Constructing A Prediction Model of Inter-purchase Time with Generalized Gamma Distribution by Hierarchical Bayesian Statistics
Date Issued
2005
Date
2005
Author(s)
Chen, Hsin-Liang
DOI
zh-TW
Abstract
Marketing researchers are always striving for how to identify the customers’ preference structure, and how to predict the customers’ purchase behavior precisely. Due to technology development, the enormous amount of information storage and the ability of data computation enable the researchers to further comprehend the purchases and preferences of consumers more directly. However, on the premise that heterogeneity is existed, if we still continuously use the traditional statistics methods to characterize the consumers’ behavior, then we always face a trade-off: while estimating the behavior of consumers, if based on the information of whole customers, then we may ignore the heterogeneity between them; or if solely based on identical customer, then the estimation may lack efficiency because of insufficient data amount.
We construct a prediction model of customer inter-purchase times based on the generalized gamma distribution, which can make the model fit the data more flexible than the other distributions. We also assume the heterogeneity of customer behavior follow the inverse generalized gamma distribution, so that the difference and the instability of consumer behavior between each customer can be reflected clearly. Additionally, our model is formulated with a hierarchical Bayesian framework with demographic variables, which can predict the behavior of new customers without gathering any purchasing information. At last, we estimate the parameters of the model by Bayesian statistics. Because of the integration of prior and sample information, Bayesian statistics can provide individualized estimation of parameters for each customer and also ensure both the heterogeneity of customers and efficiency of parameter estimating at the same time.
In order to verify the prediction capability of this hierarchical Bayesian model, the purchase records of a domestic leading petroleum company will be employed in the model and also list the pros and cons with different parameters estimated. Finally, we draw a conclusion, indicate the limitation of this investigation, and suggest the direction to be studied on possible future work.
Subjects
一般化迦瑪分配
層級貝氏模型
購買期間
Generalized Gamma Distribution
Hierarchical Bayesian Model
Inter-purchase Time
SDGs
Type
thesis
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