Network Activation Style and Returns to Brokerage: A Memory Perspective

• In Event: 40807 - Advancing Mathematical and Computational Research in Social Psychology (Co-sponsored by Section on Social Psychology)

Abstract

An individual’s social network provides a wealth of information, resources, and opportunities essential for job seeking, career guidance, and corporate acumen. Particularly, network brokers—individuals whose networks bridge disconnected groups—possess information and control advantages conducive to good ideas and sound decisions (Burt 1992, 2004, Kwon et al. 2020). Yet not all brokers benefit from their advantageous positions. Repeatedly, research shows that brokers vary substantially in their ability to harness their network positions effectively (Burt et al. 2013). We propose an important yet previously overlooked factor that explains variations in returns to brokerage: the degree to which brokers leverage diagnostic information versus nondiagnostic information when activating the opportunities in their network. We refer to this differentiation as brokers’ network activation styles. We theorize that brokers with a network-based activation style are better able to utilize their network effectively. Specifically, we introduce a novel behavioral measure that captures individuals’ network activation styles from name generators commonly used in egocentric network research. Taking stock of decades of memory research, we quantify individuals’ network activation styles as the extent to which their sequential activation patterns differ from a hypothetical agent who activates the same network using only network information. The smaller the difference, the more emphasis individuals place on network information during network activation. We find support for our theory in an archival analysis of the General Social Survey and a field survey with working professionals.

Authors

• Hui Sun, Frankfurt School of Finance & Mgmt gGmbH

• Jingze Wang, University of College London

• Tom Taiyi Yan, University of College London