A systematic analysis of acceptance of computer technology was conducted to identify variables that would provide insight to understanding technology acceptance. This led to a development of a comprehensive qualitative model that captures the individual and the organizational user characteristics that influence the acceptance of computer technology. This model suggests that designers must be mindful of the role that sociological and organizational variables play in technology acceptance. Such factors go beyond basic usability issues in the design process. Attention to these variables may increase the acceptance and therefore the diffusion of new computer technologies.
Get full access to this article
View all access options for this article.
References
1.
AgarwalR.PrasadJ. (1999). Are individual differences germane to the acceptance of new information technologies?Decision Sciences, 30, 361–391.
2.
Amoako-GyampahK.SalamA. F. (2004). An extension of the technology acceptance model in an ERP implementation environment. Information & Management, 41, 731–745.
3.
Amoako-GyampahK.SalamA. F. (2004). An extension of the technology acceptance model in an ERP implementation environment. Information & Management, 41(6), 731–745.
4.
BaldridgeJ. V.BurnhamR. A. (1975). Organizational innovation: Individual, organizational, and environmental impacts. Administrative Science Quarterly, 20, 165.
5.
CaineK. E.O'BrienM. A.ParkS.RogersW. A.FiskA. D.Van IttersumK.CaparM.ParsonsL. J. (In Press). Understanding acceptance of high technology products: 50 years of research. Proceedings of the Human Factors and Ergonomics Society 50th Annual Meeting. Santa Monica, CA: Human Factors and Ergonomics Society.
6.
CarrollJ. M. (2002). Human-Computer Interaction, the Past and the Present. In CarrollJ.M. (Eds.), Human-Computer Interaction in the New Millennium. New York: Addison-Wesley.
7.
ChaoG. T.KozlowskiS. W. J. (1986). Employee perceptions on the implementation of robotic manufacturing technology. Journal of Applied Psychology, 71, 70–76.
8.
DavisF. D.Jr. (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.
9.
FishbeinM.AjzenI. (1975). Beliefs, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley Publishing.
10.
FurnasG. (2000). Future Design Mindful of the MoRAS. Human-Computer Interaction, 15(2/3).
11.
HarrisonD. A.MykytynP. P.Jr.RiemenschneiderC. K. (1997). Executive decisions about adoption of information technology in small business: Theory and empirical tests. Information Systems Research, 8, 171.
12.
HsuM. H.ChiuC. M. (2004). Predicting electronic service continuance with a decomposed theory of planned behaviour. Behaviour & Information Technology, 23(5), 359–373.
13.
MathiesonK. (1991). Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior. Information Systems Research, 2(3), 173.
14.
MaxwellK. (2002). The Maturation of HCI: Moving Beyond Usability toward Holistic Interaction. In CarrollJ.M. (Eds.), Human-Computer Interaction in the New Millennium (191–209). New York: Addison-Wesley.
15.
MorrisM. G.DillonA. (1997). The Influence of User Perceptions on Software Utilization: Application and Evaluation of a Theoretical Model of Technology Acceptance. IEEE Software, 14(4), 58.
16.
RobertsonT. S.GatignonH. (1986). Competitive Effects on Technology Diffusion. Journal of Marketing, 50(3).
17.
VenkateshV.DavisF. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186.
