The Comparison of Three Major Occupations for User Acceptance of Information Technology: Applying the UTAUT Model

Yu Shan Cheng, Tsai Fang Yu, Chin Feng Huang, Chien Yu, Chin Cheh Yu

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DOI: 10.4236/ib.2011.32021                

Abstract

This study investigated whether the differences of gender, age, and occupation for m-learning showed significance on the utilization of the mobile devices and to figure out if the variation may influence the performance expectancy, effort expectancy and the social influence to the behavioral intention or even to the behavior of usage. When the employees’ behavioral intention was low, the director of managers or HR department can suggest the employees’ colleagues, superior manager or friends to communicate with them to enhance their behavioral intention and to use it. And it suggested that male employees and elder employees should be put more emphasis on the communication to enhance their behavioral intention. UTAUT model with different kinds of businesses for m-learning but the conclusion did not investigate the differences of the adoption of the mobile devices in each industry. Basing on this, this study attempted to investigate whether the difference occupations showed significance on the utilization of the mobile devices.

Keywords

Unified Theory of Acceptance and Use of Technology (UTAUT), Manufacturing, Service, Bank

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	T. Zhou, Y. B. Lu and B. Wang, “Integrating TTF and UTAUT to Explain Mobile Banking User Adoption,” Computers in Human Behavior, Vol. 26, No. 4, 2010, pp. 760-767. doi:10.1016/j.chb.2010.01.013
[2]	P. Y. K. Chau and P. J. H. Hu, “Investigating Healthcare Professionals’ Decisions to Accept Telemedicine Technology: An Empirical Test of Competing Theories,” Information & Management, Vol. 39, No. 4, 2002, pp. 297- 311. doi:10.1016/S0378-7206(01)00098-2
[3]	Taiwan Institute for Information Industry, “The Investigation of Corporate E-Learning into the Status-Results Report (100 Largest Financial),” National E-Learning Network Science Park plans to shape science and technology, 2005.
[4]	Industrial Development Bureau, Ministry of Economic Affairs in Taiwan, “The Ratios Among the Occupations of Manufacture, Banking and Service in Buying or Making E-Learning Platform,” 2010. http://www.moeaidb. gov.tw/.
[5]	V. Venkatesh, M. Morris, G. B. Davis and F. D. Davis, “User Acceptance of Information Technology: Toward a Unified View,” MIS Quarterly, Vol. 27, No. 3, 2003, pp. 425-478.
[6]	W. W. Chin, B. L. Marcolin and P. R. Newsted, “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,” Information Systems Research, Vol. 14, No. 2, 2003, pp. 189-217. doi:10.1287/isre.14.2.189.16018
[7]	H. Sun and P. Zhang, “The Role of Model Rating Factors in User Technology Acceptance,” International Journal Human-Computer Studies, Vol. 64, No. 2, 2006, pp. 53- 78. doi:10.1016/j.ijhcs.2005.04.013
[8]	F. D. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Quarterly, Vol. 13, No. 3, 1989, pp. 319-334. doi:10.2307/249008
[9]	R. Agarwal and J. Prasad, “Are Individual Differences Germane to the Acceptance of New Information Technologies?” Decision Sciences, Vol. 30, No. 2, 1999, pp. 361-391. doi:10.1111/j.1540-5915.1999.tb01614.x
[10]	S. Kulviwat, G. C. Bruner II, A. Kumar, S. A. Nasco and T. Clark, “Toward a Unified Theory of Consumer Acceptance Technology,” Psychology and Marketing, Vol. 24, No. 12, 2007, pp. 1059-1084. doi:10.1002/mar.20196
[11]	S. Taylor and P. A. Todd, “Understanding Information Technology Usage: A Test of Competing Models,” Information Systems Research, Vol. 6, No. 2, 1995, pp. 144-174. doi:10.1287/isre.6.2.144
[12]	V. Venkatesh and M. Morris, “Why Don’t Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior,” MIS Quarterly, Vol. 24, No. 1, 2000, pp. 115-139. doi:10.2307/3250981
[13]	V. Venkatesh, “Veterminants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model,” Information Systems Research, Vol. 4, No. 4, 2000, pp. 342-365. doi:10.1287/isre.11.4.342.11872
[14]	D. Y. Kim, J. Park and A. M. Morrison, “A Model of Traveller Acceptance of Mobile Technology,” International Journal of Tourism Research, Vol. 10, No. 5, 2008, pp. 393-407. doi:10.1002/jtr.669
[15]	R. Agarwal and J. Prasad, “A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology,” Information Systems Research, Vol. 9, No. 2, 1998, pp. 204-215. doi:10.1287/isre.9.2.204
[16]	I. Ajzen and M. Fishbein, “Understanding Attitudes and Predicting Social Behavior,” Englewood Cliffs, Prentice-Hall, New Jersey, 1980.
[17]	M. Fishbein and I. Ajzen, “Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research,” Addison-Wesley: Reading, Massachusetts, 1975.
[18]	I. Ajzen, “From Intentions to Actions: A Theory of Planned Behavior,” In: J. Kuhl, E. Beckmann Eds., In Action Control: From cognition to Behavior, Springer- Verlag, Berlin, 1985, pp. 11-39.
[19]	G. C. Moore and I. Benbasat, “Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation,” Information Systems Research, Vol. 2, No. 3, 1991, pp. 192-222. doi:10.1287/isre.2.3.192
[20]	F. D. Davis and V. Venkatesh, “A Critical Assessment of Potential Measurement Biases in the Technology Acceptance Model: Three Experiments,” Internet Journal of Human-computer Studies, Vol. 45, No. 1, 1996, pp. 19- 45.
[21]	V. Venkatesh and F. D. Davis, “A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies,” Management Science, Vol. 46, No. 2, 2000, pp. 186-204. doi:10.1287/mnsc.46.2.186.11926
[22]	F. D. Davis, R. P. Bagozzi and P. R. Warshaw, “User Acceptance of Computer Technology: A Comparison of Two Theoretical Models,” Management Science, Vol. 35, No. 8, 1989, pp. 982-1003. doi:10.1287/mnsc.35.8.982
[23]	R. L. Thompson, C. A. Higgins and J. M. Howell, “Personal Computing: Toward a Conceptual Model of Utilization,” MIS Quarterly, Vol. 15, No. 1, 1991, pp. 125- 143. doi:10.2307/249443
[24]	F. D. Davis, R. P. Bagozzi and P. R. Warshaw, “Extrinsic and Intrinsic Motivation to Use Computers in the Workplace,” Journal of Applied Social Psychology, Vol. 22, No. 14, 1992, pp. 1111-1132. doi:10.1111/j.1559-1816.1992.tb00945.x
[25]	D. R. Compeau and C. A. Higgins, “Computer Self-Efficacy: Development of a Measure and Initial Test,” MIS Quarterly, Vol. 19, No. 2, 1995, pp. 189-211. doi:10.2307/249688
[26]	D. R. Compeau, C. A. Higgins and S. Huff, “Social Cognitive Theory and Individual Reactions to Computing Technology: A Longitudinal Study,” MIS Quarterly, Vol. 23, No. 2, 1999, pp. 145-158. doi:10.2307/249749
[27]	M. Ahearne, N. Srinivasan and L. Weinstein, “Effect of Technology on Sales Performance: Progressing from Technology Acceptance to Technology Usage and Consequence,” Journal of Personal Selling & Sales Management, Vol. 24, No. 5, 2004, pp. 297-310.
[28]	I. Ajzen, “The Theory of Planned Behavior,” Organizational Behavior and Human Decision, Vol. 50, No. 2, 1991, pp. 179-211. doi:10.1016/0749-5978(91)90020-T
[29]	Y. S. Wang, M. C. Wu and H. Y. Wang, “Investigating the Determinants and Age and Gender Differences in the Acceptance of Mobile Learning,” British Journal of Educational Technology, Vol. 40, No. 1, 2009, pp. 92-118. doi:10.1111/j.1467-8535.2007.00809.x
[30]	S. Taylor and P. A. Todd, “Assessing IT Usage: The Role of Prior Experience,” MIS Quarterly, Vol. 19, No. 2, 1995, pp. 561-570. doi:10.2307/249633
[31]	H. C. Triandis, “Interpersonal Behavior,” Brooke/Cole, Monterey, CA, 1977.
[32]	E. M. Rogers, “Diffusion of Innovations,” 5th Edition, Free Press, New York, 2003.
[33]	A. Bandura, “Social Foundations of Thought and Action: A Social Cognitive Theory,” Prentice Hall, Englewood Cliffs, New Jersey, 1986.
[34]	E. M. Rogers, “Diffusion of Innovations,” Free Press, New York, 1995.
[35]	I. Ajzen and M. Fishbein, “Attitude-Behavior Relations: A Theoretical Analysis and Review of Empirical Research,” Psychol Bull, 1977, pp. 84-85.
[36]	T. Koivum?ki, A. Ristola and M. Kesti, “The Perceptions Towards Mobile Services: An Empirical Analysis of the Role of Use Facilitators,” Personal and Ubiquitous Computing, Vol. 12, No. 1, 2008, pp. 67-75.
[37]	F. C. Tung, M. S. Lee, C. C. Chen and Y. S. Hsu, “An Extension of Financial Cost and TAM Model with IDT for Exploring Users’ Behavioral Intentions to Use the CRM Information System,” Social Behavior and Personality, Vol. 37, No. 5, 2009, pp. 621-626. doi:10.2224/sbp.2009.37.5.621
[38]	Y. C. Lee, M. L. Li, T. M. Yen and T. H. Hua, “Analysis of Adopting an Integrated Decision Making Trial and Evaluation Laboratory on a Technology Acceptance Model,” Expert System with Application, Vol. 37, No. 2, 2010, pp. 1745-1754. doi:10.1016/j.eswa.2009.07.034
[39]	V. Venkatesh, M. G. Morris and P. L. Ackerman, “A Longitudinal Field Investigation of Gender Differences in Individual Technology Adoption Decision Making Processes,” Organizational Behavior and Human Decision Processes, Vol. 83, No. 1, 2000, pp. 33-60. doi:10.1006/obhd.2000.2896
[40]	T. K., Peng, Y. T. Kao and C. C. Lin, “Common Method Variance in Management Research: Its Nature, Effects, Detection, and Remedies,” Journal of Management, Vol. 23, No. 1, 2006, pp. 77-98.
[41]	J. C. Nunnally, “Psychometric Theory,” 2nd Edition, McGraw-Hill, New York, 1978.
[42]	C. Fornell and D. F. Larcker, “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error,” Journal of Marketing Research, Vol. 18, No. 1, 1981, pp. 39-50. doi:10.2307/3151312
[43]	R. P. Baggozzi and Y. Yi, “On the Evaluation of Structural Equation Models,” Academic of Marketing Science, Vol. 16, No. 1, 1988, pp. 76-94.
[44]	J. F. Jr. Hair, R. E. Anderson, R. L. Tatham and W. C. Black, “Multivariate Data Analysis,” 5th Edition, Upper Saddle River, Prentice Hall, New Jersey, 1998.
[45]	D. H. Shin, “Towards an Understanding of the Consumer Acceptance of Mobile Wallet,” Computers in Human Behavior, Vol. 25, No. 6, 2009, pp. 1343-1354. doi:10.1016/j.chb.2009.06.001
[46]	G. C. Chow, “Tests of Equality Between Sets of Coefficients in Two Linear Regressions,” Econometrica, Vol. 28, No. 3, 1960, pp. 591-605. doi:10.2307/1910133
[47]	K. Serenko, O. Turel and S. Yol, “Modelrating Roles of User Demographics in the American Customer Satisfaction Model within the Context of Mobile Services,” Journal of Information Technology Management, Vol. 17, No. 4, 2006, pp. 20-32.
[48]	T. Z. Lee and L. Y. Huang, “Related Research in Learning Motivation, Learning Satisfaction and Learning Performance of Continuing Education for In-service Personage: Taking In-service Master Program of NCKU as Example,” Journal of Human Resource Management, Vol. 7, No. 4, 2007, pp. 1-24.
[49]	A. Macaskill, J. Maltby and L. Day, “Forgiveness of Self and Others and Emotional Empathy,” The Journal of Social Psychology, Vol. 142, No. 5, 2002, pp. 663-665. doi:10.1080/00224540209603925
[50]	B. A. Gault and J. Sabini, “The Roles of Empathy, Anger, and Gender in Predicting Attitudes Toward Punitive, Reparative, and Preventative Public Policies,” Cognition and Emotion, Vol. 14, No. 4, 2000, pp. 495-520. doi:10.1080/026999300402772
[51]	K. C. McLeland and G. W. Sutton, “Sexual Orientation, Mental Health, Gender, and Spirituality: Prejudicial Attitudes and Social Influence in Faith Communities,” Journal of Psychology and Theology, Vol. 36, No. 2, 2008, pp. 104-113.
[52]	L. E. McClelland and J. A. McCubbin, “Social Influence and Pain Response in Women and Men,” Journal of Behavioral Medicine, Vol. 35, No. 1, 2008, pp. 413-420. doi:10.1007/s10865-008-9163-6