18Sep 2017

THE EFFECT OF TECHNOLOGY ACCEPTANCE MODEL (TAM) TOWARD ACTUAL USAGE THROUGH BEHAVIORAL INTENTION IN REAL EFFORT TO INCREASE INTERNET BANKING USERS IN INDONESIA.

  • Universitas Pelita Harapan Surabaya.
Crossref Cited-by Linking logo

  • Abstract
  • Keywords
  • References
  • Cite This Article as
  • Corresponding Author

Banking is one industris that is currently growing rapidly. With the development of information technology, it will create such a great opportunity for the financial service providers in this industry. This opportunity can be used to further expand its business towards information technology. One of the banking products based on information technology today is internet banking. According to Shih and Fang (2006) internet banking is a new type of information system that uses emerging techniques, such as the Internet and th e World Wide Web, and has changed the way consumers do various financial activities in a virtual space. The purpose of the study is to determine the characteristics of internet banking users and to know the factors that influence the survey user of internet banking. It is expected that this research will broaden the knowledge of the long-term information technology. This will make information technology, such as internet banking, can be used, not only in industry banking, but various commercial and non-commercial brand business. The research method used in this study is non probability sampling on several big cities in Indonesia. The data processing analysis is using multiple regression with SPSS 20.00 software. The results of this data processing will be conducted wih an in-depth discussion on the characteristics of internet banking users and the factors that affect the use of internet banking in Indonesia. The results of this study are divided into two parts. First, the results of qualitative research successfully strengthens the research model. The variables of perceived usefulness, perceived ease of use, perceived credibility, compatibility, personal innovativeness, and social influence do affect the interest in using internet banking, in in the end, the real utilization in using the internet banking. In addition, using quantitative research successfully generated indicators for each valid and reliable variables, namely 3 indicators from actual usage, 4 indicators from behavioral intention, 6 indicators from perceived usefulness, 6 indicators from perceived ease of use, 4 indicators from perceived credibility, 4 indicators from compatibility, 3 indicators from personal innovativeness, and 4 indicators from social influence.

  1. Agarwal, R. and Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research Vol. 9 No.2, 204?215.
  2. Aggelis, V., 2005. The bible of e-banking. New technologies Publications, Athens
  3. Ajzen, I. and Fishbein, M. ?Understanding Attitudes and Predicting Social Behavior?. Englewood Cliffs, NJ: Prentice-Hall. 1980.
  4. Anderson, C., Glassman, M., McAfee, R., Pinelli, T. An investigation of factors affecting how engineers and scientists seek information. Journal of Engineering and Technologi Management (JET-M) 18 (2), 131-155. 2001.
  5. Blackwell, R. D., Miniard, P. W., and Engel, J. F. (2006). Consumer Behavior 10th Mason: Thomson South-Western.
  6. Chong, A. Y.-L., Ooi, K.-B., Lin, B., and Tan, B.-I. (2010). Online banking adoption: an empirical analysis. International Journal of Bank Marketing Vol. 28 No. 4 , 267-287.
  7. Dabholkar, P., A., Bobbitt, L., Lee, E., -J., 2003. Understanding consumer motivation and behavior related to self-scanning in retailing. Implications for strategy and research on technology-based self-service. International Journal of Service Industry Management, 14, 1, 59-95
  8. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease Of Use, And User Acceptance of Information Technology. MIS Quarterly Vol. 13 No.3 , 319-340.
  9. Davis, F., D., Bagozzi, R., P., Warshaw, P., R., 1989. User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35, 8, 982-1003
  10. Devaraj, S., Kohli, R. Performance impacts of information technology: is actual usage the missing links. Management Science 49 (3), 273?289. 2003.
  11. Epper, K., Kutler, J., 1995. Dinosaur remark by Gates sets off technology alarms. The American Banker, January 4, 16
  12. Ganesan, S. ?Determinants of long-term orientation in buyer-seller relationships?; Journal of Marketing, 58 (2), 1-19. 1994.
  13. Ghozali, I. (2004). Model Persamaan Struktural: Konsep and Aplikasi dengan Program AMOS Ver.5.0. Semarang: Baand Penerbit Universitas Diponegoro.
  14. Grandy, T., 1995. Banking in E-Space. The Banker, 145, December, pp74-75
  15. Guriting, P., and Ndubisi, N. O. (2006). Borneo online banking: evaluating customer perceptions and behavioural intention. Management Research News Vol. 29 No. 1/2 , 6-15.
  16. Hair, J. R., William, C. B., & Barry, J. B. (2006). Multivariate Data Analysis 6th Amerika: Pearson Pentice Hall.
  17. Hernandez, J. M., and Mazzon, J. A. (2007). Adoption of internet banking: proposition and implementation of an integrated methodology approach. International Journal of Bank Marketing Vol. 25 No. 2 , 72-88.
  18. Hoyer, W. D., and MacInnis, D. (2007). Consumer Behavior Fourth Edition. Boston: Houghton Mifflin.
  19. Igbaria, M., Tan, M. The consequences of information technology acceptance on subsequent individual performance. Information & Management 32, 113?121. 1997.
  20. Jang, S., Liu, Y., and Namkung, Y. (2011). Effects of authentic atmospherics in ethnic restaurants: investigating Chinese restaurants. International Journal of Contemporary Hospitality Management Vol. 23 No. 5 , 662-680.
  21. Jani, D., and Han, H. (2011). Investigating the key factors affecting behavioral intentions Evidence from a full-service restaurant setting. International Journal of Contemporary Hospitality Management Vol. 23 No. 7 , 1000-1018.
  22. Jayasingh, S., and Eze, U. C. (2009). An Empirical Analysis of Consumer Behavioral Intention Toward Mobile Coupons in Malaysia. International Journal of Business and Information Vol.4 No.2 , 221-242.
  23. Kleijnen, Mirella, Martin Wetzels, and Ko de Ruyter. (2004). Consumer acceptance of wireless finance. Journal of Financial Services Marketing, Vol 8(3), 206-217.
  24. Koenig-Lewis, N., Palmer, A., and Moll, A. (2010). Predicting young consumers? take up of mobile banking services. International Journal of Bank Marketing Vol. 28 No. 5 , 410-432.
  25. Kolodinsky, J., M., Hogart, J., M., Hilgert, M., A., 2004. The adoption of electronic banking technologies by US consumers. The International Journal Of Bank Marketing, 22, 4, 238-259
  26. Kuo, Y.-F., and Yen, S.-N. (2009). Towards an understanding of the behavioral intention to use 3G mobile value-added services. Computers in Human Behavior 25 , 103?110.
  27. Lai, W.-T., and Chen, C.-F. (2011). Behavioral intentions of public transit passengers?The roles of service quality, perceived value, satisfaction and involvement. Transport Policy18 , 318?325.
  28. Lin, H.-F. (2007). Predicting consumer intentions to shop online: An empirical test of competing theories. Electronic Commerce Research and Applications 6 , 433?442.
  29. Lu, J., Liu, C., Yu, C., and Wang, K. (2008). Determinants of accepting wireless mobile data services in China. Information and Management Vol.45 No.1, 52?64.
  30. Lu, J., Yao, J. E., and Yu, C.-S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. Journal of Strategic Information Systems 14 , 245?268.
  31. Lu, J., Yu, C. S., Liu, C. and Yao, J. E. ?Technology acceptance model for wireless Internet?; Internet Research, 13(3), 206?222. 2003.
  32. Lu, Y., Zhou, T., and Wang, B. (2009). Exploring Chinese users? acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior 25 , 29?39.
  33. Luarn, P., and Lin, H.-H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior 21 , 873?891.
  34. Lymperopoulos, C., 1994. Strategic bank marketing. Interbooks Publications, Athens
  35. Molinari, L., and Blaber, S. (2002). Customer Service and its Effects on Customer Retention and Defection. Midwest Academy of Management 2002 ProceedingsAnnual Conference ?Outpacing the Competition: How do Speed, Sustainability,Technology, and Teamwork Lead to the Winner?s Circle??(p. ...). Indianapolis: University of Southern Indiana.
  36. Moon, J.-W., and Kim, Y.-G. (2001). Extending the TAM for a World-Wide-Web context. Information and Management 38 , 217-230.
  37. Moore, G. C., and Benbasat, I. (1991). Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation. Information Research Vol.2 No.3 , 192-222.
  38. Namkung, Y. and Jang, S.C. (2007). Does Food Quality Really Matter in Restaurant? Its Impact on Customer Satisfaction and Behavioral Intentions. Journal of Hospitality and Tourism Research 46, 279.
  39. Ndubisi, N. O., and Jantan, M. (2003). Evaluating IS usage in Malaysian small and medium-sized firms using the technology acceptance model. Logistics Information Management Vol. 16 , 440-450.
  40. Pollard, C. Exploring continued and discontinued use of IT: a case study of OptionFinder, a group support system. Group Decision and Negotiation 12 (3), 171?193. 2003.
  41. Premkumar, G. and Bhattacherjee, Anol. (2008). Explaining information technology usage:A test of competing models. Omega 36, 64 ? 75.
  42. Puschel, J., Mazzon, J. A., and Hernandez, J. M. (2010). Mobile banking: proposition of an integrated adoption intention framework. International Journal of Bank Marketing Vol. 28 No. 5 , 389-409.
  43. Sadiq-Sohail, M., Shanmugham, B., 2003. E-banking and customer preferences in Malaysia: an empirical investigation. Information Sciences, 150, ?, 207-217
  44. Sambasivan, M., and et.al. (2010). User acceptance of a G2B system:a case of electronic procurement system in Malaysia. Internet Research Vol. 20 No. 2 , 169-187.
  45. Santoso, S. (2000). Buku Latihan SPSS Statistik Parametrik. PT Elex Media Komputindo.
  46. Schierz, P. G., Schilke, O., and Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications 9 , 209?216.
  47. Schiffman, L. G., and Kanuk, L. L. (2007). Consumer Behavior 9th Edition . New Jersey: Pearson Prentice Hall.
  48. Serenko, A. (2008). A model of user adoption of interface agents for email notification. Interacting with Computers 20 , 461?472.
  49. Shih, Y., -Y., Fang, K., 2006. Effects of network quality attributes on customer adoption intentions of internet banking. Total Quality Management, 17, 1,61-77
  50. Shin, D.-H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior 25 , 1343?1354.
  51. Taylor, S., Todd, P. Understanding information technologi usage: a test of competing model. .Information System Research 6 (2), 144-176. 1995.
  52. Thompson, R.L., C. Higgins and J. M. Howell. (1991). Personal Computing: Towards a Conceptual Model of Utilization. MIS Quarterly, Vol. 15(1), 125-143
  53. Turner, M., Kitchenham, B., Brereton, P., Charters, S., and Budgen, D. (2010). Does the technology acceptance model predict actual use? A systematic literature review. Information and Software Technology 52 , 463?479.
  54. Venkatesh, V., Morris, M., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly Vol. 3, 425?478.
  55. Wang, Y., Lo, H. P., & Hui, Y. V. (2003). The Antecedents of Service Quality and Product Quality and Their Influences on Bank Reputation: Evidence From The Banking Industry in China. Managing Service Quality , 72-83.
  56. Yang, K. C. C. (2005). Exploring factors affecting the adoption of mobile commerce in Singapore. Telematics and Informatics, 22(3), 257?277.
  57. Zeithmal, V. A., Bitner, M. J., and Gremler, D. D. (2009). Service Marketing Integrating Customer Focus Across the Firm Fifth Edition. New York : McGraw-Hill.
  58. http://sp2010.bps.go.id/
  59. http://tonnymarezco.wordpress.com/2014/04/17/sejarah-internet-banking/
  60. bi.go.id
  61. internetworldstats.com/stats3.

[Amelia Amelia and Ronald Ronald. (2017); THE EFFECT OF TECHNOLOGY ACCEPTANCE MODEL (TAM) TOWARD ACTUAL USAGE THROUGH BEHAVIORAL INTENTION IN REAL EFFORT TO INCREASE INTERNET BANKING USERS IN INDONESIA. Int. J. of Adv. Res. 5 (Sep). 866-879] (ISSN 2320-5407). www.journalijar.com

Amelia Amelia
Universitas Pelita Harapan Surabaya

DOI:

Article DOI: 10.21474/IJAR01/5401      
DOI URL: https://dx.doi.org/10.21474/IJAR01/5401

Download Full Paper

Download PDF No. of Downloads: 398 | No. of Views: 841