Abstract
While the sales of mobile digital content have been growing exponentially, the understanding of its diffusion remains limited in the literature. In this study, we set out to enrich this understanding using a growth curve modelling approach. We applied four widely used growth curve models of innovation diffusion and compared their performance in explaining the diffusion of mobile digital content empirically. Analysis based on the data collected on a product adopted by nearly 30 million mobile phone users over a 149-week period in 31 regions in China revealed that the Gompertz model was the most effective model in depicting the diffusion process, with more than 99 % of the variance explained. Moreover, we found that population, urbanization, education level, and mobile technology usage were significant determinants of various parameters such as the diffusion rate and inflection point of the diffusion process, respectively. Implications for both researchers and practitioners are discussed.
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Notes
Source: http://it.sohu.com/20090407/n263239175.shtml, accessed on December 10, 2011.
We realize that besides ordinary least square (OLS) estimation, there are several other estimation procedures such as the maximum likelihood estimation (MLE), the nonlinear least squares (NLS), and the algebraic estimation (AE) procedures (Mahajan et al. 1986). We choose OLS because it is the easiest to implement and it is not the purpose of this paper to compare different estimation methods of the Bass model.
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Acknowledgments
This research was partly supported by a grant (no. 71102007) from National Natural Science Foundation of China to Dr. Angela Xia Liu at Tsinghua University and a Harrison McCain Foundation Emerging Scholar Award to Dr. Yinglei Wang at Acadia University.
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Liu, A.X., Wang, Y., Chen, X. et al. Understanding the diffusion of mobile digital content: a growth curve modelling approach. Inf Syst E-Bus Manage 12, 239–258 (2014). https://doi.org/10.1007/s10257-013-0224-1
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DOI: https://doi.org/10.1007/s10257-013-0224-1