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|a (JST)4129743
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|a eng
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|a Rossi, Peter E.
|e verfasserin
|4 aut
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|a Bayesian Statistics and Marketing
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|c 2003
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|a Text
|b txt
|2 rdacontent
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|a Bayesian methods have become widespread in marketing literature. We review the essence of the Bayesian approach and explain why it is particularly useful for marketing problems. While the appeal of the Bayesian approach has long been noted by researchers, recent developments in computational methods and expanded availability of detailed marketplace data has fueled the growth in application of Bayesian methods in marketing. We emphasize the modularity and flexibility of modern Bayesian approaches. The usefulness of Bayesian methods in situations in which there is limited information about a large number of units or where the information comes from different sources is noted. We include an extensive discussion of open issues and directions for future research.
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|a Copyright 2003 Institute for Operations Research and the Management Sciences
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|a Bayesian Statistics
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|a Decision Theory
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|a Marketing Models
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|a Critical Review
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|a Business
|x Business administration
|x Corporate communications
|x External corporate communications
|x Marketing
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|a Economics
|x Economic disciplines
|x Applied economics
|x Economic modeling
|x Economic models
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|a Applied sciences
|x Research methods
|x Modeling
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|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Statistical models
|x Parametric models
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|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Cognitive processes
|x Decision making
|x Bayesian theories
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|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Cognitive processes
|x Thought processes
|x Reasoning
|x Inference
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|a Mathematics
|x Pure mathematics
|x Probability theory
|x Random variables
|x Stochastic processes
|x Markov processes
|x Markov chains
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|a Mathematics
|x Mathematical values
|x Mathematical variables
|x Mathematical independent variables
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|a Information science
|x Information management
|x Data management
|x Data architecture
|x Data models
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|a Information science
|x Information analysis
|x Data analysis
|x Regression analysis
|x Multilevel models
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|a research-article
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|a Allenby, Greg M.
|e verfasserin
|4 aut
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|i Enthalten in
|t Marketing Science
|d Institute for Operations Research and the Management Sciences
|g 22(2003), 3, Seite 304-328
|w (DE-627)320627799
|w (DE-600)2023536-7
|x 1526548X
|7 nnns
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|g volume:22
|g year:2003
|g number:3
|g pages:304-328
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|u https://www.jstor.org/stable/4129743
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|d 22
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|e 3
|h 304-328
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