TY - JOUR
T1 - Information initiatives of mobile retailers
T2 - A regression analysis of zero-truncated count data with underdispersion
AU - Chou, Yen Chun
AU - Chuang, Howard Hao Chun
AU - Shao, Benjamin
N1 - Funding Information:
We thank Dr. S. Said-Fernández for providing us with the E. histolytica trophozoites used in this study, Dr. J.A. Luna for graphic work, and Miss A.C. Castañeda and Dr. C.E. Medina-de la Garza for critically reading our manuscript. This work was supported by PAICYT (UANL) Grant No. SA255-99 and SIREYES Grant No. 19980602010.
Publisher Copyright:
Copyright © 2014 John Wiley & Sons, Ltd. Copyright © 2014 John Wiley & Sons, Ltd.
PY - 2015/7/1
Y1 - 2015/7/1
N2 - 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.
AB - 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.
KW - Consul's generalized Poisson
KW - Conway-Maxwell-Poisson
KW - Poisson
KW - binomial
KW - count data
KW - mobile retailing
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U2 - 10.1002/asmb.2037
DO - 10.1002/asmb.2037
M3 - Article
AN - SCOPUS:84937642393
SN - 1524-1904
VL - 31
SP - 457
EP - 463
JO - Applied Stochastic Models in Business and Industry
JF - Applied Stochastic Models in Business and Industry
IS - 4
ER -