A STUDY ON THE ACCEPTANCE OF INFORMATION TECHNOLOGIES FROM THE PERSPECTIVES OF THE ACADEMICIANS IN TURKEY

Year 2010, Volume: 10 Issue: 3, 791 - 812, 01.08.2010

Ertugrul Tarcan Ergin Sait Varol Boran Toker

Abstract

Educational institutions have been increasingly started to use information technologies (ITs) for improving the service quality and achieving the effective organizational outputs in a competitive global environment. An individual’s intention to use ITs is a crucial factor in determining the success or failure of an information technology (IT) system implementation. This study attempts to investigate the factors affecting the intention to use ITs from the academicians’ perspectives in Turkey. This research extends the technology acceptance model (TAM) framework with subjective norm (SN) and facilitating conditions (FC) acting as external variables. The model has been tested using web-based data collected from 510 academicians. The findings demonstrate that this extended TAM can explain 80% of the variance of intention to use ITs. And also, SN and FC are potential variables that may be used to extend the TAM for the research on the academicians’ intention to use towards ITs. This study reveals that educational managers can use this research model as a helpful tool in better understanding stakeholders’ behaviors related to the technology acceptance, and also in the process of IT investment, implementation and renovation

Keywords

Academicians, Educational technology acceptance, Subjective norm, Facilitating conditions, TAM, IT, SEM

References

• Adams, D.A., Nelson, R.R. and Todd, P.A. (1992), “Perceived usefulness, ease of use, and usage of information”, MIS Quarterly, 16, 2, pp. 227-247.
• Agarwal, R. and Karahanna, E. (2000), “Time flies when you’re having fun: cognitive absorption and beliefs about information technology usage”, MIS Quarterly, 24, 4, pp. 665-694.
• Agarwal, R. and Prasad, J. (1999), “Are individual differences germane to the acceptance of new information technologies?”, Decision Sciences, 30, 2, pp. 361-391.
• Ajzen, I. and Fishbein, M. (1980), “Understanding Attitudes and Predicting Social Behavior”, Prentice Hall, Englewood Cliffs. Ajzen, I. (1991), “The theory of planned behavior”, Organizational Behavior and Human Decision Processes, 50, 2, pp. 179–211.
• Ballone,L.M. and Czerniak, C.M. (2001), “Teachers’ beliefs about accommodating students’ learning styles in Science classes”, Electronic Journal of Science Education, 6, 2, pp.1-41.
• Bannan-Ritland, B., Dabbagh, N., and Murphy, K. (2000), “Learning object systems as constructivist learning environments: related assumptions, theories, and applications”, available at: http:// www.reusability.org/read/chapters/bannan-ritland.doc (accessed 11 May 2010).
• Bielaczyc, Katerine (2006), “Designing social infrastructure: Critical issues in creating learning environments with technology”, Journal of the Learning Sciences, 15, 3, pp.301–329.
• Bratina, T.A., Hayes, D., and Blumsack, S.L. (2002), “Preparing teachers to use learning objects”, available at: http://technologysource.org/article/preparing_teachers_to_ use_learning_objects/ (accessed 11 May 2010).
• Breen, R, Lindsay, R., Jenkins, A. and Smith P. (2001), “The role of information and communication technologies in a university learning environment”, Studies in Higher Education, 26, 1. pp. 95–114.
• Burton-Jones, A. and Hubona, G.S. (2006), “The Mediation of external variables in the technology acceptance model”, Information & Management, 43, 6, pp. 706-717.
• Chau, P.Y.K. and Hu, P.J.H. (2001), “Information technology acceptance by individual professionals: a model comparison approach”, Decision Sciences, 32 4, pp. 699-719.
• Cheney, P.H. and Dickson, G.W. (1982), “Organizational characteristics and information systems: an exploratory investigation”, Academy of Management Journal, 25, 1, pp. 170-184.
• Chin, W.W. and Todd, P.A. (1995), “On the use, usefulness, and ease of use of structural equation modelling in MIS research: a note of caution”, MIS Quarterly, 19, 2, pp. 237-246.
• Daughtery, M. and Funke, B.L. (1998), “University faculty and student perceptions of web-based instruction”, Journal of Distance Education, 13, 1, pp. 21-39.
• Davis, F.D., Bagozzi, R.P., and Warshaw, P.R. (1989), ”User acceptance of computer technology: A comparison of two theoretical models”, Management Science, 35, 8, pp. 982-1003.
• Davis, F.D. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, 13, 3, pp. 319-339.
• Davis, F.D., Bagozzi, R.P., and Warshaw, P.R. (1992), “Extrinsic and intrinsic motivation to use computers in the workplace” Journal of Applied Social Psychology, 22, 1, pp. 1111-1132.
• Davis, F.D. (1993), “User acceptance of information technology: System characteristics, user perceptions and behavioral impacts” International Journal of Man-Machine Studies, 38, 3, pp. 475-487.
• Doll, W.J., Hendrickson, A., and Deng, X. (1998), “Using Davis’s perceived usefulness and ease-of-use instruments for decision making: a confirmatory and multi-group invariance analysis”, Decision Sciences, 29, 4, pp. 839-869.
• Farquhar, J.D. and Surry, D.W. (1994), “Adoption analysis: an additional tool for instructional developers”, Education and Training Technology International, 31, 1, pp. 19-25.
• Fishbein, M., and Ajzen, I. (1975), “Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research”, Addison-Wesley, Reading, Boston. Frambach, R.T. and Schillewaert, N. (2002), “Organizational innovation adoption: a multi-level framework of determinants and opportunities for future research”, Journal of Business Research, 55, 2, pp. 163-176.
• Gerbing, David W. and James C. Anderson (1988). “An updated paradigm for scale development incorporating unidimensionality and its assessment”. Journal of Marketing Research. 25 (2): 186–192.
• Groves, M.M. and Zemel, P.C. (2000), “Instructional technology adoption in higher education: an action research case study”, International Journal of Instructional Media, 27, 1, pp. 57-65.
• Hong, W., Thong, J.Y.L., Wong, W.M. and Tam, K.Y. (2001), “Determinants of user acceptance of digital libraries: an empirical examination of individual differences and system characteristics”, Journal of Management Information Systems, 18, 3, pp. 97-124.
• Hooper, D. Coughlan, J. and Mullen, M. R. (2008), “Structural equation modelling: guidelines for determining model fit”, The Electronic Journal of Business Research Methods, 6, 1, pp.53-60, available at http://www.ejbrm.com/vol6/v6-i1/v6-i1-papers.htm, (accessed 10 May 2009).
• Hu, Li-tze. and Peter M. Bentler (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6 (1), pp.1–55.
• Legris P., Ingham, J., and Collerette, P. (2003), “Why do people use information technology? A critical review of the technology acceptance model”, Information and Management, 40, 3, pp. 191-204.
• Lim, C.P. and Khine, M.S. (2006), “Managing teachers’ barriers to ICT integration in Singapore schools”, Journal of Technology and Teacher Education, 14, 1, pp. 97-125.
• Lu, J., Yao J.E., Yu, C-S. (2005), “Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology”, Journal of Strategic Information Systems, 14, 3, pp. 245–268.
• Lucas, H.C. and Spitler, V.K. (1999), “Technology use and performance: a field study of broker workstations”, Decisions Sciences, 30, 2, pp. 291-311.
• Marcinkiewicz, H. R. and Regstad, N.G. (1996), “Using Subjective Norms To Predict Teachers' Computer Use”, Journal of Computing in Teacher Education, 13, 1, pp. 27-33.
• Marriott, N, Marriott, P. and Selwyn, N. (2004). “Accounting undergraduates changing use of ICT and their views on using the Internet in higher education”, Accounting Education, 13, 1, pp.117–130.
• Martinez-Torres M.R., Marin, S.L.T., Garcia F.B., Vazquez S.G., Oliva M.A. and Torres T. (2008), “A technological acceptance of e-learning tools used in practical and laboratory teaching, according to the European higher education area”, Behaviour & Information Technology, 27, 6, pp.495–505.
• Mathieson, K. (1991), “Predicting user intentions: Comparing the technology acceptance model with the theory of planned behaviour”, Information Systems Research, 2, 3, pp.173–191.
• McMahon, J., Gardner, J., Gray, C., and Mulhern, G. (1999), “Barriers to student computer usage: staff and student perceptions”, Journal of Computer Assisted Learning, 15, 4, pp.302-311.
• Mun, Y.Y. and Hwang, Y. (2003), “Predicting the use of web-based information systems: self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model” International Journal of Human-Computer Studies, 59, 4, pp. 431-449.
• Reffell, P.and Whitworth, A. (2002), “Information Fluency: Critically Examining IT Education”, New Library World, 103, 11-12, pp.427-435.
• Reisinger, Y. and Mavondo, F. (2006), “Structural Equation Modeling: Critical Issues and New Developments”, Journal of Travel & Tourism Marketing, 21, 4, pp. 41-71.
• Selwyn, N. (2007), “The use of computer technology in university teaching and learning: a critical perspective”, Journal of Computer Assisted Learning, 23, 2, pp. 83-94.
• Schillewaert, N., Ahearne, M. J., Frambach, R. T., and Moenaert, R. K. (2005), “The adoption of information technology in the sales force”, Industrial Marketing Management, 34, 4, pp. 323-336.
• Segars, A.H. and Grover, V. (1993), “Re-examining PEOU and usefulness: a confirmatory factor analysis”, MIS Quarterly, 17, 4, pp. 517-525.
• Selwyn, N. (2007), “The use of computer technology in university teaching and learning: A critical perspective”, Journal of Computer Assisted Learning, 23, 2, pp.83–94.
• Shang, R.A., Chen, Y.C., and Shen, L. (2005), “Extrinsic versus intrinsic motivations for consumers to shop on-line”, Information & Management, 42, 3, pp. 401-413.
• Taylor, S., and Todd, P.A. (1995), “Understanding information technology usage: a test of competing models”, Information Systems Research, 6, 2, pp. l44-l76.
• Teo, T., Lee, C.B., and Chai, C.S. (2008), “Understanding pre-service teachers’ computer attitudes: applying and extending the technology acceptance model”, Journal of Computer Assisted Learning, 24, 2, pp. 128-143.
• Thompson, R.L., Higgins, C.A., and Howell, J.M. (1991), “Personal computing: toward a conceptual model of utilization”, MIS Quarterly, 15, 1, pp. 124-143.
• Turan, A.H. and Colakoglu, B.E. (2008), “Faculty’s Acceptance And Use Of Technology In Hıgher Education: An Empirical Assessment At Adnan Menderes Universıty”, Dogus Universitesi Dergisi, 9, 1, pp.106-121.
• Varol, E.S., Tarcan, E. and Ozmen, I. (2010), “The acceptance and use of elearning systems in Turkey”, International Journal of Innovation and Learning, 8, 1, pp.90-105.
• Venkatesh, V. (1999), “Creation of favourable user perceptions: exploring the role of intrinsic motivation”, MIS Quarterly, 23, 2, pp. 239-260.
• Venkatesh, V. (2000), “Determinants of PEOU: integrating control, intrinsic motivation, and emotion into the technology acceptance model”, Information Systems Research, 11, 4, pp. 342-365.
• Venkatesh, V. and Davis, F.D. (2000), “A theoretical extension of the technology acceptance model: four longitudinal field studies”, Management Science, 46, 2, pp. 186–204.
• Venkatesh, V., Morris, M.G., Davis, G.B., and Davis, F.D. (2003), “User acceptance of information technology: toward a unified view”, MIS Quarterly, 27, 3, pp. 425-478.
• Wiley, D. (2001), “Peer-to-peer and learning objects: the new potential for collaborative constructivist learning online”, Paper presented at the Proceedings of the IEEE International Conference on Advanced Learning Technology, pp.494-495.