Simulation and Managerial Decision Making:A Double-Loop Learning Framework

Authors


  • Hyunjung Kim is assistant professor in the Department of Management at California State University, Chico. She received her doctorate in public administration from the University at Albany. She uses ethnographic methods and causal mapping methods to represent and understand the social process of aligning different mental models of decision makers. She also uses systems thinking and system dynamics modeling to enhance decision making in various management groups. E-mail: hkim18@csuchico.edu

  • Roderick H. MacDonald is director of the Initiative for System Dynamics in the Public Sector at the Rockefeller College of Public Affairs and Policy, University at Albany. He earned his doctorate in public administration, focusing on the development of system dynamics simulation models as decision support tools. He has used system dynamics to address problems in various policy areas, including the delivery of mental health services, Social Security disability programs, DWI recidivism, and traffi c safety. E-mail: rod@isdps.org

  • David F. Andersen is Distinguished Service Professor of Public Administration, Public Policy, and Information Science at the University at Albany. He has served as a technical consultant to public and nonprofi t agencies in the federal, state, and local sectors, as well as corporate clients in North America and Europe. He is coauthor of Introduction to Computer Simulation: The System Dynamics Modeling Approach and Government Information Management. He holds a doctorate in management from MIT's Sloan School. E-mail: david.andersen@albany.edu

Abstract

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.

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