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Harsha, P., Natarajan, R., & Subramanian, D. (2021). A Prescriptive Machine-Learning Framework to the Price-Setting Newsvendor Problem. INFORMS Journal on Optimization, 3, 227-253.
https://doi.org/10.1287/ijoo.2019.0046

has been cited by the following article:

• TITLE: Price-Setting Newsvendor Where Customers Have Valuations

  AUTHORS: Yigal Gerchak

  KEYWORDS: Price-Setting Newsvendor, Customers’ Valuations, Unknown Population Size, Revenue Sharing, Asymmetric Nash Bargaining Solution

  JOURNAL NAME: Theoretical Economics Letters, Vol.16 No.4, August 14, 2026

  ABSTRACT: We study a price-setting newsvendor where potential customers attempt a purchase if their valuations for the product or service exceed its price. The seller does not know the valuations. The number of attempted purchases is distributed binomially. The retailer needs to embed that attempt distribution in a price-setting newsvendor problem. We analyze such a detailed model. We also consider several extensions: non-linear production costs, an unknown number of potential customers, possibly Poisson distributed, and cooperative revenue sharing contracts with a manufacturer based on a Nash bargaining solution, possibly asymmetric.