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The impact of perceived risks on internet banking adoption in Iran: a longitudinal survey

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Abstract

This paper tried to investigate the trend of changes in severity and the impact of dimensions of perceived risks by customers on their intention to adoption of internet banking (IB) by a longitudinal survey. In order to achieve this goal, based on the perceived risk theory, two surveys were conducted using the same research method in 2009 and 2019 in the Iranian context. The results showed that while the effect of all dimensions of perceived risk in both surveys (except social risk) to adoption of IB were significant, the severity and effect of security and privacy risks increased, time risk decreased and financial and performance risks remained unchanged. Finally, based on the analysis of these results, suggestions were made to modify and optimize banking strategies and policies in order to have a greater impact on reducing these risks.

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References

  1. Rawashdeh, A. (2015). Factors affecting adoption of internet banking in Jordan: Chartered accountant’s perspective. International Journal of Bank Marketing, 33(4), 510–529.

    Article  Google Scholar 

  2. 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 

  3. Hanafizadeh, P., & Khedmatgozar, H. R. (2012). The mediating role of the dimensions of the perceived risk in the effect of customers’ awareness on the adoption of Internet banking in Iran. Electronic Commerce Research, 12(2), 151–175.

    Article  Google Scholar 

  4. Ciciretti, R., Hasan, I., & Zazzara, C. (2009). Do internet activities add value? Evidence from the traditional banks. Journal of Financial Services Research, 35(1), 81–98.

    Article  Google Scholar 

  5. Jaruwachirathanakul, B., & Fink, D. (2005). Internet banking adoption strategies for development country: The case of Thailand. Internet Research, 15(3), 295–311.

    Article  Google Scholar 

  6. Moodley, T., & Govender, I. (2016). Factors influencing academic use of internet banking services: An empirical study. African Journal of Science, Technology, Innovation and Development, 8(1), 43–51.

    Article  Google Scholar 

  7. Roy, S. K., Balaji, M. S., Kesharwani, A., & Sekhon, H. (2017). Predicting Internet banking adoption in India: A perceived risk perspective. Journal of Strategic Marketing, 25(5–6), 418–438.

    Article  Google Scholar 

  8. Rahi, S., Ghani, M., Alnaser, F., & Ngah, A. (2018). Investigating the role of unified theory of acceptance and use of technology (UTAUT) in internet banking adoption context. Management Science Letters, 8(3), 173–186.

    Article  Google Scholar 

  9. Salem, M. Z., Baidoun, S., & Walsh, G. (2019). Factors affecting Palestinian customers’ use of online banking services. International Journal of Bank Marketing, 37(2), 426–451.

    Article  Google Scholar 

  10. Laursen, B. P., Little, T. D., & Card, N. A. (Eds.). (2011). Handbook of developmental research methods. New York: Guilford Press.

    Google Scholar 

  11. Littler, D., & Melanthiou, D. (2006). Consumer perceptions of risk and uncertainty and the implications for behaviour towards innovative retail services: The case of internet banking. Journal of Retailing and Consumer Services, 13(6), 431–443.

    Article  Google Scholar 

  12. Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544–564.

    Article  Google Scholar 

  13. Bauer, R. A. (1960). Consumer behavior as risk taking (pp. 384–398). Chicago, IL.

  14. Hanafizadeh, P., Keating, B. W., & Khedmatgozar, H. R. (2014). A systematic review of Internet banking adoption. Telematics and Informatics, 31(3), 492–510.

    Article  Google Scholar 

  15. Rad, M. S., Nilashi, M., & Dahlan, H. M. (2018). Information technology adoption: A review of the literature and classification. Universal Access in the Information Society, 17(2), 361–390.

    Article  Google Scholar 

  16. Damghanian, H., Zarei, A., & Siahsarani Kojuri, M. A. (2016). Impact of perceived security on trust, perceived risk, and acceptance of online banking in Iran. Journal of Internet Commerce, 15(3), 214–238.

    Article  Google Scholar 

  17. Arora, S., & Kaur, S. (2018). Perceived risk dimensions and its impact on intention to use E-banking services: A conceptual study. Journal of Commerce and Accounting Research, 7(2), 18–27.

    Google Scholar 

  18. Khedmatgozar, H. R., & Shahnazi, A. (2018). The role of dimensions of perceived risk in adoption of corporate internet banking by customers in Iran. Electronic Commerce Research, 18(2), 389–412.

    Article  Google Scholar 

  19. 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 

  20. Chen, C. (2013). Perceived risk, usage frequency of mobile banking services. Managing Service Quality: An International Journal, 23(5), 410–436.

    Article  Google Scholar 

  21. Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1–13.

    Article  Google Scholar 

  22. Yang, Q., Pang, C., Liu, L., Yen, D. C., & Tarn, J. M. (2015). Exploring consumer perceived risk and trust for online payments: An empirical study in China’s younger generation. Computers in Human Behavior, 50, 9–24.

    Article  Google Scholar 

  23. Nguyen, T. D., & Nguyen, T. C. (2017). The role of perceived risk on intention to use online banking in Vietnam. In 2017 international conference on advances in computing, communications and informatics (ICACCI) (pp. 1903–1908). IEEE.

  24. 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 

  25. Moradi, M., Ghomian, M. M., & Sarjanian, Z. (2012). Investigation of the effect of customers’ perceived risk and uncertainty on the usage of the internet banking (A Case Study of Saderat Bank of Mashhad). World Applied Sciences Journal, 18(5), 617–623.

    Google Scholar 

  26. Hua, G. (2009). An experimental investigation of online banking adoption in China. Journal of Internet Banking and Commerce, 14(1), 1–12.

    Google Scholar 

  27. Takieddine, S., & Sun, J. (2015). Internet banking diffusion: A country-level analysis. Electronic Commerce Research and Applications, 14(5), 361–371.

    Article  Google Scholar 

  28. Cohen, L., Manion, L., & Morrison, K. (2018). Research methods in education (8th ed.). New York: Routledge Palmer.

    Google Scholar 

  29. Sreejesh, S., Mohapatra, S., & Anusree, M. R. (2014). Business research methods: An applied orientation. New York: Springer. https://doi.org/10.1007/978-3-319-00539-3.

    Book  Google Scholar 

  30. Venkatesh, V., Morris, M. G., & Ackerman, P. L. (2000). A longitudinal field investigation of gender differences in individual technology adoption decision-making processes. Organizational Behavior and Human Decision Processes, 83(1), 33–60.

    Article  Google Scholar 

  31. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204.

    Article  Google Scholar 

  32. Venkatesh, V., & Brown, S. A. (2001). A longitudinal investigation of personal computers in homes: Adoption determinants and emerging challenges. MIS Quarterly, 25(1), 71–102. https://doi.org/10.2307/3250959.

    Article  Google Scholar 

  33. Hu, P. J. H., Clark, T. H., & Ma, W. W. (2003). Examining technology acceptance by school teachers: A longitudinal study. Information & Management, 41(2), 227–241.

    Article  Google Scholar 

  34. Sun, Y., & Jeyaraj, A. (2013). Information technology adoption and continuance: A longitudinal study of individuals’ behavioral intentions. Information & Management, 50(7), 457–465.

    Article  Google Scholar 

  35. Malaquias, F., Malaquias, R., & Hwang, Y. (2018). Understanding the determinants of mobile banking adoption: A longitudinal study in Brazil. Electronic Commerce Research and Applications, 30, 1–7.

    Article  Google Scholar 

  36. Lynn, P. (Ed.)., Methodology of longitudinal surveys. Chichester: Wiley.

  37. Tryfos, P. (1996). Sampling methods for applied research: Text and cases. New York: Wiley.

    Google Scholar 

  38. Westland, J. C. (2015). Structural equation models. Heidelberg: Springer. https://doi.org/10.1007/978-3-319-16507-3.

    Book  Google Scholar 

  39. Statistical Centre of Iran. (2020). https://www.amar.org.ir/. Accessed 25 Aug 2020.

  40. Tabachnick, B. G., Fidell, L. S., & Osterlind, S. J. (2001). Using multivariate statistics. Boston: Peasron.

    Google Scholar 

  41. Kunnan, A. J. (1998). An introduction to structural equation modelling for language assessment research. Language Testing, 15(3), 295–332.

    Article  Google Scholar 

  42. 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 

  43. 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 

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

    Google Scholar 

  45. 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 

  46. Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879.

    Article  Google Scholar 

  47. 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 

  48. Chin, W. (1998). Commentary: Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), Vii–Xvi. Retrieved November 1, 2020, from http://www.jstor.org/stable/249674.

  49. Matsuo, M., Minami, C., & Matsuyama, T. (2018). Social influence on innovation resistance in internet banking services. Journal of Retailing and Consumer Services, 45, 42–51.

    Article  Google Scholar 

  50. Khan, B. U. I., Olanrewaju, R. F., Anwar, F., Mir, R. N., & Yaacob, M. (2020). Scrutinising internet banking security solutions. International Journal of Information and Computer Security, 12(2–3), 269–302.

    Article  Google Scholar 

  51. Rahi, S., & Ghani, M. A. (2018). The role of UTAUT, DOI, perceived technology security and game elements in internet banking adoption. World Journal of Science, Technology and Sustainable Development, 15(4), 338–356.

    Article  Google Scholar 

  52. Alghazo, J. M., Kazmi, Z., & Latif, G. (2017). Cyber security analysis of internet banking in emerging countries: User and bank perspectives. In 2017 4th IEEE international conference on engineering technologies and applied sciences (ICETAS) (pp. 1–6). IEEE.

  53. Kaur, S., & Arora, S. (2020). Role of perceived risk in online banking and its impact on behavioral intention: Trust as a moderator. Journal of Asia Business Studies. https://doi.org/10.1108/JABS-08-2019-0252.

    Article  Google Scholar 

  54. Chang, Y., Wong, S. F., Libaque-Saenz, C. F., & Lee, H. (2018). The role of privacy policy on consumers’ perceived privacy. Government Information Quarterly, 35(3), 445–459.

    Article  Google Scholar 

  55. Fadare, O. A., Ibrahim, M. B., & Edogbanya, A. (2016). A survey on perceived risk and intention of adopting internet banking. Journal of Internet Banking and Commerce, 21(1), 1–21.

    Google Scholar 

  56. Peotta, L., Holtz, M. D., David, B. M., Deus, F. G., & De Sousa, R. T. (2011). A formal classification of internet banking attacks and vulnerabilities. International Journal of Computer Science & Information Technology, 3(1), 186–197.

    Article  Google Scholar 

  57. Vanaki, M., Taghva, M. R., & Taghavifard, M. T. (2017). IT security management implementation model in Iranian bank industry. Journal of Information Technology Management, 9(2), 379–404.

    Google Scholar 

  58. Baruh, L., Secinti, E., & Cemalcilar, Z. (2017). Online privacy concerns and privacy management: A meta-analytical review. Journal of Communication, 67(1), 26–53.

    Article  Google Scholar 

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Acknowledgements

The author is indebted to Dr. Payam Hanafizadeh from Allameh Tabataba’i University, Tehran, Iran for his guidance in basic research in 2009 and Professor Byron W. Keating from Queensland University of Technology, Brisbane, Australia for comments on earlier versions of this paper.

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Correspondence to Hamid Reza Khedmatgozar.

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Khedmatgozar, H.R. The impact of perceived risks on internet banking adoption in Iran: a longitudinal survey. Electron Commer Res 21, 147–167 (2021). https://doi.org/10.1007/s10660-021-09475-y

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