Disaggregate market share response models

被引:15
作者
DeSarbo, WS
Degeratu, AM
Ahearne, MJ
Saxton, MK
机构
[1] Penn State Univ, Smeal Coll Business, Dept Mkt, University Pk, PA 16802 USA
[2] McKinsey & Co Inc, New York, NY 10022 USA
[3] Univ Connecticut, Sch Business, Storrs, CT 06269 USA
[4] Eli Lilly & Co, Lilly Corp Headquarters, Endocrine Mkt Res, Indianapolis, IN 46285 USA
关键词
market share models; finite mixtures; random effects; prescription drugs; maximum likelihood;
D O I
10.1016/S0167-8116(02)00078-2
中图分类号
F [经济];
学科分类号
02 ;
摘要
Traditional market share response (multiplicative competitive interaction or MCI) models have been gainfully employed in marketing research practice as an effective methodology for estimating competitive effects. Legions of books and articles on MCI models and their use have been published documenting the successful formulation and implementation of this class of models. In this spirit, this paper proposes a generalization of this class of models to a latent structure framework incorporating within-segment random brand effects. We apply and contrast this new formulation against the traditional aggregate MCI model formulations in an application involving physician prescription shares for three major brands of central nervous system (CNS) ethical pharmaceuticals (known as CNS drugs). We conclude the manuscript with managerial implications and suggestions for future research. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:253 / 266
页数:14
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