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In the 21st century, technology is pervasive and worldwide. During the past hundred years people have witnessed the potential of technology to change the ways people interact, conduct commerce and, navigate a technology-enabled world (Brown, 2008). People increasingly adopt and use computers to perform their jobs, obtain degrees, network both socially and professionally, communicate, obtain information, and engage in the proliferation of rapidly expanding variety of applications. Personal computer ownership has become ubiquitous, and people are increasingly using household technologies for a wide variety of purposes. Neilson data shows that 73% of all households own some kind of personal computer technology (Brown, 2008), and the United States Census Bureau reports that the Internet has transformed households to a venue for work and school (Newburger, 2001). For decades, IS researchers have studied technology acceptance, adoption, and use (Brown, 2008; Venkatesh, 2006). Numerous models have been developed to explain technology acceptance in the workplace. The Technology Acceptance Model (TAM) (Davis, 1989; Davis et al., 1989) is one of the most widely used theories in IS research. The Unified Theory of Technology Acceptance and Use (UTAUT), developed by Venkatesh, Morris, Davis, and Davis (2003), combined TAM with other prominent theories to develop and validate a comprehensive model, the Unified Technology Acceptance Model, for explaining acceptance and use in the workplace. While these models have been found to explain workplace technology acceptance and adoptions, these models do not work in the household.
Research on household technology adoption and use has shown that the nature of technology adoption and use in the household is different from that in the workplace (Brown et al., 2006).
Significant studies on household technology adoption and use (e.g., Brown & Venkatesh, 2003; Brown et al., 2006; Venkatesh, 2006; Venkatesh & Brown, 2001) have resulted in the Model of Technology Adoption (MATH) model, which was found to explain 50 per cent of the variance in adoption (Venkatesh & Brown, 2001) and 74 per cent of the variance when Household Life Cycle is added (Brown & Venkatesh, 2005). The MATH model is less powerful for explaining household technology use as the underlying determinants of adoption and use are different (Brown et al., 2006). Thus, while a great deal is known about acceptance of technology in the workplace and adoption of technology by households, less is known about household technology use.
As the household ownership of personal computers nears market saturation, fewer households are left to adopt and it becomes more important to understand household technology use. Research on household technological use is needed to enable individuals to reap the maximum benefits from application of technologies (Brown & Venkatesh, 2006; Venkatesh & Brown, 2001). The purpose of the research is to increase the understanding of the determinants of technology use in households. This paper presents the results of a study of 202 users of household personal computers to test a new research model, which builds on the studies using the MATH model (Brown, 2008; Brown & Venkatesh, 2003, 2005; Brown et al., 2006; Venkatesh, 2006; Venkatesh & Brown, 2001).