DPA Research & Policy Seminar Series: Kate Albrecht
January 22, 2021
12:00 PM - 1:00 PM
DPA Research & Policy Virtual Seminar Series: Kate Albrecht (UIC)
Jan 22nd at 12 PM CST
Purpose-oriented Networks and their Environment: A Population Ecology of Network Domains
Purpose-oriented networks have arisen to center-stage in the field of public management as a crucial, and increasingly prevalent, forum for addressing complex or wicked public issues in local communities. Recently, scholars have identified the need for greater theorizing on environmental factors and their influence on purpose-oriented networks. Theories of population ecology aim to understand population level dynamics within organizational settings. In this study, we apply theories of population ecology to advance scholarship of network domains. Network domains are defined as populations of purpose-oriented networks active within the same mission and geographic area. Using a longitudinal bipartite dataset of 74 different purpose-oriented networks nested in three different geographic areas, we test a series of hypotheses drawn from population ecology concerning the impact of domain saturation on organizational and network-level outcomes. Analysis employs a combination of dynamic network modeling using stochastic agent-oriented models, as well case study and standard OLS regression techniques. Findings offer support for the relevance of population level dynamics in explaining network change over time. Specifically, findings indicate that the introduction of new networks into the domain attracts members away from existing networks and can lead to network dissolution. Findings further suggest that this effect is more pronounced in more saturated network domains. Implications for advancing a population ecology of networks is discussed as well as a cautionary tale for public and philanthropic initiatives which require the introduction of new networks as a requirement of funding.
Meeting info:
Join Zoom Meeting
https://uic.zoom.us/j/88937391718?pwd=SDY2Z2xTM1pmbTRtQm5rTWE5R3F4UT09
Meeting ID: 889 3739 1718
Passcode: CFiTGk4G
Date posted
Jan 19, 2021
Date updated
Jan 19, 2021