IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v59y2008i3d10.1057_palgrave.jors.2602368.html
   My bibliography  Save this article

Conceptual modelling for simulation Part I: definition and requirements

Author

Listed:
  • S Robinson

    (University of Warwick)

Abstract

Conceptual modelling is probably the most important aspect of a simulation study. It is also the most difficult and least understood. Over 40 years of simulation research and practice have provided only limited information on how to go about designing a simulation conceptual model. This paper, the first of two, discusses the meaning of conceptual modelling and the requirements of a conceptual model. Founded on existing literature, a definition of a conceptual model is provided. Four requirements of a conceptual model are described: validity, credibility, utility and feasibility. The need to develop the simplest model possible is also discussed. Owing to a paucity of advice on how to design a conceptual model, the need for a conceptual modelling framework is proposed. Built on the foundations laid in this paper, a conceptual modelling framework is described in the paper that follows.

Suggested Citation

  • S Robinson, 2008. "Conceptual modelling for simulation Part I: definition and requirements," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(3), pages 278-290, March.
    • Handle: RePEc:pal:jorsoc:v:59:y:2008:i:3:d:10.1057_palgrave.jors.2602368
    DOI: 10.1057/palgrave.jors.2602368
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/palgrave.jors.2602368
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/palgrave.jors.2602368?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Davies, Ruth & Roderick, Paul & Raftery, James, 2003. "The evaluation of disease prevention and treatment using simulation models," European Journal of Operational Research, Elsevier, vol. 150(1), pages 53-66, October.
    2. Stephen G. Powell, 1995. "The Teachers’ Forum: Six Key Modeling Heuristics," Interfaces, INFORMS, vol. 25(4), pages 114-125, August.
    3. James S. Hodges, 1991. "Six (Or So) Things You Can Do with a Bad Model," Operations Research, INFORMS, vol. 39(3), pages 355-365, June.
    4. Thomas R. Willemain, 1995. "Model Formulation: What Experts Think About and When," Operations Research, INFORMS, vol. 43(6), pages 916-932, December.
    5. William T. Morris, 1967. "On the Art of Modeling," Management Science, INFORMS, vol. 13(12), pages 707-717, August.
    6. S Robinson, 2001. "Soft with a hard centre: discrete-event simulation in facilitation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(8), pages 905-915, August.
    7. Michael Pidd, 1999. "Just Modeling Through: A Rough Guide to Modeling," Interfaces, INFORMS, vol. 29(2), pages 118-132, April.
    8. Jeffery K. Cochran & Gerald T. Mackulak & Paul A. Savory, 1995. "Simulation Project Characteristics in Industrial Settings," Interfaces, INFORMS, vol. 25(4), pages 104-113, August.
    9. Thomas R. Willemain, 1994. "Insights on Modeling from a Dozen Experts," Operations Research, INFORMS, vol. 42(2), pages 213-222, April.
    10. Steve Bankes, 1993. "Exploratory Modeling for Policy Analysis," Operations Research, INFORMS, vol. 41(3), pages 435-449, June.
    11. Thomas, Andre & Charpentier, Patrick, 2005. "Reducing simulation models for scheduling manufacturing facilities," European Journal of Operational Research, Elsevier, vol. 161(1), pages 111-125, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Brailsford, Sally C. & Eldabi, Tillal & Kunc, Martin & Mustafee, Navonil & Osorio, Andres F., 2019. "Hybrid simulation modelling in operational research: A state-of-the-art review," European Journal of Operational Research, Elsevier, vol. 278(3), pages 721-737.
    2. Khushboo E-Fatima & Rasoul Khandan & Amin Hosseinian-Far & Dilshad Sarwar & Hareer Fatima Ahmed, 2022. "Adoption and Influence of Robotic Process Automation in Beef Supply Chains," Logistics, MDPI, vol. 6(3), pages 1-20, July.
    3. Priscilla Avegliano & Jaime Simão Sichman, 2023. "Equation-Based Versus Agent-Based Models: Why Not Embrace Both for an Efficient Parameter Calibration?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 26(4), pages 1-3.
    4. Elias Hartvigsson & Erik Oscar Ahlgren & Sverker Molander, 2020. "Tackling complexity and problem formulation in rural electrification through conceptual modelling in system dynamics," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(1), pages 141-153, January.
    5. Alireza Moumivand & Adel Azar & Abbas Toloie Eshlaghy, 2022. "Combined soft system methodology and agent‐based simulation for multi‐methodological modelling," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(2), pages 200-217, March.
    6. Gogi, Anastasia & Tako, Antuela A. & Robinson, Stewart, 2016. "An experimental investigation into the role of simulation models in generating insights," European Journal of Operational Research, Elsevier, vol. 249(3), pages 931-944.
    7. Tako, Antuela A. & Kotiadis, Kathy, 2015. "PartiSim: A multi-methodology framework to support facilitated simulation modelling in healthcare," European Journal of Operational Research, Elsevier, vol. 244(2), pages 555-564.
    8. Robert, Marion & Thomas, Alban & Sekhar, Muddu & Badiger, Shrinivas & Ruiz, Laurent & Raynal, Hélène & Bergez, Jacques-Eric, 2017. "Adaptive and dynamic decision-making processes: A conceptual model of production systems on Indian farms," Agricultural Systems, Elsevier, vol. 157(C), pages 279-291.
    9. Raghu KC & Mika Aalto & Olli-Jussi Korpinen & Tapio Ranta & Svetlana Proskurina, 2020. "Lifecycle Assessment of Biomass Supply Chain with the Assistance of Agent-Based Modelling," Sustainability, MDPI, vol. 12(5), pages 1-14, March.
    10. Huajie Jin & Paul Tappenden & Stewart Robinson & Evanthia Achilla & David Aceituno & Sarah Byford, 2020. "Systematic review of the methods of health economic models assessing antipsychotic medication for schizophrenia," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-18, July.
    11. J H Powell & N Mustafee, 2017. "Widening requirements capture with soft methods: an investigation of hybrid M&S studies in health care," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1211-1222, October.
    12. A A Tako & S Robinson, 2009. "Comparing discrete-event simulation and system dynamics: users' perceptions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(3), pages 296-312, March.
    13. Eric Innocenti & Claudio Detotto & Corinne Idda & Dawn Cassandra Parker & Dominique Prunetti, 2023. "Spécification conceptuelle MR POTATOHEAD -Property Market Edition du système complexe d'un territoire touristique à deux marchés : application au territoire corse," Post-Print hal-04121402, HAL.
    14. Martin Comis & Catherine Cleophas & Christina Büsing, 2021. "Patients, primary care, and policy: Agent-based simulation modeling for health care decision support," Health Care Management Science, Springer, vol. 24(4), pages 799-826, December.
    15. Robinson, Stewart & Radnor, Zoe J. & Burgess, Nicola & Worthington, Claire, 2012. "SimLean: Utilising simulation in the implementation of lean in healthcare," European Journal of Operational Research, Elsevier, vol. 219(1), pages 188-197.
    16. Hana M Dobrovolny & Micaela B Reddy & Mohamed A Kamal & Craig R Rayner & Catherine A A Beauchemin, 2013. "Assessing Mathematical Models of Influenza Infections Using Features of the Immune Response," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-20, February.
    17. Penny R. Breeze & Hazel Squires & Kate Ennis & Petra Meier & Kate Hayes & Nik Lomax & Alan Shiell & Frank Kee & Frank de Vocht & Martin O’Flaherty & Nigel Gilbert & Robin Purshouse & Stewart Robinson , 2023. "Guidance on the use of complex systems models for economic evaluations of public health interventions," Health Economics, John Wiley & Sons, Ltd., vol. 32(7), pages 1603-1625, July.
    18. Zichong Lyu & Dirk Pons & Yilei Zhang & Zuzhen Ji, 2022. "Minimum Viable Model (MVM) Methodology for Integration of Agile Methods into Operational Simulation of Logistics," Logistics, MDPI, vol. 6(2), pages 1-28, June.
    19. Gerrit Muller, 2021. "Applying Roadmapping and Conceptual Modeling to the Energy Transition: A Local Case Study," Sustainability, MDPI, vol. 13(7), pages 1-16, March.
    20. Chong, Adrian & Augenbroe, Godfried & Yan, Da, 2021. "Occupancy data at different spatial resolutions: Building energy performance and model calibration," Applied Energy, Elsevier, vol. 286(C).
    21. D Champion & J M Wilson, 2010. "The impact of contingency factors on validation of problem structuring methods," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(9), pages 1420-1431, September.
    22. Jason Madan & Meghan Bruce Kumar & Miriam Taegtmeyer & Edwine Barasa & Swaran Preet Singh, 2020. "SEEP-CI: A Structured Economic Evaluation Process for Complex Health System Interventions," IJERPH, MDPI, vol. 17(18), pages 1-12, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. T R Willemain & S G Powell, 2007. "How novices formulate models. Part II: a quantitative description of behaviour," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(10), pages 1271-1283, October.
    2. Michael Pidd, 1999. "Just Modeling Through: A Rough Guide to Modeling," Interfaces, INFORMS, vol. 29(2), pages 118-132, April.
    3. S Robinson, 2008. "Conceptual modelling for simulation Part II: a framework for conceptual modelling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(3), pages 291-304, March.
    4. Frederic H. Murphy, 2005. "ASP, The Art and Science of Practice: Elements of a Theory of the Practice of Operations Research: Expertise in Practice," Interfaces, INFORMS, vol. 35(4), pages 313-322, August.
    5. Tako, Antuela A. & Robinson, Stewart, 2010. "Model development in discrete-event simulation and system dynamics: An empirical study of expert modellers," European Journal of Operational Research, Elsevier, vol. 207(2), pages 784-794, December.
    6. Lane, David & Husemann, Elke & Holland, Darren & Khaled, Abdul, 2019. "Understanding foodborne transmission mechanisms for Norovirus: A study for the UK's Food Standards Agency," European Journal of Operational Research, Elsevier, vol. 275(2), pages 721-736.
    7. S G Powell & T R Willemain, 2007. "How novices formulate models. Part I: qualitative insights and implications for teaching," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(8), pages 983-995, August.
    8. P Keys, 2006. "On becoming expert in the use of problem structuring methods," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(7), pages 822-829, July.
    9. Marjolijn Haasnoot & Hans Middelkoop & Astrid Offermans & Eelco Beek & Willem Deursen, 2012. "Exploring pathways for sustainable water management in river deltas in a changing environment," Climatic Change, Springer, vol. 115(3), pages 795-819, December.
    10. Morgan, Jennifer Sian & Howick, Susan & Belton, Valerie, 2017. "A toolkit of designs for mixing Discrete Event Simulation and System Dynamics," European Journal of Operational Research, Elsevier, vol. 257(3), pages 907-918.
    11. Kleijnen, Jack P. C., 1995. "Verification and validation of simulation models," European Journal of Operational Research, Elsevier, vol. 82(1), pages 145-162, April.
    12. Franco, L. Alberto & Hämäläinen, Raimo P., 2016. "Behavioural operational research: Returning to the roots of the OR profession," European Journal of Operational Research, Elsevier, vol. 249(3), pages 791-795.
    13. Moallemi, Enayat A. & Elsawah, Sondoss & Ryan, Michael J., 2020. "Strengthening ‘good’ modelling practices in robust decision support: A reporting guideline for combining multiple model-based methods," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 175(C), pages 3-24.
    14. Walker, Warren E., 2009. "Does the best practice of rational-style model-based policy analysis already include ethical considerations?," Omega, Elsevier, vol. 37(6), pages 1051-1062, December.
    15. Merrick, James H. & Weyant, John P., 2019. "On choosing the resolution of normative models," European Journal of Operational Research, Elsevier, vol. 279(2), pages 511-523.
    16. Jan Kwakkel & Willem Auping, 2021. "Reaction: A commentary on Lustick and Tetlock (2021)," Futures & Foresight Science, John Wiley & Sons, vol. 3(2), June.
    17. Robinson, Stewart & Worthington, Claire & Burgess, Nicola & Radnor, Zoe J., 2014. "Facilitated modelling with discrete-event simulation: Reality or myth?," European Journal of Operational Research, Elsevier, vol. 234(1), pages 231-240.
    18. Moallemi, Enayat A. & Elsawah, Sondoss & Ryan, Michael J., 2020. "Robust decision making and Epoch–Era analysis: A comparison of two robustness frameworks for decision-making under uncertainty," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    19. Robinson, Stewart, 2002. "General concepts of quality for discrete-event simulation," European Journal of Operational Research, Elsevier, vol. 138(1), pages 103-117, April.
    20. Hämäläinen, Raimo P. & Lahtinen, Tuomas J., 2016. "Path dependence in Operational Research—How the modeling process can influence the results," Operations Research Perspectives, Elsevier, vol. 3(C), pages 14-20.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:jorsoc:v:59:y:2008:i:3:d:10.1057_palgrave.jors.2602368. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.