CC BY
140
Вестник Челябинского государственного университета. 2019. № 7 (429). Экономические науки, вып. 65. С. 161—171.
УДК 339 10.24411/1994-2796-2019-10718
ББК 65.9 (5Вье)
FACTORS AFFECTING THE INTENTION TO USE OF INTERNET BANKING OF CUSTOMERS IN VIETNAM'S COMMERCIAL BANKS IN INDUSTRIAL REVOLUTION CONTEXT 4.0
Nguyen Chien Thang, Ly Hoang Mai1, Nguyen Thi Kim Chi2, Vu Trung Kien3
1 Vietnam Institute of Economics, Vietnam Academy of Social Sciences 2Hanoi university of Business and Technology 3 Service Department, Vietcombank Contact Center (VCC)
The goal of this research to sport out factors affecting the intention to use internet banking service at Vietnam's commercial banks in context 4.0. Quantitative questionaire is used to measure responses of participants. Regresstion results show that perceived usefulness (with Beta coefficient 0.144), perceived easy to use (with Beta coefficient 0.145) have a positive impact on the intention to use internet banking services at commercial banks in Vietnam. In addition, perceived financial cost has beta coefficient -0.502 meaning opposite effect on the intention to use internet banking. Attitude toward using does not have a positive impact on the intention to use.
Keywords: intention, internet banking, commercial banks.
1. Introduction
Nowadays, a commercial bank is a financial intermediary that plays an important role in the national economy and acts as a general intermediary. Researchers note that commercial banks are formed on the basic of product development and commodity exchange. As production develops, the need to expand production in the country and between nations is increases and the money was born. When commodity exchanges grow back to stimulate commodity production. Along with that development, the business is gradually developed such as holding money, payment ... on the basic of doing credit activities.
Since the establishment of the commercial banking system, commercial banks have emerged only in the context that the economy has developed to a certain level, resulting in the inevitable necessity of system formation. The banking system is closely linked to economic development.
National Bank of Vietnam was born on May 5, 1951 under Decree No. 15/SL of the President of the DRV. In the period 1951-1987, in Vietnam, one-tier banking system was created, only in line with the central planning management mechanism. As Vietnam moves its economy into a market economy, the one-stop banking system must be transformed into a two-tier banking system: management and business. After Decree No. 53/HDBT was
promulgated on March 26, 1998, the SBV's apparatus was organized into a unified system throughout the country, comprising two levels, the State Bank and specialized banks. The State Bank of Vietnam system operates under the regime of economic accounting and socialist business. According to Banking Ordinance No. 38-LTC/HNNNN8 dated 24/05/1990, the commercial banks are: "monetary organizations which operate mainly to receive deposits from customers with the responsibility to repay and use that amount to lend, perform the discount function and serve as a means of payment."
In recent years, under the impact of the 4th industrial revolution, Vietnam's digital economy has developed continuously in terms of infrastructure and market. In 2017, Vietnam ranked in the top 20 countries with the largest population of Internet users in the world with 64 million people, approximately 67% of the population. In this context, commercial banks in Vietnam have actively applied new technologies such as IA, Big Data and new services such as Mobile Banking, Internet Banking ... to be able to serve customers anywhere, anytime.
Commercial banks, on the one hand, attract idle money in the economy and, on the other hand, use the money they have raised to lend to the economic sectors of society, in other words, the role of "bridge" between the excess capital and the lack of capital. Through this transfer, Commercial banks
play an important role in promoting economic growth, increasing employment, improving living standards and stabilizing government revenue and expenditure. At the same time, this function also plays an important role in regulating monetary circulation and curbing inflation. It then shows that this is the most basic function of commercial banks.
If all social payments are made outside the bank, the cost of implementation is huge, including the cost of printing, casting, preserving, transporting money. Most of the payments made in the sale and exchange of goods and services of the society are gradually carried out through banks, with appropriate forms of payment and simple, quick and convenient procedures. With more and more modern technology, thanks to the concentration of social payment in the bank, the circulation of goods and services becomes faster, safer and more economical. Moreover, due to the implementation of the intermediary payment function, commercial banks have conditions to mobilize deposits of the whole society in general and enterprises in particular, to create capital for development investment, accelerating the bank's business.
Derived from the ability to replace the money in the circulation of money through other means of payment such as checks, mandate payment... This function is carried out through credit and investment banking system in close connection with the national reserve system. Credit system is a necessary condition for economic growth based on solid growth factor. The purpose of the national reserve policy is to provide a consistent supply of stable prices, sustainable economic growth and employment.
Any country with a developed, developing or even undeveloped economy, banking activity has a huge impact on the economy. In the market economy, the bank's role is as follows: (1) the bank is a place to concentrate idle money and provide capital for production and business; (2) banks are intermediaries in the payment process, contributing to the rapid circulation of goods; (3) the bank regulates and controls the money market and capital markets; (4) the bank contributes to attracting and expanding domestic and foreign investment and providing other financial services
Internet banking, as the era trend, is a means of optimal transaction that banks have to equip or they will be backward in banking operations in general and in their own business operations in particular. Studying factors affecting the intention to use of internet banking aims at deepening the core factors
that form and develop internet banking, contributing the quality, as well as, the developing trend, both in short-term and in long-term, of internet banking services in Vietnam's commercial banks.
2. Literature Review 2.1. Internet banking
Internet banking appeared with the rise of the Internet. First, the Internet was used as an introduction and advertisement channel for traditional banking services. Then, together with the e-commerce breakthrough and the Internet development, new banking services were founded through online gadgets. According to Truong Duc Bao (2003), Internet banking is the ability that allows remote access to a particular bank with the aims including: gathering information, dealing with financial payment transactions based on deposits. E-bank consists of all transactions between banks and customers (including individuals and organizations). Through data processing and transferring, E-bank offer end-users its products and services.
As a tool of banks, Internet banking helps diversify products and services that banks provided to their customers. Thanks to technology and telecommunication innovation, most of banking services now are able to be digitalize and becoming Internet banking services, which improves the banks' revenue ratio by promoting additional banking services and decreases their credit revenue so that the systematic risks are controlled.
Furthermore, Internet banking reduces costs related to transactions by taking advantages of hightech application, therefore, increases profits for banks. This service also expands the networking with customer using banking services — diversifies and increases the number of users.
2.2. Overall of behavior of intention to use and acceptance use of services
The appearance of definitions of behavior of acceptance and use of services comes from theories of behavioral psychology. Researchers attempt to build framework of theory and models to predict individual behaviors. Accordingly, individual actions are the chain of psychological reactions influenced by internal and external factors. Research of behavior of acceptance and use of services in technology come from the development of Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB) and other theories as
Social Cognitive Theory (SCT), etc. to build theories predicting acceptance and use as Technology Acceptance Model (TAM) (Davis, 1989; Davis et al., 1993; Venkatesh et al., 2000), Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), Model of Information Systems Success (ISS) (Delone & McLean, 1992; 2003).
Behavior of acceptance and use is simply understood as the action of accepting and using a particular service. In this research, the author defined the behavior of acceptance and use in both two aspects "behavior" and "cognition". Behavior of acceptance and use is assumed as action of really using services and committing cognition of maintaining services use of customers. Behavior of acceptance and use is determined by satisfactions of services, considering use of services as accurate actions, bringing interest to customers and commitment using services continuously in the future.
The study of Luarn and Lin (2004) about the intention to use internet banking in Taiwan, this study expands the capable of application of TAM in the context of online commercial banks by adding to a structure based on the perceived usefulness; perceived ease to use and the Cost to the research model. Research results showed all factors had positive impact on the intention to use the service, except the Cost, which had negative impact on the intention to use the internet banking service.
Fig. 1. Model of Reasoned Luarn and Lin (2004)
A theoretically sound model linking antecedents of an organizationally new software implementation to behavioral intentions to use this software is presented and empirically tested. The organization is a university in the United States and the users are primarily faculty. The model found that ease of system use impacts both self-efficacy and outcome expectancy/usefulness, which both self-efficacy and outcome expectancy/usefulness and attitude have impact attitudes towards Digital Measures, which in turn influences behavioral intentions to use Digital Measures.
Perceived usefulness
Intention to use
Fig. 2. Model of Baker-Eveleth & Stone (2008)
3. Model and Hypotheses
Proposing the research model of this study, with previous studies, the author proposes the research model based on the model of Luarn & Lin (2004); Baker-Eveleth & Stone (2008) model:
Independent variables: Perceived financial Cost; Attitude toward using; Perceived ease of use; Perceived Usefulness
Dependent variable: Intention to use
Fig. 3. The model research
The cost of using the service generally makes the customer think about whether to use the service. In case of high cost, the customer will have less desire or less motivation. Conversely, with a reasonable cost to the customer will increase the use of the service. Thus, the hypothesis is as follows:
H1: The "Perceived financial cost" factor has a positive effect on intention to use
Attitudes that affect the decision of the customer to use the service or not. For Internet banking, customers with a positive outlook on the service may be more likely to accept it. Various studies have shown that positive attitudes or attitudes have an influence on intention to use (Luarn & Lin, 2005). So this study hypothesizes:
H2: The "Attitude toward using" has a positive effect on intention to use
Ease of use is the degree to which an individual's trust in using the service will bring freedom and comfort (Pham Duy Khanh, 2017, and Bui Hai Yen, 2012). Internet banking services make it easier for customers to access and use banking services than traditional counter services. Various studies around the world have shown that the ease
Attitude
Self-efficacy
of use of the service affects the customer's perception of service usefulness and customer service perspectives. So this study hypothesizes:
H3: The "Perceived ease to use" factor has a positive influence on intention to use
Sensitive perception is a determining factor for whether or not a customer accepts the service and influences the customer's perspective on the service. Internet banking is a convenience alternative to traditional bank banking, and the convenience of using the service anytime, anywhere can be a factor in the decision to use the service. Various studies have shown that perceived usefulness has a positive effect on the intended use of services (Luarn & Lin, 2005) and customer perception of service (Davis, 1993). So this study hypothesizes:
H4: The "Perceived usefulness" has a positive effect on intention to use
4. Research method
Research objects: Examining factors affecting the intention to use of internet banking of customers in Vietnam's commercial banks.
Scope: within commercial banks in Viet Nam Authors uses quantitative method. Authors collects data by internet and questionnaire to bank's customers. After data was collected, authors analyse data by multiple variables statistic (descriptive, Cronbach's Alpha test, EFA test, regression and analysis variance).
Questionaire and scale design
With factors and observational variables referenced from the Luarn & Lin (2004) with the combination of Pham Duy Khanh (2017) and Bui Hai Yen (2012) model, the author uses a 5 point Likert scale to measure each of the factors. Although in principle use, the scales have as many points as accurate; however, in some languages, there are so many levels in the express of the scale confusing the respondent. Therefore, to ensure to avoid confusion for participants in the study author used a 5 point Likert scale level 1 is totally disagree and 5 is completely agree (Tab. 1).
Sampling and data collection method
Sampling: Comprehensive study of customers use internet banking in commercial Banks. However, the overall investigation was impossible, so the study used a sampling survey. There are different sampling methods: According to Hair et al (2006), the minimum sample size for quantitative studies is 100. For research using regression analysis Tabenick & Fidell (2007) formulated sample: n > = 50 + 8p, (n is the sample size, p is the number of independent variables). Applying this rule, the minimum sample size of the research necessary: n = 50 + 8 * 5 = 90.
This study considers taking an average size sample according to Hair et al (2006) and Tabenick & Fidell (2007) with the expected sample size of 100 to 200.
Data collection method and analysis
The author conducted survey forms directly for customers use internet banking in commercial Banks. After recovery of the questionnaire, the author conducted encoding and put into SPSS for analysis.
After being filtered, research data will be analyzed with the support from SPSS software with the following analysis steps: Sample description statistics, Test the reliability of scales, Explore factor analysis, Correlation Analysis, Regression analysis and research hypotheses test
5. Results and Discussion
5.1. Descriptive Statistics for Demographic
Total questionnaires gathered for analysis is 171. The results show that the number of male customers surveyed is 89, accounting for 52% and women are 82, accounting for 48%. The results show that the rate of random sampling between male and female clients is the same, with no difference between the male and female rates using internet banking. The highest age group is between 26 and 35 (53 people accounting for 31%); and the
Table 1
The questionaire
Content Items Code Sources
Perceived easy to use 4 PEU1, PEU2, PEU3, PEU4 Luarn & Lin (2004); Baker-Eveleth & Stone (2008)
Perceived Usefulness 5 PU1, PU2, PU3, PU4, PU5 Luarn & Lin (2004); Baker-Eveleth & Stone (2008)
Attitude toward using 4 ATI, AT2, AT3, AT4 Luarn & Lin (2004); Baker-Eveleth & Stone (2008)
Perceived finacial cost 3 COS1, COS2, COS3 Luarn & Lin (2004); Baker-Eveleth & Stone (2008)
Intention to use 4 IT1, IT2, IT3, IT4 Luarn & Lin (2004); Baker-Eveleth & Stone (2008)
smallest group is 36-45, with 40 people making up 23.4%. Young customers tend to use internet banking more than other age groups. Older audiences tend to use less because of lower access to technology. In terms of education level, the majority of the subjects are in university (73 people, 43.7%); in contrast, there are only 11 high school students (6.4%). According to income, the largest group is the group of 5-10 million (74 customers, 43.3%) and the smallest group have income lower than 5 million which has 12 people accounting for 7%.
5.2. Reliability measures
The descriptive statistic and Cronbach's Alpha coefficient of this survey were showed in Tab. 2. The Cronbach's Alpha was calulated to test the reliability off questionaires. The reliability of this survey was tested for 7 factors on framework structure of this study.
Table 2
Cronbach's Alpha coefficient
Variable Cronbach's Alpha N of items
PEU .874 4
PU .897 5
AT .838 4
COS .788 3
IT .899 4
The test results show that with the Cronbach's Alpha coefficient should be higher than 0.7 and the correlation coefficient of all items is greater than 0.3.
5.3. The result of factor analysis
Based on the research model and hypothesis, the author conducts explore factor analysis for independent and dependent variables.
5.3.1. Explore factor analysis (EFA) for independent variables Table 3 shows that switching cost factor satisfies KMO's requirement of 0.834 is greater than 0.5;
Table 3
KMO and Bartlett test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .834
Bartlett's Test of Sphericity Approx. Chi-Square 1750.242
df 120
Sig. .000
For proper EFA analysis, the author continues to consider the Variance Explained. Variance Explained is 72.838% greater than 50%. The results also show that only 4 factors are formed as the hypothesis (Tab. 4).
Table 4
Total Variance Explained
Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %
1 6.599 41.243 41.243 6.599 41.243 41.243 3.602 22.513 22.513
2 2.462 15.388 56.630 2.462 15.388 56.630 3.280 20.501 43.014
3 1.521 9.505 66.135 1.521 9.505 66.135 2.425 15.154 58.168
4 1.001 6.253 72.389 1.001 6.253 72.389 2.275 14.220 72.389
5 .822 5.139 77.527
6 .627 3.916 81.443
7 .458 2.861 84.304
8 .430 2.686 86.991
9 .417 2.606 89.596
10 .373 2.329 91.926
11 .359 2.242 94.167
12 .270 1.686 95.853
13 .242 1.511 97.363
14 .187 1.170 98.533
15 .135 .843 99.376
16 .100 .624 100.000
The results of the factors are formed as follows (Tab. 5).
Table 5
Explore factor analysis results for independent variables
5.3.2. Explore factor analysis (EFA) for intention factors Table 6 shows that KMO's requirement of 0.805 is greater than 0.5;
Table 6
The results of the factors are formed as follows (Tab. 8).
Table 8
Explore factor analysis results for intention factors
Components
1
IT4 0.939
IT1 0.9
IT3 0.883
IT2 0.785
Source: The researcher's collecting data and SPSS.
5.4. Correlation analysis
Prior to introducing variables into regression analysis, the author carries out correlations to determine if the independent variables and dependent variables are correlated. The correlation matrix shows that independent variables are correlated with dependent variables (IT) (Tab. 9). Therefore, the inclusion of independent variables in regression analysis is appropriate.
Table 9
The correlation coefficient matrix
Correlations
IT PEU PU AT COS
IT 1 .404** .492** .535** -.682**
PEU 1 .275** .522** -.276**
PU 1 .477** -.478**
AT 1 -.545**
COS 1
** Correlation is significant at the 0.01 level (2-tailed).
5.5. Building the regression function and research hypotheses
5.5.1. Multiple linear Regression for Intention
The researchers conducted regression analysis to determine the specific of each factor to intention to use. Regression analysis will be performed with four independent variables PEU, PU, AT, COS and the dependent variable: intention to use (Tab. 10).
KMO and Bartlett test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .805
Bartlett's Test of Sphericity Approx. Chi-Square 474.641
df 6
Sig. .000
The Total Variance Explained is 77.18% greater than 50%. The results also show that only one factor is formed as the hypothesis (Tab. 7).
Table 7
Total Variance Explained
Component Initial Eigenvalues Extraction Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 3.088 77.189 77.189 3.088 77.189 77.189
2 .499 12.476 89.665
3 .273 6.817 96.482
4 .141 3.518 100.000
Component
1 2 3 4
PU4 0.89
PU5 0.835
PU2 0.832
PU3 0.798
PU1 0.634
PEU4 0.924
PEU3 0.864
PEU1 0.807
PEU2 0.687
COS2 0.869
COS1 0.767
COS3 0.663
AT2 0.826
AT4 0.717
AT1 0.636
AT3 0.537
a. Predictors: (Constant), PEU, PU, AT, COS ; b. Dependent Variable: IT; c. *p< .05; **p< .01 and ***p < .001 Regression analysis results of the factor "Intention of use"
Table 10
Model summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .737a 0.543 0.532 0.48673
a. Predictors: (Constant), PEU, PU, AT, COS
ANOVA
Model Sum of Squares df Mean Square F Sig.
Regression 46.804 4 11.701 49.389 .000***
1 Residual 39.342 166 0.237
Total 86.146 170
Unstandardized Coefficients Standardized Coefficients t Sig. VIF
B Std. Error Beta
(Constant) 3.225 0.367 8.787 .000***
PEU 0.145 0.052 0.172 2.797 .006** 1.376
PU 0.144 0.057 0.157 2.506 .013* 1.421
AT 0.095 0.074 0.093 1.279 .203 1.924
COS -0.502 0.065 -0.509 -7.764 .000*** 1.561
a. Predictors: (Constant), PEU, PU, AT, COS
b. Dependent Variable: IT
c. *p< .05; **p< .01 and ***p < .001
The empirical multiple regression model is follow:
IT = 3.225*** + 0.145** * PEU + 0.144* * PU + + 0.095 * AT -0.502*** * COS+ Error Term
Table 10 shows the coefficients of multiple regression analysis. There are 3 hypotheses, which have significance level less than 0.05, are supported; and 1 hypothesis, which have significance level greater than 0.05, are unsupported. In the other words, Attitude toward using (AT) do not have significance relationship with Intention to use (IT); Perceived ease of use (PEU), Perceived Usefulness (PU) and Perceived financial Cost (COS) do. Therefore, the empirical results show that we can utilize Perceived ease of use (PEU), Perceived Usefulness (PU) and Perceived financial Cost (COS) 3 factors to explain the dependent variable Intention to use (IT). Moreover, regression results show that the model does not have multi-col-linearity (the VIF coefficients of the independent variables are less than 10).
After the regression run, the author conducts a model fit test through the residual standard histogram (Fig. 4).
With a residual-bell-shaped distribution graph, it is possible to see a reliable regression model for analysis.
The authors continue to examine the degree of deviation between the estimated value and the observed value through the P-plot (Fig. 5).
The P-plot shows the estimated values close to the observed value, so the regression model is capable of explaining well the intention of the customer.
To test the hypotheses of the study, p-value of the corresponding t-statistic are directly compared with the value 0.05, 0.01 or 0.001 as the common level of significance. The research hypotheses test results in as following: The factor "Perceived finacial cost" has opposite impact on intention of use with P = -0.502 < 0 and the corresponding t-statistic has the p-value = 0.000 < 0.001. From the research data, we can conclude that the P coefficient of the variable COST is negative. The factor "Attitude forward using" positive affects on intention (P = 0.095 > 0 and p-value = 0.203 > 0.05). From the research data, we can conclude that the AT is not significant. The factor "Perceived easy to use" positive impact on intention of use (p-values are 0.006 less than 0.05 and positive beta coefficient P = 0.145 > 0) The factor "Perceived usefulness" positive impact on intention of use (P = 0.144 > 0 and the corresponding t-statistic has the p-value = 0.013 < 0.05) (Tab. 11).
-2 0 2 4
Regression Standardized Residual
Fig. 4. Histogram of residual
Normal P-P Plot of Regression Standardized Residual Dependent Variable: IT
Observed Cum Prob
Fig. 5.2. P-Plot
Table 11
Summary of hypothesis testing results
Hypothesis Factor Results
H1 H1: The "Perceived financial cost" factor has a positive effect on intention to use Accepted
H2 H2: The "Attitude toward using" has a positive effect on intention to use Accepted
H3 The "Perceived ease to use" factor has a positive influence on intention to use Accepted
H4 H4: The "Perceived usefulness" has a positive effect on intention to use Accepted
Source: Authors synthesize.
5.2. Analysis of the differences among customer groups in intention to use
Gender
Table 12
Comparison of differences between gender groups
of two groups, male has intention to use higher than female (difference is 0.36).
Age
That p-value of ANOVA test equals to 0.634 indicates that there is no difference in intention to use among consumers of different ages (Tab. 13).
Table 13
Comparison of differences among age groups
Test of Homogeneity of Variances ANOVA
Levene Statistic P-value F P-value
.651 .583 .573 .634
Education
That p-value of ANOVA test equals to 0.007 indicates that there is difference in intention to use among consumers of different educations and p-value of Variances test equals to 0.008, shows that: Equal variances not assumed (Tab. 14).
Table 14
Levene's Test for Equality of Variances t-test for Equality of Means
F P-value t P-value (2-tailed) Mean Difference Std. Error Difference
IT Equal variances assumed 2.650 .105 3.406 .001 .36003 .10571
Equal va riances not assumed 3.383 .001 .36003 .10644
The result shows that there is a difference in intention to use between male and female (p-value of t test is 0.001, which is less than 0.05). Based on the means
Comparison of differences among age groups
Test of Homogeneity of Variances ANOVA
Levene Statistic P-value F P-value
2.853 0.008 4.18 0.007
Dependent Variable: IT Tamhane
(I) Education Mean Difference (I-J) p-value
High school Intermediate/ College -0.0345 1
University 0.18991 0.699
Post- graduate -.46713* 0.02
Intermediate/ College High school 0.03446 1
University 0.22437 0.441
Post- graduate -.50158* 0.004
University High school -0.1899 0.699
Intermediate/ College -0.2244 0.441
Post- graduate 0.27721 0.205
Post- graduate High school .46713* 0.02
Intermediate/ College .50158* 0.004
University -0.2772 0.205
* The mean difference is significant at the 0.05 level.
To show differences, the author uses post hoc tests with equal variances not assumed. The results indicate that Post-graduate has who has intention to use higher than High school and Intermediate/College.
Income
Table 15
Comparison of differences among income groups
Test of Homogeneity of Variances ANOVA
Levene Statistic P-value F P-value
1.337 .740 .634 .594
The intention to use of customers at different income levels is the same (p-value of ANOVA test equals to 0.594, which is greater than 0.05; 0.1).
6. Conclusion
This study applies the TAM to the newly emerging context of internet banking, which has recently become available. Limitations of the TAM includes the omission of cost-based construct in the context of electronic/internet commerce and the assumption that there are no barriers preventing an individual from using an information system if they choose to do so.
The results show that the Perceived usefulness, Perceived easy to use have a positive impact on the intention to use internet banking services at commercial banks in Vietnam. In addition, Cost has the opposite effect on the intention of use internet banking. Attitude toward using has not a positive impact on the intention of use.
Recommendation to improve cost
The first, Cost has negative impact on intention of use. Perceived financial cost is also a significant barrier for users of internet banking. Given that internet banking use is completely voluntary, lacks organizational resource support, and has a target user group consisting of large numbers of people with greatly diversified backgrounds, the findings of this study suggest that in order to attract more users to internet banking, it will require more than simply making the system easier to use. It is of paramount importance to develop internet banking systems with valuable functions and a perceived trustworthiness to protect the security and privacy of the users. In addition, the internet banking authorities must reduce the users' perceived financial cost through creative promotional and pricing strategies.
Recommendation to improve usefulness
Banks need to build more gadgets that users can use for daily payments. These utilities allow customers to carry out transactions and payments with nonbank suppliers (telecommunications, electricity, etc.). The construction of various utilities on the internet banking service allows customers to use the internet banking service apart from the money transfer which can also be used to pay for everyday bills. However, the utility should be built on the interface or simple operation and have specific user instructions for easy access and use. Regularly update content changes for customers through SMS or e-mail system to help customers know the changes of internet banking services on the newly added banking services. The new service information to help customers see the usefulness of internet banking services.
The bank implements the communication to bring the message of utility to the customer in a way that is different from the traditional services at the counter. Especially in the group of customers less time to the counter or often moving. Messages on the usefulness of the service should be emphasized on attributes that help customers improve banking transactions through the use of e-banking systems. Make customers clearly see the benefits of using internet banking. From then, customers always have the desire to use internet banking services.
The banks should focus on locating in the minds of customers about the benefits that internet banking offers. At the same time, banks are able to provide guidance and training to customers using the service system so that they feel that Internet Banking is not so difficult as to be confident in this service. All banking policies should aim at making the customer look positive on the service, showing that internet banking is an easy to use service as well as showing that internet banking is useful to customers. Since then, it is hoped that it will improve and increase the number of customers using online banking services in the area.
This requires the branch to have a plan to bring into play the advantages that Internet banking can bring to customers. In addition, in order to make it easy for customers to learn how to use the Internet — banking, branches need to have detailed instructions, in short, with visual images. In addition, banks should ensure that the security and privacy of banking systems over the Internet are properly built and that users should also be aware that systems are secure and personal as consumers' financial information is protected.
To encourage the use of Internet banking services, the Vietnamese government can help ensure that clear rules and regulations governing Internet banking. In addition, the government, the regulatory body
should direct banking services over the Internet and monitor banks' operations to ensure that they operate legally.
Reference
1. Ajzen I. From intentions to actions: A theory of planned behavior. New York, Springer, 1985.
2. Baker-Eveleth I., Stone R.W. Expectancy Theory and Behavioral Intentions to Use Computer Applications. Interdisciplinary Journal of Information, Knowledge, and Management, 2008, no. 3, pp. 135-146.
3. Bui Hai Yen. Results of impact of a number offactors to consider the use of internet — banking ofpersonal customers in agribank thang long branch. The thesis master. National economics university, 2012.
4. Davis F.D. Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 1989, no. 13 (3), pp. 319-339.
5. Davis F.D. User acceptance of computer technology: System characteristics user perceptions and behavior characteristics. International Man-Machine studies, 1993, no. 38, pp. 475-487.
6. Delone W.H., McLean E.R. Information systems success: the quest for the dependent variable. Information Systems Research, 1992, no. 3 (1), pp. 60-95.
7. Delone W.H., McLean E.R. The DeLone and McLean model of information systems success: a ten-year update. Journal of Management Information Systems, 2003, no. 19 (4), pp. 9-30.
8. Hair J.F., Black W.C., Babin B.J., Anderson R.E., Tatham R.L. Multivariate Data Analysis. 6th ed. Upper Saddle River NJ, Prentice-Hall, 2006.
9. Luarn P., Lin H.H. Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 2005, no. 21, pp. 873-891.
10. Pham Duy Khanh. The factors affecting the internet banking interest of personal customers in vietnam bank of investment and development joint stock company Ba Ria-Vung Tau branch. Master thesis. BaRia Vung-Tau University, 2016.
11. Tabachnick B.G., Fidell L.S. Using Multivariate Statistics (5th ed.). New York, Allyn and Bacon, 2007.
12. Venkatesh V., Davis F.D. A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 2000, 45:2, pp. 186-204.
Information about the authors
Nguyen Chien Thang — Vietnam Institute of Economics, Vietnam Academy of Social Sciences. [email protected]
Ly Hoang Mai — Vietnam Institute of Economics, Vietnam Academy of Social Sciences. [email protected]
Nguyen Thi Kim Chi — Hanoi university of Business and Technology. [email protected]
Vu Trung Kien — Service Department, Vietcombank Contact Center (VCC).
