Forthcoming and Online First Articles

International Journal of Inventory Research

International Journal of Inventory Research (IJIR)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Inventory Research (One paper in press)

Regular Issues

  • Learning under the inventory problem of economic order quantity: a behavioural study   Order a copy of this article
    by Yan Wu, Kay-Yut Chen, Yan Lang 
    Abstract: Inventory management relies on the economic order quantity (EOQ) and newsvendor models. While the newsvendor model has received much attention in the field of behavioural operations management (BOM), the EOQ problem remains largely untouched. This study presents one of the first empirical examinations of inventory decisions under the deterministic EOQ model. The experiments analyse learning behaviours in response to stationary and non-stationary parametric environments. Results show that participants are less likely to repeat suboptimal decisions when parameters remain static. When confronted with cost parameter shocks, most players can improve decisions over time and benefit from past experiences. Two behavioural models, a modified experience-weighted-attraction (EWA) model and an exploratory behaviour-based error reduction model (ERM), are developed to analyse the decision-making process. These models reveal the impact of different behavioural traits on learning under EOQ. Additional experiments are conducted to improve empirical performance.
    Keywords: economic order quantity; EOQ; inventory management; behavioural operations management; BOM; learning; reinforcement; probabilistic choice.
    DOI: 10.1504/IJIR.2023.10054788
     

 

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