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The mediating role of the dimensions of the perceived risk in the effect of customers’ awareness on the adoption of Internet banking in Iran

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Abstract

One of the major issues banks are faced with in providing Internet Banking (IB) services is the adoption of these services by the customers. This study seeks answer to the question that whether bank customers’ awareness of the services and advantages of IB is effective in reducing the negative effect of customers’ perceived risk on their intention of IB adoption. To this end, the two constructs of the dimensions of the perceived risk and IB awareness are simultaneously considered. Besides, in the research model, the effect of IB awareness on each dimension of the perceived risk and the effect of these dimensions on intention of IB adoption by the customers are investigated. The results indicate that IB awareness acts as a factor reducing all dimensions of the perceived risk (including time, financial, performance, social, security, and privacy). In addition, it was found out that except for social risk, other dimensions of the perceived risk have significantly negative effect on the intention of IB adoption. Finally, proving the direct and positive effect of IB awareness on adoption intention, it was concluded that the dimensions of customers’ perceived risk plays a mediating role in the positive effect of IB awareness on IB adoption intention. In this respect, management approaches centered on the concept of IB awareness are offered for reducing the dimensions of customers’ perceived risk.

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References

  1. Ajzen, I. (1985). From intentions to actions: a theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action control: from cognition to behavior (pp. 11–39). Heidelberg: Springer.

    Google Scholar 

  2. Akinci, S., Aksoy, S., & Atilgan, E. (2004). Adoption of Internet banking among sophisticated consumer segments in an advanced developing country. International Journal of Bank Marketing, 22(3), 212–232.

    Article  Google Scholar 

  3. Aladwani, A. M. (2001). Online banking: a field study of drivers, development challenges and expectations. International Journal of Information Management, 21(3), 213–225.

    Article  Google Scholar 

  4. Aldas-Manzano, J., Lassala-Navarre, C., Ruiz-Mafe, C., & Sanz-Blas, S. (2009). The role of consumer innovativeness and perceived risk in online banking usage. International Journal of Bank Marketing, 27(1), 53–75.

    Article  Google Scholar 

  5. Al-Somali, S. A., Gholami, R., & Clegg, B. (2009). An investigation into the acceptance of online banking in Saudi Arabia. Technovation, 29(2), 130–141.

    Article  Google Scholar 

  6. Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.

    Article  Google Scholar 

  7. Angelakopoulos, G., & Mihiotis, A. (2011). E-banking: challenges and opportunities in the Greek banking sector. Electronic Commerce Research, 11(3), 297–319.

    Article  Google Scholar 

  8. Association of Payment Clearing Services (Apacs). http://www.ukpayments.org.uk/media_centre/press_releases/-/page/871/. Last accessed on 2010-10-24.

  9. Azouzi, D. (2009). The adoption of electronic banking in Tunisia: An exploratory study. Journal of Internet Banking and Commerce, 14(3), 1–11.

    Google Scholar 

  10. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs: Prentice-Hall.

    Google Scholar 

  11. Baron, R., & Kenny, D. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic and statistical considerations. Journal of Personality and Social Psychology. Monograph Supplement, 51(6), 1173–1182.

    Article  Google Scholar 

  12. Barrett, P. (2007). Structural equation modeling: Adjudging model fit. Personality and Individual Differences, 42(5), 815–824.

    Article  Google Scholar 

  13. Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246.

    Article  Google Scholar 

  14. Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606.

    Article  Google Scholar 

  15. Bestavros, A. (2000). Banking industry walks ‘tightrope’ in personalization of web services. Bank Systems + Technology, 37(1), 54–56.

    Google Scholar 

  16. Bollen, B., & Long, B. C. (1993). Testing structural equation models. Newbury Park: Sage.

    Google Scholar 

  17. Butler, R. A. (2007). Framework of anti-phishing measures aimed at protecting the online consumer’s identity. Electronic Library, 25(5), 517–533.

    Article  Google Scholar 

  18. Castañeda, J. A., & Montoro, F. J. (2007). The effect of Internet general privacy concern on customer behavior. Electronic Commerce Research, 7(2), 117–141.

    Article  Google Scholar 

  19. Central Bank of I.R. Iran. http://www.cbi.ir/simplelist/2546.aspx. Last accessed on 2010-10-24.

  20. Chan, S., & Lu, M. (2004). Understanding Internet banking adoption and use behavior: a Hong Kong perspective. Journal of Global Information Management, 12(3), 21–43.

    Article  Google Scholar 

  21. Chau, P. Y. K. (1997). Re examining a model for evaluating information center success using a structural equation modeling approach. Decision Sciences, 28(2), 309–334.

    Article  Google Scholar 

  22. Chiang, M. H., & Teng, C. I. (2003). Installed base collapsing strategies with network externalities. Journal of Management, 20(5), 829–857.

    Google Scholar 

  23. Cook, J. D., Hepworth, S. J., Wall, T. D., & Warr, P. B. (1981). The experience of work. San Diego: Academic Press.

    Google Scholar 

  24. Cooper, R. G. (1997). Examining some myths about new product winners. In R. Katz (Ed.), The human side of managing technological innovation (pp. 550–560). London: Oxford University Press.

    Google Scholar 

  25. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of computer technology. Management Information Systems Quarterly, 13(3), 319–340.

    Article  Google Scholar 

  26. DePallo, M. (2000). National survey on consumer preparedness and e-commerce: A survey of computer users age 45 and older. Washington: AARP.

    Google Scholar 

  27. Dowling, G. R. (2004). The art and science of marketing. Oxford: Oxford University Press.

    Book  Google Scholar 

  28. Eriksson, K., Kerem, K., & Nilsson, D. (2008). The adoption of commercial innovations in the former Central and Eastern European markets: The case of Internet banking in Estonia. International Journal of Bank Marketing, 26(3), 154–169.

    Article  Google Scholar 

  29. Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: a perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474.

    Article  Google Scholar 

  30. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: an introduction to theory and research. Reading: Addison Wesley.

    Google Scholar 

  31. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

    Article  Google Scholar 

  32. Gemünden, H. G. (1985). Perceived risk and information search: a systematic meta-analysis of the empirical evidence. International Journal of Research in Marketing, 2(2), 79–100.

    Article  Google Scholar 

  33. Gerrard, P., Cunningham, J. B., & Devlin, J. F. (2006). Why consumers are not using Internet banking: a qualitative study. The Journal of Services Marketing, 20(3), 160–168.

    Article  Google Scholar 

  34. Gholami, R., Dolores Anon Higon, M., Hanafizadeh, P., & Emrouznejad, A. (2010). Is ICT the key to development? Journal of Global Information Management, 18(1), 66–83.

    Article  Google Scholar 

  35. Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1995). Multi-variate data analysis with readings. Englewood Cliffs: Prentice-Hall International.

    Google Scholar 

  36. Hatcher, L. (1994). A step-by-step approach to using the SAS(R) system for factor analysis and structural equation modeling. Cary: SAS Institute.

    Google Scholar 

  37. Heeler, R. M., & Ray, M. L. (1972). Measure validation in marketing. Journal of Marketing Research, 9(4), 361–370.

    Article  Google Scholar 

  38. Hernandez, J. M. C., & Mazzon, J. A. (2007). Adoption of Internet banking: proposition and implementation of an integrated methodology approach. International Journal of Bank Marketing, 25(2), 72–88.

    Article  Google Scholar 

  39. Hinkin, T. R. (1995). A review of scale development practices in the study of organizations. Journal of Management, 21(5), 967–988.

    Article  Google Scholar 

  40. Howcroft, B., Hamilton, R., & Hewer, P. (2002). Consumer attitude and the usage and adoption of home-based banking in the United Kingdom. International Journal of Bank Marketing, 20(2), 111–121.

    Article  Google Scholar 

  41. Hu, L. T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to under parameterized model misspecification. Psychological Methods, 3(4), 424–453.

    Article  Google Scholar 

  42. Internet Word State (UK). http://www.Internetworldstats.com/eu/uk.htm. Last accessed on 2010-10-24.

  43. Internet Word State (IRI). http://www.Internetworldstats.com/me/ir.htm. Last accessed on 2010-10-24.

  44. Jackson, P. R., Wall, T. D., Martin, R., & Davids, K. (1993). New measures of job control, cognitive demand, and production responsibility. Journal of Applied Psychology, 78(5), 753–762.

    Article  Google Scholar 

  45. Jacoby, J., & Kaplan, L. B. (1972). The components of perceived risk. Paper presented at the 3rd Annual Convention of the Association for Consumer Research, Chicago, Illinois, 2–6 November.

  46. Jarvenpaa, S. L., & Todd, P. A. (1997). Consumer reactions to electronic shopping on the World Wide Web. Journal of Electronic Commerce Research, 1(2), 59–88.

    Google Scholar 

  47. Jun, M., & Cai, S. (2001). The key determinants of Internet banking service quality: A content analysis. International Journal of Bank Marketing, 19(7), 276–291.

    Article  Google Scholar 

  48. Kalakota, R., & Whinston, A. (1997). Electronic commerce: a manager’s guide. Reading: Addison Wesley.

    Google Scholar 

  49. Kaplan, L. B., Szybillo, G. J., & Jacoby, J. (1974). Components of perceived risk in product purchase: a cross validation. Journal of Applied Psychology, 59(3), 278–291.

    Article  Google Scholar 

  50. Kenny, D. A. (2001). Measuring model fit. New York: Wiley.

    Google Scholar 

  51. Lai, V. S., & Li, H. (2005). Technology acceptance model for Internet banking: an invariance analysis. Information & Management, 42(2), 373–386.

    Article  Google Scholar 

  52. Lee, M. C. (2009). Factors influencing the adoption of Internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8(3), 130–141.

    Article  Google Scholar 

  53. Lichtenstein, S., & Williamson, K. (2006). Understanding consumer adoption of Internet banking: an interpretive study in the Australian context. Journal of Electronic Commerce Research, 7(2), 50–66.

    Google Scholar 

  54. Lim, N. (2003). Consumers’ perceived risk: sources versus consequences. Electronic Commerce Research and Applications, 2(3), 216–228.

    Article  Google Scholar 

  55. Littler, D., & Melanthiou, D. (2003). Consumer perceptions of risk and uncertainty and the implications for behavior towards innovative retail services: the case of Internet banking. Journal of Retailing and Consumer Services, 13(6), 431–443.

    Article  Google Scholar 

  56. Mandrik, C. A., & Bao, Y. (2005). Exploring the concept and measurement of general risk aversion. Advances in Consumer Research, 32, 531–539.

    Google Scholar 

  57. Marsh, H. W., & Hocevar, D. (1985). Application of confirmatory factor analysis to the study of self-concept: First- and higher order factor models and their invariance across groups. Psychological Bulletin, 97(3), 562–582.

    Article  Google Scholar 

  58. Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(1), 20–38.

    Article  Google Scholar 

  59. Mukherjee, A., & Nath, P. (2003). A model of trust in online relationship banking. International Journal of Bank Marketing, 21(1), 5–15.

    Article  Google Scholar 

  60. Narayanasamy, K., Rasiah, D., & Tan, T. M. (2011). The adoption and concerns of e-finance in Malaysia. Electronic Commerce Research, 11(4), 383–400.

    Article  Google Scholar 

  61. Ndubisi, N. O. (2007). Customers’ perceptions and intention to adopt Internet banking: the moderation effect of computer self-efficacy. Journal of Knowledge, Culture and Communication (AI & SOCIETY), 21(3), 315–327.

    Google Scholar 

  62. Nunnally, J. C. (1978). Psychometric theory (Vol. 2). New York: McGraw-Hill.

    Google Scholar 

  63. Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101–134.

    Google Scholar 

  64. Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: an extension of the technology acceptance model. Internet Research, 14(3), 224–235.

    Article  Google Scholar 

  65. Polasik, M., & Wisniewski, T. P. (2009). Empirical analysis of Internet banking adoption in Poland. International Journal of Bank Marketing, 27(1), 32–52.

    Article  Google Scholar 

  66. Prompattanapakdee, S. (2009). The adoption and use of personal Internet banking services in Thailand. The Electronic Journal on Information Systems in Developing Countries, 37(6), 1–31.

    Google Scholar 

  67. Rogers, E. M. (1983). Diffusion of innovations. New York: Free Press.

    Google Scholar 

  68. Rogers, E. M., & Shoemaker, F. (1971). Communications in innovation. New York: Free Press.

    Google Scholar 

  69. Roselius, T. (1971). Consumer rankings of risk reduction methods. Journal of Marketing, 35(1), 56–61.

    Article  Google Scholar 

  70. Sathye, M. (1999). Adoption of Internet banking by Australian consumers: an empirical investigation. International Journal of Bank Marketing, 17(7), 324–334.

    Article  Google Scholar 

  71. Sayar, C., & Wolfe, S. (2007). Internet banking market performance: Turkey versus the UK. International Journal of Bank Marketing, 25(3), 122–141.

    Article  Google Scholar 

  72. Schriesheim, C. A., & Hill, K. (1981). Controlling acquiescence response bias by item reversal: The effect on questionnaire validity. Educational and Psychological Measurement, 41(4), 1101–1114.

    Google Scholar 

  73. Segars, A. H., & Grover, V. (1993). Re-examining perceived ease of use and usefulness: a confirmatory factor analysis. Management Information Systems Quarterly, 17(4), 517–525.

    Article  Google Scholar 

  74. Spector, P. E. (1992). Summated rating scale construction: An introduction. Sage University paper series on quantitative applications in the social sciences. Newbury Park: Sage.

    Google Scholar 

  75. Straub, D., Boudreau, M. C., & Gefen, D. (2004). Validation guidelines for IS positivist research. Communications of the Association for Information Systems, 13, 380–427.

    Google Scholar 

  76. Suh, B., & Han, I. (2002). Effect of trust on customer acceptance of Internet banking. Electronic Commerce Research and Applications, 1(3), 247–263.

    Article  Google Scholar 

  77. Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: a test of competing models. Information Systems Research, 6(2), 144–176.

    Article  Google Scholar 

  78. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 45(2), 186–204.

    Article  Google Scholar 

  79. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. Management Information Systems Quarterly, 27(2), 425–478.

    Google Scholar 

  80. Vrechopoulos, A. P., Siomkos, G. J., & Doukidis, G. I. (2001). Internet shopping adoption by Greek consumers. European Journal of Innovation Management, 4(3), 142–153.

    Article  Google Scholar 

  81. Westland, J. C. (2002). Transaction risk in electronic commerce. Decision Support Systems, 33(1), 87–103.

    Article  Google Scholar 

  82. White, H., & Nteli, F. (2004). Internet banking in the UK: why are there not more customers? Journal of Financial Services Marketing, 9(1), 49–56.

    Article  Google Scholar 

  83. Yiu, C. S., Grant, Y. K., & Edgar, D. (2007). Factors affecting the adoption of Internet banking in Hong Kong: implications for the banking sector. International Journal of Information Management, 27(5), 336–351.

    Article  Google Scholar 

  84. Yousafzai, S. Y., Pallister, J. G., & Foxall, G. R. (2003). A proposed model of e-trust for electronic banking. Technovation, 23(11), 847–860.

    Article  Google Scholar 

  85. Zhao, A. L., Hanmer-Lloyd, S., Ward, P., & Goode, M. M. H. (2008). Perceived risk and Chinese consumers’ Internet banking services adoption. International Journal of Bank Marketing, 26(7), 505–525.

    Article  Google Scholar 

  86. Zolait, A. H. S., & Ainin, S. (2008). Incorporating the innovation attributes introduced by Rogers’ theory into theory of reasoned action: An examination of Internet banking adoption in Yemen. Computer and Information Science, 1(1), 36–51.

    Google Scholar 

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  1. School of Management and Accounting, Allameh Tabataba’i University, Nezami Ganjavi Street, Tavanneer, Valy Asr Avenue, P.O. Box 14155-6476, Tehran, Iran

    Payam Hanafizadeh

  2. Department of Financial Engineering, University of Science and Culture, Tehran, Iran

    Hamid Reza Khedmatgozar

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  1. Payam Hanafizadeh
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Hanafizadeh, P., Khedmatgozar, H.R. The mediating role of the dimensions of the perceived risk in the effect of customers’ awareness on the adoption of Internet banking in Iran. Electron Commer Res 12, 151–175 (2012). https://doi.org/10.1007/s10660-012-9090-z

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