The originating article of the Unified Theory of Acceptance and Use of Technology (UTAUT) has been cited by a large number of studies. However, a detailed examination of such citations revealed that only small proportion (43 articles) of these citations actually utilized the theory or its constructs in their empirical research for examining IS/IT related issues. In order to examine whether the theory is performing consistently well across various studies, this research aims to undertake a statistical meta-analysis of findings reported in 43 published studies that have actually utilized UTAUT or its constructs in their empirical research. Findings reveal the underperformance of theory in subsequent studies in comparison to the performance of UTAUT reported in the originating article. The limitations experienced while conducting the meta-analysis, recommendations, and the future scope for the further research in this area have also been briefly explained in concluding section.


Adoption Diffusion UTAUT TAM Meta-analysis Information Systems 


  1. Abu-Shanab, E., Pearson, M.: Internet Banking in Jordan: An Arabic Instrument Validation Process. International Arab Journal of Information Technology 6(3), 235–244 (2009)Google Scholar
  2. Aggelidis, V.P., Chatzoglou, P.D.: Using a modified technology acceptance model in hospitals. International Journal of Medical Informatics 78(2), 115–126 (2009)CrossRefGoogle Scholar
  3. Alapetite, A., Andersen, H.B., Hertzum, M.: Acceptance of speech recognition by physicians: A survey of expectations, experiences, and social influence. International Journal of Human-Computer Studies 67(1), 6–49 (2009)CrossRefGoogle Scholar
  4. Al-Gahtani, S.S., Hubona, G.S., Wang, J.: Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT. Information & Management 44(8), 681–691 (2007)CrossRefGoogle Scholar
  5. Baron, S., Patterson, A., Harris, K.: Beyond technology acceptance: understanding consumer practice. International Journal of Service Industry Management 17(2), 111–135 (2006)CrossRefGoogle Scholar
  6. Borenstein, M.: Effect Sizes for Continuous Data. In: Cooper, H., Hedges, L.V., Valentine, J.C. (eds.) The Handbook of Research Synthesis and Meta-Analysis. Russell Sage Foundation, New York (2009)Google Scholar
  7. Chang, I.C., Hwang, H.G., Hung, W.F., Li, Y.C.: Physicians’ acceptance of pharmacokinetics-based clinical decision support systems. Expert Systems with Applications 33(2), 296–303 (2007)CrossRefGoogle Scholar
  8. Chiu, C.M., Wang, E.T.G.: Understanding Web-based learning continuance intention: The role of subjective task value. Information & Management 45(3), 194–201 (2008)CrossRefGoogle Scholar
  9. Chiu, C.M., Huang, H.Y., Yen, C.H.: Antecedents of trust in online auctions. Electronic Commerce Research and Applications 9(2), 148–159 (2010)CrossRefGoogle Scholar
  10. Curtis, L., Edwards, C., Fraser, K.L., Gudelsky, S., Holmquist, J., Thornton, K.: Adoption of social media for public relations by non-profit organizations. Public Relations Review 36(1), 90–92 (2010)CrossRefGoogle Scholar
  11. Dadayan, L., and Ferro, E. 2005. “When technology meets the mind: A comparative study of the technology acceptance model,” In M. A. Wimmer, R. Traunmuller, A. Gronlund & K. V. Andersen (Eds.), Electronic Government, Proceedings (3591), pp. 137-144. CrossRefGoogle Scholar
  12. Deng, X., Doll, W.J., Hendrickson, A.R., Scazzero, J.A.: A multi-group analysis of structural invariance: an illustration using technology acceptance model. Information & Management 42(5), 745–759 (2005)CrossRefGoogle Scholar
  13. Duyck, P., Pynoo, B., Devolder, P., Voet, T., Adang, L., Ovaere, D.: Monitoring the PACS Implementation Process in Large University Hospital-Discrepancies between Radiologists and Physicians. Journal of Digital Imaging 23(1), 73–80 (2010)CrossRefGoogle Scholar
  14. Field, A.P.: Meta-analysis of correlation coefficients: a Monte Carlo comparison of fixed- and random-effects methods. Psychological Methods 6(2), 161–180 (2001)CrossRefGoogle Scholar
  15. Gupta, B., Dasgupta, S., Gupta, A.: Adoption of ICT in a government organization in a developing country: An empirical study. Journal of Strategic Information Systems 17(2), 140–154 (2008)CrossRefGoogle Scholar
  16. Hausenblas, H.A., Carron, A.V., Mack, D.V.: Application of the theories of reasoned action and planned behavior to exercise behavior: A meta-analysis. Journal of Sport & Exercise Psychology 19(1), 36–51 (1997)Google Scholar
  17. He, D.H., Lu, Y.B., Alfred, U.: An integrated framework for mobile business acceptance. Alfred Univ., Alfred (2007)Google Scholar
  18. Hung, Y.H., Wang, Y.S., Chou, S.C.T.: User Acceptance of E-Government Services. Natl Sun Yat-Sen Univ., Kaohsiung (2007)Google Scholar
  19. Huser, V., Narus, S.P., Rocha, R.A.: Evaluation of a flowchart-based EHR query system: A case study of RetroGuide. Journal of Biomedical Informatics 43(1), 41–50 (2010)CrossRefGoogle Scholar
  20. Jong, D., Wang, T.S.: Student Acceptance of Web-based Learning System. Acad. Publ., Oulu (2009)Google Scholar
  21. Kijsanayotin, B., Pannarunothai, S., Speedie, S.M.: Factors influencing health information technology adoption in Thailand’s community health centers: Applying the UTAUT model. International Journal of Medical Informatics 78(6), 404–416 (2009)CrossRefGoogle Scholar
  22. King, W.R., He, J.: A meta-analysis of the technology acceptance model. Information & Management 43, 740–755 (2006)CrossRefGoogle Scholar
  23. Laumer, S., Eckhardt, A., Trunk, N.: Do as your parents say?-Analyzing IT adoption influencing factors for full and under age applicants. Information Systems Frontiers 12(2), 169–183 (2010)CrossRefGoogle Scholar
  24. Lee, Y., Kozar, K.A., Larsen, K.R.T.: The Technology Acceptance Model: Past, Present, and Future. Communications of the Association for Information System 12, 752–780 (2003)Google Scholar
  25. Legris, P., Ingham, J., Collerette, P.: Why do people use information technology? A critical review of the technology acceptance model. Information & Management 40(3), 191–204 (2003)CrossRefGoogle Scholar
  26. Li, W.: Virtual knowledge sharing in a cross-cultural context. Journal of Knowledge Management 14(1), 38–50 (2010)CrossRefGoogle Scholar
  27. Lin, C.P., Anol, B.: Learning online social support: An investigation of network information technology based on UTAUT. Cyber Psychology & Behavior 11(3), 268–272 (2008)Google Scholar
  28. Loo, W.H., Yeow, P.H.P., Chong, S.C.: User acceptance of Malaysian government multipurpose smartcard applications. Government Information Quarterly 26(2), 358–367 (2009)CrossRefGoogle Scholar
  29. Luo, X., Li, H., Zhang, J., Shim, J.P.: Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services. Decision Support System 49(2), 222–234 (2010)CrossRefGoogle Scholar
  30. Ma, Q., Liu, L.: The technology acceptance model: a meta-analysis of empirical findings. Journal of Organizational and End User Computing 16(1), 59–72 (2004)CrossRefGoogle Scholar
  31. Nov, O., Ye, C.: Resistance to Change and the Adoption of Digital Libraries: An Integrative Model. Journal of the American Society for Information Science and Technology 60(8), 1702–1708 (2009)CrossRefGoogle Scholar
  32. Nunnaly, J.: Psychometric theory. McGraw-Hill, New York (1978)Google Scholar
  33. Santos, J.R.A.: Chronbach’s Alpha: A Tool for Assessing the Reliability of Scales. Journal of Extension 37(2), 1–5 (1999)Google Scholar
  34. Sapio, B., Turk, T., Cornacchia, M., Papa, F., Nicolo, E., Livi, S.: Building scenarios of digital television adoption: a pilot study. Technology Analysis & Strategic Management 22(1), 43–63 (2010)CrossRefGoogle Scholar
  35. Schaupp, L.C., Carter, L., McBride, M.E.: E-file adoption: A study of US taxpayers’ intentions. Computers in Human Behavior 26(4), 636–644 (2010)CrossRefGoogle Scholar
  36. Sheeran, P., Taylor, S.: Predicting Intentions to Use Condoms: A Meta-Analysis and Comparison of the Theories of Reasoned Action and Planned Behavior. Journal of Applied Social Psychology 29(8), 1624–1675 (1999)CrossRefGoogle Scholar
  37. Shin, D.H.: Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior 25(6), 1343–1354 (2009)CrossRefGoogle Scholar
  38. Tsai, Y.H., Lin, C.P., Chiu, C.K., Joe, S.W.: Understanding learning behavior using location and prior performance as moderators. Social Science Journal 46(4), 787–799 (2009)CrossRefGoogle Scholar
  39. van Biljon, J., Kotze, P.: Cultural Factors in a Mobile Phone Adoption and Usage Model. Journal of Universal Computer Science 14(16), 2650–2679 (2008)Google Scholar
  40. van Biljon, J., Renaud, K.: A Qualitative Study of the Applicability of Technology Acceptance Models to Senior Mobile Phone Users. In: Song, I.-Y., Piattini, M., Chen, Y.-P.P., Hartmann, S., Grandi, F., Trujillo, J., Opdahl, A.L., Ferri, F., Grifoni, P., Caschera, M.C., Rolland, C., Woo, C., Salinesi, C., Zimányi, E., Claramunt, C., Frasincar, F., Houben, G.-J., Thiran, P. (eds.) ER Workshops 2008. LNCS, vol. 5232, pp. 228–237. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  41. van Dijk, J., Peters, O., Ebbers, W.: Explaining the acceptance and use of government Internet services: A multivariate analysis of 2006 survey data in the Netherlands. Government Information Quarterly 25(3), 379–399 (2008)CrossRefGoogle Scholar
  42. Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: Toward a unified view. MIS Quarterly 27(3), 425–478 (2003)Google Scholar
  43. Wang, Y.S., Shih, Y.W.: Why do people use information kiosks? A validation of the Unified Theory of Acceptance and Use of Technology. Government Information Quarterly 26(1), 158–165 (2009)CrossRefGoogle Scholar
  44. Ye, C., Seo, D., Desouza, K.C., Sangareddy, S.P., Jha, S.: Influences of IT Substitutes and User Experience on Post-Adoption User Switching: An Empirical Investigation. Journal of the American Society for Information Science and Technology 59(13), 2115–2132 (2008)CrossRefGoogle Scholar
  45. YenYuen, Y., Yeow, P.H.P.: User Acceptance of Internet Banking Service in Malaysia. In: Cordeiro, J., Hammoudi, S., Filipe, J. (eds.) Web Information Systems and Technologies, vol. 18, pp. 295–306. Springer, Berlin (2009)CrossRefGoogle Scholar
  46. Yeow, P.H.P., Yuen, Y.Y., Tong, D.Y.K., Lim, N.: User acceptance of Online Banking Service in Australia. Int. Business Information Management Assoc-Ibima, Norristown (2008)Google Scholar
  47. Zhou, T., Lu, Y.B., Wang, B.: Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior 26(4), 760–767 (2010)CrossRefMathSciNetGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2011

Authors and Affiliations

  • Yogesh K. Dwivedi
    • 1
  • Nripendra P. Rana
    • 1
  • Hsin Chen
    • 2
  • Michael D. Williams
    • 1
  1. 1.School of Business & EconomicsSwansea UniversitySwanseaUK
  2. 2.Business Systems DepartmentUniversity of BedfordshireUK

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