The Technology Acceptance Model (TAM) is an [information systems] theory that models how users come to accept and use a technology. The model suggests that when users are presented with a new software package, a number of factors influence their decision about how and when they will use it, notably:
o Perceived usefulness (PU)
“The degree to which a person believes that using a particular system would enhance his or her job performance”.
By Fred Davis
o Perceived ease-of-use (EOU)
“The degree to which a person believes that using a particular system would be free from effort”.
By Fred Davis
The technology acceptance model is one of the most influential extensions of Ajzen and Fishbein’s theory of reasoned action (TRA) in the literature. It was developed by Fred Davis and Richard Bagozzi. TAM replaces many of TRA’s attitude measures with the two technology acceptance measures, ease of use, and usefulness. TRA and TAM, both of which have strong behavioral elements, assume that when someone forms an intention to act, that they will be free to act without limitation. In the real world there will be many constraints, such as limited ability, time constraints, environmental or organizational limits, or unconscious habits which will limit the freedom to act.
Theory of Reasoned Action
TRA posits that individual behavior is driven by behavioral intentions where behavioral intentions are a function of an individual’s attitude toward the behavior and subjective norms surrounding the performance of the behavior.
Attitude toward the behavior is defined as the individual’s positive or negative feelings about performing a behavior. It is determined through an assessment of one’s beliefs regarding the consequences arising from a behavior and an evaluation of the desirability of these consequences. Formally, overall attitude can be assessed as the sum of the individual consequence x desirability assessments for all expected consequences of the behavior.
Subjective norm is defined as an individual’s perception of whether people important to the individual think the behavior should be performed. The contribution of the opinion of any given referent is weighted by the motivation that an individual has to comply with the wishes of that referent. Hence, overall subjective norm can be expressed as the sum of the individual perception x motivation assessments for all relevant referents.
Algebraically TRA can be represented as B ≈ BI = w1AB + w2SN where B is behavior, BI is behavioral intention, AB is attitude toward behavior, SN is subjective norm, and w1 and w2 are weights representing the importance of each term.
The model has some limitations including a significant risk of confounding between attitudes and norms since attitudes can often be reframed as norms and vice versa. A second limitation is the assumption that when someone forms an intention to act, they will be free to act without limitation. In practice, constraints such as limited ability, time, environmental or organizational limits, and unconscious habits will limit the freedom to act. The theory of planned behavior (TPB) attempts to resolve this limitation.
Theory of Planned Behavior
TPB posits that individual behavior is driven by behavioral intentions where behavioral intentions are a function of an individual’s attitude toward the behavior, the subjective norms surrounding the performance of the behavior, and the individual’s perception of the ease with which the behavior can be performed (behavioral control).
Behavioral control is defined as one’s perception of the difficulty of performing a behavior. TPB views the control that people have over their behavior as lying on a continuum from behaviors that are easily performed to those requiring considerable effort, resources, etc.
Although Ajzen has suggested that the link between behavior and behavioral control outlined in the model should be between behavior and actual behavioral control rather than perceived behavioral control, the difficulty of assessing actual control has led to the use of perceived control as a proxy.
Unified Theory of Acceptance and use of Technology
The UTAUT aims to explain user intentions to use an IS and subsequent usage behavior. The theory holds that four key constructs (performance expectancy, effort expectancy, social influence, and facilitating conditions) are direct determinants of usage intention and behavior. Gender, age, experience, and voluntaries of use are posited to mediate the impact of the four key constructs on usage intention and behavior. The theory was developed through a review and consolidation of the constructs of eight models that earlier research had employed to explain IS usage behavior (theory of reasoned action, technology acceptance model, and motivational model, theory of planned behavior, a combined theory of planned behavior/technology acceptance model, model of PC utilization, innovation diffusion theory, and social cognitive theory). Subsequent validation of UTAUT in a longitudinal study found it to account for 70% of the variance in usage intention.
Conclusion
The recent development of information technology applications that target highly specialized individual professionals, such as physicians and lawyers, has proliferated substantially. Considering the rapid growth of these innovative technology applications that target individual professionals, it is important to examine the extent to which existing theories can explain or predict their technology acceptance. In this vein, the current study represents a conceptual replication of some previous model comparison by re-examining prevalent theoretical models in a healthcare setting that involves different users and technologies. Specifically, this study empirically tests the applicability of three theoretical models: the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and a decomposed TPB model that is potentially adequate for the targeted professional context. Our investigative focus is the extent to which each model can explain physicians’ acceptance of telemedicine technology.