Tako, Antuela, Kotiadis, Kathy (2018) Participative Simulation (Partisim): A Facilitated Simulation Approach for Stakeholder Engagement. In: Rabe, M. and Juan, A.A. and Mustafee, N. and Skoogh, A. and Jain, S. and Johansson, B., eds. Winter Simulation Conference 2018 Proceedings. . pp. 192-206. IEEE (doi:10.1109/WSC.2018.8632434) (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:73068)
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. (Contact us about this Publication) | |
Official URL: http://dx.doi.org/10.1109/WSC.2018.8632434 |
Abstract
Facilitated discrete event simulation offers an alternative mode of engagement with stakeholders (clients) in simulation projects. It is particularly beneficial when modeling systems with complex behavior, involving many stakeholders with plurality of opinions and objectives. PartiSim - short for Participative Simulation - is a facilitated modeling approach developed to support simulation projects through a framework, stakeholder-oriented tools, and manuals in facilitated workshops. This tutorial describes the PartiSim approach, available for analysts and simulation modelers to use. A PartiSim study includes six stages, four of which involve facilitated workshops. PartiSim has been developed and tested through working with health care organizations. It can, however, be applied to analyze operational problems in any other context within the services and manufacturing domains. This tutorial introduces PartiSim by describing the PartiSim framework and tools, some applications and example tools, a roadmap to adopting it and concludes with some tips for potential users.
Item Type: | Conference or workshop item (Proceeding) |
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DOI/Identification number: | 10.1109/WSC.2018.8632434 |
Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD29 Operational Research - Applications |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Kathy Kotiadis |
Date Deposited: | 19 Mar 2019 10:26 UTC |
Last Modified: | 05 Nov 2024 12:35 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/73068 (The current URI for this page, for reference purposes) |
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