Groups and Teams

OVERVIEW

Dynamic network theory and network goal analysis are highly applicable to group and team dynamics, given their focus on goals and objectives. Going beyond a purely group-level focus alone, dynamic network theory illustrates that out-group entities in the dynamic network system can also be very influential, as illustrated in the network goal graph / dynamic network chart below:

Multilevel Views

A multilevel perspective appears when we see multiple teams in an organization, as illustrated below. Here, a portrayal of the entire organization can be seen. In this simple example, technologies could also allow one to toggle between different groups and their effects on different organizational goals and objectives. To note, the term "dynamic network system", our original term, is interchangeable with the newer term "network goal systems", to help promote further conceptual differentiation from other systems approaches.

Analyses

Researchers involved in group or team studies have the capacity to examine the complex network dynamics at individual and group levels. For example, individual contributions can be compared with overall averages to expose the dynamics of the complete system. When multiple team members are included in a network goal survey, we can also calculate dynamic network intelligence among participating members. This gauges the degree to which each team member knows others’ motives in the system. Click here for more details about team analyses.

NEW: Recent work presented at academic societies:

Society for Judgement and Decision Making, New York, Winter 2024

Title:

Integrating Behavioral Reasoning Theory and Dynamic Network Theory to Predict Group Decisions: A Multi-level Analysis of Observable Discussions

Authors:

Elisabeth Mah and James D. Westaby

Abstract:

This paper integrates dynamic network theory and behavioral reasoning theory to understand observable group decision making. The framework explains how initial individual reasoning from a focal actor sets the stage for their contributions into group decision-making discussions. Then, observable reasoning from the focal actor in conjunction with observable support vs. resistance from actors in the network (i.e., alters) is then expected to impact final decisions. Results from the multi-group study highlight the predictive advantage of the network reasoning framework over traditional models. The framework also uniquely allows for the network visualization of group reasoning and support.