An Empirical Study on Demand Models for a Price-Setting Newsvendor

33 Pages Posted: 14 Dec 2009

See all articles by Emel Arikan

Emel Arikan

Vienna University of Economics and Business

Johannes Fichtinger

Cranfield University - School of Management

Date Written: December 14, 2009

Abstract

We consider the price-setting newsvendor model where the ordering and pricing decisions have to be made at the beginning of a selling period before demand is realized. Unsatisfied demand is lost and excess inventory has to be salvaged. The standard approach is to assume stochastic demand to be composed of deterministic functions decreasing in price and a stochastic error term. We present an empirical study which includes demand modelling as well as price and inventory optimization. Using the sales data of a retailing company, additive and multiplicative demand models are estimated and their adequacy of representing the data is assessed according to some statistical methods. Seeing the need and possibility of using a more general demand model we suggest estimating a more flexible demand distribution in a simple way. Applying the newsvendor problem formulation, the optimal policies under each of the three models as well as the policy under the sequential approach are calculated. The performance of each model is evaluated by simulating the corresponding policies using the same data set. We conclude that using a general model can increase the profits significantly.

Keywords: Inventory, Pricing, Newsvendor model, Regression, Price-dependent demand distribution

JEL Classification: M11, M31, C53

Suggested Citation

Arikan, Emel and Fichtinger, Johannes, An Empirical Study on Demand Models for a Price-Setting Newsvendor (December 14, 2009). Available at SSRN: https://ssrn.com/abstract=1523262 or http://dx.doi.org/10.2139/ssrn.1523262

Emel Arikan (Contact Author)

Vienna University of Economics and Business ( email )

Welthandelsplatz 1
Vienna, Wien 1020
Austria

Johannes Fichtinger

Cranfield University - School of Management ( email )

Bedfordshire, MK43 0AL
United Kingdom

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