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Title: Modeling Managerial Behavior: Misperceptions of Feedback in a Dynamic Decision Making Experiment
Author: John D. Sterman
Journal: Management Science
Volume: 35
Number: 3
Pages: 321--339
Year: 1989
Abstract: Studies in the psychology of individual choice have identified numerous cognitive and other bounds on human rationality, often producing systematic errors and biases. Yet for the most part models of aggregate phenomena in management science and economics are not consistent with such micro-empirical knowledge of individual decision-making. One explanation has been the difficulty of extending the experimental methods used to study individual decisions to aggregate, dynamic settings. This paper reports an experiment on the generation of macrodynamics from microstructure in a common managerial context. Subjects manage a simulated inventory distribution system which contains multiple actors, feedbacks, nonlinearities, and time delays. The interaction of individual decisions with the structure of the simulated firm produces aggregate dynamics which systematically diverge from optimal behavior. An anchoring and adjustment heuristic for stock management is proposed as a model of the subjects' decision processes. Econometric tests show the rule explains the subjects' behavior well. The estimation results identify several `misperceptions of feedback' which account for the poor performance of the subjects. In particular, subjects are shown to be insensitive to the feedbacks from their decisions to the environment. Finally, the generality of the results is considered and implications for behavioral theories of aggregate social and economic dynamics are explored.

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@Article{sterman89a,
  author =	 {John D. Sterman},
  title =	 {Modeling Managerial Behavior: Misperceptions of
                  Feedback in a Dynamic Decision Making Experiment},
  journal =	 {Management Science},
  year =	 1989,
  volume =	 35,
  number =	 3,
  pages =	 {321--339},
  abstract =	 {Studies in the psychology of individual choice have
                  identified numerous cognitive and other bounds on
                  human rationality, often producing systematic errors
                  and biases. Yet for the most part models of
                  aggregate phenomena in management science and
                  economics are not consistent with such
                  micro-empirical knowledge of individual
                  decision-making. One explanation has been the
                  difficulty of extending the experimental methods
                  used to study individual decisions to aggregate,
                  dynamic settings. This paper reports an experiment
                  on the generation of macrodynamics from
                  microstructure in a common managerial
                  context. Subjects manage a simulated inventory
                  distribution system which contains multiple actors,
                  feedbacks, nonlinearities, and time delays. The
                  interaction of individual decisions with the
                  structure of the simulated firm produces aggregate
                  dynamics which systematically diverge from optimal
                  behavior. An anchoring and adjustment heuristic for
                  stock management is proposed as a model of the
                  subjects' decision processes. Econometric tests show
                  the rule explains the subjects' behavior well. The
                  estimation results identify several `misperceptions
                  of feedback' which account for the poor performance
                  of the subjects. In particular, subjects are shown
                  to be insensitive to the feedbacks from their
                  decisions to the environment. Finally, the
                  generality of the results is considered and
                  implications for behavioral theories of aggregate
                  social and economic dynamics are explored.},
  url = 	 {http://jmvidal.cse.sc.edu/library/sterman89a.pdf},
  keywords = 	 {economics complexity beergame},
  cluster = 	 {9864740858624482687}
}
Last modified: Wed Mar 9 10:13:46 EST 2011