A challenge to any study of technology adoption is that technology media and uses are developing incredibly fast and in unimagined ways. For instance, the media landscape has experienced a paradigm shift (Kuhn, 1996) with recent advances in social media, smart phone technologies, global positioning satellite (GPS) tracking, and the blending of actuality (e.g. Google Maps) with virtuality (e.g. Aurasuma) in what is known as augmented reality (McCullagh, 2010). Moreover, there seems to be no finality to the technology use question so long as technologies continue to advance, and people continue to adapt technologies to their purposes, along with being shaped by them (Civin, 1999). To illustrate, the technology acceptance model (Davis, Bagozzi, & Warshaw, 1989), the theory of planned behavior (Ajzen, 1991), and the diffusion of innovations (Rogers, 2003) – have all shown clear signs of disparities resulting from the derivative works about information technology use (Bagozzi, 2007).
To highlight this issue, in the 1990s, research on the technology acceptance model – or TAM ( Davis et al., 1989) was so intensive that researchers began to refer to it as TAM fatigue. Over the intervening years, TAM was criticized for a variety of reasons (c.f. Goodhue, 2007 and Straub and Burton-Jones, 2007). For example, Lee, Lee, and Lee (2006) pointed out various insufficiencies in accounting for social influences among the dominant technology adoption and use theories and models, and thus numerous competing theories and models emerged (c.f. Taylor & Todd, 1995). In addition, studies meanwhile had introduced numerous factors into the mix such as feelings and emotions concerning a given technology ( Ha, Yoon, & Choi, 2007) including the use of new technologies as a means of sensation seeking stimuli ( Dupagne, 1999 and Karaiskos et al., 2011).
In the early 2000s, there was a purported consolidation in the literature (Lee et al., 2006) around the unified theory of acceptance and use of technology – UTAUT (Venkatesh, Morris, Davis, & Davis, 2003), which predicts a single use outcome measure. Nevertheless, research using the UTAUT has to date tended only to examine a single outcome measure for a specific technology (c.f. Zhou, Lub, & Wang, 2010) leaving a fragmented picture of technology use. New technologies such as smart devices and social media, along with changes in technology literacy among the populace demographic, have again raised the technology use question (Brandtzaeg, 2012). In particular, there are indications that the use of new technology may depend on the technology itself (Maass, Klöpper, Michel, & Lohaus, 2011) – raising questions about the agglomeration of technologies into one dependent concept as asserted in the UTAUT.
We encountered this research problem when we were engaged by an insurance provider in the United States to conduct a study of who might be interested in “wellness” products such as diet plans, exercise resources, spa memberships, smoking cessation programs and products, using social media (e.g. Facebook, Twitter, LinkedIn, YouTube, MySpace) and smart device applications (e.g. iPhone, iPad, Android) such as diet managers, product and service promotions, and exercise reality imitation and simulations – or “immutations” using augmented reality apps (c.f. McCullagh, 2010).
Our overall research goal was to understand what factors would predict who might be most likely to use these new media to share and get product information in a contemporary context, and thus update the literature. To ground our study, as indicated, we utilized the unified theory of acceptance and use of technology or UTAUT (Venkatesh et al., 2003), adapted to fit with non-work related and discretionary technology use. In so doing, we contribute to the literature in at least four important ways: (1) We update the literature on technology use by examining “smart device” technologies and “social media” concurrently thereby contrasting outcome measures, (2) we provoke a “new look” at previously asserted factors associated with discretionary use of these new technology media for commercial purposes using the UTAUT, (3) we challenge the notion that the factors asserted in the UTAUT uniformly predicts a single dependent construct, and (4) although not formally hypothesized, we indicate from post hoc analyses that gender and age may not play significant roles in technology use in certain contexts as has been asserted in the literature.
