Reza Azad Gholami (), Leif K. Sandal () and Jan Ubøe ()
Additional contact information
Reza Azad Gholami: Dept. of Business and Management Science, Norwegian School of Economics, Postal: NHH , Department of Business and Management Science, Helleveien 30, N-5045 Bergen, Norway
Leif K. Sandal: Dept. of Business and Management Science, Norwegian School of Economics, Postal: NHH , Department of Business and Management Science, Helleveien 30, N-5045 Bergen, Norway
Jan Ubøe: Dept. of Business and Management Science, Norwegian School of Economics, Postal: NHH , Department of Business and Management Science, Helleveien 30, N-5045 Bergen, Norway
Abstract: Almost every vendor faces uncertain and time-varying demand. Inventory level and price optimization while catering to stochastic demand are conventionally formulated as variants of newsvendor problem. Despite its ubiquity in potential applications, the time-dependent (multi-period) newsvendor problem in its general form has received limited attention in the literature due to its complexity and the highly nested structure of its ensuing optimization problems. The complexity level rises even more when there are more than one decision maker in a supply channel, trying to reach an equilibrium. The purpose of this paper is to construct an explicit and e cient solution procedure for multi-period price-setting newsvendor problems in a Stackelberg framework. In particular, we show that our recursive solution algorithm can be applied to standard contracts such as buy back contracts, revenue sharing contracts, and their generalizations.
Keywords: Stochastic demand; time-dependent demand; price-dependent demand; memory functions; market engineering; demand manipulation; prescriptive analytics; pricing theory
42 pages, September 9, 2019
Full text files
2614274 Full text
Questions (including download problems) about the papers in this series should be directed to Stein Fossen ()
Report other problems with accessing this service to Sune Karlsson ().
RePEc:hhs:nhhfms:2019_008This page generated on 2024-09-13 22:16:23.