Decision Bias in the Newsvendor Problem: On the Comparison of Managers and Students as Newsvendors with Decision Support System as Debiasing Strategy

Pitaloka, Elok and Masruroh, Nur Aini and Lin, Shi Woei (2019) Decision Bias in the Newsvendor Problem: On the Comparison of Managers and Students as Newsvendors with Decision Support System as Debiasing Strategy. In: IEEE International Conference on Industrial Engineering and Engineering Management, 2019.

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Abstract

A growing number of studies in the newsvendor problem provided evidence that subjects' ordering behavior deviates from the optimal order quantity. Furthermore, almost all existing studies only engage students as subjects, and it leaves an essential question of whether the insights of those studies can be applied in real business practices. In this empirical study, we experimented with investigating decision biases in the newsvendor setting and presenting a structured comparison of the order decisions made by managers and students. We also proposed a Decision Support System as a debiasing strategy to prevent the order decision bias. To provide a piece of evidence about the effectiveness of the proposed DSS, we experimented with comparing the ordering behavior, before and after DSS implementation. This study found that both managers and students showed demand chasing bias, but the magnitude of the bias differed significantly. This study also showed that an informational DSS generally improved inventory decision-making performance in terms of adjustment behavior and long-term profitability.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Library Dosen
Uncontrolled Keywords: Artificial intelligence; Decision support systems; Managers; Students; Behavioral operations; Business practices; Decision bias; Empirical studies; Inventory decisions; Newsvendor problem; Newsvendors; Optimal order quantity; Decision making
Subjects: T Technology > TJ Mechanical engineering and machinery
Divisions: Faculty of Engineering > Mechanical and Industrial Engineering Department
Depositing User: Sri JUNANDI
Date Deposited: 02 Mar 2026 03:55
Last Modified: 02 Mar 2026 03:55
URI: https://ir.lib.ugm.ac.id/id/eprint/25089

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