How do TAM and UTAUT differ?

TAM is a parsimonious model focused on two core beliefs, perceived usefulness and ease of use; UTAUT integrates TAM with several other theories and adds social influence, facilitating conditions and moderators.

Does the technology acceptance model apply to consumers?

It was built to explain use of workplace systems in organizations, but extensions such as UTAUT2 are widely used to study consumer adoption of mobile apps, online shopping and similar technologies.

Technology Acceptance Model

💼 Business By CampusDown Wiki Editorial Team Last updated October 26, 2026

The technology acceptance model (TAM) is a leading information-systems theory holding that whether people adopt a new information technology depends mainly on its perceived usefulness and its perceived ease of use.

Contents

1. Origins and basic structure
2. Extensions: TAM2, UTAUT, TAM3
3. Assessment and critiques
4. FAQ
5. References

Origins and basic structure

Fred Davis proposed the technology acceptance model in his 1986 MIT doctoral thesis, and his 1989 MIS Quarterly paper made it widely known. Its roots lie in Fishbein and Ajzen's (1975) theory of reasoned action, in which attitudes and subjective norms predict behavior through intentions. Davis simplified this for information technology: two beliefs, perceived usefulness (PU), that the technology will improve one's performance, and perceived ease of use (PEOU), that using it will be free of effort, shape attitudes and intentions that lead to actual use. Ease of use also affects usefulness. Davis, Bagozzi and Warshaw (1989) tracked MBA students' use of a word processor and showed TAM was more parsimonious than the theory of reasoned action with similar explanatory power.

Extensions: TAM2, UTAUT, TAM3

Venkatesh and Davis's (2000) TAM2 added social and cognitive determinants of usefulness such as subjective norm, image, job relevance and output quality. Venkatesh et al. (2003) proposed UTAUT, unifying eight models including TAM, the theory of planned behavior and Rogers's diffusion of innovations; its core constructs are performance expectancy, effort expectancy, social influence and facilitating conditions, moderated by gender, age, experience and voluntariness. Venkatesh and Bala's (2008) TAM3 detailed the determinants of ease of use, and UTAUT2 (Venkatesh et al., 2012) adapted the model to consumers by adding hedonic motivation, price value and habit. These models are used widely to study e-commerce, mobile banking, online learning, health information systems and, recently, adoption of generative AI tools.

Assessment and critiques

King and He's (2006) meta-analysis of 88 studies found perceived usefulness to be a strong predictor of intention, with ease of use acting mostly indirectly through usefulness. Critics are numerous. Bagozzi (2007) called for a "paradigm shift," arguing TAM is overly simple and neglects the gap between intention and behavior and the roles of goals and emotions. Benbasat and Barki (2007) argued that the proliferation of variants added variables without theoretical progress and still said little about how to design systems that people find useful. Reliance on self-report surveys rather than measures of actual use is a frequent methodological concern. Even so, TAM remains one of the most cited starting points for explaining technology adoption.

FAQ

How do TAM and UTAUT differ?: TAM is a parsimonious model focused on two core beliefs, perceived usefulness and ease of use; UTAUT integrates TAM with several other theories and adds social influence, facilitating conditions and moderators.
Does the technology acceptance model apply to consumers?: It was built to explain use of workplace systems in organizations, but extensions such as UTAUT2 are widely used to study consumer adoption of mobile apps, online shopping and similar technologies.

Sources reviewed: 2026-10-26

References

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
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.
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior. Reading, MA: Addison-Wesley.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204.
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., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315.
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending UTAUT. MIS Quarterly, 36(1), 157–178.
Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), 244–254.
King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & Management, 43(6), 740–755.
Benbasat, I., & Barki, H. (2007). Quo vadis, TAM? Journal of the Association for Information Systems, 8(4), 211–218.
Rogers, E. M. (1962). Diffusion of Innovations. New York: Free Press.

Reports and materials that use this theory (Korean)

There are no materials dedicated to this theory yet, but you can search related reports in the CampusDown library (Korean).

Find more reports · Search '기술수용모델' on CampusDown →

Theory of Reasoned ActionFishbein and Ajzen's theory of reasoned action: attitude and subjective norm as determinants of intention, the expectancy-value calculation, the theory of planned behavior with perceived behavioral control, applications and limits.🧠 Psychology Diffusion of InnovationsDiffusion of innovations explained: Everett Rogers' theory, the five adopter categories and their percentages, the five attributes that speed adoption, the innovation-decision process, the S-curve, the chasm, and key critiques.👥 Sociology Disruptive innovationWhat disruptive innovation is, Clayton Christensen’s Innovator’s Dilemma, how it differs from sustaining innovation, low-end and new-market disruption, classic examples, the Uber misconception and criticisms.💼 Business Network Effects and Platform EconomicsNetwork effects and platform economics explained: direct and indirect network effects, critical mass and tipping, two-sided market pricing, multi-homing and the platform regulation debate, based on the original papers.📈 Economics AI Search Algorithms: A* and MinimaxAI search algorithms explained: state-space search, breadth-first and depth-first search, Dijkstra, heuristics and A* (admissibility, consistency), game trees, minimax and alpha-beta pruning, based on the original papers.⚙️ Engineering & Technology Moore's LawWhat Moore's law is, Gordon Moore's 1965 paper and 1975 revision, how Dennard scaling sustained it, its economic impact on computing costs and productivity, the slowdown since the mid-2000s, and debates about computing after Moore.⚙️ Engineering & Technology

Latest ArticlesView all ›

New guides for college study and assignments (Korean)

This article was last updated on October 26, 2026. It is based on widely recognized original works and textbooks; when citing it in a paper, please check the original sources listed in the references.