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◆ International Journal of Production Research2026-08-01· Newsvendor model

Beyond heuristics: an experimental study on the impact of math self-efficacy and cognitive reflection on newsvendor decision-making performance

Sina Zare, Yasaman Ghasemi, Kay‐Yut Chen

原始摘要(英文原文)· Original abstract
Behavioural newsvendor research has documented persistent deviations from optimal ordering – demand chasing, pull-to-center, and anchoring – yet the psychological foundations underlying these biases remain underspecified. We distinguish two constructs: cognitive reflection (CRT), the disposition to override intuitive responses, and math self-efficacy (MSE), a domain-specific motivational belief supporting the persistent application of rule-based reasoning under uncertainty. Using a repeated-round laboratory newsvendor experiment (N = 43 participants, 100 incentivized rounds), we examine the associations between CRT, MSE, and profit, whether MSE attenuates demand-chasing bias, and whether MSE moderates round-by-round learning. CRT and MSE are positively associated with profit, and the estimates are consistent with an indirect association linking CRT to performance via MSE. MSE significantly attenuates demand-chasing bias, primarily in later rounds as participants gain task experience. By contrast, MSE does not moderate the rate of learning but is associated with greater within-subject stability and consistency of ordering behaviour, consistent with motivational stability rather than cognitive bias correction. These findings indicate that reasoning style and motivational beliefs play complementary roles in reducing decision biases: CRT supports analytic override of intuitive responses, whereas MSE sustains consistent rule-based ordering under uncertainty. The study advances the psychological foundations of behavioural operations and informs training and decision-support systems.
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Beyond heuristics: an experimental study on the impact of math self-efficacy and cognitive reflection on newsvendor decision-making performance — 科研速览 Science Skim