Solving the Price-Setting Newsvendor Problem with Parametric Operational Data Analytics (ODA)

Leon Yang Chu (), Qi Feng (), J. George Shanthikumar (), Zuo-Jun Max Shen () and Jian Wu ()
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Leon Yang Chu: Cheung Kong Graduate School of Business, Shanghai 201107, China
Qi Feng: Mitchell E. Daniels, Jr., School of Business, Purdue University, West Lafayette, Indiana 47907
J. George Shanthikumar: Mitchell E. Daniels, Jr., School of Business, Purdue University, West Lafayette, Indiana 47907
Zuo-Jun Max Shen: Faculty of Engineering and Faculty of Business and Economics, The University of Hong Kong, Hong Kong
Jian Wu: Mitchell E. Daniels, Jr., School of Business, Purdue University, West Lafayette, Indiana 47907

Management Science, 2025, vol. 71, issue 8, 6627-6646

Abstract: We study the data-integrated, price-setting newsvendor problem in which the price–demand relationship is described by some parametric model with unknown parameters. We develop the operational data analytics (ODA) formulation of this problem that features a data-integration model and a validation model. The data-integration model consists of a class of functions called the operational statistics. Each operational statistic maps the available data to the ordering decision. The validation model finds, among the set of candidate operational statistics, the ordering decision that leads to the highest actual profit, which is unknown because of the unknown demand parameters. This ODA framework leads to a consistent estimate of the profit function with which we optimize the pricing decision. The derived quantity and price decisions demonstrate robust profit performance even when the sample size is very small in relation to the demand variability. Compared with the conventional approach with which the unknown parameters are estimated and then the decisions are optimized, the ODA framework produces significantly superior performance in the mean, standard deviation, and minimum of the profit, suggesting the robustness of the ODA solution especially in the small-sample regime.

Keywords: price-setting newsvendor problem; data-integration model; operational statistics; small sample size (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:71:y:2025:i:8:p:6627-6646

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