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Using soft systems methodology to determine the simulation study objectives

Kotiadis, K. (2007) Using soft systems methodology to determine the simulation study objectives. Journal of Simulation, 1 (3). pp. 215-222. ISSN 1747-7778. E-ISSN 1747-7786. (doi:10.1057/palgrave.jos.4250025) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:91530)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
https://doi.org/10.1057/palgrave.jos.4250025

Abstract

This paper demonstrates, through a case study in health care, that Soft Systems Methodology (SSM) can be used to determine the conceptual model's most important component, the simulation study objectives. Conceptual modelling is a critical part of the simulation methodology because it is the problem structuring stage in which the questions of what, why and how in terms of modelling the system of interest are answered. Therefore, it is surprising that very little has been done to link problem structuring methods to Discrete Event Simulation (DES). SSM is the most popular problem structuring approach to be used in DES and although various papers advocate its usefulness to the simulation study in general, SSM has not been used it to determine the simulation study objectives. In this study, one of the SSM tools is extended to better fit with the process of eliciting the simulation study objectives and the approach is demonstrated through a case study. This paper provides potential adopters with a set of guidelines for this SSM extension and also provides a discussion on the benefits of using SSM and its potential for being adapted for simulation conceptual modelling. Areas that would benefit from further research are identified.

Item Type: Article
DOI/Identification number: 10.1057/palgrave.jos.4250025
Uncontrolled keywords: Conceptual modelling; soft systems methodology; health care
Subjects: T Technology
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Kathy Kotiadis
Date Deposited: 11 Nov 2021 20:51 UTC
Last Modified: 16 Nov 2021 10:27 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/91530 (The current URI for this page, for reference purposes)

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