Virtual organizational design laboratory: Agent-based modeling of the co-evolution of social service delivery networks with population dynamics

Authored by Oscar Herrera-Restrepo, Alexandra Medina-Borja

Date Published: 2018

DOI: 10.1016/j.eswa.2018.01.018

Sponsors: United States National Science Foundation (NSF)

Platforms: Java AnyLogic

Model Documentation: Other Narrative Flow charts

Model Code URLs: Model code not found

Abstract

This paper extends the concept of biological co-evolution to explain the performance and survival of one type of service organizations. It proposes that service delivery network design would benefit from complex adaptive systems (CAS) modeling approaches to recreate organizational phenomena driven by the interaction of the organization with its operating environment. This approach, paired with experimental design methods can serve as a virtual laboratory. We take the case of social service delivery (SSD) organizations that are structured as nonprofit organizations providing humanitarian assistance and relief services. These organizations often serve different geographical regions, thus, racial composition, migration patterns, and wealth of the populations served are factors that vary between locations. SSDs operate through service nodes (i.e., field offices, chapters, branches) in a network configuration. Therefore, the managerial decision of where to locate the field offices is an important one. An agent-based model to recreate agents' interactions as proxies of those exchanges occurring in real SSD settings is used. A series of validation experiments instill confidence that our model can be used as a virtual research laboratory. This paper contributes to the field of organizational design by testing a model able to recreate different policies that combined with different operating conditions impact the network over time and space. In addition, it provides experimental insights on what type of network configuration might provide a higher number of services delivered over time across the service network. The results can inform those defining the service system architecture looking to achieve SSD's goals considering the demographics of the markets served. Published by Elsevier Ltd.
Tags
Complexity Complex adaptive systems systems organizational design Service systems engineering Virtual laboratory Service delivery network