Title: Learning under the inventory problem of economic order quantity: a behavioural study
Authors: Yan Wu; Kay-Yut Chen; Yan Lang
Addresses: San Jose State University, San Jose, CA 95192, USA ' University of Texas at Arlington, Arlington, Texas 76019, USA ' State University of New York at Oswego, Oswego, NY 13126, USA
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.
International Journal of Inventory Research, 2026 Vol.6 No.5, pp.1 - 34
Received: 18 Sep 2022
Accepted: 11 Feb 2023
Published online: 06 Jul 2026 *


