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Mobile commerce is resulting from the convergence of two of the fastest growing industries the Internet and mobile communications markets (Lord, 2004). The distinction between electronic commerce and mobile commerce is becoming blurred as the capabilities of the mobile devices become more sophisticated. Mobile access to the Internet is expanding significantly in breadth and depth of use (Ishii 2004). In addition mobile commerce offers extra functionality to existing electronic commerce such as location and localization services (Junglas & Watson 2008) and personal mobile support (Adams et al., 2003). Urbaczewski et al. (2003) argue that we need new methods, tools and ways of thinking to take full advantage of mobility and its potential. Mobile technologies offer much potential in developing business and social activity, developing new structures and value chains (Anckar & D’Incau 2002). From a strategic perspective, mobile technologies are fueling significant changes in business and working practices. “M-business is likely to have a tremendous impact on organizations, as wireless technologies and applications begin to change the existing processes, strategies, structures, roles of individuals, and even cultures of organizations” (Barnes, 2003, p2). Some argue that the first decade of the 21st century will be the decade of mobile computing and mobile commerce (Urbaczewski et al., 2003). In a longer timeframe mobility and mobile computing are likely to play an increasingly significant role in personal, social and working life (Brooks 2008; Constantiou et al., 2007; Ling, 2004). Investigating mobile technology adoption are fertile areas of investigation for technology developers, marketing managers and researchers. Technology adoption refers to the stage in which a technology is selected for use by an individual or an organization (Carr, 2005).
This article explores the use of mobile technologies from a stratified sample of users from a city in China (Beijing) and a city in the UK (Portsmouth). The theoretical foundation drew upon Davis’ Technology Adoption Model (Davis, 1989; Barnes, 2003; Kleijnen, 2003). One attribute being investigated was ‘perceived cost’ as this is identified as one of the main influences on people using technology (Kleijnen et al., 2003). The research consisted of a large survey supported with qualitative data from focus group sessions.
When conducting the research and analyzing the resultant datasets it became clear that understanding technology adoption requires researchers to separate the user from the payers, both for the initial purchaser and the ongoing service bills. However, existing theories of technology adoption, such as Davis’ (1989) Technology Adoption Models (TAM) and extensions (Barnes, 2003; Kleijnen, 2003; and others) do not distinguish between the users, the initial purchasers and the service payers of mobile technologies, and consequently do not capture the complex relationship between these stakeholders in the technology adoption process. This seems a major gap in the technology adoption literature.