Information initiatives of mobile retailers: a regression analysis of zero-truncated count data with underdispersion

Our paper presents an empirical analysis of the association between firm attributes in electronic retailing and the adoption of information initiatives in mobile retailing. In our attempt to analyze the collected data, we find that the count of information initiatives exhibits underdispersion. Also,...

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Bibliographic Details
Published in:Applied stochastic models in business and industry 2015-07, Vol.31 (4), p.457-463
Main Authors: Chou, Yen-Chun, Chuang, Howard Hao-Chun, Shao, Benjamin B.M.
Format: Article
Language:English
Subjects:
Approximation
binomial
Binomials
Business
Consul's generalized Poisson
Conway-Maxwell-Poisson
count data
Counting
Empirical analysis
Mathematical models
mobile retailing
Poisson
Regression
Retailing
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Summary:Our paper presents an empirical analysis of the association between firm attributes in electronic retailing and the adoption of information initiatives in mobile retailing. In our attempt to analyze the collected data, we find that the count of information initiatives exhibits underdispersion. Also, zero‐truncation arises from our study design. To tackle the two issues, we test four zero‐truncated (ZT) count data models—binomial, Poisson, Conway–Maxwell–Poisson, and Consul's generalized Poisson. We observe that the ZT Poisson model has a much inferior fit when compared with the other three models. Interestingly, even though the ZT binomial distribution is the only model that explicitly takes into account the finite range of our count variable, it is still outperformed by the other two Poisson mixtures that turn out to be good approximations. Further, despite the rising popularity of the Conway–Maxwell–Poisson distribution in recent literature, the ZT Consul's generalized Poisson distribution shows the best fit among all candidate models and suggests support for one hypothesis. Because underdispersion is rarely addressed in IT and electronic commerce research, our study aims to encourage empirical researchers to adopt a flexible regression model in order to make a robust assessment on the impact of explanatory variables. Copyright © 2014 John Wiley & Sons, Ltd.
ISSN:1524-1904
1526-4025
DOI:10.1002/asmb.2037