TY - JOUR
T1 - A computational approach to managing performance dynamics in networked governance systems
AU - Kim, Yushim
AU - Johnston, Erik
AU - Kang, H.
N1 - Funding Information:
An earlier version of this paper was presented at the 10th Public Management Research Conference, Columbus, Ohio, October 1–3, 2009. the authors thank the anonymous reviewers for their comments and tanya Musgrave and Jennifer Auer for their assistance. Professor Johnston’s work on this paper was funded by grants from the National Science foundation: Virtual Organizations and Socio-technical Systems (VOSS) 0838206 and 0838295.
PY - 2011/6/1
Y1 - 2011/6/1
N2 - 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.
AB - 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.
KW - agent-based modeling
KW - complex adaptive systems
KW - networked governance systems
KW - performance management
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U2 - 10.2753/PMR1530-9576340407
DO - 10.2753/PMR1530-9576340407
M3 - Article
AN - SCOPUS:84857180728
VL - 34
SP - 580
EP - 597
JO - Public Performance & Management Review
JF - Public Performance & Management Review
SN - 1530-9576
IS - 4
ER -