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Boom, Bust, and Failures to Learn in Experimental Markets

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Author Info

  • Mark Paich

    (Department of Economics, Colorado College, Colorado Springs, Colorado 80903)

  • John D. Sterman

    (Sloan School of Management, Massachusetts Institute of Technology, 50 Memorial Drive, Cambridge, Massachusetts 02142)

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    Abstract

    Boom and bust is a pervasive dynamic for new products. Word of mouth, marketing, and learning curve effects can fuel rapid growth, often leading to overcapacity, price war, and bankruptcy. Previous experiments suggest such dysfunctional behavior can be caused by systematic "misperceptions of feedback," where decision makers do not adequately account for critical feedbacks, time delays, and nonlinearities which condition system dynamics. However, prior studies often failed to vary the strength of these feedbacks as treatments, omitted market processes, and failed to allow for learning. A decision making task portraying new product dynamics is used to test the theory by varying the strength of key feedback processes in a simulated market. Subjects performed the task repeatedly, encouraging learning. Nevertheless, performance relative to potential is poor and is severely degraded when the feedback complexity of the environment is high, supporting the misperception of feedback hypothesis. The negative effects of feedback complexity on performance were not moderated by experience, even though average performance improved. Models of the subjects' decision making heuristics are estimated; changes over trials in estimated cue weights explain why subjects improve on average but fail to gain insight into the dynamics of the system. Though conditions for learning are excellent, experience does not appear to mitigate the misperceptions of feedback or systematic dysfunction they cause in dynamic decision making tasks. We discuss implications for educational use of simulations and games.

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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 39 (1993)
    Issue (Month): 12 (December)
    Pages: 1439-1458

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    Handle: RePEc:inm:ormnsc:v:39:y:1993:i:12:p:1439-1458

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    Related research

    Keywords: decision making; simulation; feedback; experimental economics; system dynamics;

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    Cited by:
    1. Atun, Rifat A. & Lebcir, Reda M. & McKee, Martin & Habicht, Jarno & Coker, Richard J., 2007. "Impact of joined-up HIV harm reduction and multidrug resistant tuberculosis control programmes in Estonia: System dynamics simulation model," Health Policy, Elsevier, vol. 81(2-3), pages 207-217, May.
    2. Atkins, Paul W. B. & Wood, Robert E. & Rutgers, Philip J., 2002. "The effects of feedback format on dynamic decision making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 88(2), pages 587-604, July.
    3. Roth, George Lothar. & Senge, Peter M. & Society for Organizational Learning., 1997. "From theory to practice : research territory, processes and structure at the MIT Center for Organizational Learning," Working papers WP 3967-97., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    4. Iván Barreda-Tarrazona & Nikolaos Georgantzís & Constantine Manasakis & Evangelos Mitrokostas & Emmanuel Petrakis, 2012. "Managerial compensation contracts in quantity-setting duopoly," Working Papers 2012/17, Economics Department, Universitat Jaume I, Castellón (Spain).
    5. Arquitt, Steve & Johnstone, Ron, 2008. "Use of system dynamics modelling in design of an environmental restoration banking institution," Ecological Economics, Elsevier, vol. 65(1), pages 63-75, March.
    6. Howick, Susan, 2005. "Using system dynamics models with litigation audiences," European Journal of Operational Research, Elsevier, vol. 162(1), pages 239-250, April.
    7. Lurie, Nicholas H. & Swaminathan, Jayashankar M., 2009. "Is timely information always better? The effect of feedback frequency on decision making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 108(2), pages 315-329, March.
    8. Monks, Thomas & Robinson, Stewart & Kotiadis, Kathy, 2014. "Learning from discrete-event simulation: Exploring the high involvement hypothesis," European Journal of Operational Research, Elsevier, vol. 235(1), pages 195-205.
    9. Pagani, Margherita & Otto, Peter, 2013. "Integrating strategic thinking and simulation in marketing strategy: Seeing the whole system," Journal of Business Research, Elsevier, vol. 66(9), pages 1568-1575.
    10. Schnier, Kurt E. & Anderson, Christopher M., 2006. "Decision making in patchy resource environments: Spatial misperception of bioeconomic models," Journal of Economic Behavior & Organization, Elsevier, vol. 61(2), pages 234-254, October.
    11. Gibson, Faison P., 2000. "Feedback Delays: How Can Decision Makers Learn Not to Buy a New Car Every Time the Garage Is Empty?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 83(1), pages 141-166, September.
    12. Tibor Neugebauer & John D. Hey & K Sadrieh, 2008. "An Experimental Analysis of Optimal Renewable Resource Management: The Fishery," LSF Research Working Paper Series 08-10, Luxembourg School of Finance, University of Luxembourg.
    13. Ingrid Kubin & Laura Gardini, 2012. " Border Collision Bifurcations in Boom and Bust Cycles," Department of Economics Working Papers wuwp137, Vienna University of Economics, Department of Economics.
    14. Langley, Paul A. & Morecroft, John D. W., 2004. "Performance and learning in a simulation of oil industry dynamics," European Journal of Operational Research, Elsevier, vol. 155(3), pages 715-732, June.
    15. Gärling, Tommy & Eek, Daniel & Loukopoulos, Peter & Fujii, Satoshi & Johansson-Stenman, Olof & Kitamura, Ryuichi & Pendyala, Ram & Vilhelmson, Bertil, 2002. "A conceptual analysis of the impact of travel demand management on private car use," Transport Policy, Elsevier, vol. 9(1), pages 59-70, January.
    16. Moxnes, Erling, 2014. "Discounting, climate and sustainability," Ecological Economics, Elsevier, vol. 102(C), pages 158-166.
    17. Weil, Henry Birdseye., 1996. "Commoditization of technology-based products and services : a generic model of market dynamics," Working papers #144-96. Working paper (S, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    18. Lane, David C., 1999. "Social theory and system dynamics practice," European Journal of Operational Research, Elsevier, vol. 113(3), pages 501-527, March.
    19. Arango, Santiago & Moxnes, Erling, 2012. "Commodity cycles, a function of market complexity? Extending the cobweb experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 84(1), pages 321-334.
    20. John Sterman, 2011. "Communicating climate change risks in a skeptical world," Climatic Change, Springer, vol. 108(4), pages 811-826, October.
    21. Varun Dutt & Cleotilde Gonzalez, 2012. "Human control of climate change," Climatic Change, Springer, vol. 111(3), pages 497-518, April.

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