This paper studies the progress of the ‘Technology Acceptance Model’ and then goes on to evaluate it from a philosophy of science viewpoint. Technology Acceptance Model (TAM) was introduced in 1989 by Fred Davis to explain the user adoption or acceptance of Information Systems (IS). Based on Ajzen and Fishbein’s Theory of Reasoned Action, which is a psychological theory that explains behavior, TAM has its roots in cognitive psychology and assumes that an individual’s information systems acceptance is determined by two major variables:

• Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) The Technology Acceptance Model, version 1. (Davis 1989) The Technology Acceptance Model (TAM) is considered the most influential and commonly employed theory for describing an individual’s acceptance of information systems. During the past 23 years, the information systems community has considered TAM a parsimonious and powerful theory (Venkatesh and Davis, 2000). Further supporting the notion of TAM’s popularity, Venkatesh and Bala [2008] found that the first two TAM articles, by Davis [1989] and Davis et al. 1989] received 424 journal citations in the Social Science Citation Index (SSCI) by the beginning of 2000 and 698 journal citations by 2003. TAM has been applied to different technologies (e. g. word processors, workstations, WWW, telemedicine) under different situations (e. g. time, culture, geographies) and has undergone a series of empirical, statistical and meta-analysis. Currently, researchers in the IS field consider TAM one of the information systems fields’ own theories, and still put much effort into ongoing research using the theory.

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Evaluation of TAM using Philosophy of Science – Kuhnian View The Kuhnian view of philosophy of science accounts for scientific progress through the concept of a paradigm: the common terminology and basic theories of a scientific community. According to Kuhn, scientific research necessarily takes place within a paradigm, as within this paradigm, a scientist knows the facts that are relevant and can build on past research. Kuhn calls this period of operating with a paradigm as a period of normal science.

During "normal science”, research occurs within a paradigm, scientists are busy "puzzle solving", an activity conducted to "add to the scope and precision with which the paradigm can be applied". Normal science however, contains a mechanism that uncovers anomalies, inconsistencies within the paradigm. When the inconsistent details significantly threaten a paradigm, perhaps because they concern a topic of central importance, a crisis occurs and normal science comes to a halt. During a crisis, alternate paradigms are proposed, usually by scientists who are young or new to the field and thus more open-minded.

Slowly, one of the alternate paradigms triumphs over the competing paradigms marking a period of scientific revolution (Kuhn, 1970). Kuhn showed that scientific knowledge in this way is socially constructed, negotiated and evolving. TAM can essentially be viewed as a normal science as per Kuhn’s definition as, ever since its introduction in 1989, it has provided a basic construct for measuring the adoption of technology under different circumstances and has been evaluated, tested, applied and extended.

TAM has served as a paradigm for further scientific research and can also be demonstrated to satisfy the three normal foci for factual scientific investigation as per Kuhn [1970]. First, a paradigm has shown to be particularly revealing in solving a set of problems or determination of a significant fact in a large variety of situations. TAM has been very successful over the past 20 odd years in predicting acceptance of different technologies under different situations as studied by various researchers and practitioners.

TAM constructs of PU and PEOU have been vastly successful in predicting intentions to adopt a technology and some extensions of TAM have been able to predict actual usage as well (Szajna, 1996). Second normal focus of scientific investigation involves the matching of fact with theory. TAM has its roots in psychology and the technology adoption predictions are constantly matched with the vast theories of behavioral and cognitive psychology. Third and most important focus of scientific investigation is the articulation of theory.

It consists of empirical work undertaken to articulate the paradigm theory. TAM continues to be the focal point of a ariety of empirical studies and meta-analysis with growing number of researchers from the IS community that use TAM constructs to validate the model under different technology perspectives. Davis’ (1989) article has been cited widely and has also become the center of further modifications and adaptations (Venkatesh and Davis, 2000). Assessing the vast number of research articles that apply TAM, we can infer that there is a critical mass of information systems researchers that have accepted the postulates of the model as a paradigm and are conducting extended research under the umbrella of TAM as normal science.

A paradigm is also constituted by instruments, methods, and techniques that illustrate how to conduct research within the boundaries of the theory and how to emulate the success of the exemplary pieces of research. TAM exhibits this last condition in the multiple instruments available for collecting data and in the ways researchers use confirmatory statistical techniques. An IS researcher equipped with the theoretical model, the data collection instruments, and the right statistical package is ready to explore the beliefs related to the adoption and usage of almost every technology (Silva, 2007).

As in any developing normal science, overtime, anomalies surface questioning some of the postulates of the paradigm. TAM has also been faced with several such anomalies. For example, in the study conducted by Straub et al. , [1997], testing the technology acceptance model across three different countries, the results indicated that TAM held for both the U. S. and Switzerland, but not for Japan.

This suggested that the model may not predict technology use across all cultures. Another study by Lucas et al. [2000] studying the implementation of workstations and networks, showed that TAM and its extensions were weak predictors of the acceptance of a broker workstation. They concluded that variance models like TAM, combined with qualitative research, offer the best opportunity for understanding the implementation of modern information technology.

Some of the other anomalies were technology specific and were resolved by adding specific additional external variables. Overall, through this analysis, I feel it is reasonable to appreciate the iew of TAM as a Kuhnian paradigm inside which researchers and practitioners continue to conduct experiments and analysis to predict the adoption of various types of technology. The past 23 years have witnessed an expansion in the TAM variables to better explain the relation between technology and TAM constructs. However, it isn’t an unimaginable situation where severe anomalies force a scientific revolution challenging TAM and leading to a gestalt flip in the way technology acceptance is predicted in the future.