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

被引:30
作者
Monks, Thomas [1 ]
Robinson, Stewart [2 ]
Kotiadis, Kathy [3 ]
机构
[1] Univ Southampton, Fac Hlth Sci, Southampton SO17 1BJ, Hants, England
[2] Univ Loughborough, Sch Business & Econ, Loughborough LE11 3TU, Leics, England
[3] Univ Kent, Sch Comp, Canterbury CT2 7NZ, Kent, England
关键词
Behavioural OR; Psychology of decision; Model building; Model reuse; Discrete-event simulation; DISCRETE-EVENT SIMULATION; SOFT; KNOWLEDGE; FRAMEWORK;
D O I
10.1016/j.ejor.2015.08.037
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
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. (C) 2015 The Authors. Published by Elsevier B.V.
引用
收藏
页码:919 / 930
页数:12
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