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Learning from discrete-event simulation: exploring the high involvement hypothesis

Learning from discrete-event simulation: exploring the high involvement hypothesis
Learning from discrete-event simulation: exploring the high involvement hypothesis
Discussion of learning from discrete-event simulation often takes the form of a hypothesis stating that involving clients in model building provides much of the learning necessary to aid their decisions. Whilst practitioners of simulation may intuitively agree with this hypothesis they are simultaneously motivated to reduce the model building effort through model reuse. As simulation projects are typically limited by time, model reuse offers an alternative learning route for clients as the time saved can be used to conduct more experimentation. We detail a laboratory experiment to test the high involvement hypothesis empirically, identify mechanisms that explain how involvement in model building or model reuse affect learning and explore the factors that inhibit learning from models. Measurement of learning focuses on the management of resource utilisation in a case study of a hospital emergency department and through the choice of scenarios during experimentation. Participants who reused a model benefitted from the increased experimentation time available when learning about resource utilisation. However, participants who were involved in model building simulated a greater variety of scenarios including more validation type scenarios early on. These results suggest that there may be a learning trade-off between model reuse and model building when simulation projects have a fixed budget of time. Further work evaluating client learning in practice should track the origin and choice of variables used in experimentation; studies should also record the methods modellers find most effective in communicating the impact of resource utilisation on queuing.
psychology of decision, learning, model building, model reuse, generic models, simulation
0377-2217
195-205
Monks, Thomas
fece343c-106d-461d-a1dd-71c1772627ca
Robinson, Stewart
1003a3e5-df15-4119-8f68-890f7de7bff1
Kotiadis, Kathy
11adfca2-462f-41d0-b7bb-f1b1acf7a8fd
Monks, Thomas
fece343c-106d-461d-a1dd-71c1772627ca
Robinson, Stewart
1003a3e5-df15-4119-8f68-890f7de7bff1
Kotiadis, Kathy
11adfca2-462f-41d0-b7bb-f1b1acf7a8fd

Monks, Thomas, Robinson, Stewart and Kotiadis, Kathy (2014) Learning from discrete-event simulation: exploring the high involvement hypothesis. European Journal of Operational Research, 235 (1), 195-205. (doi:10.1016/j.ejor.2013.10.003).

Record type: Article

Abstract

Discussion of learning from discrete-event simulation often takes the form of a hypothesis stating that involving clients in model building provides much of the learning necessary to aid their decisions. Whilst practitioners of simulation may intuitively agree with this hypothesis they are simultaneously motivated to reduce the model building effort through model reuse. As simulation projects are typically limited by time, model reuse offers an alternative learning route for clients as the time saved can be used to conduct more experimentation. We detail a laboratory experiment to test the high involvement hypothesis empirically, identify mechanisms that explain how involvement in model building or model reuse affect learning and explore the factors that inhibit learning from models. Measurement of learning focuses on the management of resource utilisation in a case study of a hospital emergency department and through the choice of scenarios during experimentation. Participants who reused a model benefitted from the increased experimentation time available when learning about resource utilisation. However, participants who were involved in model building simulated a greater variety of scenarios including more validation type scenarios early on. These results suggest that there may be a learning trade-off between model reuse and model building when simulation projects have a fixed budget of time. Further work evaluating client learning in practice should track the origin and choice of variables used in experimentation; studies should also record the methods modellers find most effective in communicating the impact of resource utilisation on queuing.

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Monks et al. 2014.pdf - Accepted Manuscript
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More information

e-pub ahead of print date: October 2013
Published date: 16 May 2014
Keywords: psychology of decision, learning, model building, model reuse, generic models, simulation
Organisations: Faculty of Health Sciences

Identifiers

Local EPrints ID: 367142
URI: http://eprints.soton.ac.uk/id/eprint/367142
ISSN: 0377-2217
PURE UUID: 7638df19-573f-4f9c-a91b-13e6b7f529ca
ORCID for Thomas Monks: ORCID iD orcid.org/0000-0003-2631-4481

Catalogue record

Date deposited: 23 Jul 2014 16:30
Last modified: 15 Mar 2024 05:03

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Contributors

Author: Thomas Monks ORCID iD
Author: Stewart Robinson
Author: Kathy Kotiadis

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