Since the seminal Technology Acceptance Model (TAM) was introduced over two decades ago by Davis (Davis, 1989), the IS field has leveraged this parsimonious model in a myriad of
contexts (Hsieh & Wang, 2007; Legris, Ingham, & Collerette, 2003), including the Healthcare IT realm (Holden 2010). TAM and variants of TAM, such as the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh, Morris, Davis, & Davis, 2003) are individual level models which incorporate core antecedents such as perceived ease of use and perceived
usefulness of a technology to predict behavioral intention to use the technology. Typically, TAM and TAM derivatives have been used as a theoretical lens to evaluate the behavioral intention to adopt an IT just prior to the implementation phase, or alternatively by lean measures of actual use shortly after implementation. UTAUT confirms that the effects of ease of use are attenuated, or not significant, in periods after initial adoption (Venkatesh et al., 2003). Within the healthcare domain, usefulness remains a significant predictor of intention and use of technology, yet ease of use, even during the introduction phase, is not a significant antecedent (Chau & Hu, 2002;
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Holden & Karsh, 2010). As a result, the HIT context is an environment where empirical tests of even well-established IS theories can produce contradictory results.
While the impact of a technology on outcomes may produce the greatest variance immediately following implementation, accrued benefits to the organization rely on continued use after the shake down phase (Bhattacherjee, 2001). The implementation literature refers to this stage as Incorporation (Kwon & Zmud, 1987) or Routinization (Cooper & Zmud, 1990). Research
focused on Information Technology in a continued use environment has been limited, with the IS Continuance Model (Bhattacherjee, 2001) serving as an early example of a conceptual model for studying use in environments well after the shake down phase. The ISC model relies on
expectation confirmation theory (Oliver, 1980) from the consumer behavior literature, with Confirmation of expectations, and Satisfaction added to Perceived Usefulness (TAM) as antecedents to Continuance Intentions. Confirmation is defined as the perceived level of
congruence between expectations from use of a technology, to the actual performance, whereas Satisfaction is defined as users’ feelings about prior use (Bhattacherjee, 2001). In a continued use environment, Satisfaction with the IS was found as the primary predictor of IS Continuance Intention with Perceived Usefulness as a significant secondary antecedent, while Confirmation is the primary antecedent of Satisfaction. Studies suggest that hospitals in more advanced stages of HIT adoption derive a greater benefit (Agarwal et al., 2010; Borzekowski, 2009), which
highlights the relevance of HIT research in extended use environments.
Research has concentrated on use in binary terms, rather than understanding the nuanced use of advanced IT systems (Burton-Jones & Straub, 2006; Hsieh & Wang, 2007). Attempts to describe the nuanced use of an IS across users include Extended Use (Hsieh & Wang, 2007; Saga &
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Zmud, 1994), Effective Use (Pavlou, Dimoka, & Housel, 2008; Pavlou & El Sawy, 2006), Deep Structure Use (Burton-Jones & Straub, 2006; DeSanctis & Poole, 1994), and Rich Use (Burton- Jones & Straub 2006). Extended Use espouses the notion that over time, users incorporate an increasing array of the capabilities of an IT to support an increasingly comprehensive set of work tasks (Hsieh & Wang, 2007; Saga & Zmud, 1994). Deep Structure Use is defined as the use of key features of an Advanced IT that support the underlying structure of the task (Burton-Jones & Straub, 2006), whereas Very Rich Use such as Exploitive Use is described as the extent to which a user exploits the features of the technology to perform the task (Burton-Jones & Straub, 2006).
To conceptualize use in a contextually relevant manner, Burton-Jones & Straub (2006) suggest a two-staged approach, incorporating definition and selection. The definition stage requires that researchers provide an explicit definition of what constitutes system usage in their study and what are the associated underlying assumptions. During the selection stage, system usage is conceptualized and explicated in terms of its structure and function. Structure is formed through the elements of task, technology and users that are contextually relevant to the research study. Finally, function entails the selection of measures for each element of usage – the user, the task, and the technology, based on other constructs within the nomological network (Burton-Jones & Straub, 2006). By incorporating a structured approach to the conceptualization of use in a research study, researchers are more likely to uncover explanations for the use- performance relationships, particularly if rich and very rich measures of use are instituted (Burton-Jones & Straub, 2006).
Traditional lean measures attempt to capture use as a composite, without regard for the most relevant aspect of use in a specific context, whereas very rich measures incorporate the nature of
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the usage activity (Burton-Jones & Straub 2006).To date, there are few studies which attempt to describe according to Rich Use principles (Pavlou et al., 2008; Pavlou & El Sawy, 2006), perhaps due to the difficulties with identification when capturing a formative construct, when analysis is based on CBSEM techniques (Burton-Jones & Straub, 2006).
While we have learned a great deal about individual level use intentions, very few organizational studies of use incorporate group (Kane & Labianca, 2011), or firm level (Devaraj & Kohli, 2003) empirical analysis (Burton-Jones & Gallivan, 2008). Organizational research conclusions can often differ as a function of which level of analysis is emphasized (Burton-Jones & Gallivan, 2008; Klein, Dansereau, & Hall, 1994). This dissertation includes data collection at the
individual and group (team) level, with the level of analysis and theory building occurring at the team level. We find Deep Structure Use (DSU) as a suitable lens to study nuanced use at the team level in a contextually relevant manner. Given that there are no studies that we are aware of that incorporate Team DSU in a healthcare environment, research establishing this construct would contribute to both the IS and Health IT literature streams
While perceived usefulness and perceived ease of use have proven to be salient antecedents to lean measures of individual level behavior intention to adopt an IT, far fewer studies have investigated the antecedents of Rich measures of Use at the team or group level (Burton-Jones & Straub, 2006). In the following section, we suggest that Structuration and Adaptive Structuration Theory (AST) provide a particularly useful theoretical lens in the healthcare context, and that the AST constituents of Faithfulness of Appropriation and Consensus on Appropriation are
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