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A Bayesian Model to Predict Saturation and Logistic Growth

 

作者: OliverRobert M.,  

 

期刊: Journal of the Operational Research Society  (Taylor Available online 1987)
卷期: Volume 38, issue 1  

页码: 49-56

 

ISSN:0160-5682

 

年代: 1987

 

DOI:10.1057/jors.1987.6

 

出版商: Taylor&Francis

 

关键词: Bayesian forecasting;growth prediction;logistic growth;market saturation;new-product growth;non-linear growth models

 

数据来源: Taylor

 

摘要:

AbstractThis paper formulates a Bayesian model to predict growth and eventual market saturation of a recently introduced (and possibly expensive) consumer-durable product. The mathematical model assumes that each new buyer buys only one item of the product, that the number of new buyers of the product in the next period of time is influenced by the current number of non-buyers and that the probability an individual will buy is the result of a diffusion of news among satisfied buyers. The solution of the prediction problem includes a two-stage Bayesian updating formula which first revises the prior distribution of market saturation based on the most recent number of new buyers and then, conditional on the saturation level, computes the predictive distribution of new buyers in future time-periods.

 

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