A COMPUTATIONAL APPROACH TO MANAGING PERFORMANCE DYNAMICS IN NETWORKED GOVERNANCE SYSTEMS
Authored by Yushim Kim, Erik W. Johnston, H. S. Kang
Date Published: 2011-06
DOI: 10.2753/pmr1530-9576340407
Sponsors:
United States National Science Foundation (NSF)
Platforms:
NetLogo
Model Documentation:
Other Narrative
Model Code URLs:
Model code not found
Abstract
Governance systems continue to become more networked, collaborative, and interdependent. A computational approach to understanding and capitalizing on the complexity of such systems can provide invaluable insights on managing and enhancing performance. Building upon a complex adaptive systems view, this article demonstrates the use of computer simulation modeling to understand performance in networked governance systems and inform practitioners on how benefits can be harvested from the evolution of governance structures. The article contributes to the performance management field by directing attention to ex ante conditions and dynamic tensions among multiple stakeholders, in contrast to collecting ex post performance data. It also discusses the inherent challenges of a computational approach and how they can be mitigated.
Tags
Agent-based modeling
Complex adaptive systems
networked governance systems
performance management