A Fractiles Perspective to the Joint Price/Quantity Newsvendor Model
Gal Raz,
Evan L. Porteus
Australian Graduate School of Management, University of New South Wales, Sydney, New South Wales 2052, Australia
Graduate School of Business, Stanford University, Stanford, California 94305
galraz{at}agsm.edu.au
eporteus{at}leland.stanford.edu
Pricing and quantity decisions are critical to many firms across different industries. We study the joint price/quantity newsvendor model where only a single quantity and price decision is made, such as a fashion or holiday product that cannot be replenished and where the price is advertised nationally and cannot be changed. Demand is uncertain and sensitive to price. We develop a method for easily finding the optimal price and quantity that applies to more general cases than the usual one in which uncertainty is either additive, multiplicative, or a combination of the two. We represent a quantity by its fractile of the probability distribution of demand for a given price. We use a standard approach to approximating a given distribution with a finite number of representative fractiles and assume that these fractile functions are piecewise linear functions of the price. We identify effects that are not usually seen in a joint price/quantity newsvendor model. For example, although the optimal quantity is a decreasing function of the unit cost, the optimal price can be nonmonotone in the unit cost and we shed insight into why. We illustrate that using a simplified structure of demand uncertainty can result in substantially lower profits.
Key Words: pricing; simultaneous production planning; newsvendor model; supply chain management
History: Received: November 13, 2003;
Copyright © 2006 by INFORMS.