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