Capital-constrained bi-objective newsvendor model with risk-averse preference and bankruptcy threshold
Industrial Management & Data Systems
ISSN: 0263-5577
Article publication date: 25 October 2019
Issue publication date: 22 January 2020
Abstract
Purpose
The purpose of this paper is to investigate the major factors influencing retailer’s optimal ordering strategy in a supply chain consisting of one supplier and one retailer, where the retailer is newsvendor-like and capital-constrained, and further explore the issue of supply chain coordination.
Design/methodology/approach
Based on bi-objective programming which is modeled under the mean-variance framework, the retailer’s optimal ordering strategy is derived. Furthermore, through comparative analysis between decentralized system and centralized system along with a numerical simulation, this study examines the theoretical conclusions about supply chain coordination.
Findings
This study shows that a poor retailer with a high Expected Terminal Wealth Target Threshold (ETWTT) would ignore bankruptcy risk and order more, whereas a rich retailer is relatively conservative. It also reveals that in some cases, the optimal order quantity and performance of decentralized system could be both improved. However, the centralized system can always get more profit than the decentralized one.
Originality/value
This study uses a bankruptcy threshold to describe retailer’s bankruptcy risk, and considers retailer’s wealth status to formulate the model as an innovative bi-objective programming. The type of retailer as rich or poor in terms of his wealth status and asset structure is distinguished. Moreover, the impacts of retailer’s type and ETWTT on ordering strategy are examined.
Keywords
Citation
Yang, C., Wu, D. and Fang, W. (2020), "Capital-constrained bi-objective newsvendor model with risk-averse preference and bankruptcy threshold", Industrial Management & Data Systems, Vol. 120 No. 2, pp. 406-424. https://doi.org/10.1108/IMDS-03-2019-0200
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited