Digital banking in vietnam: An application of the utaut model

Nội dung text: Digital banking in vietnam: An application of the utaut model

1. DIGITAL BANKING IN VIETNAM: AN APPLICATION OF THE UTAUT MODEL Ph.D Do Thi Ngoc Anh1 – Ph.D Nguyen Thi Bich Vuong2 MA. Han Thi Thuy Linh3 Abstract: Before the outbreak of information technology, the great benefits of digital banking services brought to banks, so Vietnamese commercial banks implemented this service. However, the number of Vietnamese people using digital banking services is not much or they use but mainly use payment money transfer services. The purpose of this study is to find out the factors affecting the adoption of digital banking services by customers, so that there are suggestions for the bankers in developing this service. Research model based on UTAUT theory with 4 factors (expected effectiveness, expected effort, favorable conditions, social influence) and 2 additional factors (convenience, reliability). The author conducted a survey of 273 customers using digital banking services at commercial banks in Hanoi city and using SPSS 25.0 software for analysis. Research results show that there are 6 factors that positively affect the adoption of digital banking services: expected efficiency, expected effort, favorable conditions, social influence, convenience, reliability and in which the convenience factor has the strongest influence. This research result will be a suggestion for Vietnamese bankers in the development of digital banking services. Keywords: Digital banking service, UTAUT model, Vietnamese commercial bank. 1. INTRODUCTION In recent years, the development of information technology has allowed banks to revolutionize new service delivery models that meet consumer expectations and maintain a competitive advantage. Among new service delivery platforms, digital banking is a channel providing efficient and cost– effective banking services. Therefore, the deployment of digital banking services at commercial banks in Vietnam is now necessary. Digital banking brings great benefits to both banks and customers. For customers, Digital Banking saves time and costs (Malhotra, 2010; Pew, 2003). For banks, Digital Banking helps banks save costs, increase profits (Malhotra, 2010), improve customer satisfaction, and increase customer loyalty to the bank (Yiu and Edgar, 2007; Guru et al., 2003). In fact, in recent years, the number of Vietnamese people using digital banking services is increasing, but the percentage of users is still low and the majority use money transfer services, few people use transmission services such as deposits and loans on the Digital Banking services of banks. According to a survey by IDG Vietnam, 81% of respondents said they used Digital Banking in 2018, while it was 21% in 2015. However, according to Vietnamese market habits and characteristics, Vietnam's digital banking service also faces certain obstacles. In Vietnam, the majority of people use cash for payment, according to Standard Chartered Bank in 2019, Vietnam has 90.1% of cash payments for online purchases. Therefore, research on the customer's acceptance to use digital banking services at Vietnamese commercial banks is necessary. 1 Deputy Head of Accounting and Commercial Banking Payments Department, Hanoi University of Business and Technology. Email: nddothingocanh@gmail.com. 2 Head of Banking and Finance Faculty, Bac Ha International University. E.mail: Violet1072007@gmail.com. 3 Deputy Dean of Accounting Faculty, Dai Nam University. Email: hanthuylinh@gmail.com. 86
2. 2. RESEARCH OVERVIEW Digital Banking is a relatively new concept in Vietnam. Digital banking is a form of banking that digitizes all traditional banking activities, including Internet Banking and Mobile Banking. Customers can make all transactions on the bank's website and mobile application on devices connected to the Internet without going to the bank, anytime, anywhere. Digital Banking is the transformation of all traditional banking operations and services into a digital environment (Sarma, 2017). The empirical studies on the intention to use and accept the use of digital banking services in the past based on theories, theoretical research models: planned behavioral theory TPB (Ajzen; 1985); Technology Acceptance Model – TAM (Davis et al., 1989); Diffusion of Innovation Theory – IDT (Rogers, 1995); The Unified Theory of Acceptance and Use of Technology – UTAUT (Venkatesh et al., 2003) to explain customers' adoption of digital banking, has shown influencing factors such as: security, usefulness, ease of use, convenience, reliability, risk. The UTAUT theory is considered to be the most effective in explaining technology adoption intent and behavior, accounting for 70% of the difference in the interpretation of technology intentions (Venkatesh et al., 2003). In this study, using UTAUT theory to explain about the bank's adoption of digital banking services by the impacting factors: expected effectiveness, expected effort, social influence and favorable conditions. 3. RESEARCH MODEL AND HYPOTHESIS The research model is designed based on domestic and foreign overview on the research of factors affecting the use of digital banking services, the model in this study is beyond 4 factors (Expected effectiveness, Expected effort, Social influences, Favorable conditions) of the UTAUT theoretical model by Venkatesh et al. (2003) with two additional factors (Reliability, Convenience) to study their effects to the acceptance of using Digital Banking service of customers at Vietnamese commercial banks. Diagram 1. Research model Expected effectiveness effectiveness Expected effort effectiveness effectivenessSocial influence Accept using digital banking services Favorable conditions Reliability Convenience Source: Author proposed Research hypothesis: The expected effectiveness is the extent to which a person can easily participate in the technology system and use the technology system (Vankatesh et al., 2003). "Effortless Expectation" has a similarity in understanding with the concept of "Ease of Use Perception". Researches on the acceptance of using digital banking services, Internet banking service by Emadand Michael (2009); Apostolos et 87
3. al. (2012); Tiong (2020) thinks that the factor "Effort to expect" has a positive effect. Customers who feel easy to use digital banking services will accept to use more. Expected effectiveness is the confidence of individuals that using a technology system will help them achieve greater effectiveness (Vankatesh et al., 2003). The concept "Expected effectiveness" has a similarity with "Usefulness to use". The UTAUT theory of Vankatest et al. (2003) shows that "Expected effectiveness" has a significant effect on technology adoption. Apostolos et al. (2012); Praja (2005); Tiong (2020) thinks that the expected effectiveness has a positive effect on the acceptance of using digital banking services and Internet banking services by customers at banks. Therefore, the author proposes the research hypothesis as: H1: Expected effectiveness has a positive impact on the adoption of digital banking services at commercial banks in Vietnam. The expected effort is the extent to which a person can easily participate in the technology system and use the technology system (Vankatesh et al., 2003). "Expected effort" has a similarity in understanding with the concept of "Ease of use perception". Researches on the acceptance of using digital banking services, Internet banking service by Emadand Michael (2009); Apostolos et al. (2012); Tiong (2020) thinks that the factor "Expected effort" has a positive effect. Customers who feel easy to use digital banking services will accept to use more. Therefore, the author proposes the research hypothesis as: H2: Expected effort has a positive impact on the adoption of digital banking services at commercial banks in Vietnam. The favorable condition is that the individual believes that the organization's support and the facilities will facilitate the use of the system (Venkatesh et al., 2003).Venkatesh et al. (2003) points out the factor "Favorable conditions" that directly affects the behavior of using technology. This is confirmed in the research results of Emad and Michael (2009); Foon et al. (2011), Dong (2009) said that it has a significant influence on the intention and behavior of using digital banking. Therefore, if the bank has the support and creates favorable conditions for customers, they will accept to use more. Therefore, the author proposes the research hypothesis as: H3: Favorable condition has a positive impact on the adoption of digital banking services at commercial banks in Vietnam. The social influence is defined by Venkatesh et al. (2003), social influence is the influence of others on personal feelings that will have a strong impact on their use of the new system. The factor “Social influence” has a positive and significant influence on the “Intended use behavior” and indirectly affects the “Actual use behavior” of the technology system. This result is also confirmed in studies on digital banking services such as Dong (2009); Emadand Michael (2009); Foon et al. (2011); Tiong (2020) Therefore, the adoption of digital banking services is influenced by those around. Therefore, the author proposes the research hypothesis as: H4: Social influence has a positive impact on the adoption of digital banking services at commercial banks in Vietnam. The convenience of digital banking users is not simply 24/7, time–saving access but an Internet extension that helps digital banking users to learn more and more services. their needs and convenient implementation (Sharman, 2006). The more convenient digital banking service, the more customers accept it (Wadie, 2011; Jayaraman et al., 2012). Therefore, the author proposes the research hypothesis as: 88
4. H5: Convenience has a positive impact on the adoption of digital banking services at commercial banks in Vietnam. The reliability is supposed to be customers who trust in using the service without fear of risk of personal financial information or assets. The higher the customer confidence in a bank's digital banking service, the more customers will accept to use it. The customer has sufficient confidence, and the customer will find a more useful website or banking application (Stewart, 2003). This is also confirmed in the research results of Foon et al. (2011); Ingoo Han (2002); Gang Liu et al. (2008). Therefore, the author proposes the research hypothesis as: H6: Reliability has a positive impact on the adoption of digital banking services at commercial banks in Vietnam. 4. RESEARCH METHODOLOGY Data for the study was collected through a questionnaire. The questionnaire is designed based on a 2–part research overview: The first part is the demographic assessment of the respondents including gender, age, education level, occupation and the second part is Customer's perception of digital banking service with a 5–level Likert scale from 1–Strongly disagree to 5–Strongly agree. Research using a sampling method is a convenient method. Survey subjects are customers who are using digital banking services of commercial banks in Hanoi city. Survey time is from August 2020 to the end of September 2020. The way to distribute the survey is done by 2 methods: Method 1 send the answer answer link via Email; Method 2 survey directly at transaction counters of banks. The tool used to analyze is the data analysis software SPSS 25.0. 5. RESEARCH RESULTS 5.1. Sample analysis results The number of questionnaires is 300 votes, the number of valid collected votes for analysis is 274. Collected data were used using SPSS 25.0 software for statistical analysis. The characteristics of the study sample detailed in Table 1 below show that 51.6% of the respondents are female and 48.4% of the respondents are male. Most of the respondents are from 18 to 45 years old, accounting for 76.2%. Respondents' education level is 10.9% at high school, 37.6% at high school, 27.5% at university, and 28.9% above university. Most of the respondents have a monthly income of over 5 million to 10 million, accounting for 40.3%. Table 1. Sample survey statistics Gender Frequency Percent Female 141 51.6 Valid Male 132 48.4 Total 273 100 Age Frequency Percent Under18 25 9.2 Valid From 18 to 30 96 35.2 From 31 to 45 112 41.0 89
5. From 46 to 60 30 10.6 Above 60 10 4.0 Total 273 100 Education level Frequency Percent High school 30 10.9 Intermediate and college 89 37.6 education levels Valid University education 75 27.5 Education level above 79 28.9 university Total 273 100 Occupation Frequency Percent Under 5million 33 12.0 5 million to10 million 110 40.3 Valid 10 million to 20 million 68 24.9 Above 20 million 62 22.7 Total 273 100 Source: Research results of the author 5.2. Results assess the reliability of the scale Cronbach's Alpha coefficients are used to evaluate the reliability of the scale in the study. In the test to assess the reliability of Cronbach's Alpha on the scales, only variables with total variable correlation coefficients greater than 0.3 and Cronbach's Alpha coefficient greater than 0.6 are considered acceptable and appropriate to include in next step analysis. Test results for groups of observed variables are shown as follows: Table 2. Summary of scale measurement results Cronbach's Scale Mean if Scale Variance if Corrected Item– Cronbach' Item Alpha if Item Item Deleted Item Deleted Total Correlation s Alpha Deleted Expected Effectiveness HQ1 11.49 5.317 0.565 0.790 HQ2 11.37 5.131 0.645 0.754 0.810 HQ3 11.25 4.951 0.599 0.776 HQ4 11.29 4.668 0.705 0.723 Expected Effort NL1 7.070 2.293 0.458 0.721 NL2 7.420 1.929 0.640 0.495 0.727 NL3 7.330 2.179 0.520 0.649 90
6. Social Influence XH1 13.81 13.711 0.870 0.942 XH2 13.76 13.484 0.872 0.941 XH3 13.84 13.859 0.847 0.946 0.953 XH4 13.83 13.369 0.858 0.944 XH5 13.75 13.414 0.901 0.936 Favorable Condition DK1 10.22 6.089 0.802 0.862 DK2 10.19 6.483 0.816 0.859 0.900 DK3 10.13 6.583 0.758 0.879 DK4 10.08 6.210 0.743 0.886 Reliability TC1 10.80 6.588 0.763 0.856 TC2 10.77 6.514 0.796 0.843 0.892 TC3 10.63 6.748 0.746 0.862 TC4 10.67 6.897 0.724 0.870 Convenience TL1 10.74 7.250 0.797 0.912 TL2 10.67 7.235 0.817 0.905 0.925 TL3 10.67 7.184 0.830 0.901 TL4 10.66 7.153 0.858 0.891 Accept using digital banking services CNSD1 7.000 1.835 0.721 0.797 CNSD2 6.940 1.805 0.707 0.811 0.853 CNSD3 7.000 1.728 0.744 0.775 Source: Research results of the author The results of the scale test show that the total variable correlation coefficients of all observed variables with the factors that these variables represent are greater than 0.3, the lowest is the NL1 scale with the total variable correlation coefficient of 0.458. Cronbach's Alpha coefficients total of all factors are greater than 0.7, in which the factor with the lowest total Cronbach's Alpha coefficient is the factor “Expected effort” is 0.727. Crobach's Alpha if the variable types of all observed variables of each factor are less than Crobach's Alpha total. Thus, no observed variables are removed and the scale is suitable and reliable for the next EFA analysis. 5.3. Results of Exploratory Factor Analysis (EFA) After testing the reliability of the scale with Crobach's Alpha coefficients, the scales are suitable for exploratory factor analysis EFA. Exploratory factor analysis (EFA) is the next step in factor 91
7. analysis to make judgments about the convergence of factors and the number of factors given from the survey data. In factor analysis results, it is necessary to satisfy the following requirements: KMO coefficient (Kaiser – Meyer – OlKIN) ≥ 0.5, significance level of Bartllett test ≤ 0.05. Factor Loading ≥ 0.50, if any observed variable has factor load factor <0.50, it will be disqualified. The scale is accepted when the total variance extracted is ≥ 50%. The Eigenvalue coefficient must be ≥ 1. The analytical results are shown in Table 3 below: Table 3. Results of Exploratory Factor Analysis (EFA) Item 1 2 3 4 5 6 XH5 0.879 XH2 0.838 XH1 0.821 XH4 0.817 XH3 0.789 TL4 0.875 TL2 0.841 TL3 0.838 TL1 0.837 DK2 0.881 DK1 0.873 DK3 0.805 DK4 0.795 TC3 0.837 TC1 0.827 TC2 0.824 TC4 0.823 HQ4 0.793 HQ3 0.745 HQ2 0.698 HQ1 0.694 NL2 0.801 NL3 0.755 NL1 0.604 Total variance 36.928 48.678 57.772 66.263 71.404 76.161 Eigenvalues 8.863 2.820 2.183 2.038 1.234 1.142 KMO = 0.876, Sig = 0.000 Source: Research results of the author 92
8. According to the analysis results shown in the table above, it shows: Bartlett's test results show that there are correlation between the variables in the population (Sig = 0.000 1, confirming that there are 06 factors drawn from the analysis; The total variance coefficients extracted from 06 factors is 76.161%, showing the variation of the factors given by the analysis, which can explain 76,161% of the variation of the original survey data. The extracted variance value is greater than 50%, so it also meets the analysis requirements. The analysis results of the rotation matrix show that there are observations that XH1 has a load factor of factor 1 and component 5 and the difference of the load factor in these 2 components is > 0.3; and observing that HQ2 also has load factor in component 5 and component 1, the effect of load factor in these 2 components is > 0.3. Therefore, none of the observed types XH1, HQ2 and observed variables are converged in 6 factors, and the above observed variables all have factor load coefficients greater than 0.5 to ensure the standard, no observed variables have coefficient lies in the two groups with the deviation < 0.3. Therefore, it is not necessary to exclude any observed variables in the analysis. 5.4. Results of correlation analysis Correlation analysis is used to evaluate the relationship between the independent variables HQ, NL, XH, DK, TC, TL to the dependent variable. Pearson correlation test is used to test linear relationships between the independent variables and the dependent variable. The test results are shown in Table 4 below: Table 4. Correlation matrix among the variables HQ NL XH DK TC TL CNSD HQ 1 NL 0.489 1 XH 0.560 0.521 1 DK 0.200 0.227 0.396 1 TC 0.256 0.252 0.403 0.309 1 TL 0.380 0.311 0.375 0.396 0.395 1 CNSD 0.550 0.521 0.704 0.580 0.622 0.700 1 Correlation is significant at the 0.01 level (2–tailed). * Correlation is significant at the 0.05 level (2–tailed). Source: Research results of the author The Pearson correlation test results in the table above show that the independent variables are correlated with the dependent variable "Accept to use Digital banking" with significance level Sig = 0.000 < 0.01. Pearson's correlation coefficient between the dependent and independent variables is relatively high. All independent variables are positively related to the variable accepting Digital banking service with coefficients in the range from 0.521 to 0.704. Therefore, it can be seen that the factors "Expected Effectiveness, Expected Effort, social influence, favorable conditions, convenience, reliability" are all correlated with the acceptance of the Digital banking service in Vietnam. In which, the factor “Favorable conditions” has the largest correlation coefficient 0.704, 93
9. followed by the factor “Convenience” with the correlation coefficient of 0.622 and the lowest is the factor “Social influence” with correlation coefficient is 0.521. 5.5. Results of regression analysis The results of correlation coefficient analysis show that there is a correlation of the independent variables to the dependent variable, the regression analysis will confirm this correlation and give the influence of each factor with the variable depends on that. Regression analysis, we care about the following values: Adjusted R Square according to theory > 50% to ensure reliability, the model is consistent with the research data; Sig in ANOVA analysis 50% of the evaluation results on the adoption of digital banking services by customers in Vietnam. This shows that the research data model ensures the reliability and consistency of the model with the research data. The Durbin–Watson coefficient = 1.910, close to the value 2, showing the residuals of the independent variables with no correlation. 94
10. The coefficient F = 213.221, Sig = 0.000 < 0.05 in the ANOVA test shows that the reliability of the regression analysis results is guaranteed with low error. Next looking at the regression results table, we see that the Sig coefficient of the factors in the regression table also has the value Sig < 0.05, which confirms that the factors that affect the dependent variable are accept using Digital banking services. VIF coefficients of all factors reach value less than 2, so there is no multicollinearity phenomenon between independent variables. Thus, the test results for the regression model have achieved good results, the regression function represents the influence of the independent variables with the dependent variable in the model with high reliability. The standardized regression equation takes the following form: CNSD = 0.108*HQ + 0.107*NL + 0.272*XH + 0.213*DK + 0.259*TC + 0.337*TL The results of regression analysis show that all 6 factors positively affect the adoption of digital banking services in Vietnam: Expected Effectiveness (HQ), Expected Effort (NL), Social Influence (XH), Favorable Conditions (DK), Reliability (TC), Convenience (TL). In which the factor "Convenience" has the strongest influence with the impact coefficient of 0.337, followed by the factor "Social influence" with the coefficient 0.272, followed by the factor "Reliability" with the coefficient 0.259, another is "Favorable Condition" with the coefficient 0.213 and the factor with low effect is " Expected Effectiveness" with the coefficient 0.108 and "Expected Effort" with the coefficient 0.107. 6. CONCLUSION Research results show that customers' perception of the Expected effectiveness of Digital banking services has a positive impact on adoption. This result is consistent with the UTAUT theory and the previous research results of Apostolos et al. (2012); Praja (2005); Tiong (2020). Customers feel that the more useful Digital banking services are to use, the more they will accept to use them. When banks improve the usefulness of Digital banking services to perform all over–the–counter transactions, the number of customers accepting Digital banking services increases. Therefore, the factor "Expected Effectiveness" has a positive influence on the use of Digital banking customers in the bank. Research results show that efforts to expect customer perception of Digital banking services have a positive effect on adoption. This result is consistent with UTAUT theory and previous studies on the adoption of Digital banking by Emadand Michael (2009); Apostolos et al. (2012); Tiong (2020). Research results show that the easier it is to use Digital banking, the more customers will accept this service. Therefore, the bank designed the App, the website meets the optimal standards of service quality, the login makes Digital banking transactions easily, user–friendly, using easy–to–understand words. The simplest and most adaptable device with Internet connection, but security, the number of people using this service increases. Therefore, the factor "Expected Effort" has a positive influence on the customer's acceptance of using Digital banking services. The analysis results show that the factor "Social influence" positively affects the adoption of Digital banking services. This research result is consistent with UTAUT theory and some findings in the studies of Foon et al. (2011); Tiong (2020); Dong (2009). Customers accepting to use Digital banking services are influenced by those around them via Electronic word of mouth, through word of mouth. Therefore, the greater the factor "Social influence" on Digital banking services, the more and more acceptance it will use. The factor "Favorable conditions" in this study has been shown to have a positive impact on customers' adoption of Digital banking services. This is consistent with UTAUT theory and findings 95
11. indicated in studies by Foon et al. (2011), Dong (2009). This result is consistent with the fact in banks, if banks are willing to support and promptly handle incidents, it will increase customer satisfaction and increase the level of using this service. Thus, customers' perceptions of “Favorable conditions” have a significant positive impact on their use of Digital banking services. The results of this study also show that customers' perceptions of the reliability of Digital banking services have a positive effect on adoption. This result is consistent with previous studies by Foon et al. (2011); Ingoo Han (2002); Gang Liu et al. (2008). In fact, customers are still afraid, they are afraid of insecurity and certainty in Digital banking transactions. Therefore, the greater the perception of customers about the reliability of Digital banking transactions, the more acceptance of this service will be. The research results show that the convenience of Digital banking has a positive effect on customers' acceptance of this service. The study's findings are consistent with those of previous studies by Wadie (2011); Jayaraman et al. (2012). The convenience of Digital banking will determine the customer's acceptance for use. Customers can perform over–the–counter transactions via Digital banking anywhere, when except for cash withdrawal. Therefore, the more convenient customers feel that Digital banking is, the more they will accept it. Based on the theory of accepting the use of UTAUT technology, review of studies to build research models, survey questionnaires. The collected data was cleaned and analyzed, the results showed that there are 6 factors that affect the adoption of customers' Digital banking at commercial banks in Vietnam, that is: Expected Effectiveness, Expected Effort, Favorable conditions, Social influence, Reliability and Convenience in which convenience has the strongest influence. REFERENCES 1. Ajzen, I. (1985), From Intentions to Actions: A Theory of Planned Behavior’, in Action Control, From Cognition to Behavior, J. Kuhl and J. Beckmann (eds.), New York: Springer–Verlag, pp.11–39. 2. Apostolos, G. (2006), Internert banking and the law in Europe, Regulation, Financial Integration and Electronic Commerce, University Cambrige, pp.8 3. Davis, F.D., Bagozzi, R.P. and Warshaw, P.R. (1989),User acceptance of computer technology: a comparison of two theoretical models, Management Science, Vol.8, pp. 982–1003. 4. Dong, C. (2009), User acceptance of internet banking: an extension of the UTAUT model with trust and quality constructs, Int. J. Services Operations and Informatics, Vol.4, pp.378–393 5. Emad, A. and Michael, P. (2009), Internet Banking in Jordan: An Arabic Instrument Validation Process, The International Arab Journal of Information Technology, Vol.3, pp. 235–247 6. Foon, Y., and F., B., (2011), Internet Banking Adoption in Kuala Lumpur: An Application of UTAUT Model, International Journal of Business and Management, Vol. 4, pp.161–167. 7. Gang Liu, G., Su–Ping, H., Xin–Kai, Z. (2008), User acceptance of Internet banking in an uncertain and risky environment, The International Conference on Risk Management & Engineering Management, pp.381–386 8. Guru, B., Shanmugam, B., Alam, N., & Perera, J. (2003), An Evaluation Of Internet Banking Sites In Islamic Countries, Journal of Internet Banking and Commerce, Vol.8, pp.1–11. 9. Ingoo and Bomil, (2002), Effect of trust on customer acceptance of Internet banking, Electronic Commerce Research and Applications, Vol.1, pp. 247–263. 96
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