Skip to contentScholarGate
LibraryBookshelfDeskReview StudioAssistant
Sign in
On this page
IntuitionHow it worksWhen to use itStrengths & limitationsCommon pitfallsApplicationsFrequently asked🔒 Read the full methodSourcesRelated methods
Cite this pageSpotted an issue on this page? Report or suggest a fix →
Home›Operations Research›Newsvendor Model
Regression modelInventory control

Newsvendor Model

Newsvendor (Single-Period Inventory) Model · Also known as: Newsboy Model, Single-Period Inventory Model, Christmas Tree Problem, Gazete Satıcısı Modeli

The Newsvendor Model is a single-period stochastic inventory optimization framework that determines the profit-maximizing order quantity when demand is uncertain and unsold units cannot be carried forward. Formally introduced by Arrow, Harris, and Marschak (1951) in their foundational work on optimal inventory policy, the model balances the cost of ordering too much (overage) against the cost of ordering too little (underage) to yield a closed-form optimality condition known as the critical ratio.

ScholarGate
  1. Regression model
  2. v1
  3. 1 Sources
  4. PUBLISHED
Cite this page →
Tools & resources
Download slides
Learn & explore

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Method map

The neighbourhood of related methods — select a node to explore.

Newsvendor Model
Economic Order QuantitySafety StockStochastic Optimization

When to use it

The Newsvendor Model is appropriate when inventory decisions are made once per period, unsold stock has limited or no carry-over value, and demand is stochastic with an estimable distribution. Typical assumptions include a known and stationary demand distribution, linear overage and underage costs, and no replenishment during the selling season. The model is less suitable for multi-period settings with inventory carry-over, non-stationary demand, or correlated lead times. In such cases, extensions such as the base-stock model, dynamic programming formulations, or simulation-based approaches provide better alternatives.

Strengths & limitations

Strengths
  • Provides a closed-form, analytically tractable optimality condition that is easy to implement.
  • Directly incorporates demand uncertainty into the ordering decision without requiring simulation.
  • Scales well: the critical ratio framework applies to any demand distribution, continuous or discrete.
  • Serves as the theoretical foundation for a broad family of inventory and revenue management models.
Limitations
  • Restricted to a single selling period; cannot handle multi-period inventory dynamics or carry-over stock.
  • Requires an accurately estimated demand distribution; misspecification can significantly degrade performance.
  • Assumes linear cost structure; quantity discounts, fixed ordering costs, or capacity constraints violate this assumption.
  • Does not account for supplier lead-time uncertainty or correlated demand across products.

Frequently asked

What happens to Q* if the underage cost equals the overage cost?

When c_u = c_o the critical ratio equals 0.5, so the optimal order quantity equals the median of the demand distribution. This is the symmetric case where the cost of a shortage and the cost of excess inventory are identical, and ordering the median demand minimizes total expected cost. For skewed demand distributions the median and mean diverge, so Q* will differ from the average demand.

How do I estimate the demand distribution in practice?

Common approaches include fitting a parametric distribution (normal, Poisson, negative binomial) to historical sales data using maximum likelihood estimation, while correcting for demand censoring caused by stockouts. Non-parametric methods using empirical quantiles are also used when sufficient data are available. The choice of distribution should be validated against goodness-of-fit tests, and parameter uncertainty should be acknowledged when computing Q*.

Can the Newsvendor Model be extended to multiple products?

Yes. The unconstrained multi-product newsvendor decomposes into independent single-product problems, each solved by its own critical ratio. When a shared budget or shelf-space constraint is binding, the problem becomes a constrained stochastic knapsack, typically solved via a Lagrangian relaxation approach that adds a uniform shadow price to all overage costs until the constraint is satisfied.

Sources

  1. Arrow, K. J., Harris, T., & Marschak, J. (1951). Optimal inventory policy. Econometrica, 19(3), 250–272. DOI: 10.2307/1906813 ↗

How to cite this page

ScholarGate. (2026, June 2). Newsvendor (Single-Period Inventory) Model. ScholarGate. https://scholargate.app/en/operations-research/newsvendor-model

Related methods

Economic Order QuantitySafety StockStochastic Optimization

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

  • Economic Order QuantityOperations Research↔ compare
  • Safety StockOperations Research↔ compare
  • Stochastic OptimizationOptimization↔ compare
Compare side by side →

Referenced by

Economic Order QuantitySafety Stock

Similar methods

Economic Order QuantitySafety StockStochastic Linear ProgrammingVendor-Managed InventoryInventory RoutingABC AnalysisWagner-Whitin AlgorithmRobust Optimization

Related reference concepts

Supply Chain ManagementOperations ManagementCriteria for Decision-Making under Risk and UncertaintyOnline AlgorithmsMarkovian QueuesDecision Theory and Utility

Spotted an issue on this page? Report or suggest a fix →

ScholarGate — Newsvendor Model (Newsvendor (Single-Period Inventory) Model). Retrieved 2026-07-21 from https://scholargate.app/en/operations-research/newsvendor-model · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Arrow, Harris & Marschak
Year
1951
Type
Stochastic single-period inventory optimization
Subfamily
Inventory control
Decision Variable
Order quantity Q*
Optimality Condition
Critical ratio (cu / (cu + co))
Related methods
Economic Order QuantitySafety StockStochastic Optimization
ScholarGate

A content-first reference library for research methods — what each one is, how it works, and where it comes from.

Open data (CC-BY)

Explore

  • Library
  • Search the library…
  • Browse by field
  • Fields
  • Journey
  • Compare
  • Which method?

Reference

  • Subjects
  • Atlas
  • Glossary
  • Methodology
  • Philosophy

Your tools

  • Bookshelf
  • Desk
  • Chat

Company

  • About
  • Pricing
  • Contact
  • Suggest a method

Entries are compiled from published sources for reference. Verifying the accuracy and suitability of any information for your own use remains your responsibility.

© 2026 ScholarGate · A research-method reference library
  • Privacy
  • Cookies
  • Terms
  • Delete account