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System-dynamics-based modeling of business simulation algorithms

Author

Listed:
  • Steven Gold

    (Rochester Institute of Technology, stevengold@cob.rit.edu)

Abstract

Research on the internal algorithms used to model business simulations have focused on individual components of the business system. Yet the business environment is complex in nature, characterized by interdependencies and nonlinear relationships that require a systems approach if effective game design is to be achieved. In this article, a system-dynamics-basedd interactive model of a business enterprise simulation is developed consisting of 18 equations. The model draws heavily on the economic theory of the firm and the expansive body of prior research on the design of business simulations. The focus is on the linkages between the production, cost, revenues, profits, and stock market value of the firm. A working model of the recommended system is tested, and its empirical properties are discussed. It is found that to develop effective algorithms within each functional area of business, the dynamic impacts on the whole enterprise must be evaluated.

Suggested Citation

  • Steven Gold, 2005. "System-dynamics-based modeling of business simulation algorithms," Simulation & Gaming, , vol. 36(2), pages 203-218, June.
    • Handle: RePEc:sae:simgam:v:36:y:2005:i:2:p:203-218
    DOI: 10.1177/1046878104272433
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    References listed on IDEAS

    as
    1. Steven C. Gold & Thomas F. Pray, 2001. "Historical Review of Algorithm Development for Computerized Business Simulations," Simulation & Gaming, , vol. 32(1), pages 66-84, March.
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    Cited by:

    1. James N. Cannon & Hugh M. Cannon & James T. Low, 2013. "Modeling Tactical Product-Mix Decisions," Simulation & Gaming, , vol. 44(5), pages 624-644, October.
    2. Hugh M. Cannon & Manfred Schwaiger, 2005. "An algorithm for incorporating company reputation into business simulations: Variations on the Gold standard," Simulation & Gaming, , vol. 36(2), pages 219-237, June.
    3. Hugh M. Cannon & James N. Cannon & Manfred Schwaiger, 2010. "Incorporating Customer Lifetime Value Into Marketing Simulation Games," Simulation & Gaming, , vol. 41(3), pages 341-359, June.
    4. John R. Dickinson, 2014. "A Mathematical Law for Assessing Outcome Values of Games," Simulation & Gaming, , vol. 45(3), pages 318-331, June.
    5. James N. Cannon & Hugh M. Cannon & Manfred Schwaiger, 2012. "Modeling the “Profitable-Product Death Spiralâ€," Simulation & Gaming, , vol. 43(6), pages 761-777, December.

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