Skip to main content
Kent Academic Repository

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

Robinson, Stewart, Dimitriou, Stavrianna, Kotiadis, Kathy (2017) Addressing the sample size problem in behavioural operational research: Simulating the newsvendor problem. Journal of the Operational Research Society, 68 (3). pp. 253-268. ISSN 0160-5682. (doi:10.1057/s41274-016-0016-3) (KAR id:68580)

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. © 2016 The Operational Research Society.

Item Type: Article
DOI/Identification number: 10.1057/s41274-016-0016-3
Uncontrolled keywords: Decision making; Sampling; Supply chain management, Agent based simulation; Decision-making strategies; Experimental research; Laboratory experiments; Newsvendor problem; Operational research; Sample size problems; Testing hypothesis, Behavioral research
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Tracey Pemble
Date Deposited: 16 Aug 2018 11:48 UTC
Last Modified: 05 Nov 2024 12:30 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/68580 (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.