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Simulation and Managerial Decision Making:A Double‐Loop Learning Framework
Author(s) -
Kim Hyunjung,
MacDonald Roderick H.,
Andersen David F.
Publication year - 2013
Publication title -
public administration review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.721
H-Index - 139
eISSN - 1540-6210
pISSN - 0033-3352
DOI - 10.1111/j.1540-6210.2012.02656.x
Subject(s) - context (archaeology) , computer science , double loop , process (computing) , system dynamics , knowledge management , process management , management science , artificial intelligence , business , engineering , paleontology , biology , operating system
Systems approaches present opportunities for public managers and policy makers to view policies and programs in a broader context. This article presents a framework to explain how simulation modeling promotes double‐loop learning in management teams by building and exploring collective mental models as well as by enhancing accuracy of the mental models. The authors discuss the types of problems that may benefit from simulation modeling and illustrate how double‐loop learning occurs in the process of dynamic hypothesis testing. Using a case from New York State's Division of Disability Determination, the article shows how simulation modeling built confidence in a management team's decision by providing the team with tools to share and examine multiple hypotheses about a declining trend in initial disability recipients in the state between 1998 and 2004 .