Technology acceptance model

Acronym
TAM

Alternate name(s)
N/A

Main dependent construct(s)/factor(s)
Behavioral intention to use, System usage

Main independent construct(s)/factor(s)
Perceived usefulness, Perceived ease of use

Concise description of theory
TAM is an adaptation of the Theory of Reasoned Action (TRA) to the field of IS. TAM posits that perceived usefulness and perceived ease of use determine an individual's intention to use a system with intention to use serving as a mediator of actual system use. Perceived usefulness is also seen as being directly impacted by perceived ease of use. Researchers have simplified TAM by removing the attitude construct found in TRA from the current specification (Venkatesh et. al., 2003). Attempts to extend TAM have generally taken one of three approaches: by introducing factors from related models, by introducing additional or alternative belief factors, and by examining antecedents and moderators of perceived usefulness and perceived ease of use (Wixom and Todd, 2005).

TRA and TAM, both of which have strong behavioural elements, assume that when someone forms an intention to act, that they will be free to act without limitation. In practice constraints such as limited ability, time, environmental or organisational limits, and unconscious habits will limit the freedom to act.

Originating author(s)
Davis (1986); Davis (1989)

Seminal articles
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. (Doctoral dissertation, Sloan School of Management, Massachusetts Institute of Technology).

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.

Originating area
Information Systems, Technology Adoption

Level of analysis
Individual

IS articles that use the theory
Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information: A replication. MIS Quarterly, 16(2), 227-247.

Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision Sciences, 30(2), 361-391.

Al-Gahtani, S. (2001). The applicability of TAM outside north america: An empirical test in the united kingdom. Information Resources Management Journal, 14(3), 37-46.

Amoako-Gyampah, K., & Salam, A. F. (2004). An extension of the technology acceptance model in an ERP implementation environment. Information & Management, 41(6), 731-745.

Brosnan, M. J. (1999). Modeling technophobia: A case for word processing. Computers in Human Behavior, 15(2), 105-121.

Brown, S. A., Massey, A. P., Montoya-Weiss, M. M., & Burkman, J. R. (2002). Do I really have to? user acceptance of mandated technology. European Journal of Information Systems, 11(4), 283-295.

Chan, S., & Lu, M. (2004). Understanding internet banking adoption and use behavior: A hong kong perspective. Journal of Global Information Management, 12(3), 21-43.

Chau, P. K. Y. (1996). An empirical assessment of a modified technology acceptance model. Journal of Management Information Systems, 13(2), 185-204.

Chau, P. Y. K., & Hu, P. J. (2002). Investigating healthcare professionals' decisions to accept telemedicine technology: An empirical test of competing theories. Information & Management, 39(4), 297-311.

Chau, P. Y. K., & Hu, P. J. (2001). Information technology acceptance by individual professionals: A model comparison approach. Decision Sciences, 32(4), 699-719.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.

Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. (Doctoral dissertation, Sloan School of Management, Massachusetts Institute of Technology).

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.

Devaraj, S., Fan, M., & Kohli, R. (2002). Antecedents of b2C channel satisfaction and preference: Validation e-commerce metrics. Information Systems Research, 13(3), 316-333.

Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task-technology fit constructs. Information & Management, 36(1), 9-21.

Elwood, S., Changchit, C. & Cutshall, R. (2006). Investigating students' perceptions on laptop initiative in higher education: An extension of the technology acceptance model. Campus Wide Information Systems, 23(5), 336-349.

Gefen, D. (2003). TAM or just plain habit: A look at experienced online shoppers. Journal of End User Computing, 15(3), 1-13.

Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51-90.

Gefen, D., & Straub, D. W. (2000). The relative importance of perceived ease of use in IS adoption: A study of E-commerce adoption. Journal of the Association for Information Systems, 1(8), 1-28.

Gefen, D., & Straub, D. W. (1997). Gender differences in the perception and use of E-mail: An extension to the technology acceptance model. MIS Quarterly, 21(4), 389-400.

Gentry, L., & Calantone, R. (2002). A comparison of three models to explain shop-bot use on the web. Psychology & Marketing, 19(11), 945-955.

Gong, M., Xu, Y., & Yu, Y. (2004). An enhanced technology acceptance model for web-based learning. Journal of Information Systems Education, 15(4), 365-374.

Hsu, C. L. and Lin, J. C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation, Information & Management, 45, 65-74.

Hsu, C. L. and Lu, H. P. (2007). Consumer behavior in on-line game communities: a motivational factor perspective Computers in Human Behavior, 23, 1642-1659.

Hsu, C. L. and Lu, H. P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience, Information & Management, 41(7), 853-868.

Igbaria, M., Guimaraes, T., & Davis, G. B. (1995). Testing the determinants of microcomputer usage via a structural equation model. Journal of Management Information Systems, 11(4), 87-114.

Igbaria, M., Zinatelli, N., Cragg, P., & Cavaye, A. L. M. (1997). Personal computing acceptance factors in small firms: A structural equation model. MIS Quarterly, 21(3), 279-305.

Jackson, C. M., Chow, S., & Leitch, R. A. (1997). Toward an understanding of the behavioral intention to use an information system. Decision Sciences, 28(2), 357-389.

Kamel, S., & Hassan, A. (2003). Assessing the introduction of electronic banking in egypt using the technology acceptance model. Annals of Cases on Information Technology, 5, 1-25.

Kamis, A. and Stohr, E. (2006), Parametric Search Engines: What Makes them Effective when Shopping Online for Differentiated Products? Information & Management, 43(7): 904-918.

Kim, S. S., & Malhotra, N. K. (2005). A longitudinal model of continued IS use: An integrative view of four mechanisms underlying postadoption phenomena. Management Science, 51(5), 741-755.

Klopping, I. M., & McKinney, E. (2004). Extending the technology acceptance model and the task-technology fit model to consumer E-commerce. Information Technology, Learning, and Performance Journal, 22(1), 35-48.

Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205-223.

Lederer, A. L., Maupin, D. J., Sena, M. P., & Zhuang, Y. (2000). The technology acceptance model and the world wide web. Decision Support Systems, 29(3), 269-282.

Lim, J. (2003). A conceptual framework on the adoption of negotiation support systems. Information and Software Technology, 45(8), 469-477.

Lu, H., Hsu, C., & Hsu, H. (2005). An empirical study of the effect of perceived risk upon intention to use online applications. Information Management & Computer Security, 13(2/3), 106-120.

Lucas, H. C.,Jr, & Spitler, V. K. (1999). Technology use and performance: A field study of broker workstations. Decision Sciences, 30(2), 291-311.

Ma, Q., & Liu, L. (2004). The technology acceptance model: A meta-analysis of empirical findings. Journal of Organizational and End User Computing, 16(1), 59-72.

Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173-191.

McCloskey, D. (2003). Evaluating electronic commerce acceptance with the technology acceptance model. The Journal of Computer Information Systems, 44(2), 49-57.

McCoy, S., Everard, A., & Jones, B. M. (2005). An examination of the technology acceptance model in uruguay and the US: A focus on culture. Journal of Global Information Technology Management, 8(2), 27-45.

Ndubisi, N. O., Gupta, O. K., & Ndubisi, G. C. (2005). The moguls' model of computing: Integrating the moderating impact of users' persona into the technology acceptance model. Journal of Global Information Technology Management, 8(1), 27-47.

Ndubisi, N. O., & Jantan, M. (2003). Evaluating IS usage in malaysian small and medium-sized firms using the technology acceptance model. Logistics Information Management, 16(6), 440-450.

Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: An extension of the technology acceptance model. Internet Research, 14(3), 224-235.

Plouffe, C. R., Hulland, J. S., & Vandenbosch, M. (2001). Research report: Richness versus parsimony in modeling technology adoption decisions - understanding merchant adoption of a smart card-based payment system. Information Systems Research, 12(2), 208-222.

Riemenschneider, C. K., & Hardgrave, B. C. (2001). Explaining software development tool use with the technology acceptance model. The Journal of Computer Information Systems, 41(4), 1-8.

Riemenschneider, C. K., Harrison, D. A., & Mykytn, P. P.,Jr. (2003). Understanding IT adoption decisions in small business: Integrating current theories. Information & Management, 40(4), 269-285.

Roberts, P., & Henderson, R. (2000). Information technology acceptance in a sample of government employees: A test of the technology acceptance model. Interacting with Computers, 12(5), 427-443.

Shih, H. (2004). Extended technology acceptance model of internet utilization behavior. Information & Management, 41(6), 719-729.

Spacey, R., Goulding, A., & Murray, I. (2004). Exploring the attitudes of public library staff to the internet using the TAM. Journal of Documentation, 60(5), 550-564.

Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Management Science, 42(1), 85-92.

Szajna, B. (1994). Software evaluation and choice: Predictive validation of the technology acceptance instrument. MIS Quarterly, 18(3), 319-324. Taylor, S., & Todd, P. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly, 19(4), 561-570.

Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.

Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365.

Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481.

Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for dirrections? gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.

Venkatesh, V., Speier, C., & Morris, M. G. (2002). User acceptance enablers in individual decision making about technology: Toward an integrated model. Decision Sciences, 33(2), 297-316.

Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: The case for an augmented technology acceptance model. Information & Management, 41(6), 747-762.

Wang, W., & Benbasat, I. (2005). Trust in and Adoption of Online Recommendation Agents. Journal of the Association for Information Systems, 6(3), 72-101.

Wang, C., Hsu, Y., & Fang, W. (2004). Acceptance of technology with network externalities: An empirical study of internet instant messaging services. JITTA : Journal of Information Technology Theory and Application, 6(4), 15-28.

Wang, Y., Wang, Y., Lin, H., & Tang, T. (2003). Determinants of user acceptance of internet banking: An empirical study. International Journal of Service Industry Management, 14(5), 501-519.

Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85-102.

Yu, J. L. C., Liu, C., & Yao, J. E. (2003). Technology acceptance model for wireless internet. Internet Research, 13(3), 206-222.

Links from this theory to other theories
Theory of planned behavior, Theory of reasoned action, Unified theory of acceptance and use of technology, Delone and McLean IS success model

Original Contributor(s)
Brent Furneaux Please feel free to make modifications to this site. In order to do so, you must register. Return to Theories Used in IS Research