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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/21840

Title: Addressing the sample size problem in behavioural operational research: Simulating the newsvendor problem
Authors: Robinson, Stewart
Dimitriou, Stavrianna
Kotiadis, Katherine
Keywords: Behavioural operational research
Experimental research
Agent-based simulation (ABS)
Supply chain management
Newsvendor problem
Issue Date: 2016
Publisher: © Operational Research Society. Published by Palgrave Macmillan
Citation: ROBINSON, S., DIMITRIOU, S. and KOTIADIS, K., 2016. Addressing the sample size problem in behavioural operational research: Simulating the newsvendor problem. Journal of the Operational Research Society, In Press.
Abstract: Laboratory based experimental studies with human participants are beneficial for testing hypotheses in behavioural operational research. However, such experiments are not without their problems. One specific problem is obtaining a sufficient sample size, not only in terms of the number of participants, but also the time they are willing to devote to an experiment. In this paper we explore how agent-based simulation can be used to address the sample size problem and demonstrate the approach in the newsvendor setting. The decision-making strategies of a small sample of individual decision-makers are determined through laboratory experiments. The interactions of these suppliers and retailers are then simulated using an agent-based simulation (ABS) to generate a large sample set of decisions. With only a small number of participants, we demonstrate that it is possible to produce similar results to previous experimental studies that involved much larger sample sizes. We conclude that agent-based simulation provides the potential to extend the scope of experimental research in behavioural operational research.
Description: This paper is in closed access for 12 months.
Version: Accepted for publication
URI: https://dspace.lboro.ac.uk/2134/21840
Publisher Link: http://link.springer.com/journal/41274
ISSN: 1476-9360
Appears in Collections:Closed Access (Business School)

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