Understanding Technology Adoption: Theory and Future Directions for Informal Learning

Jun. 15, 2009

Source: Review of Educational Research,Vol. 79, Iss. 2; p. 625-649. (June 2009).
(Reviewed by the Portal Team)

How and why individuals adopt innovations has motivated a great deal of research. This paper examines individuals' computing adoption processes through the lenses of three adoption theories: Rogers's innovation diffusion theory, the Concerns-Based Adoption Model, the Technology Acceptance Model, and the United Theory of Acceptance and Use of Technology. Therefore, the question this paper seeks to understand is this: Can any one of these theories (or a combination of theories) bring meaning and understanding to why an individual chooses to adopt or reject a particular innovation (and in particular a technology-based innovation)?

Rogers's Innovation Diffusion Theory

In IDT, the adoption process is inseparable from the diffusion process. Diffusion is composed of individual adoptions. Diffusion describes the adoption process across a population over time. The adoption decision process describes five stages that individuals go through during their evaluation of an innovation (Rogers, 1995).

Hall's CBAM

By approaching adoption through the eyes of the adoptees, the CBAM provides a developmental perspective on how an individual's concerns influence his or her integration of an innovation. The CBAM was developed based on six explicit assumptions: Change is a process, not an event; Change is accomplished by individuals; Change is a highly personal experience; Change involves developmental growth; and Change is best understood in operational terms.
The focus of facilitation should be on individuals, innovations, and context
(Hord, Rutherford, Huling- Austin, & Hall, 1987).

Technology Acceptance Model and the United Theory of Acceptance and Use of Technology

The TAM F. Davis (1989) examined how an individual's perceptions of a technology innovation affect the eventual use of that technology. Davis identified two perceived characteristics about an innovation that he believed to predict the usage outcomes. The first is the perceived ease of use; and the second characteristic is perceived usefulness.

Ultimately, the study on the development of the UTAUT suggested that performance expectancy, effort expectancy, and social influence for predicting behavioral intention in turn predicted usage behaviors. Gender, age, experience, and the perception of voluntariness of change were all moderating factors for intention (Venkatesh, 2000).
Incorporating all three models, this review suggests three conclusions about technology adoption and diffusion theories: (a) technology adoption is a complex, inherently social, developmental process; (b) individuals construct unique (but malleable) perceptions of technology that influence the adoption process; and (c) successfully facilitating a technology adoption needs to address cognitive, emotional, and contextual concerns. This paper also focuses specific attention on adoption theory outside of a formal organization and the implications of adoption theory on informal environments.

Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319-340.
Hall, G. E. (1979). The concerns-based approach to facilitating change. Educational Horizons, 57, 202-208.
Hord, S. M., Rutherford, W. L., Huling-Austin, L., & Hall, G. E. (1987). Taking charge of change. Alexandria, VA: Association for Supervision and Curriculum Development.
Rogers, E. (1995). Diffusion of innovations (4th ed.). New York: Free Press.
Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating perceived behavioral control, computer anxiety and enjoyment into the technology acceptance model. Information Systems Research, 11, 342-365.

Updated: Jul. 01, 2009