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Can involving clients in simulation studies help them solve their future problems? A transfer of learning experiment

Monks, Thomas, Robinson, Stewart, Kotiadis, Kathy (2015) Can involving clients in simulation studies help them solve their future problems? A transfer of learning experiment. Euorpean Journal of Operational Research, 249 (3). pp. 919-930. ISSN 0377-2217. (doi:10.1016/j.ejor.2015.08.037) (KAR id:51026)

Abstract

It is often stated that involving the client in operational research studies increases conceptual learning about a system which can then be applied repeatedly to other, similar, systems. Our study provides a novel measurement approach for behavioural OR studies that aim to analyse the impact of modelling in long term problem solving and decision making. In particular, our approach is the first to operationalise the measurement of transfer of learning from modelling using the concepts of close and far transfer, and overconfidence. We investigate learning in discrete-event simulation (DES) projects through an experimental study. Participants were trained to manage queuing problems by varying the degree to which they were involved in building and using a DES model of a hospital emergency department. They were then asked to transfer learning to a set of analogous problems. Findings demonstrate that transfer of learning from a simulation study is difficult, but possible. However, this learning is only accessible when sufficient time is provided for clients to process the structural behaviour of the model. Overconfidence is also an issue when the clients who were involved in model building attempt to transfer their learning without the aid of a new model. Behavioural OR studies that aim to understand learning from modelling can ultimately improve our modelling interactions with clients; helping to ensure the benefits for a longer term; and enabling modelling efforts to become more sustainable.

Item Type: Article
DOI/Identification number: 10.1016/j.ejor.2015.08.037
Uncontrolled keywords: Behavioural OR; Psychology of decision; Model building; Model reuse; Discrete-event simulation
Subjects: Q Science > Operations Research - Theory
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Kathy Kotiadis
Date Deposited: 14 Oct 2015 19:41 UTC
Last Modified: 05 Nov 2024 10:36 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/51026 (The current URI for this page, for reference purposes)

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