Addressing the sample size problem in behavioural operational research: simulating the newsvendor problem

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 (ABS) 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 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 ABS provides the potential to extend the scope of experimental research in behavioural operational research.

Keywords:

• behavioural operational research
• experimental research
• agent-based simulation (ABS)
• supply chain management
• newsvendor problem