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Rationality in the Analysis of Behavioral Simulation Models

Author

Listed:
  • John D. W. Morecroft

    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

Abstract

An important task in the analysis of a behavioral simulation model is to explain clearly how the model's organizational assumptions lead to its simulated behavior. All too often, model-based arguments involve an uncomfortable "leap of logic" between equations and consequences. This paper proposes two methods of analysis, premise description and partial model testing, which provide stepping stones between model equations and their simulated consequences. Premise description examines the bounded rationality of policies or decision functions in the model, pointing out the process and cognitive limitations assumed in decisionmaking. Partial model tests expose the intended rationality of smalt combinations of policies, showing that policies produce "sensible" actions with respect to their premises. The application of those methods is illustrated with a simulation model of a sales organization in which sales-force productivity is prone to decline. The behavior of productivity is traced to dysfunctional interactions between objectives, overtime, and salesforce motivation.

Suggested Citation

  • John D. W. Morecroft, 1985. "Rationality in the Analysis of Behavioral Simulation Models," Management Science, INFORMS, vol. 31(7), pages 900-916, July.
    • Handle: RePEc:inm:ormnsc:v:31:y:1985:i:7:p:900-916
    DOI: 10.1287/mnsc.31.7.900
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    Citations

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    Cited by:

    1. John D. W. Morecroft, 2012. "Metaphorical Models for Limits to Growth and Industrialization," Systems Research and Behavioral Science, Wiley Blackwell, vol. 29(6), pages 645-666, November.
    2. Oliva, Rogelio. & Sterman, John., 1999. "Cutting corners and working overtime : quality erosion in the service industry," Working papers WP 4075-99., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    3. David C. Lane & Birgit Kopainsky & David C. Lane, 2017. "‘Behavioural System Dynamics’: A Very Tentative and Slightly Sceptical Map of the Territory," Systems Research and Behavioral Science, Wiley Blackwell, vol. 34(4), pages 414-423, July.
    4. Khalid Saeed, 2014. "Jay Forrester's operational approach to economics," System Dynamics Review, System Dynamics Society, vol. 30(4), pages 233-261, October.
    5. Oliva, Rogelio, 2003. "Model calibration as a testing strategy for system dynamics models," European Journal of Operational Research, Elsevier, vol. 151(3), pages 552-568, December.
    6. M H Kunc & J D W Morecroft, 2009. "Resource-based strategies and problem structuring: using resource maps to manage resource systems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(2), pages 191-199, February.
    7. Florian Kapmeier & Paulo Gonçalves, 2018. "Wasted paradise? Policies for Small Island States to manage tourism‐driven growth while controlling waste generation: the case of the Maldives," System Dynamics Review, System Dynamics Society, vol. 34(1-2), pages 172-221, January.
    8. Larsen, Erik R. & Morecroft, John D. W. & Thomsen, Jesper S., 1999. "Complex behaviour in a production-distribution model," European Journal of Operational Research, Elsevier, vol. 119(1), pages 61-74, November.
    9. Stephen J. Mezias & Ya-Ru Chen & Patrice R. Murphy, 2002. "Aspiration-Level Adaptation in an American Financial Services Organization: A Field Study," Management Science, INFORMS, vol. 48(10), pages 1285-1300, October.
    10. Ali Akhavan & Paulo Gonçalves, 2021. "Managing the trade‐off between groundwater resources and large‐scale agriculture: the case of pistachio production in Iran," System Dynamics Review, System Dynamics Society, vol. 37(2-3), pages 155-196, April.
    11. Sterman, John., 1986. "Testing behavioral simulation models by direct experiment," Working papers 1752-86., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    12. Sterman, John, 1987. "Misperceptions of feedback in dynamic decisionmaking," Working papers 1899-87., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    13. Sterman, John, 1987. "Modeling managerial behavior--misperceptions of feedback in a dynamic decisionmaking experiment," Working papers 1933-87., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    14. Federico Cosenz & Guido Noto, 2016. "Applying System Dynamics Modelling to Strategic Management: A Literature Review," Systems Research and Behavioral Science, Wiley Blackwell, vol. 33(6), pages 703-741, November.
    15. Paich, Mark. & Sterman, John., 1992. "Boom, bust and failures to learn in experimental markets," Working papers 3441-92., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    16. M H Kunc & J D W Morecroft, 2007. "Competitive dynamics and gaming simulation: lessons from a fishing industry simulator," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(9), pages 1146-1155, September.
    17. Rogelio Oliva & John D. Sterman, 2001. "Cutting Corners and Working Overtime: Quality Erosion in the Service Industry," Management Science, INFORMS, vol. 47(7), pages 894-914, July.
    18. John D. Sterman & Jason Wittenberg, 1999. "Path Dependence, Competition, and Succession in the Dynamics of Scientific Revolution," Organization Science, INFORMS, vol. 10(3), pages 322-341, June.
    19. John D. Sterman & Rebecca Henderson & Eric D. Beinhocker & Lee I. Newman, 2007. "Getting Big Too Fast: Strategic Dynamics with Increasing Returns and Bounded Rationality," Management Science, INFORMS, vol. 53(4), pages 683-696, April.
    20. Wang, Xinchun & Lou, Tianyang, 2020. "The effect of performance feedback on firms’ unplanned marketing investments," Journal of Business Research, Elsevier, vol. 118(C), pages 441-451.

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