Uncertainty and Information Acquisition in Newsvendor Problem

Uncertainty and Information Acquisition in Newsvendor Problem

• Associate Professor of Economics Priyanka Sharma
• Chaoqun Gao

Abstract:

This paper extends the classical Newsvendor model to incorporate supply uncertainty and blockchain technology—two factors that are increasingly becoming relevant in supply chain management. We model supply uncertainty by allowing for the possibility that only a fraction of ordered goods remains saleable upon delivery. In contrast to the traditional retailer, the blockchain-integrated retailer in our framework has access to predictive, real-time product quality assessments before placing its order and knows precisely what portion of goods will be usable upon delivery. Integrating blockchain technology into the supply chain allows the blockchain retailer to make more informed inventory decisions. Accordingly, he revises the inventory decision to order more than the traditional retailer under certain conditions and less in the other. We also establish that the availability of predictive information leads to consistently higher expected profits. We finally use numerical simulations to compare order quantity and profits under specific distributions of demand and supply. Our results underscore the economic advantages of integrating blockchain-based freshness tracking into perishable supply chains and point toward promising future research directions in inventory management.

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