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Widening requirements capture with soft methods: an investigation of hybrid M&S studies in health care

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  • J H Powell

    (University of Exeter Business School)

  • N Mustafee

    (University of Exeter Business School)

Abstract

A simulation study consists of several stages: problem formulation, model implementation, verification and validation, experimentation and output data analysis. The application of multiple techniques in the model implementation stage is referred to as hybrid simulation, which we distinguish in this paper from a hybrid M&S study, the latter referring to studies that apply methods and techniques from disciplines like Operations Research (OR), Systems Engineering and Computer Science to one or more stages of a simulation study. Our paper focuses on the contribution of soft OR methods in the problem formulation stage of a simulation study (and by extension a hybrid M&S study). Soft Systems Methodology (SSM) has, arguably, been the most widely used qualitative approach for eliciting system requirements. In this paper, we present Qualitative System Dynamics (QSD), a soft systems method, as having potential use in the problem formulation stage of a healthcare M&S study. The contribution of this paper is thus twofold: (1) a review of the literature in SSM for healthcare operations management and (2) an examination of QSD as an additional soft OR method, complementing (rather than supplanting) existing approaches, which can further aid the understanding of the system in the problem formulation/conceptual modelling stage of a hybrid M&S study.

Suggested Citation

  • 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.
  • Handle: RePEc:pal:jorsoc:v:68:y:2017:i:10:d:10.1057_s41274-016-0147-6
    DOI: 10.1057/s41274-016-0147-6
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    References listed on IDEAS

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    Cited by:

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    2. Armenia, Stefano & Franco, Eduardo & Iandolo, Francesca & Maielli, Giuliano & Vito, Pietro, 2024. "Zooming in and out the landscape: Artificial intelligence and system dynamics in business and management," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    3. Alexandre de A. Gomes Júnior & Vanessa B. Schramm, 2022. "Problem Structuring Methods: A Review of Advances Over the Last Decade," Systemic Practice and Action Research, Springer, vol. 35(1), pages 55-88, February.
    4. Claudia Archetti & M. Grazia Speranza & Emirena Garrafa, 2020. "Managing an automated clinical laboratory: optimization challenges and opportunities," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 8(1), pages 41-60, May.
    5. Alexandre de A. Gomes Júnior & Vanessa B. Schramm & Fernando Schramm, 2023. "Problem Structuring Methods in Social-Ecological Systems," Systemic Practice and Action Research, Springer, vol. 36(3), pages 461-478, June.
    6. 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.
    7. Spanellis, Agnessa & MacBryde, Jillian & Dӧrfler, Viktor, 2021. "A dynamic model of knowledge management in innovative technology companies: A case from the energy sector," European Journal of Operational Research, Elsevier, vol. 292(2), pages 784-797.

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