Determinants of User Acceptance of Online Airline Reservation System.

Determinants of User Acceptance of Online Airline Reservation System.

The growth of the IT usage has been tremendous in the world of business today and no doubt it has been widely used in the area of airline industry. The online airline reservation system is one of the examples of such application of the technology. This study is a userfocused research that aims to i...

Full description

Saved in:
Bibliographic Details
Main Author: Ahmad Tahawi, Mohamad
Format: Thesis
Language:eng
eng
Published: 2007
Subjects:
HF5001-6182 Business
HF5601-5689 Accounting
Online Access:https://etd.uum.edu.my/28/1/ahmad_tahawi.pdf
https://etd.uum.edu.my/28/2/ahmad_tahawi.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-uum-etd.28
record_format uketd_dc
institution Universiti Utara Malaysia
collection UUM ETD
language eng
eng
topic HF5001-6182 Business
HF5601-5689 Accounting
spellingShingle HF5001-6182 Business
HF5601-5689 Accounting
Ahmad Tahawi, Mohamad
Determinants of User Acceptance of Online Airline Reservation System.
description The growth of the IT usage has been tremendous in the world of business today and no doubt it has been widely used in the area of airline industry. The online airline reservation system is one of the examples of such application of the technology. This study is a userfocused research that aims to identify the factors that determine acceptance of online airline reservation system by users. Adapting the technology acceptance model (TAM) as a theoretical framework, this study examines the variables perceived usefulness and perceived ease of use as antecedents of behavior intention to use the technology. Furthermore this study examines the effect of computer self-efficacy (external variable) as determinant towards perceived usefulness and perceived ease of use. A survey of 51 lecturers representing different faculties in Universiti Utara Malaysia (UUM) supports TAM in predicting the intention of users to adopt online airline reservation system. Findings also show the significant effect of computer self-efficacy in explaining behavior intention through perceived ease of use and perceived usefulness.
format Thesis
qualification_name masters
qualification_level Master's degree
author Ahmad Tahawi, Mohamad
author_facet Ahmad Tahawi, Mohamad
author_sort Ahmad Tahawi, Mohamad
title Determinants of User Acceptance of Online Airline Reservation System.
title_short Determinants of User Acceptance of Online Airline Reservation System.
title_full Determinants of User Acceptance of Online Airline Reservation System.
title_fullStr Determinants of User Acceptance of Online Airline Reservation System.
title_full_unstemmed Determinants of User Acceptance of Online Airline Reservation System.
title_sort determinants of user acceptance of online airline reservation system.
granting_institution Universiti Utara Malaysia
granting_department College of Business (COB)
publishDate 2007
url https://etd.uum.edu.my/28/1/ahmad_tahawi.pdf
https://etd.uum.edu.my/28/2/ahmad_tahawi.pdf
_version_ 1747826829550419968
spelling my-uum-etd.282013-07-24T12:05:21Z Determinants of User Acceptance of Online Airline Reservation System. 2007 Ahmad Tahawi, Mohamad College of Business (COB) Faculty of Business Management HF5001-6182 Business HF5601-5689 Accounting The growth of the IT usage has been tremendous in the world of business today and no doubt it has been widely used in the area of airline industry. The online airline reservation system is one of the examples of such application of the technology. This study is a userfocused research that aims to identify the factors that determine acceptance of online airline reservation system by users. Adapting the technology acceptance model (TAM) as a theoretical framework, this study examines the variables perceived usefulness and perceived ease of use as antecedents of behavior intention to use the technology. Furthermore this study examines the effect of computer self-efficacy (external variable) as determinant towards perceived usefulness and perceived ease of use. A survey of 51 lecturers representing different faculties in Universiti Utara Malaysia (UUM) supports TAM in predicting the intention of users to adopt online airline reservation system. Findings also show the significant effect of computer self-efficacy in explaining behavior intention through perceived ease of use and perceived usefulness. 2007 Thesis https://etd.uum.edu.my/28/ https://etd.uum.edu.my/28/1/ahmad_tahawi.pdf application/pdf eng validuser https://etd.uum.edu.my/28/2/ahmad_tahawi.pdf application/pdf eng public masters masters Universiti Utara Malaysia Adams D. A., Nelson R. R, and Todd P. A, (1992). Perceived usefulness, ease of use, and usage of information technology: A replication. MIS Quarterly, 16(2), 227-247. Agarwal, R. and Prasad, J. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences, 28(3), 557-582. Agarwal, R. and Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information System Research, 9(2), 204-215. Agarwal, R. and Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision Sciences, 30(2), 361-391. Agarwal, R., Sambamurthy, V. and Stair, R.M. (2000). Research report: the evolving relationship between general and specific computer self-efficacy - an empirical assessment. Information Systems Research, 11(4), 418-430. AirAsia Press Released (2006, August 3). AirAsia announces 20 million guests flown. Retrieved<April 21, 2007> available from http://www.airasia.com Alavi, M. and Joachimsthaler E.A. (1992). Revisiting DSS implementation research: A meta-analysis of the literature and suggestion for researchers. MIS Quarterly, 16(1),95-116. Azjen, I. and Fishbein M. (1980). Understanding attitude and predicting social behavior. Prentice Hall, Engelwood Cliffs, NJ. Bandura, A. (1986). Social Foundations of Thought and Action. Prentice-Hall, Englewood Cliffs, NJ. Bohmstedt, G. W. (1970). Reliability and validity assessment in attitude measurement in Summers, G.F. (Ed.), Attitude Measurement, Rand-McNally, Chicago, IL, 80-99. Chau P. Y. K (1996). An empirical assessment of a modified technology acceptance model. Journal of Management Information Systems, 13(2), 185-204. Chau, P.Y.K. (2001). Influence of computer attitude and self-efficacy on IT usage behavior. Journal of End User Computing, 13(1), 26-33. Chen, L., Gillenson, M. & Sherrell, D (2002). Enticing online consumers: an extended technology acceptance perspective. Information & Management, 39(8), 705-719. Chin W. W. and Todd P. A. (1995). On the use, usefullless, and ease of use of structural equation modeling in MIS research: A note of caution. MIS Quarterly, 19(2), 237-246. Compeau, D.R., and Higgins, C.A. (1995). Computer self-efficacy: Development of a measure and initial test. IMIS Quarterly, 19(2), 189-211. Compeau, D.R.; Higgins, C.A.; and Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23(2), 145-158. Copeland D.G. and McKenny, J.L. (1988).Airline reservation systems: lessons from history. MIS Quarterly, 352-370. Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 318-339. Davis, L.D., Bagozzi, R.P. and Warshaw, P.R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982-1003. DeCoster, J. (1998). Overview of factor analysis. Retreived<March 17,2007> available from http://www.stat-help.com/notes.html Dillon, A,, & Morris, M.G (1996). User acceptance of information technology: Theories and models. Annual Review of Information Science and Technology, 31,3-32. 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 Science, 29(4), 839-69. Eastin, M., (2002). Diffusion of e-commerce: an analysis of the adoption of four e.commerce activities. Telematics and Informatics, 19(3), 251-267. Fishbein, M. and Azjen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Addison-wesley, Reading, MA. Ginzberg, M.J. (1981). Key recurrent issues in the MIS implementation processes. MIS Quarterly, 5(2), 47-59. Gitte 1. (1994). Usability testing and system evaluation. Chapman & Hall, London. Hair, J.T., Anderson, R.E., Tatham, R.L. and Black, W.C. (1992), Multivariate Data Analysis with Readings, 3rd ed., Macmillan, New York, NY. Hauser, J.R and S. M. Shugen (1980). Intensity measures of consumer preference. Operation Research, 28. Hill, T., and Smith, N.D. (1987). Role of efficacy expectations in predicting the decision to use advanced technologies: The case of computers. Journal of Applied Psychology, 72(2), 307-313. 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), 97- 124. Hu, P.J., Chau, P.Y.K., Sheng, O.R.L. and Tam, K.Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91-112. Igbaria, M. and Iivari, J. (1995). The effects of self-efficacy on computer usage. Omega, 23(6), 587-605. Jackson, C.M., Chow, S. and Leitch, R.A. (1997). Toward an understanding of the behavioral intention to use an information system. Decision Sciences, 28(2), 357-389. Johnson, R.D. and Marakas, G.M. (2000). Research report: the role of behavior modeling in computer skills acquisition - toward refinement of the model. Information Systems Research, 11(4), 402-417. Karahanna, E., Straub, D. W., and Chervany, N.L.(1999). Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183-213. Larcker, D. F and V. P Lessig (1980). Perceived usefulness of information: a psychometric information. Decision Science, 11, 121 -134. Lucas, H.C., Jr., Ginzberg, M.J. and Schultz, R.L. (1990). Information system implementation: Testing a structural model. Ablex publishing corporation, Nonvood, NJ. Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173- 191. Moore, G.C. and Benbasat, I. (1991). Development of instrument to measure the perceptions of adopting an information technology innovation. information Systems Research, 2(3), 192-222. Moore, G.C. and Benbasat, I. (1996). Integrating diffusions of innovations and theory of reasoned action models to predict utilization of information technology by endusers. Diffusion and adoption of information technology, K. Kautz and J. Pries-Heges (eds.), Chapman and Hall, London, 132-146. Pakiam, R(2007, March 27). Finding a life on the internet. The New Straits Times. p.6. Pallant, J. (2000). SPSS survival manual: A step by step guide to data analysis using SPSS for Windows (Version 10). Allen & Unwin. Plouffe, C. R., Hulland, J. S., and Vandenbosch, M.(2001). Research report: richness versus parsimony in modeling technology adoption decisions- understanding merchant adoption of a smart card-based payment system. Information Systems Research, 12(2), 208-222. Rogers, E. M. (1995). Diffusion of innovations (4th ed.). New York: The Free Press Roscoe, J. T. (1975). Fundamental research statistics for the behavior: A systematic guide to method. New York: Holt, Rinehart and Winston. Salancik, G.R., & Pfeffer, J. (1987). A social information processing approach to job attitudes and task design. Administrative Science Quarterly, 23,224-253. Sekaran, U. (2003). Research methods fro business: A skill building approach, Fourth Ed. John Wiley & Sons, Inc. Straub D., Keil M., and Brenner W. (1997). Testing the technology acceptance model across cultures: A three-country study. Information and Management, 33(1), 1-11. Surry, D.W. (1997). Diffusion Theory and Instructional Technology. Paper presented at the Annual Conference of the Association for Educational Communications and Technology (AECT), Albuquerque, New Mexico February 12-15,1997. [Online] Available http://intro.base.org/docs/diffusion/. Swanson, E. B (1974). Management information system: appreciation and involvement. Management Science, 21, 178-188. Tait. P and Vassey, I (1989). The effect of user involvement on system success: A contingency approach. MIS Quarterly, 12(1), 91 - 107. Taylor, S. and Todd, P.A. (1995). Understanding inforination technology usage: a test of competing models. Information Systems Rescarch, 6(2), 144- 176. Tornatzky, L.G. and Klien, K.J.(1982). Innovation characteristics and innovation adoption-implementation: a meta-analysis of findings. IEEE Transactions on Engineering Management, 29(1), 28-45. Trevino, L. K., Lengel, R. H., & Daft, R. L. (1987). Media symbolism, media richness, and media choice in organizations: A symbolic integrationist perspective. Communication Research, 14(5), 553-74. Venkatesh V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365. Venkatesh V. and Davis, F. D. (1996). A model of the perceived ease of use development and test. Decision Sciences, 27(3). 451-481. Venkatesh, V. and Davis, F.D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. Venkatesh, V. and Morris, M.G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139. Westland, J. C. and Clark, (2000). T. H- K. Global Electronic Commerce: Theory and Case Studies, MIT Press, Cambridge, MA.

Similar Items