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Teachers' Forum: Spreadsheet Modeling and Simulation Improves Understanding of Queues

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  • Thomas A. Grossman

    (Faculty of Management, University of Calgary, Calgary, Alberta, Canada T2N 1N4)

Abstract

Process-driven spreadsheet queuing simulation is a better vehicle for understanding queue behavior than queuing theory or dedicated simulation software. Spreadsheet queuing simulation has many pedagogical benefits in a business school end-user modeling course, including developing students' intuition, giving them experience with active modeling skills, and providing access to tools. Spreadsheet queuing simulations are surprisingly easy to program, even for queues with balking and reneging. The ease of prototyping in spreadsheets invites thoughtless design, so careful spreadsheet programming practice is important. Spreadsheet queuing simulation is inferior to dedicated simulation software for analyzing queues but is more likely to be available to managers and students.

Suggested Citation

  • Thomas A. Grossman, 1999. "Teachers' Forum: Spreadsheet Modeling and Simulation Improves Understanding of Queues," Interfaces, INFORMS, vol. 29(3), pages 88-103, June.
  • Handle: RePEc:inm:orinte:v:29:y:1999:i:3:p:88-103
    DOI: 10.1287/inte.29.3.88
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    References listed on IDEAS

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    1. Stephen G. Powell, 1997. "The Teachers' Forum: From Intelligent Consumer to Active Modeler, Two MBA Success Stories," Interfaces, INFORMS, vol. 27(3), pages 88-98, June.
    2. Arthur M. Geoffrion, 1976. "The Purpose of Mathematical Programming is Insight, Not Numbers," Interfaces, INFORMS, vol. 7(1), pages 81-92, November.
    3. William T. Morris, 1967. "On the Art of Modeling," Management Science, INFORMS, vol. 13(12), pages 707-717, August.
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    Cited by:

    1. Thomas A. Grossman, 2002. "Student Consulting Projects Benefit Faculty and Industry," Interfaces, INFORMS, vol. 32(2), pages 42-48, April.
    2. Christophe Oggier & Emmanuel Fragnière & Jeremy Stuby, 2005. "Nestlé Improves Its Financial Reporting with Management Science," Interfaces, INFORMS, vol. 35(4), pages 271-280, August.
    3. Larry J. LeBlanc & Michael R. Galbreth, 2007. "Implementing Large-Scale Optimization Models in Excel Using VBA," Interfaces, INFORMS, vol. 37(4), pages 370-382, August.
    4. Jeffrey W. Herrmann, 2008. "Disseminating Emergency Preparedness Planning Models as Automatically Generated Custom Spreadsheets," Interfaces, INFORMS, vol. 38(4), pages 263-270, August.
    5. Kiygi Calli, M. & Weverbergh, M. & Franses, Ph.H.B.F., 2017. "Call center performance with direct response advertising," Econometric Institute Research Papers EI2017-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Kiygi-Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans, 2021. "Forecasting time-varying arrivals: Impact of direct response advertising on call center performance," Journal of Business Research, Elsevier, vol. 131(C), pages 227-240.

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