If you do not know who knows what: Advice seeking under changing conditions of uncertainty after an acquisition.

Mirc, N.; Parker, A.

Abstract

In this study we develop a model to explain the dynamics of advice seeking after an acquisition. We build on a theory of advice seeking that draws from prospect theory and expectancy theory. We theorize that immediately after an acquisition there is uncertainty about who knows what, but over time individuals become more aware of the expertise within the organization and they change their advice networks based upon this increased awareness. Our model examines four micro-processes of advice seeking: reciprocity, preferential attachment, transitivity, and legacy-firm tie preferences. To test our hypotheses we use post-acquisition data over four time periods in a recruitment consulting firm. Our longitudinal analysis uses a stochastic actor-orientated model and our results indicate that immediately after the acquisition individuals have a tendency to seek advice based upon reciprocity and preferential attachment. However, over time these tendencies diminish. Surprisingly, transitivity does not play a significant role, which suggests that other micro-processes such as reciprocity are dominant. In addition, individuals in the acquired firm have a tendency to make more ties and there is a preference for same firm ties in both legacy firms, with the tendency being higher in the acquired firm. Our findings add to theories on the process of advice seeking under conditions of uncertainty, on knowledge transfer processes in mergers and acquisitions, and the knowledge based view of the firm.

Citation

Mirc, N., & Parker, A. (2020). If you do not know who knows what: Advice seeking under changing conditions of uncertainty after an acquisition. Social Networks, 61, 53-66. https://doi.org/10.1016/j.socnet.2019.08.006

• Journal Article Type: Article
• Online Publication Date: Sep 12, 2019
• Publication Date: 2020-05
• Deposit Date: Sep 21, 2021
• Journal: Social Networks
• Print ISSN: 0378-8733
• Electronic ISSN: 1879-2111
• Publisher: Elsevier
• Volume: 61
• Pages: 53-66
• DOI: https://doi.org/10.1016/j.socnet.2019.08.006
• Public URL: https://durham-repository.worktribe.com/output/1240336