Quality information acquisition and ordering decisions with risk aversion

Abstract

This paper investigates a retailer’s quality information acquisition and ordering decisions in the presence of risk aversion. We formulate a newsvendor model and derive the retailer’s optimal order quantity under two scenarios, one with and one without quality information acquisition, by minimising expected risk based on the CVaR criterion. Then, we compare the optimal ordering quantities and the profits under the two scenarios and discuss the quality information acquisition decision. Our results show that it will be more effective for the retailer to acquire quality information if the retailer exhibits greater risk aversion or the information is more precise; the retailer would order less when she is more risk-averse and the impact of risk aversion would be reduced by quality information acquisition. Interestingly, the retailer’s profits may decrease even when the quality information is more precise.

KEYWORDS:

• Quality information acquisition
• ordering
• risk aversion
• CVaR
• newsvendor

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 2018 China smartphone market competition situation and user behaviour data monitoring report

2 https://techcrunch.com/2018/09/24/walmart-is-bettingon-the-blockchain-to-improve-food-safety/,

3 http://www.ibm.com/blogs/events/think-2018/think-2018-present/improving-food-safety-intenet-things/

Additional information

Funding

This work was supported by National Natural Science Foundation of China: [Grant Number 72032001,71972071].

Notes on contributors

Yang Song

Yang Song is a Ph.D. candidate in the Department of Management Science and engineering, East China university of Science and Technology. She received her Bachelor degree from East China university of Science and Technology in 2016. Her research interest is the interface of operations management and marketing science.

Tijun Fan

Tijun Fan received the Ph.D. degree from the Huazhong University of Science and Technology of China, Wuhan, Hubei, China, in 2003. He is a Professor of operations and supply chain management with East China University of Science and Technology, Shanghai, China. His research has been published several journals such as Production and Operations Management, Energy Economics, the European Journal of Operational Research, Transportation Research Part D, the International Journal of Production Economics, among others. His research interests include operations management, logistics management, and supply chain management.

Yuewu Tang

Yuewu Tang is a Ph.D. candidate in the Department of Management Science and engineering, East China university of Science and Technology. He received the master’s degree in Management Science and engineering from East China university of Science and Technology in 2009. His research interest lies in supply chain management.

Fengli Zou

Fengli Zou received the master’s degree in Management Science and engineering from East China university of Science and Technology in 2019. Her research interest lies in supply chain management and operations management.