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Retailers’ optimal ordering policies for a dual-sourcing procurement

Xinsheng Xu (College of Science, Binzhou University, Binzhou, China)
Ping Ji (Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, China)
Felix T.S. Chan (Department of Decision Sciences, Macau University of Science and Technology, Macau, China)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 9 February 2023

Issue publication date: 9 March 2023

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Abstract

Purpose

Optimal ordering decision for a retailer in a dual-sourcing procurement is an important research area. The main purpose of this paper is to explore a loss-averse retailer’s ordering decision in a dual-sourcing problem.

Design/methodology/approach

For a loss-averse retailer, the study obtains the optimal ordering decision to maximize expected utility. Based on sensitivity analysis, the properties of the optimal ordering decision are well discussed.

Findings

Under the optimal ordering quantity that maximizes expected loss aversion utility, the relevant expected profit of a retailer turns to be smaller under a bigger loss aversion coefficient. For this point, a retailer needs to balance between expected loss aversion utility maximization and expected profit maximization in deciding the optimal ordering policy in a dual-sourcing problem.

Originality/value

This paper reveals the influence of loss aversion on a retailer’s ordering decision in a dual-sourcing problem. Managerial insights are suggested to devise the optimal ordering policy for retailers in practice.

Keywords

Acknowledgements

This work is supported by the National Natural Science Foundation of China (Project No.71871026), the Taishan Scholars of Shandong Province (Project No.tsqn202103120), Natural Science Foundation of Shandong Province (Project No.ZR2017MG002), and a grant from The Hong Kong Polytechnic University of China (Project No. UAHR).

Citation

Xu, X., Ji, P. and Chan, F.T.S. (2023), "Retailers’ optimal ordering policies for a dual-sourcing procurement", Industrial Management & Data Systems, Vol. 123 No. 3, pp. 1052-1072. https://doi.org/10.1108/IMDS-07-2022-0458

Publisher

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Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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