Examining the Impact of Training in the Unified Theory of Acceptance and Use of Technology

References

• Agarwal R, Prasad J, Zanino, MC. Training experiences and usage intentions: A field study of a graphical user interface. Int J Hum-Comput Stud. 1996;45(2):215–241.
   Web of Science ®Google Scholar
• Ajzen I. The theory of planned behavior. Organiz Behav Hum Decis Processes. 1991;50(2):179–211.
   Web of Science ®Google Scholar
• Alavi M, Carlson P. A review of MIS research and disciplinary development. J Manage Inf Syst. 1992;8(4):45–62.
   Google Scholar
• Alliger GM, Tannenbaum SI. A meta-analysis of the relations among training criteria. Personnel Psychol. 1997;50(2):341–358.
   Web of Science ®Google Scholar
• Bandura A. Social foundations of thought and action: A social cognitive theory. Englewood Cliffs (NJ): Prentice Hall; 1986.
   Google Scholar
• Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J Person Soc Psychol. 1986;51(6):1173–1182.
   PubMed Web of Science ®Google Scholar
• Bassi LJ, Benson G, Cheney S. The top ten trends. Training Dev. 1996;50:28–42.
   Google Scholar
• Benson-Armer R, Otto S, Webster G. Building capabilities for performance; 2015 [cited 2016 Aug 24]. Available from http://www.mckinsey.com/business-functions/organization/our-insights/building-capabilities-for-performance.
   Google Scholar
• Brancheau JC, Wetherbe JC. Key issues in information systems management. MIS Q. 1987;11(1):23–45.
   Web of Science ®Google Scholar
• Brancheau JC, Janz BD, Wetherbe JC. Key issues in information systems management: 1994–95 SIM Delphi Results. MIS Q. 1996;20(2):225–242.
   Web of Science ®Google Scholar
• Carifio J, Perla RJ. Ten common misunderstandings, misconceptions, persistent myths and urban legends. J Soc Sci. 2007;3(3):106–116.
   Google Scholar
• Carmines EG, Zeller RA. Reliability and Validity Assessment. Beverly Hills (CA): Sage Publications, Inc.; 1979.
   Google Scholar
• Chin WW, Marcolin BL, Newsted PR. A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo Simulation study and an electronic-mail emotion/adoption study. Inf Syst Res. 2003;14(2):189–217.
   Web of Science ®Google Scholar
• Colquitt JA, LePine JA, Noe RA. Toward an integrative theory of training motivation: A meta-analytic path analysis of 20 years of research. J Appl Psychol. 2000;85(5):678–707.
   PubMed Web of Science ®Google Scholar
• Dalcher D., Genus A. Avoiding IS/IT implementation failure. Technol Anal Strategic Manage. 2003;15(4):403–407.
   Web of Science ®Google Scholar
• Davis FD, Bagozzi RP, Warshaw PR. User acceptance of computer technology: A comparison of two theoretical models. Manage Sci. 1989;35(8):982–1003.
   Web of Science ®Google Scholar
• Dulebohn JH. Information technology implementation: The need for compensation system congruency. Adv Hum Perform Cognit Eng Res. 2003;3:153–185.
   Google Scholar
• Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Marketing Res. 1981;18(1):39–50.
   Web of Science ®Google Scholar
• George D, Mallery P. SPSS for Windows step by step: A simple guide and reference, 18.0 update (11th ed.), Boston (MA): Allyn and Bacon; 2010.
   Google Scholar
• Gist ME, Schwoerer C, Rosen B. Effects of alternative training methods on self-efficacy and performance in computer software. J Appl Psychol. 1989;74(6):884–891.
   Web of Science ®Google Scholar
• Glass GV, Peckham PD, Sanders JR. Consequences of failure to meet assumptions underlying the fixed effects analyses of variance and covariance. Rev Educ Res. 1972;42(3):237–288.
   Web of Science ®Google Scholar
• Goldfinch S. Pessimism, computer failure, and information systems development in the public sector. Public Administration Rev. 2007;67(5):917–929.
   Web of Science ®Google Scholar
• Hair JF, Hult GT, Ringle CM, Sarstedt M. A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks (CA): Sage Publications, Inc.; 2014.
   Google Scholar
• Hu PJ, Chau PYK, Sheng ORL, Kar Yan T. Examining the Technology Acceptance Model using physician acceptance of telemedicine technology. J Manage Inf Syst. 1999;16(2):91–112.
   Web of Science ®Google Scholar
• Kahneman D, Tversky A. Prospect theory: An analysis of decision under risk. Econometrica. 1979;47:263–293.
   Web of Science ®Google Scholar
• Kirkpatrick J. The hidden power of Kirkpatrick’s four levels. Training Dev. 2007;61(8):34–37.
   Google Scholar
• Landro L. How technology can deliver broad improvements in health care; 2016. Available from http://www.wsj.com/articles/how-technology-can-deliver-broad-improvements-in-health-care-1466992980.
   Google Scholar
• Leidner DE, Jarvenpaa SL. The use of information technology to enhance management school education: A theoretical view. MIS Q. 1995;19(3):265–291.
   Web of Science ®Google Scholar
• Lubke GH, Muthen BO. Applying multigroup confirmatory factor models for continuous outcomes to Likert scale data complicates meaningful group comparisons. Struct Equ Model. 2004 Oct;11(4):514–534.
   Web of Science ®Google Scholar
• Markus ML, Keil M. If we build it, they will come: Designing information systems that people want to use. Sloan Manage Rev. 1994;35(4):11–25.
   Web of Science ®Google Scholar
• Marler JH, Dulebohn JH. A model of employee self-service technology acceptance. Res Personnel Hum Resour Manage. 2005;24:137–180.
   Google Scholar
• Marler JH, Liang X, Dulebohn JH. Training and effective employee information technology use. J Manage. 2006;32(5):721–743.
   Web of Science ®Google Scholar
• Marshall BA. An empirical investigation of factors influencing the adoption of the technical standards found in government regulations. 2006: Dissertations & Theses @ Utah State University database. ( AAT 3229524).
   Google Scholar
• Marshall BA, Mills RJ, Olsen D. The role of end-user training in technology acceptance. Rev Bus Inf Syst. 2008;12(2):1–8.
   Google Scholar
• Merrill MD. Component display theory. In Reigeluth C, editor. Instructional design theories and models. Hillsdale (NJ): Erlbaum Associates; 1983.
   Google Scholar
• Merrill MD. First principles of instruction. Educ Technol Res Dev. 2002 September;50(3):43–59.
   Web of Science ®Google Scholar
• Mills RJ, Lawless KA, Pratt JA. Training groups of end users: Examining group interactions in a computer-based learning environment. J Comput Inf Syst. 2006;46(3):104–109.
   Web of Science ®Google Scholar
• Mills RJ, Beaulieu TY, Johnson JJ. Using SQL as a theory of planned behavior moderator to examine curriculum-oriented and promotional IS enrollment strategies. J Comput Inf Syst. In Press.
   Google Scholar
• Niederman, F., Brancheu JC. Information systems management issues for the 1990s. MIS Q. 1991;15(4):475–500.
   Web of Science ®Google Scholar
• Nunnally JC, Bernstein IH. Psychometric Theory (3rd ed.). New York: McGraw-Hill; 1994.
   Google Scholar
• Patel L. Overcoming barriers and valuing evaluation. Training Dev. 2010 February;64(3):62–63.
   Google Scholar
• Rogers E. Diffusion of Innovations. New York: Free Press; 1995.
   Google Scholar
• Scott JE, Vessey I. Managing risks in enterprise systems implementations. Commun ACM. 2002;45(4):74–81.
   Web of Science ®Google Scholar
• Shelton S, Alliger GM. Who’s afraid of level 4 evaluation? A practical approach. Training Dev J. 1993;47:43–44.
   Google Scholar
• Sheppard BH, Hartwick J, Warshaw PR. The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. J Consum Res. 1998;15(3):325–343.
   Web of Science ®Google Scholar
• Taylor S, Todd PA. Understanding information technology usage: A test of competing models. Inf Syst Res. 1995;6(2):144–176.
   Web of Science ®Google Scholar
• Thompson R, Higgins C, Howell J. Personal computing: Toward a conceptual model of utilization. MIS Q. 1991;15(1):125–143.
   Web of Science ®Google Scholar
• Vallerand RJ. Toward a hierarchical model of intrinsic and extrinsic motivation. Adv Exp Soc Psychol. 1997;29:271–360.
   Web of Science ®Google Scholar
• Vaverek KA, Saunders C. Computerspeak: Message content and perceived appropriateness in an educational setting. J Educ Technol Syst. 1994;22(2):123–139.
   Google Scholar
• Venkatesh V, Davis FD. A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Manage Sci. 2000;46(2):186–204.
   Web of Science ®Google Scholar
• Venkatesh V, Morris MG, Davis FD. User acceptance of information technology: Toward a unified view. MIS Q. 2003;27(3):424–478.
   Web of Science ®Google Scholar