Abstract

The emergence of device convergence with regard to new design and data services have transformed the use of mobile phones from solely for voice and text  communication into various purposes, namely personal information management (PIM), entertainment, e-mail communication, and commercial transactions. However, most of the existing literature on mobile technology adoption has thus far focused on the adoption of mobile phone as a single function device and hence does offer very limited explanatory power to understand the utility of mobile phone as a converged device. In addition, the scope of previous studies has been limited to a single country. Therefore, this paper intends to address both these limitations. The aim is to explain the use of mobile phone as a converged device and the determinants that influence such use. Data were collected based on a cross-national survey in Australia and Taiwan. Although the findings indicate that the individual profiles and usage patterns in both countries are similar, the empirical framework explains more variances in the Australian sample. Among the psychometrical factors, individuals’ perception of enjoyment is the dominant factor that drives people to use mobile phones for various purposes in both Australia and Taiwan. Users’ age does differentiate the use of mobile phones for different purposes in both samples. Gender seems to have some influence as well. Male and female users show significant differences in using their mobile phones for entertainment, e-mail and commercial transactions. The findings also pinpoint the effects of individuals’ perceptions, demographics, and technology choices are heterogeneous when using mobile phones for specific purposes. Some effects, such as risk and enjoyment can be explained by cultural differences. Therefore, product manufacturers and service providers should dedicate their marketing efforts in accordance to match with the heterogeneous demand from their customers.

Key words: TAM, mobile commerce, moderating effect, logistic regression.