An Empirical Assessment of a Modified Technology Acceptance Model

Abstract:

The technology acceptance model (TAM) is one of the most influential research models in studies of the determinants of information systems/information technology (IS/IT) acceptance. In TAM, perceived usefulness and perceived ease of use are hypothesized and empirically supported as fundamental determinants of user acceptance of a given IS/IT. A review of the IS and psychology literature, however, suggests that perceived usefulness can be of two distinct types: near-term usefulness and long-term usefulness. This paper reviews the concept of perceived usefulness and modifies TAM to include the two types of perceived usefulness. Data collected from nearly 285 administrative/clerical staff in a large organization were tested against the modified model using the structural equation modeling approach. The results of the study showed that, even though perceived near-term usefulness had the most significant influence on the behavioral intention to use a technology, perceived long-term usefulness also exerted a positive, though lesser, impact. No significant, direct relationship was found between ease of use and behavioral intention to use a technology. Implications of the findings and future research areas are discussed.

Key Words and Phrases:

• perceived ease of information systems use
• perceived usefulness of information systems
• structural equation modeling
• technology acceptance model

Additional information

Notes on contributors

Patrick Y.K. Chau

Patrick Y.K. Chau is an Assistant Professor of Information and Systems Management at the Hong Kong University of Science and Technology. He received his Ph.D. in business administration from the Western Business School, University of Western Ontario. His research interests include decision support systems, visual interactive simulation, and IS/IT adoption and implementation. He has published papers in Journal of the Operational Research Society; European Journal of Information Systems, Information and Management, INFOR, Journal of Decision Systems, International Transactions in Operational Research, Information and Decision Technologies, Journal of Information Science, and other journals.