Examining a technology acceptance model of intention to use internet by a academics within Indonesia higher learning institution

A variety of information technology acceptance model had been proposed with different sets of determinants and most of them have been developed in the U.S. It is therefore questioned whether the models of technology acceptance that have been developed in the U.S. can be used in other countries, espe...

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主要作者:	Sriwindono, Haris
格式:	Thesis
語言:	English English
出版:	2017
主題:	L Education (General) LB Theory and practice of education
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id	my-utem-ep.20473
record_format	uketd_dc
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
advisor	Yahya, Salleh
topic	L Education (General) LB Theory and practice of education
spellingShingle	L Education (General) LB Theory and practice of education Sriwindono, Haris Examining a technology acceptance model of intention to use internet by a academics within Indonesia higher learning institution
description	A variety of information technology acceptance model had been proposed with different sets of determinants and most of them have been developed in the U.S. It is therefore questioned whether the models of technology acceptance that have been developed in the U.S. can be used in other countries, especially in Indonesia. It is also questioned whether there might be other determinants such as cultural dimension that also play important roles in this specific environment (Veiga et al., 2001; Bagchi et al.,2003). However, the role of cultural dimensions on internet acceptance research currently lacks a comprehensive conceptual framework for explaining the intention of internet usage especially in Indonesia. To fill this gap, this study extends the Unified Theory of Acceptance and Use of Technology Model (UTAUT) (Venkatesh et el., 2003) by adding a set of cultural constructs that are derived from Hofstede's national culture dimensions as the antecedents. The constructs of UTAUT used in this research were Attitude (ATT), Self Eficacy (SEF), Anxiety (ANX), Perceived ease of Use (PEOU), Perceived Usefulness (PU) and Social Influence (SI) and Compatibility (COM), while Hofstede's dimensions used in this research were Individualism (IDV), Power Distance (PDI), User Avoidance (UAI) and Long Term Orientation (LTO). Questionnaire survey method was used to collect primary data from academics within Private Universities in Indonesia. The survey yielded 401 usable questionnaires. Statistical analysis methods and Structural Equation Modeling with SmartPLS version 2.0 were used to analyse data. The findings indicate that the Perceived Usefulness (PU) and Social Influence (SI) are the most significant determinant of intention to use internet, while ATT, SEF and ANX are not. It is indicate that individual context not influence the intention to use. PEOU and COM has no effect on the intention, it means that the difficulties and compatibility using the internet have no effect on the intention. Meanwhile Individualism (IDV) is a variable that most influence on this model because IDV affect the SEF, ANX, PEOU and PU, followed by Power Distance (PDI) affecting the SEF and SI. Then LTO effect on PU and COM. While User Avoidance (UAI) only affect the SEF, and UAI did not affect the PEOU as originally hypothesized. In general, it can be said that the cultural dimensions are quite important in the acceptance of internet. Findings should assist organizations to understand the influence of cultural dimensions on internet technology acceptance and can be used as consideration when implementing internet in a higher learning institution in Indonesia. Finally, suggestions for future research were also provided for practitioners and academicians.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Sriwindono, Haris
author_facet	Sriwindono, Haris
author_sort	Sriwindono, Haris
title	Examining a technology acceptance model of intention to use internet by a academics within Indonesia higher learning institution
title_short	Examining a technology acceptance model of intention to use internet by a academics within Indonesia higher learning institution
title_full	Examining a technology acceptance model of intention to use internet by a academics within Indonesia higher learning institution
title_fullStr	Examining a technology acceptance model of intention to use internet by a academics within Indonesia higher learning institution
title_full_unstemmed	Examining a technology acceptance model of intention to use internet by a academics within Indonesia higher learning institution
title_sort	examining a technology acceptance model of intention to use internet by a academics within indonesia higher learning institution
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty Of Technology Management And Technopreneurship
publishDate	2017
url	http://eprints.utem.edu.my/id/eprint/20473/1/Examining%20A%20Technology%20Acceptance%20Model%20Of%20Intention%20To%20Use%20Internet%20By%20A%20Academics%20Within%20Indonesia%20Higher%20Learning%20Institution.pdf http://eprints.utem.edu.my/id/eprint/20473/2/Examining%20a%20technology%20acceptance%20model%20of%20intention%20to%20use%20internet%20by%20a%20academics%20within%20Indonesia%20higher%20learning%20institution.pdf
_version_	1747833967602565120
spelling	my-utem-ep.204732022-06-03T15:57:38Z Examining a technology acceptance model of intention to use internet by a academics within Indonesia higher learning institution 2017 Sriwindono, Haris L Education (General) LB Theory and practice of education A variety of information technology acceptance model had been proposed with different sets of determinants and most of them have been developed in the U.S. It is therefore questioned whether the models of technology acceptance that have been developed in the U.S. can be used in other countries, especially in Indonesia. It is also questioned whether there might be other determinants such as cultural dimension that also play important roles in this specific environment (Veiga et al., 2001; Bagchi et al.,2003). However, the role of cultural dimensions on internet acceptance research currently lacks a comprehensive conceptual framework for explaining the intention of internet usage especially in Indonesia. To fill this gap, this study extends the Unified Theory of Acceptance and Use of Technology Model (UTAUT) (Venkatesh et el., 2003) by adding a set of cultural constructs that are derived from Hofstede's national culture dimensions as the antecedents. The constructs of UTAUT used in this research were Attitude (ATT), Self Eficacy (SEF), Anxiety (ANX), Perceived ease of Use (PEOU), Perceived Usefulness (PU) and Social Influence (SI) and Compatibility (COM), while Hofstede's dimensions used in this research were Individualism (IDV), Power Distance (PDI), User Avoidance (UAI) and Long Term Orientation (LTO). Questionnaire survey method was used to collect primary data from academics within Private Universities in Indonesia. The survey yielded 401 usable questionnaires. Statistical analysis methods and Structural Equation Modeling with SmartPLS version 2.0 were used to analyse data. The findings indicate that the Perceived Usefulness (PU) and Social Influence (SI) are the most significant determinant of intention to use internet, while ATT, SEF and ANX are not. It is indicate that individual context not influence the intention to use. PEOU and COM has no effect on the intention, it means that the difficulties and compatibility using the internet have no effect on the intention. Meanwhile Individualism (IDV) is a variable that most influence on this model because IDV affect the SEF, ANX, PEOU and PU, followed by Power Distance (PDI) affecting the SEF and SI. Then LTO effect on PU and COM. While User Avoidance (UAI) only affect the SEF, and UAI did not affect the PEOU as originally hypothesized. In general, it can be said that the cultural dimensions are quite important in the acceptance of internet. Findings should assist organizations to understand the influence of cultural dimensions on internet technology acceptance and can be used as consideration when implementing internet in a higher learning institution in Indonesia. Finally, suggestions for future research were also provided for practitioners and academicians. 2017 Thesis http://eprints.utem.edu.my/id/eprint/20473/ http://eprints.utem.edu.my/id/eprint/20473/1/Examining%20A%20Technology%20Acceptance%20Model%20Of%20Intention%20To%20Use%20Internet%20By%20A%20Academics%20Within%20Indonesia%20Higher%20Learning%20Institution.pdf text en public http://eprints.utem.edu.my/id/eprint/20473/2/Examining%20a%20technology%20acceptance%20model%20of%20intention%20to%20use%20internet%20by%20a%20academics%20within%20Indonesia%20higher%20learning%20institution.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=105857 phd doctoral Universiti Teknikal Malaysia Melaka Faculty Of Technology Management And Technopreneurship Yahya, Salleh 1. Abdul-Gadar, H., 1997. Information Systems Strategies in Multi-National Companies in Arab Gulf Countries. International Journal of Information Management, 17 (1), pp. 3-12. 2. 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), pp. 227-247. 3. Adler, N. J., 1997. International Dimensions of Organizational Behaviour, 3rd ed. Cincinnati, OH: Shout-Western College Publishing. 4. Agarwal, R. and Karahanna, E.,1998. On The Multi-Dimensional Nature of Compatibility Beliefs in Technology Acceptance”, DIGIT, available at: http://disc-nt.cba.uh.edu/chin/digit98/first. [Accesed on 2 March 2011]. 5. Agarwal, A., and Karahanna, E., 2000. Time Flies When You’re having Fun: Cognitive Absorption and Beliefs About Information Technology Ese. MIS Quarterly, 24 (4), pp. 665–694. 6. Agarwal, R., and Prassad, J., 1997. The Role of Innovation Characteristics and Perceived Voluntariness in the Acceptance of Information Technologies. Decision Sciences, 28 (3), pp. 557–582. 7. Aibinu, A.A., and Al-Lawati, A.M., 2010. Using PLS-SEM Technique to Model Construction Organizations' Willingness to Participate in E-bidding. Automation in Construction, 19 (6), pp. 714–724. 8. Ajzen, I., 1991. The Theory of Planned Behavior. Organizational Behavior and Human. 9. Decision Processes, 50, pp. 179–211. 10. Ajzen, I., and Fishbein, M., 1975. Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley. 11. Ajzen, I., and Fishbein, M., 1980. Understanding Attitudes and Predicting Social Behavior. Prentice-Hall Inc. NJ: Englewood Cliffs. 12. Akter, S., Ambra, J. D., and Ray, R., 2011. An Evaluation of PLS Based Complex Models: The Roles of Power Analysis, Predictive Relevance and GoF Index. Proceedings of the 17th Americas Conference on Information Systems, Detroit, Mich, USA, 4 – 8 August 2011. Published by ACIS. 13. Alavi, M., Gallupe, R. B., 2003. Using Information Technology in Learning: Case Studies in Business and Management Education Programs. Academy of Management Learning & Education, 2 (2), pp. 139-154. 14. AlAwadhi, S., and Morris, A., 2008. The Use of The UTAUT Model in the Adoption of E- Government Services in Kuwait. In: Proceedings of the 41st Annual Hawaii International Conference on System Sciences, Hawaii, USA, 7 – 10 January, 2008, HICSS Publisher. 15. Al-Ghatani, S. S., Hubona, G. S., and Wang, J., 2007. Information Technology in Saudi Arabia: Culture and the Acceptance and Use of IT. Information and Managemet, 44, pp 681-691. 16. Ali, M., and Alshawi, S., 2004. A Cultural Approach to Study Customer Relationship Management (CRM) Systems. In: Proceedings of Conference of Information Science and Technology Management, Alexandria, Egypt, 8 – 9 July 2004, CISTM Publisher. 17. Ali, R. H. R. M., Tretiakov, A., and Crump, B., 2008. Understanding the Impact of National Culture on Strategic Planning. In: Proceeding of 19th Australiasian Conference on Information Systems. Christchurch, 2-5 December 2008. ACIS Publisher. 18. Ali, R. H. R. M., Tretiakov, A., and Crump, B., 2009. Models of National Culture in Information System Research. In: Proceeding of 20th Australasian Conference of Information Systems. Melbourne, 2-4 December 2009. AISeL publisher. 19. Bagchi, K., Cerveny, R., Paul, H., and Petserson, M., 2003. The Influence of National Culture in Information Technology Product Adoption. In: Proceedings of the Ninth 20. Americas Conference on Information Systems 2003, Tampa, FL, USA, 4-6 August 2003. AMCIS publisher. 21. Baltzan, P., Phillips, A., and Haag, S., 2009. Bussiness Driven Technology. Riverview, MI. USA: McGraw-Hill/Irwin. 22. Bandura, A., 1977. Self-Efficacy: Toward a Unifying Theory of Behavioral Change. Psychology Review, 84, pp. 191-215. 23. Bandura, A., 1986. Social Foundations of Thought and Action: A Social Cognitive Theory. Prentice-Hall, Inc. 24. Bandyopadhyay, K., and Fraccastoro, K.A., 2007. The Effect of Culture on User Acceptance of Information Technology. Communication of the Association for Information System, 19, pp. 522-543. 25. Barclay, D., Higgin, C., and Thompson, R., 1995. The Partial Least Squares Approach to Causal Modeling: Personal Computer Adoption and Use as an Illustration. Technology Studies, 2, pp. 285–309. 26. Bates, A.W., 2000. Managing Technological Change. Strategies for College and University Leaders. San Francisco: The Jossey-Bass Higher and Adult Education Series. 27. Berger, P. L., and Luckmann, T., 1967. The Social Construction of Reality. New York: Doubleday. 28. Bhattacherjee, A., and Parthasarathy, M., 1998. Understanding Post-Adoption Behaviour in the Context of Online Services. Information Systems Research, 9 (4). 29. Billings, R. S., and Wroten, S. P., 1978. Use of Path Analysis in Industrial/Organizational Psychology: Criticisms and Suggestions, Journal of Applied Psychology, 63 (6), pp. 677- 688. 30. Blalock, H., 1961. Causal Inferences in Nonexperimental Research. Chapel Hill, NC: University of North Carolina Press. 31. Bollen, K. A., and Long, S. J., 1993. Testing Structural Equation Models. SAGE Focus Edition, 154. 32. Bollen, K., Lennox, R., 1991. Conventional Wisdom on Measurement: A Structural Equation Perspective. Psychological Bulletin, 110 (2), 305-314. 33. Bond, M. H., 1987. Chinese Values and The Search for Culture-Free Dimensions of Culture. Journal of Cross-Cultural Psychology, 18, pp. 143-164. 34. Brancheau, J. C., Wetherbe, J. C., 1990. The Adoption of Spreadsheet Software: Testing Innovation Diffusion Theory in the Context of End-User Computing. Information Systems Research, 1 (2), pp. 115–143. 35. Brosnan, M. J., 1998. The Impact of Computer Anxiety and Self‐Efficacy Upon Performance. Journal of Computer Assisted Learning, 14 (3), pp. 223–234. 36. Byrne, D., 2006. Theory, Role of (in measurement). Encyclopedia of Social Measurement III. 37. Cameron, C. A., 2006. Examining the Relationship that Age, Gender, Experience and Communication Technology has on Acceptance and Use of IT: Using UTAUT model. Ph.D Dissertation, Touro University International, California. 38. Carey, J. M., and Kacmar, C. J., 2010. Cultural and Language Affects on Technology Acceptance and Attitude: Chinese Perspectives. International Journal of Information Technology, 16 (1), pp 1-19. 39. Chau, P. Y. K., 1996. An Empirical Assessment of a Modified Technology Acceptance Model. Journal of Management Information Systems, 13 (2), pp. 185–204. 40. Chau, P. Y. K., and Hu, P. J., 2001. Information Technology Acceptance by Individual Professionals: A Model Comparison Approach. Decision Science, 32 (4), pp. 699-719. 41. Chau, P. Y. K., and Hu, P. J., 2002. Examining a Model Information Technology Acceptance by Individual Professionals: An Exploratory Study. Journal of Management Information System, 18 (4), pp. 191-229. 42. Chen, L., Gillenson, M. L., Sherrell, D. L., 2002. Enticing Online Consumers: A Technology Acceptance Perspective. Information and Management, 39, pp. 705-719. 43. Cheng, Y. S., et. al., 2011. The Comparison of Three Major Occupations for User Acceptance of Information Technology: Applying The UTAUT Model. I-Business, 3, pp. 147-158. 44. Chin, W. W., 2010. How to Write Up and Report PLS Analyses. In Handbook of Partial Least Squares: Concepts, Methods and Application. (Vinzi, E. V.; Chin, W.W.; Henseler, J.; Wang, H.), pp. 645-689. Germany: Springer. 45. Chin, W. W., 1998. The Partial Least Squares Approach to Structural Equation Modeling. In : Modern Methods for Business Research. (G.A. Marcaulides), pp. 295-336. Hillsdale, NJ : Lawrence Erlbraum. 46. Chin, W., and Gopal, A., 1995. Adoption Intention in GSS: Relative Importance of Beliefs. Database, 26 (2 & 3), pp. 42-61. 47. Chin, W.W., and Todd, P. A., 1995. On The Use, Usefulness, and Ease of Use of Structural Equation Modeling in MIS Research: A Note of Caution. MIS Quarterly, 19 (2), pp. 237. 48. Cohen, J., 1988. Statistical Power Analysis for The Behavioral Sciences, 2nd edition. Hillsdale, NJ: Lawrence Erlbaum Associates. 49. Cohen, J., Cohen, P., West, S. G., and Aiken, L. S., 2003. Applied Multiple Regression /Correlation Analysis for the Behavioral Sciences, 3rd edition. Mahwah, NJ: Lawrence Erlbaum Associates. 50. Compeau, D. R., and Higgins, C. A., 1995. Computer Self-Efficacy: Development of a Measure and Initial Test. Management Information Systems Quarterly, 19 (2), pp. 189– 211. 51. 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), pp. 145-158. 52. Cooper, D. R., and Schindler, P. S., 2001. Business Research Methods. New York: McGrew-Hill Companies. 53. Cooper, R. B., 1994. The Inertial Impact of Culture on IT Implementation. Information & Management, 27 (1), pp.17-31. 54. Cronbach, L. J., 1951. Coefficient Alpha and The Internal Structure of Tests. Psychometrika, 16, pp. 297-334. 55. Crothers, L. M., Hughes, T. L., and Morine, K. A., 2008. Theory and Cases in School- Based Consultation: A Resource for School Psychologists, School Counselors, Special Educators, and Other Mental Health Professionals. New York: Routledge Taylor & Francis Group. 56. Crotty, M., 1998. The Foundations of Social Research: Meaning and Perspective in The Research Process. Australia: Allen and Unwin. 57. Davison, A., Burgess, S., and Tatnall, A., 2004. Internet Technologies and Business. Heidelberg, Vic: Data Publishing. 58. Davis, F., 1986. A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results. Doctoral Dissertation, Sloan School of Management, MIT. 59. Davis, F., 1989. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13 (3), 319–340. 60. Davis, F., 1993. User Acceptance of Information Technology - System Characteristics, User Perceptions and Behavioural Impacts. International Journal of Man-Machine Studies, 38 (3), pp. 475-487. 61. 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. 62. 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 (14), pp. 1111-1132. 63. Davison, A. J., Burgess, S., and Tatnall, A., 2003. Internet Technologies and Business. Heidelberg, Vic: Data Publishing Pty Ltd. 64. Davison, A. C., and Hinkley, D.V., 1997. Bootstrap Methods and Their Application. UK: Cambridge University Press. 65. Dorfman, W. P., and Howell J. P., 1988. Dimensions of National Culture and Effective Leadership Patterns: Hofstede Revisited. Advances in International Comparative Management, 3, pp. 127-150. 66. Downey, J., 2006. Measuring General Computer Self-efficacy: The Surprising Comparison of Three Instruments in Predicting Performance, Attitudes, and Usage. In: Proceedings of The 39th Hawaii International Conference on System Sciences. Hawaii, USA, 4-7 January 2006. ICSS Publisher. 67. Edwards, J. R., Bagozzi, R. P., 2000. On The Nature and Direction of Relationships Between Constructs and Measures. Psychological Methods, 5 (2), pp. 155-174. 68. Efron B., Tibshirani, R. J., 1993. An Introduction to The Bootstrap. Monographs on Statistics and Applied Probability. NewYork, NY,USA: Chapman and Hall,\. 69. England, G. W., 1975. The Manager and His Values. Cambridge, MA: Ballinger. 70. Entsua-Mensah, C., 1996. Towards Effective Information Management: A View from Ghana. International Journal of Information Management, 16 (2), pp. 149–56. 71. Erumban, A. A., and de Jong, S. B., 2006. Cross-Country Differences in ICT Adoption: A Consequence of Culture?, Journal of World Business, 41 (4), pp. 302-314. 72. Evers, V., and Day, D., 1997. The Role of Culture in Interface Acceptance. In: Proceeding of IFI TC13 International Conference of Human Computer Interaction. (S.Howard, J. Hammond and G. Lindegaard), London, UK, 14-18 July 1997. Chapman and Hall Publisher. 73. Faisal, S and Yasik, N., 1985. Sosiologi Pendidikan. Surabaya: Usaha Nasional. 74. Falk, R. F., and Miller, N. B., 1992. A Primer for Soft Modeling. Akron, OH: The University of Akron. 75. Fishbein, M., and Azjen, I., 1975. Belief, Attitude, Intention and Behavior. MA : Addison- Wesley, Reading. 76. Fornell, C., and Larcker, D. F., 1981. Evaluating Structural Equation Models With Unobservable Variables and Measurement Error. Journal of Marketing Research, 18 (1), pp. 39-50. 77. Fox, N., Hunn, A., and Mathers, N., 2009. Sample and Sampling. Yorkshire: National Institute for Health Research. 78. Freund, C. L., Weinhold, D., 2002. The Internet and International Trade in Services. The American Economic Review, 92 (2), pp. 236-240. 79. Garvin, D.A., 1993. Building a Learning Organisation. Harvard Business Review, July- August, pp.78-91. 80. Gefen, D., and Straub, D.W., 1997. Gender Differences in The Perception and Use of E- mail: An Extension to The Technology Acceptance. MIS Quarterly, 21 (4), pp. 389 81. Gefen, D., Karahanna, E., and Straub, V., 2003. Trust and TAM in Online Shopping: An Integrated Model. MIS Quarterly, 27 (1), pp. 51–90. 82. Gefen D., and Keil M., 1998. The Impact of Developer Responsiveness on Perceptions of Usefulness and Ease of Use: An Extension of The Technology Acceptance Model. ACM SIGMIS Database, 29 (2), pp. 35-49. 83. Gefen, D., Straub, D. W., and Boudreau, M. C., 2000. Structural Equation Modeling and Regression: Guideline for Research Practice. Communication of the Association for Information System, 1 (7), pp. 1-76. 84. Gefen, D., Straub, D. W., 2000. The Relative Importance of Perceived Ease of Use in IS Adoption: A Study of E-Commerce Adoption, Journal of the Association for Information Systems, 1 (8), pp. 1-30. 85. Geisser, S., 1975. The Predictive Sample Reuse Method With Applications. Journal of the American Statistical Association, 70, pp. 320–328. 86. Geisser, S., 1974. A Predictive Approach to the Random Effects Model, Biometrika 61 (1), pp. 101-107. 87. Ghorab, K. E., 1997. The Impact of Technology Acceptance Considerations on System Usage, and Adopted Level of Technological Sophistication: An empirical investigation. International Journal of Information Management, 17 (4), pp. 249-259. 88. Gill, J., and Johnson, P. , 1997. Research Methods for Managers, 2nd edition. London: Paul Chapman Publishing Ltd. 89. Ginzberg, Michael J., 1981. Key Recurrent Issues in The MIS Implementation Process. MIS Quarterly, 5, pp. 47-59. 90. Gogus, A., Nistor, N., and Lerche, T., 2012. Educational Technology Acceptance Across Cultures: A Validation of The Unified Theory of Acceptance and Use of Technology in The Context of Turkish National Culture. The Turkish Online Journal of Educational Technology, 11 (4), 394-408. 91. Götz, O., Gobbers, K. L., and Krafft, M., 2010. Evaluation of Structural Equation Models using the Partial Least Squares (PLS) Approach. In, Handbook of Partial Least Squares: Concepts, Methods and Applications in Marketing and Related Fields. (Vinzi, V. E., Wang, H., Henseler, J., and Chin, W. W.), Heidelberg: Springer. 92. Haag, S., Baltzan, P., and Phillips, A., 2005. Business Driven Technology. McGraw- Hill/Irwin. 93. Hair, J. F., et. al., 2006. Multivariate Data Analysis: (6 ed). Upper Saddle River, NJ: Prentice Hall. 94. Hair, J. F., William, C. B., Barry, J.B., Anderson, R.E., 2010. Multivariate Data Analysis. Englewood Cliffs, NJ, USA: Prentice Hall. 95. Hair, J. F., Ringle, C. M., Sarstedt, M., 2011. PLS-SEM: Indeed a Silver Bullet. Journal of Marketing Theory and Practice, 19 (2), pp. 139–151. 96. Hair, J. F., Ringle, C. M., Sarstedt, M., Mena, J. A., 2012. An Assessment of The Use of Partial Least Squares Structural Equation Modeling in Marketing Research. Journal of The Academy of Marketing Science, 40 (3), pp. 414–433. 97. Hair, J. F., Ringle, C. M., Sarstedt, M., 2012. Partial Least Squares: The Better Approach to Structural Equation Modeling. Long Range Planning, 45, pp. 312-319. 98. Hall, E. T., 1976. Beyond Culture, New York: Anchor Press. 99. Hall, E., and Hall, M., 1990. Understanding Cultural Differences: Germans, French and Americans. Yarmouth: Intercultural Press. 100. Hamilton Consultants, 2009. Economic Value of the Advertising Supported Internet Ecosystem. Cambridge, Massachusetts. 101. Han, K. T., 2003. A Reliable and Valid Self-Rating Measure of The Restorative Quality of Natural Environments. Landscape and Urban Planning, 64 (4), pp. 209-232. 102. Hasan, H., and Ditsa, G., 1999. The Impact of Culture on the Adoption of IT: An Interpretive Study. Journal of Global Information Management, 7 (1), pp. 5–15. 103. Hatcher, L., 1994. A Step-by-Step Approach to Using the SAS® System for Factor Analysis and Structural Equation Modeling. Cary, N.C.: SAS Institutte, Inc. 104. Haynes, S. N., Richard, D. C. S., and Kubany, E. S., 1995. Content Validity in Psychological Assessment: A Functional Approach to Concepts and Methods. Psychological Assessment, 7, pp. 238-247. 105. Heijden, H. V. D., 2003. Factors Influencing The Usage of Websites-The Case of a Generic Portal in The Netherlands. Information & Management, 40 (6), pp. 541. 106. Hendrickson, A. R., and Collins, M. R., 1996. An Assessment of Structure and Causation of IS Usage. Data Base for Advances in Information Systems, 27 (2), pp. 61-70. 107. Henseler, J., Ringle, C. M., and Sinkovics, R. R., 2009. The Use of Partial Least Squares Pathmodeling in International Marketing. Advances in International Marketing, 20, pp. 277–319. 108. Herskovitz, M. J., 1955. Cultural Anthropology. New York: Knopf. 109. Hill, C. R., Loch, K. D., Straub, D. W., and El-Sheshai, K., 1998. A Qualitative Assessment of Arab Culture and Information Technology Transfer. Journal of Global Information Management, 6 (3), pp. 29–38. 110. Hoffer, J. A., and Alexander, M. B., 1992. The Diffusion of Database Machines. ACM SIGMIS Database, 23 (2), pp. 13-19. 111. Hofstede, G. 1984. Culture Consequences. Newbury Park, CA: Sage. Hofstede, G., 1991. Cultures and Organizations. London: McGraw-Hill, 112. Hofstede, G., 2001. Culture’s Consequences: Comparing Values, Behaviors, Institutions and Organizations Across Nations. 2nd ed. Thousand Oaks: Sage Publications. 113. Hofstede, G., 1993. Cultural Constraints in Management Theories. Academy of Management Executive, 1, pp. 81–94. 114. Hofstede, G., 1980. Motivation, Leadership, and Organizations: Do American Theories Apply Abroad? Organizational Dynamics, 9 (1), pp. 42–63. 115. Hofstede, G., and Bond, M., 1988. The Confucius Connection: From Cultural Roots to Economic Growth. Organizational Dynamics, 16 (1), pp. 4–21. 116. Hofstede, G. H., Hofstede, G. J., and Minkov, M., 2010. Cultures and Organizations: Software of the Mind. Revised and Expanded 3rd Edition. New York: McGraw-Hill. 117. Hong, W. Y., 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. 118. House, R., Javidan, M., and Dorfman, P., 2001. Project GLOBE: An Introduction. Applied Psychology: An International Review, 50 (4), pp. 489-505. 119. 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), pp. 91-112. 120. Huang, K. Y., Choi, N., and Smith, I. C., 2010. Cultural Dimensions as Moderator of the UTAUT Model: A Research Proposal in Healtcare Context. In : Proceeding of 16th American Conference on Information System. Lima, Peru, 12-15 August 2010. AMCIS publisher. 121. Hujran, O., Dalahmeh, A., and Aloudat, A., 2011. The Role of National Culture on Ciizen Adoption of E-Government Services: An Empirical Study. Electronic Journal of e- Government, 9 (2), pp 93-104. 122. Hulland, J., 1999. Use of Partial Least Squares (PLS) in Strategic Management Research: A Review of Four Recent Studies. Strategic Management Journal, 20, pp. 195-224. 123. Hunter, J. E., and Schmidt, F. L., 1990. Methods of Meta-Analysis: Correcting Error and Bias in Research Findings. Newbury Park, CA: Sage. 124. Hussey, J., and R. Hussey, 1997. Business Research: A Practical Guide for Undergraduate and Postgraduate Students. London: Macmillan. 125. Hwang, Y., 2005. Investigating Enterprise System Adoption: Uncertainty Avoidance, Intrinsic Motivation, and The Technology Acceptance Model. European Journal of Information System, 14, pp. 150-161. 126. Hwang, Y., and Yi, M. Y., 2002. Predicting The Use of Web-Based Information Systems: Intrinsic Motivation and Self-Efficacy. Proceedings of The 8th Americas Conference on Information Systems. 127. Igbaria, M., Parasuraman, S., and Baroudi, J. J., 1996. A Motivational Model of Microcomputer Usage, Journal of Management Information Systems, 13 (1), pp. 127-143. 128. Igbaria, M., Zinatelli, N., Cragg, P., and Cavaye, A. L. M., 1997. Personal Computing Acceptance Factors in Small Firms: A Structural Equation Modelling, MIS Quarterly, 21 (3), pp. 279-305. 129. Il, I., Seongtae, H., and Myung, S. K., 2011. An International Comparison of Technology Adoption. Information & Management, 48, pp. 1-8. 130. Iman, A., Khaled, A., Donald, M., and Musa, D., 2006. An Exploratory Analysis of Culture, Perceive Ease of Use, Perceive Usefulness, and Internet Acceptance: The Case of Jordan. Journal of Internet Commerce, 5 (3). 131. Ives, B., and Jarvenpaa, S., 1991. Applications for Global Information Technology: Key issues for Management. MIS Quarterly, 15 (1), pp. 32-49. 132. Jackofsky, E.F., and Slocum, J.W., 1988. CEO Roles Across Cultures. The Executive Effect: Concepts and Methods for Studying Top Managers, 2, pp. 67-98. 133. 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), pp. 357- 389. 134. Jan, A. U., and Contreras, V., 2011. Technology Acceptance Model for The Use of Information Technology in Universities. Computers in Human Behavior, 27, pp. 845-851. 135. Kankanhalli, A., Tan, B. C. Y., Wei, K. K., and Holmes, M. C., 2004. Cross Cultural Differences and Information Systems Developer Values. Decision Support Systems, 38 (2), pp. 183-195. 136. Karahanna, E., and Straub, D., 1999. The Psychological Origins of Perceived Usefulness and Ease of Use. Information & Management, 35, pp. 237–250. 137. 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). 138. Karahanna, E., Evaristo, J. R., and Srite, M., 2005. Levels of Culture and Individual Behavior: An Integrative Perspective. Journal of Global Information Management, 13 (2), pp. 1-20. 139. Kedia, B. L., and Bhagat, R. S.,1998. Cultural Constraints on Transfer of Technology Across Nations: Implications for Research in International and Comparative Management. Academy of Management Review, 13 (4), pp. 559–571. 140. Keeton, K. E., 2008. An Extension of the UTAUT Model: How Organizational Factors and Individual Difference Technology Acceptance. Ph.D Dissertation, University of Houston, Houston. 141. Keller, G., 2005. Statistics for Management and Economics, 7th ed. Duxburym: The Thomson Corporation. 142. Kirsch, L. J., 1996. Portfolios of Control Modes and IS Project Management. Information Systems Research, 8 (3), pp. 215–239. 143. Kirsch, L. J., 2000. Software Project Management: An Integrative Perspective for an Emerging Paradigm. In Framing the Domains of IT Management (ZMUD RW, Eds), pp. 285–304. Cincinnati, OH: Pinnaflex Educational Resources Inc. 144. Kirsch, L. J., and Cumming, L. L., 1997. Contextual Influences on Self-Control of IS Professionals Engaged in Systems Development. Accounting, Management, and Information Technologies, 6 (3), pp. 191–219. 145. Krejcie, R. V., and Morgan, D. W., 1970. Determining Sample Size for Research Activities. Educational and Psychological Measurement, 30, 607-610. 146. Kripanont, N., 2007. Examining a Technology Acceptance Model of Internet Usage by Academics within Thai Business Schools. Ph.D Dissertation. Victoria University, Melbourne, Australia. 147. Kydd, C. T., and Jones, L. H., 1989. Corporate Productivity and Shared Information Technology. Information & Management. 17 (5), pp. 277-282. 148. Lacity, M., and Jansen, M. A., 1994. Understanding Qualitative Data: A Framework of Text Analysis Methods. Journal of Management Information Systems, 11, pp. 137-166. 149. Lederer, A. L., Maupin, D. J., Sena, M. P., and Zhuang, Y. L., 2000. The Technology Acceptance Model and The World Wide Web. Decision Support Systems, 29 (3), pp. 269- 282. 150. Lee, Y., Lee, J., and Lee, Z., 2006. Social Influence of Technology Acceptance Behavior: Self-Identity Theory Prespective. Database for Advance in Information System, Spring 2006, 37 (2/3), pp. 60-75. 151. Lee, O., 2002. Science Inquiry for Elementary Students from Diverse Backgrounds. In W. 152. G. Secada (Ed.), Review of Research in Education, 26, pp. 23-69. 153. Legris, P., Ingham, J., and Collerette, P., 2003. Who Do People Use Information Iechnology? A critical Review of The Technology Acceptance Model. Information & Management, 40, pp. 191-204. 154. Leidner, D. and Kayworth, T., 2006. Review: A Review of Culture In Information Systems Research: Toward a Theory of Information Technology Culture Conflict, MIS Quarterly, 30 (2), pp. 357-399. 155. Leso, T., and Peck, K. L., 1992. Computer Anxiety and Different Types of Computer Courses. Journal of Educational Computing Research, 8 (4), pp. 469-478. 156. Leung, K. Bhagat, R. S., Buchan, N. R., Erez, M., and Gibson, C. B., 2005. Culture and International Business: Recent Advances and Their Implications for Future Research, Journal of International Business Studies, 36 (4), pp. 357–378. 157. Lieras, C., 2005. Path Analysis. Encyclopedia of Social Measurement, 3, pp. 25–30, 2005. 158. Litwin, M. S., 1995. How To Measure Survey Reliability and Validity. The Survey Kit, 7th edition. Thousand Oaks, CA: Sage Publications. 159. Liu, L., 2006. Perceived System Performance: A Test of Extended TAM. Database for Advance in Information System, Spring 2006, 37 (2-3), pp. 51-59. 160. Lodge, G., and Vogel, E., 1987. Ideology and National Competitiveness. Boston: Harvard Business School Press. 161. Lucas, H. C. J., and Spitler, V. K., 1999. Technology Use and Performance: A Field Study of Broker Workstations. Decision Sciences, (30:2), pp. 291-311. 162. MacCallum, R. C.,and Browne, M. W. 1993. The Use of Causal Indicators in Covariance Structure Models: Some Practical. Psychological Bulletin, 114 (3), pp. 533-541. 163. Malhotra, N. K., 2009. Basic Marketing Research: A Decision-Making Approach, 3rd ed, New Jersey, Prentice Hall. 164. Mao, E., and Palvia, P., 2001. Information Technology Acceptance: How Much Do We Know? In : Proceedings of The Seventh Americas Conference on Information System, Boston, USA. 165. Marchewka, J. T., Kostiwa, K., 2007. An Application of UTAUT Model for Understanding Student Persecptions Using Course Management Software. Communication of the IIMA, 7 (2), pp. 93-104. 166. Marin, G., and Marin, B. O., 1991. Research with Hispanic Populations, Newbury Park: Sage Publications. 167. Masiello, B., and Slater, D., Embracing An Innovation Stimulus Package. [online] Available at http://dx.doi.org/10.2139/ssrn.2104350 [Accessed on 12 July 2012]. 168. Mathieson, K., 1991. Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior. Information Systems Research, 2 (3), pp. 173–191. 169. Mathieson, K. Peacock, E. and Chin, W. W., 2001. Extending The Technology Acceptance Model: The Influence of Perceived User Resources. Database for Advances in Information Systems, 32 (3), pp. 86. 170. McCoy, S., 2003. Integrating National Cultural Into Individual IS Adoption Research: The Need for Individual Level Measures. Ninth Americas Conference on Information Systems, USA. 171. McCoy, S., and Everard, A., 2000. The Effect of Culture on IT Diffusion: Using the Technology Acceptance Model to Predict Email Usage in Latin America. Americas Conference on Information Systems, pp. 1899-1901. 172. McCoy, S., Everard, A., and Jones, B., 2005. An Examination of The Technology Acceptance Model in Uruguay and the U.S.: A Focus on Culture. Journal of Global Information Technology, 8, pp. 27-45. 173. McCoy, S., Galletta, D. F., and King, W. R., 2007. Applying TAM Across Cultures: The Need for Caution. European Journal of Information Systems, 16, pp. 81-90. 174. McDonald, R. P., and Ringo Ho, M., 2002. Principles and Practice in Reporting Structural Equation Analyses. Psychological Methods, 7 (1), pp. 64-82. 175. Mead, G. H, 1985. Thought as internalised conversation. Pages 268–281 In Collins, R. (ed.) The Sociological Traditions: Selected Readings. New York: Oxford University Press. 176. Melone, and Nancy, P., 1990. A Theoretical Assessment of the User-Satisfaction Construct in Information Systems Research. Management Science, 36, pp. 76-91. 177. Moon, J. W., and Kim, Y. G., 2001. Extending The TAM for a World-Wide-Web Context. Information & Management, 38 (4), pp. 217-230. 178. Moore, G. C., and Benbasat, I., 1991. Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation. Information Systems Research, 2 (3), pp. 273– 291. 179. Myers, M. D., and Tan, F. B., 2002. Beyond Models of National Culture in Information Systems Research. Journal of Global Information Management, 10 (1), pp. 24-32. 180. Namboodiri, N. K., Carter, L. F., and Blalock, H. M., 1975. Applied Multivariate Analysis and Experimental Designs. New York: McGraw-Hill. 181. Nunnally, J.C., 1979. Psychometric Theory. New York : McGraw-Hill. 182. Pallant, J., 2005. SPSS Survival Manual: A Step by Step Guide to Data Analysis Using SPSS for Windows (Version 12). 2nd. ed. Maidenhead: Open University Press. 183. Palvia, S., Palvia, P. C., and Zigli, M.R., 1992. The Global Issues of Information Technology Management. London: Information Science Publishing. 184. Park, S. Y., 2009. An Analysis of the Technology Acceptance Model in Understanding University Students’ Behavioral Intention to Use E-Learning. Educational Technology & Society, 12 (3), pp. 150-162. 185. Peter, J. P., 1979. Reliability: A Review of Psychometric Basics and Recent Marketing Practices. Journal of Marketing Research, 16, pp. 6-17. 186. Petrides, L. A., 2000. Cases on Information Technology in Higher Education: Implications for Policy and Practice. London: Information Science Publishing. 187. Pinheiro, J. C., and Bates, D. M., 2000. Mixed-Effects Models in S and S-PLUS. Springer Science & Business Media. 188. Png, I. P. L., Tan, B. C. Y., and Wee, K. L., 2001. Dimensions of National Culture and Corporate Adoption of IT Infrastructure. IEEE Transactions on Engineering Management, 48 (1). 189. Prescott, M. B., and Conger, S. A., 1995. Information Technology Innovations: A Cclassification by IT Locus of Impact and Research Approach. Database Advances in Information Systems, 26 (2-3), pp. 20-41. 190. Preston, D. S., Karahanna, E., and Rowe, F., 2006. Development of Shared Understanding Between the Chief Information Officer and Top Management Team in U.S. and French Organizations: A Cross-Cultural Comparison. IEEE Transactions on Engineering Management (53) 2, pp. 191-206. 191. Priyantono, R., 2010. An Investigation Into The Role of Moderating Variables on Mobile Broadband Technology Acceptance in Indonesia. PhD Disertation. Melbourne. RMIT University. 192. Raja Mohd Ali, R. H., Tretiakov, A., and Crump, B., 2009. Models of National Culture in Information System Research. ACIS 2009 Proceeding. Paper 80. 193. Raman, K. S., and Wei, K. K., 1992. The GDSS Research Project. In R. P. Bostrom, R. T. Watson & S. T. Kinney, (Eds.), Computer Augmented Teamwork: A Guided Tour. New York: Van Nostrand Reinhold. 194. Robey, D., and Azevedo, A., 1994. Cultural Analysis of The Organizational Consequences of IT. Accounting, Management and Information Technology, 4 (1), pp. 23–37. 195. Robinson, John P., Shaver, Phillip R., and Wrightsman, Lawrence S., 1991. Criteria for Scale Selection and Evaluation. In: Measures of Personality and Social Psychological Attitudes, (John P. Robinson, Phillip R. Shaver, and Lawrence S. Wrightsman), pp. 1-15. San Diego, CA: Academic. 196. Rogers, E. M., 1983. Diffusion of Innovations. 3rd ed. New York: The Free Press,. 197. Rogers, E. M., 1995. Diffusion of innovations. 4th ed. New York: The Free Press. 198. Roscoe, J. T., 1975. Fundamental Research Statistics for The Behavioural Sciences, 2nd edition. New York: Holt Rinehart & Winston. 199. Rose, G., and Straub, D. W., 1998. Predicting general IT Use: Applying TAM to The Arabic World. Journal of Global Information Management, 6 (3), pp. 39–46. 200. Rosen, L. and Weil, M., 1995. Computer Availability, Computer Experience and Technophobia Among Public School Teachers. Computer in Human Behavior. 11 (1), pp. 9-31. 201. Roy, S., Tarafdar, M., Ragu-Nathan, T. S., and Marsillac, E., 2012. The Effect of Misspecification of Reflective and Formative Constructs in Operations and Manufacturing Management Research. The Electronic Journal of Business Research Methods, 10 (1), pp. 34-52. 202. Ryan, S., Scott, B., Freeman, H., and Patel, D., 2000. The Virtual University: The Internet and Resource-Based Learning. London: Kogan Page. 203. Saadé, R., and Kira, D., 2009. Computer Anxiety in E–learning: The Effect of Computer Self–Efficacy. Journal of Information Technology Education, 8, pp. 1-15. 204. Saadé, R., and Otrakji, C., 2007. First Impressions Last a Lifetime: Effect of Disorientation and Cognitive Load. Computers in Human Behavior, 23 (1), pp. 525-535. 205. Saga, V., and Zmud, R., 1994. The Nature and Determinants of IT Acceptance, Routinization, and Infusion. Proceedings of The IFIP TC8 Working Conference on Diffusion, Transfer and Implementation of Information Technology, pp. 67-86. 206. Sarker, S., Sarker, S., Nicholson, D. B., and Joshi, K. D., 2005. Knowledge Transfer in Virtual Systems Development Teams: An Exploratory Study of Four Key Enablers. IEEE Transactions On Professional Communication, 48 (2), pp. 201. 207. Schaper, L. K., and Pervan, G. P., 2007. ICT and OTs: A Model of Information and Communication Technology Acceptance and Utilization by Occupational Therapists. International Journal of Medical Informatics, 76S, pp. 212-221. 208. Schumacker, R. E., and Lomax, R. G., 1996. A Beginners Guide to Structural Equation Modeling. Hillsdale, NJ: Erlbaum. 209. Schweder, R., and Levine, R., 1984. Culture Theory. New York: Cambridge University Press. 210. Segars, A.H., and Grover, V., 1993. Re-examining Perceived Ease of Use and Usefulness: A Confirmatory Factor Analysis. MIS Quarterly, 17 (4), pp. 517-525. 211. Sekaran, U., 2003. Research Methods for Business A Skill Building Approach, 4th ed. New York: John Willey & Sons, Inc. 212. Semuel, P., 2014. Indonesia Needs to Focus on Internet Development to Boost GDP growth. [online] Available at i. [Accessed on 8 June 2015] 213. Shore, B and Venkatachalam, V., 1994. Prototyping - A Metaphor for Cross-Cultural Transfer and Implementation of IS Applications. Information and Management, 27, pp. 175-184. 214. Shweder, R. A, and Levine, R. A., 1984. Culture Theory: Essays on Mind, Self and Emotion. New York : Cambridge University Press. 215. Smith, B., Caputi, P., and Rawstone, P., 2000. Differentiating Computer Experience and Attitudes towards Computers: An Empirical investigation. Computers in Human Behavior, 16, pp. 59-81. 216. Soares A.M., Farhangmehr, M., and Shoham A., 2007. Hofstede's Dimensions of Culture in International Marketing Studies. Journal of Business Research, 60 (3), pp. 277-284. 217. Srite, M., and Karahanna, E., 2006. The Role of Espoused National Cultural Values in Technology Acceptance. MIS Quarterly 30 (3), pp. 679–704. 218. Sriwindono, H., and Yahya, S., 2012. The Effect of Cultural Dimension on MIS Acceptance. In : Proceeding of 6th IEEE International Conference on Management and Innovation of Technology 2012. Denpasar, Indonesia, 11-13 June 2012. IEEE publisher. 219. Sriwindono, H., and Yahya, S., 2012. Toward Modeling the Effects of Cultural Dimension on ICT Acceptance in Indonesia. In : Proceeding of International Congress on Interdiciplinary Business and Social Science 2012. Jakarta, Indonesia, 1-2 December 2012. Published by Elsevier Ltd. 220. Sriwindono, H., and Yahya, S., 2014. The Influence of Cultural Dimension on ICT Acceptance in Indonesia Higher Learning Institution. Australian Journal of Basic and Applied Sciences, 8S (5), pp. 215-225. 221. Stahl, B. C., 2003. Cultural Universality Versus Particularity In CMC. In: Proceedings of the Ninth Americas Conference on Information Systems, Tampa, FL, USA. 14-16 August 2003. ACIS publisher. 222. Steenkamp, J. E. M., Hofstede, F. T., and Wedel, M., 1999. A Cross-National Investigation into the Individual and National Cultural Antecedents of Consumer Innovativeness. Journal of Marketing, 63 (2), pp. 55–69. 223. Stone, M., 1974. Cross-Validatory Choice and Assessment of Statistical Predictions, Journal of the Royal Statistical Society, 36 (2), pp. 111-147. 224. Stone, M., 1975. Cross-Validatory Choice and Assessment of Statistical Predictions. 225. Journal of The Royal Statistical Society, 36 (2), pp. 111–133. 226. Straub, D. W., 1994. The Effect of Culture on IT Diffusion: E-mail and FAX in Japan and the U.S. Information Systems Research, 5 (1), pp. 23–47. 227. Straub, D. W., Keil, M., and Brenner, W., 1997. Testing The Technology Acceptance Model Across Cultures: A Three Country Study. Information & Management, 33 (1), pp. 1–11. 228. Straub, D. W., Loch, K., Evaristo, R., Karahanna, E., and Srite, M., 2002. Toward a Theory-Based Measurement of Culture. Journal of Global Information Management, 10 (1), 13–23. 229. Subramanian, G. H., 1994. A Replication of Perceived Usefulness and Perceived Ease of Use Measurement. Decision Sciences, 25 (5-6), pp. 863-874. 230. Szajna, B., 1994. Software Evaluation and Choice: Predictive Validation of The Technology Acceptance Instrument. MIS Quarterly, 18 (3), pp. 319-324. 231. Tarcan, E., Varol, E. S., and Toker, B., 2010. A Study on The Acceptance of Information Technologies from The Perspective of Academicians in Turkey. Ege Academic Review, 10 (3), pp. 793-812. 232. Tatnall, A., Paull, S., Burgess, S., and Davey, W., 2003. Business Information System. Heidelberg, Vic : Data Publishing. 233. Taylor, S., and Todd, P. A., 1995. Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, 6 (2), pp. 144–176. 234. Teo, T. S. H., and Lim, R. Y. C., 1999. Intrinsic and Extrinsic Motivation in Interent Usage. OMEGA: International Journal of Management Science, 27, pp. 25-37. 235. 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. 236. Ticehurst, G. W., and Veal, A. J., 2000. Business Research Methods: A Managerial Approach. NSW : Pearson Education Australia. 237. Tornatzky, L. G., and Klein, K. J., 1982. Innovation Characteristics and Innovation Adoption-Implementation: A Meta-Analysis of Findings. IEEE Transactions on Engineering Management, 29 (1), pp. 28-45. 238. Tractinsky, N. & Jarvenpaa, S. L., 1995. Information Systems Design Decisions in a Global Versus Domestic Context. MIS Quarterly, 16 (4), pp. 507-534. 239. Trahan, M. P., 2010. A Structural Equation Modeling Approach to Factors that Contribute to The Impact MyMathlab has on Commitment and Integration of Technology. PhD Dissertation, The Department of Educational Theory, Policy and Practice, Lousiana State University. 240. Triandis, H. C., 1972. The Analysis of Subjective Culture. New York: John Wiley & Sons. 241. Trompenaars, F., 1996. Riding The Waves of Culture: Understanding Cultural Diversity in Business. London: Nicholas Brealey Publishing Limited. 242. Turban, E., Rainer, R. K., and Potter, R. E., 2005. Introduction to Information Technology, 243. 3rd Edition. Pennsylvania : John Willey & Sons, Pennsylvania State University. 244. Van Maanen, J., and Laurent, A., 1993. The Low of Culture: Some Notes on Globalization and The Multinational Corporation. In: Organization Theory and The Multinational Corporation. (Ghoshal, S. and Westney, D.E.), pp. 275–312. New York: St Martin’s Press, 245. Veiga, J. F., Floyd, S., and Dechant, K., 2001. Towards Modeling the Effects of National Culture on IT Implementation and Acceptance. Journal of Information Technology, 16, pp. 145-158. 246. Veiga, J. F., Yanouzas, J., and Buchholtz, A., 1993. Business Practices: An Exercise Comparing Russian Managers. Proceedings of the Fifth Biennial International Management Conference of the Eastern Academy of Management, Berlin, Germany, pp. 56–60. 247. Veiga, J. F., Yanouzas, J., and Buchholtz, A., 1995. Emerging Cultural Values Among Russian Managers: What Will Tomorrow Bring? Business Horizons, 38 (4), pp. 20–27. 248. Venkatesh, V., 1999. Creation of Favorable User Perceptions: Exploring The Role of Intrinsic Motivation. MIS Quarterly, 23, pp. 239–260. 249. Venkatesh, V., 2000. Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into The Technology Acceptance Model. Information Systems Research, 11, pp. 342–365. 250. Venkatesh, V., and Davis, F. D., 1996. A Model of The Antecedents of Perceived Ease of Use: Development and Test. Decision Sciences, 27 (3), pp. 451–481. 251. 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. 252. Venkatesh, V., Morris, M. G., 2000. Why Don’t Men Stop To Ask For Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior, MIS Quarterly, 24 (1), pp. 115-139. 253. 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, pp. 425-475. 254. Venkatesh, V., and Zhang, X., 2013. Unified Theory of Acceptance and Use of Technology: U.S. vs. China. Journal of Global Information Technology Management, 13 (1), 5-27. 255. Vondras, D., 2005. Influence of Individualism-Collectivism on Learning Barriers and Self- Efficacy of Performance Ratings in an Introductory Life-Span Development Course. Paper presented at the annual meeting of the American Psychological Society, Los Angeles, CA. 256. Veena, P., Praveen, P., John, B., and Choton, B. 2005. Perceived Usefulness of Information Technology: Across National Model. Journal of Global Information Technology Management, 8 (4). 257. Werner, O., and Campbell, D., 1970. Translating, Working through Interpreters and The Problem of Decentering. In: Handbook of Cultural Anthropology (R. Naroll and R. Cohen). New York: American Museum of National History. 258. Wold, H., 1982. Soft Modeling: The Basic Design and Some Extensions. In: Systems Under Indirect Observation, (K.G. Jöreskog, Wold, H.), pp. 1-54. Amsterdam: North Holland. 259. Wood, R. E., and Bandura, A., 1989. Social Cognitive Theory of Organizational Management. Academy of Management Review, 14 (3), pp. 361-384. 260. Yi, M. 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, pp. 431–449. 261. Yi, M. Y., et.al., 2006. Understanding Information Technology Acceptance by Individual professionals: Toward an Integrative View. Information and Management, 43, pp 350-363. 262. Yoo, B., Donthu, N., and Lenartowicz, T., 2011. Measuring Hofstede's Five Dimension of Cultural Values at the Individual Level: Development and Validation of Cvscale. Journal of International Consumer Marketing, 23, pp. 193-201. 263. Yoon, C., 2009. The Effects of National Culture Values on Consumer Acceptance of e- Commerce: Online Shoppers in China. Information & Management, 46, pp. 294-301. 264. Yu, L. W., Yu, H. T., and Pei, C. Y., 2007. Using UTAUT to explore the behavior of 3G mobile communication users. Industrial Engineering and Engineering Management, pp. 199-203. 265. Yusron, H., 2014. Akses Internet Perguruan Tinggi Masih Rendah. [online] Available at: 266. http://bisniskeuangan.kompas.com/read/2014/06/11/1609339/Akses.Internet.Perguruan.Tin ggi.Masih.Rendah [Accessed on 10 July 2015] 267. Zhang, A., Yue, X., and Kong, Y., 2011. Exploring Culture Factor Affecting The Adoption of Mobile Payment. In: Proceeding of the 10th International Conference on Mobile Business. Como, Italy, 20-21 June 2011. IEEE Computer Society. 268. Zhao, X. Barbara, B. F., and Roth, A. V., 2007. Decision Sciences Research in China: Current Status, Opportunities, and Propositions for Research in Supply Chain Management, Logistics, and Quality Management. Decision Sciences, 38 (1), pp 39-80. 269. Zikmund, W. G., 2003. Business Research Methods, 7th ed. Ohio: Thomson South- Western. 270. Zorayda, R. A., 2003. E-commerce and E-Business. Manila, Philippines: UNDP-APDIP.

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