Leadership
This paper examines how dormant tie reactivation serves as a coping mechanism in highly virtual R&D teams that adopt shared leadership. Drawing on affiliative coping theory, we argue that employees facing heightened stress from distributed responsibilities and limited face-to-face interaction deliberately reconnect with inactive ties. These reactivated dormant ties retain both the familiarity of strong ties and the novelty of weak ties, thereby offering fresh information and trusted collaboration. Integrating dormant tie theory and innovation literature, we develop a multilevel model positing that the combined influences of team virtuality and shared leadership prompt the reactivation of such ties, which in turn facilitates enhanced innovative performance. We propose to test these hypotheses using hierarchical linear modeling of data from R&D scientists in a multinational high-tech organization.
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