Title :
Stochastic Entry of Competitors and Marketing Decisions
Author :
Huang, Yeu-Shiang ; Ho, Jyh-Wen
Author_Institution :
Dept. of Ind. & Inf. Manage., Nat. Cheng Kung Univ., Tainan, Taiwan
Abstract :
The research on determination of product life so far has been mostly focusing on the perspective of strategic development. This study, from a quantitative perspective, assumes that the decision to keep selling or stop selling a product is essentially affected by competitors´ behaviors, and employs a stochastic approach in which the entry process of rival competitors and its effects within the planned product life are considered. The objective is to provide the managers with an informative decision process in formulating an appropriate strategy to maximize the product profits in a competitive market from the viewpoint of an incumbent firm. A nonhomogeneous Poisson process with a power law intensity function is assumed to be proper for modeling the entry process of rival competitors. The Bayesian decision analysis is utilized to recapitulate the assumptions and provide systematic criteria of rational judgments for quality decision making. Finally, a numerical example is given and the results of the proposed approach are discussed after performing sensitivity analyses.
Keywords :
Bayes methods; competitive intelligence; decision making; decision theory; organisational aspects; product life cycle management; profitability; stochastic processes; strategic planning; Bayesian decision analysis; competitive market; competitors behaviors; entry process; incumbent firm; informative decision process; marketing decisions; nonhomogeneous Poisson process; planned product life; power law intensity function; product profits; quality decision making; rational judgments; rival competitors; sensitivity analyses; stochastic entry; strategic development; systematic criteria; Bayesian methods; Companies; Compounds; Joints; Numerical models; Sensitivity analysis; Stochastic processes; Bayesian decision analysis; competitors' entry; nonhomogeneous Poisson process (NHPP);
Journal_Title :
Engineering Management, IEEE Transactions on
DOI :
10.1109/TEM.2010.2049852