Team problem solving and motivation under disorganization: an agent-based modeling approach

Purpose: This paper aims at simulating on how “disorganization” affects team problem solving and motivation. The prime objective is to determine how team problem solving varies between an organized and disorganized environment.
Design/methodology/approach: Using agent-based modeling, we use a real world data set from 226 volunteers at five different types of non-profit organizations in Southwest England in order to define some attributes of the agents. We introduce the concepts of natural, structural and functional disorganization while operationalizing natural and functional disorganization.
Findings: The simulations show that “disorganization” is more conducive for problem solving efficiency than “organization” given enough flexibility (range) to search and acquire resources. Our findings further demonstrate that teams with resources above their hierarchical level (access to better quality resources) tend to perform better than teams that have only limited access to resources.
Originality/value: Our nuanced categories of “(dis-)organization” allow us to compare between various structural limitations, thus generating insights for improving the way managers structure teams for better problem solving.