Demand Modeling of Stochastic Product Diffusion Over the Life Cycle
Abstract
Planning during the product life cycle (PLC) poses a number of challenges for managers due to the pace of change and uncertainties in the marketplace. The ability to better understand, predict, and make decisions based on manifestations of demand forms a set of important operational problems that ultimately affect the profitability of enterprises. This paper models the stochastic diffusion of a product in the market as a geometric Brownian motion (GBM) process that has a time-varying drift rate. The model is calibrated such that model parameters are able to feature different product types and diffusion conditions. Imperfect information on the expected peak demand is treated as model uncertainty, and a Bayesian approach is employed to update knowledge on it. The demand model demonstrates robust performance over a wide range of conditions despite model uncertainty. It provides both qualitative and quantitative information for manufacturers and service providers to design strategies for stochastic PLC conditions as well as dynamic production planning.
Recommended Citation
R. Qin and D. Nembhard, "Demand Modeling of Stochastic Product Diffusion Over the Life Cycle," International Journal of Production Economics, vol. 137, no. 2, pp. 201 - 210, Elsevier, Jun 2012.
The definitive version is available at https://doi.org/10.1016/j.ijpe.2012.01.027
Department(s)
Engineering Management and Systems Engineering
Keywords and Phrases
Diffusion Theory; Product Life Cycle; Geometric Brownian Motion; Dynamic Planning
International Standard Serial Number (ISSN)
0925-5273
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2012 Elsevier, All rights reserved.
Publication Date
01 Jun 2012