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Distribution information safety and factors affecting the intention to use digital banking in Vietnam

The Journal of Distribution Science / The Journal of Distribution Science, (P)1738-3110; (E)2093-7717
2020, v.18 no.6, pp.83-91
https://doi.org/https://doi.org/10.15722/jds.18.6.202006.83
NGUYEN, Dat Ngoc
NGUYEN, Dat Dinh
NGUYEN, Duy Van
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Abstract

Purpose: Research on the behavior of using digital banking services plays an important role for banks in the context of increasingly competitive banks, not only for domestic banks but also for foreign banks. Along with the development of science and technology brings new approaches to banking industry, digital banking increases the effectiveness of banking activities. Besides, information safety brings different feeling about digital banking system. Therefore, this research evaluates the relationship between Information safety and Intention to use banking services in Vietnam. Research design, data and methodology: With 329 Vietnamese customers using digital banking, reliability test, and structural equation model (SEM) analysis method. Results: the research shows that information safety has directly effects on perceived ease of use (PU), perceived risk (RIS) of customers to digital banking services. Perceived trust (TRU) has a negative impact on RIS. Perceived of usefulness (PEU) has a positive impact on attitude towards service (ATT), and RIS has a negative impact on ATT. RIS, PEU, ATT, convenience and enterprise image have positive effects on intention to use digital banking service. Conclusions: From the research results, the authors also propose some recommendations to enhance the intention to use digital banking services in Vietnam.

keywords
Distribution information safety, intention to use, digital banking

Reference

1.

Ajzen, I., & Fishbein, M. (1975). A Bayesian analysis of attribution processes. Psychological Bulletin, 82(2), 261–277. https://doi.org/10.1037/h0076477

2.

Chang, Y.-W., & Polonsky, M. J. (2012). The influence of multiple types of service convenience on behavioral intentions: The mediating role of consumer satisfaction in a Taiwanese leisure setting. International Journal of Hospitality Management,31(1), 107–118. https://doi.org/10.1016/j.ijhm.2011.05.003

3.

Chen, Y.-H., Hsu, I.-C., & Lin, C.-C. (2010). Website attributes that increase consumer purchase intention: A conjoint analysis. Journal of Business Research, 63(9), 1007–1014.https://doi.org/10.1016/j.jbusres.2009.01.023

4.

Dam, V. H., & Bui, T. T. D. (2017). Researching customers’intention to use electronic banking services at Vietnamese commercial banks. 242, 69–79.

5.

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. JSTOR. https://doi.org/10.2307/249008

6.

Davis, F. D. (1993). User acceptance of information technology:System characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3),475–487. https://doi.org/10.1006/imms.1993.1022

7.

Eastlick, M. A., Lotz, S. L., & Warrington, P. (2006). Understanding online B-to-C relationships: An integrated model of privacy concerns, trust, and commitment. Journal of Business Research, 59(8), 877–886.https://doi.org/10.1016/j.jbusres.2006.02.006

8.

Erkan, I., & Evans, C. (2016). The influence of eWOM in social media on consumers’ purchase intentions: An extended approach to information adoption. Computers in Human Behavior, 61, 47–55.https://doi.org/10.1016/j.chb.2016.03.003

9.

Fortes, N., & Rita, P. (2016). Privacy concerns and online purchasing behaviour: Towards an integrated model. European Research on Management and Business Economics, 22(3),167–176. https://doi.org/10.1016/j.iedeen.2016.04.002

10.

Glover, S., & Benbasat, I. (2010). A Comprehensive Model of Perceived Risk of E-Commerce Transactions. International Journal of Electronic Commerce, 15(2), 47–78. https://doi.org/10.2753/JEC1086-4415150202

11.

Guru, B., Shanmugam, B., Alam, N., & Perera, J. (2003). An Evaluation Of Internet Banking Sites In Islamic Countries. Journal of Internet Banking and Commerce, 8, 1–11.

12.

Ha, S., & Stoel, L. (2009). Consumer e-shopping acceptance:Antecedents in a technology acceptance model. Journal of Business Research, 62(5), 565–571.https://doi.org/10.1016/j.jbusres.2008.06.016

13.

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham,R. L. (2006). Multivariate data analysis 6th Edition. Critique and Reformulation. Journal of Abnormal Psychology, 87, 49–74.

14.

Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural Equation Modelling: Guidelines for Determining Model Fit. Electronic Journal of Business Research Methods, 6(1), 53–60.

15.

Kang, G., & James, J. (2004). Service quality dimensions: An examination of Grönroos’s service quality model. Managing Service Quality: An International Journal, 14(4), 266–277.https://doi.org/10.1108/09604520410546806

16.

Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling, Fourth Edition. New York, NY: Guilford Publications.

17.

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.https://doi.org/10.1016/j.elerap.2008.11.006

18.

Mbama, C. I., & Ezepue, P. O. (2018). Digital banking, customer experience and bank financial performance: UK customers’perceptions. International Journal of Bank Marketing, 36(2),230–255. https://doi.org/10.1108/IJBM-11-2016-0181

19.

Nguyen, N. D., Nguyen, T. H., Dang, B. N., & Nguyen, V. D.(2016). Factors affecting consumer’s buying behaviour toward tourism products on internet: An empirical investigation of Hanoi Consumers. Journal of Economics and Development, 245, 77–88.

20.

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.https://doi.org/10.1080/10864415.2003.11044275

21.

Sayar, C., & Wolfe, S. (2007). Internet banking market performance: Turkey versus the UK. International Journal of Bank Marketing, 25(3), 122–141.https://doi.org/10.1108/02652320710739841

22.

Smith, H. J., Milberg, S. J., & Burke, S. J. (1996). Information Privacy: Measuring Individuals’ Concerns about Organizational Practices. MIS Quarterly, 20(2), 167–196. JSTOR. https://doi.org/10.2307/249477

23.

Tabachnick, B. G., & Fidell, L. S. (2006). Multivariate analysis of grouped data (Palm Springs). In Invited workshop presented to the meeting of the Western Psychological Association.

24.

Van Slyke, C., Shim, J. T., Johnson, R., & Jiang, J. J. (2006). Concern for Information Privacy and Online Consumer Purchasing. Journal of the Association for Information Systems, 7(6). https://doi.org/10.17705/1jais.00092

25.

Venkatesh, V. (2000). Determinants of Perceived Ease of Use:Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. Information Systems Research, 11(4), 342–365. https://doi.org/10.1287/isre.11.4.342.11872

26.

Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926

27.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478. JSTOR. https://doi.org/10.2307/30036540

28.

Wang, J.-S., & Pho, T. S. (2009). Drivers of customer intention to use online banking: An empirical study in Vietnam. African Journal of Business Management, 3(11), 669–677.

29.

Werthner, H., & Klein, S. (1999). ICT and the Changing Landscape of Global Tourism Distribution. Electronic Markets,9(4), 256–262. https://doi.org/10.1080/101967899358941

30.

Westin, A. F. (1970). Privacy and Freedom. Science and Society, 34(3), 360–363.

31.

Yoon, H. S., & Barker Steege, L. M. (2013). Development of a quantitative model of the impact of customers’ personality and perceptions on Internet banking use. Computers in Human Behavior, 29(3), 1133–1141.https://doi.org/10.1016/j.chb.2012.10.005

The Journal of Distribution Science