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Competitive dynamics and gaming simulation: lessons from a fishing industry simulator

Author

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  • M H Kunc

    (London Business School)

  • J D W Morecroft

    (London Business School)

Abstract

Experiments with a gaming simulator of the fishing industry show that a wide range of firm and industry performance can arise from players’ differing perceptions of the competitive environment. When transferred into the arena of applied strategy development, the results suggest that modellers should give more attention to modelling alternative conceptualizations of strategic intent in the minds of rival business leaders and the firms they create. This new interpretive emphasis should complement the traditional modelling of cross-functional coordination that has been the hallmark of much published work in strategic modelling and simulation. When leaders and firms in the same industry adopt quite different views of the overall system of resources in the industry, it is important to model the heterogeneity of rival firms in order to understand the dynamic performance of the firm and the industry. We propose a modelling approach that captures heterogeneity among the strategic resources that rival firms seek to build and in the operating goals and coordinating processes they use to build them.

Suggested Citation

  • 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.
  • Handle: RePEc:pal:jorsoc:v:58:y:2007:i:9:d:10.1057_palgrave.jors.2602246
    DOI: 10.1057/palgrave.jors.2602246
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    Cited by:

    1. Diego Damásio Lima & Daniel Pacheco Lacerda & Miguel Afonso Sellitto, 2017. "Systemic Analysis of the Brazilian Production Chain of Semiconductors: Graphic Representation and Leverage Points," Systemic Practice and Action Research, Springer, vol. 30(3), pages 295-316, June.
    2. E Tapinos & R G Dyson & M Meadows, 2011. "Does the Balanced Scorecard make a difference to the strategy development process?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(5), pages 888-899, May.
    3. Rossen Kazakov & Martin Kunc, 2016. "Foreseeing the Dynamics of Strategy: An Anticipatory Systems Perspective," Systemic Practice and Action Research, Springer, vol. 29(1), pages 1-25, February.
    4. Schaffernicht, Martin & Groesser, Stefan N., 2011. "A comprehensive method for comparing mental models of dynamic systems," European Journal of Operational Research, Elsevier, vol. 210(1), pages 57-67, April.
    5. Wang, Juite & Lai, Jung-Yu, 2020. "Exploring innovation diffusion of two-sided mobile payment platforms: A system dynamics approach," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    6. Torres, Juan Pablo & Kunc, Martin & O'Brien, Frances, 2017. "Supporting strategy using system dynamics," European Journal of Operational Research, Elsevier, vol. 260(3), pages 1081-1094.
    7. You, Mengjie & Li, Shuang & Li, Dingwei & Cao, Qingren & Xu, Feng, 2020. "Evolutionary game analysis of coal-mine enterprise internal safety inspection system in China based on system dynamics," Resources Policy, Elsevier, vol. 67(C).
    8. Marieke de Wijse-van Heeswijk, 2021. "Ethics and the Simulation Facilitator: Taking your Professional Role Seriously," Simulation & Gaming, , vol. 52(3), pages 312-332, June.

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