Quotation Ledolter, Johannes. 2007. Random-Coefficient Hidden-Markov Poisson-Regression Models for Inferring a Competitor's Promotion Strategy. Applied Stochastic Models in Business and Industry 23 (2007): 293-305.


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Abstract

In this paper we consider the case of a drug manufacturer who has physician-level information on the prescription volume for its own brand and its competitor, has complete physician-level data on its own free-sampling plan, but has only sparse data on the competitor's promotion strategy. We investigate whether one is able to predict the competitor's promotion strategy from such limited data. We treat the competitor's promotion as a latent (unobservable) event, and propose a hidden Markov model (HMM) to describe its progression over time. Analysis of actual and simulated data shows that the HMM improves our ability to infer the missing promotion event if promotions are serially correlated. A simpler model assuming that the probability of transition from one sampling state to the other is independent of the current state is adequate if the serial correlation among promotions is weak.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Applied Stochastic Models in Business and Industry
Citation Index SCI
Language English
Title Random-Coefficient Hidden-Markov Poisson-Regression Models for Inferring a Competitor's Promotion Strategy
Volume 23
Number 2007
Year 2007
Page from 293
Page to 305
Reviewed? Y
URL http://www3.interscience.wiley.com/journal/114175445/abstract?CRETRY=1&SRETRY=0

Associations

People
Ledolter, Johannes (Former researcher)
Organization
Institute for Statistics and Mathematics IN (Details)
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