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Descriptive Statistics on Banking Service Usage


Chart 5: Customer occupation

Regarding occupation, civil servants and public employees account for the highest proportion (32.8%), followed by business and small traders with 28.1%. The rest are housewives (12.5%), retirees (9.4%), manual laborers (10.9%) and other occupations (6.2%).

2.3.1.2 Descriptive statistics on banking service usage

Table 5: Descriptive statistics on service usage at Maritime Bank


Criteria

Frequency (people)

Percent (%)


Service time

Under 6 months

30

23.4

From 6 months to 1 year

42

32.8

From 1 to 2 years

36

28.1

Over 2 years

20

15.6


Purpose of deposit

Enjoy interest

92

71.9

Save money

60

46.9

Avoid risk

50

39.1

Use utility services

44

34.4

Other purposes

16

12.5


Customer source of information

Friends and relatives

86

67.2

Bank employee

64

50

NH activities

32

25

Television media

56

43.8

Internet

40

31.2

Other channels

20

15.6

Maybe you are interested!

Descriptive Statistics on Banking Service Usage

(Source: Results of survey data processing)

Regarding the time of using Maritime Bank's services, the collected results show that most customers have just used the bank's services from less than 6 months to 2 years, the remaining only 20 people (15.6%) have used Maritime Bank's services for more than 2 years. This is explained by the fact that Maritime Bank has only recently entered Hue, so the bank's long-term customers are still limited, not yet


get much

Chart 6: Purpose of deposit

Regarding the purpose of customers when depositing savings at the bank, most customers deposit money at the bank to get interest on deposits (71.9%), besides, the purpose of saving money for future purposes is also agreed by customers with 46.9%. On the other hand, customers deposit money to avoid risks when having to keep money themselves (39.1%) and to use some utilities at the bank such as money transfer, card payment... are also mentioned by customers (34.4%). Accurately grasp the purposes

Customers' information when depositing money will help the bank proactively implement activities to meet customers' purposes, helping the bank attract more potential customers in the future.

Besides, information sources that help customers know about the bank also come from

many sides. Mostly information from friends, relatives and colleagues (with

Up to 67.2% of customers receive information about the bank through this channel). The second is information received from bank employees when customers are consulted about information about products and services. In addition, bank activities (25%), television (43.8%) and the internet (31.2%) are also channels that help customers know about the bank.

Additionally, when statistics describe the features that customers are most interested in when sending

savings in the bank, after investigation, we have the following results:

Table 6: Factors customers care about when depositing money at the bank



The first

Second

Tuesday

Wednesday

Thursday

Friday

Total

High interest rate

54

42.2%

42

32.8%

14

10.9%

14

10.9%

0

0%

0

0%

124

96.9%

Reputable bank

30

23.4%

28

21.9%

40

31.2%

8

6.2%

10

7.8%

0

0%

116

90.6%

Used before

0

0%

8

6.2%

0

0%

20

15.6%

20

15.6%

30

23.4%

78

60.9%

Good service

24

18.8%

14

10.9%

32

25%

16

12.5%

20

15.6%

4

3.1%

110

85.9%

Have relatives

20

15.6%

16

12.5%

16

12.5%

16

12.5%

16

12.5%

12

9.4%

96

75%

Regular QC

0

0%

20

15.6%

22

17.2%

40

31.2%

14

10.9%

20

15.6%

116

90.6%


(Source: Results of survey data processing)

Chart 7: Customer Interest

The survey results show that when depositing money at a bank, customers are most concerned about interest rates, which is clearly seen when the factor "High interest rate" is chosen by customers to be the most important and second most important (accounting for 75% of customers' thoughts). The next important factor chosen by customers is "Reputable bank" with 45.3% of customers choosing the first and second most important items, 31.2% of customers ranked this factor as the third most important.

Two other factors, “Good banking services” and “Having relatives working in the bank” are ranked by customers after the above two factors with equal importance. Obviously, these two factors have not been emphasized by customers when choosing a bank to deposit savings, but they are also an important factor that affects customers' decisions.

The two remaining factors that customers care least about when choosing a bank to deposit their savings are “Have used the bank’s services before” and “Frequent advertising on television”. Customers do not rate these two factors highly, they are often ranked fourth, fifth and sixth by customers.

2.3.2 Testing the reliability of the scale and checking the normal distribution

2.3.2.1 Assessing the reliability of the scale using Cronbach's Alpha coefficient

All variables are measured by a Likert scale (5 points), from strongly disagree to strongly agree. After completing the sample collection, the scales are tested for reliability by Cronbach's Alpha coefficient to examine the level of internal consistency and as a basis for eliminating unqualified variables based on the total item correlation coefficient. Variables with a total item correlation coefficient less than 0.3 will be eliminated and the criterion for selecting the scale is that the Cronbach's Alpha coefficient must be greater than 0.6. If the scale does not meet the standard, it will be eliminated from the model.

Table 7: Cronbach's Alpha of the scale corresponding to the test times


Scale Rating Operation

Cronbach's Alpha coefficient

After variable removal

First run

0.917

…

Run the second time

0.920

Q19

Run 3rd time

0.924

Q19, Q4

(Source: Results of survey data processing)

The analysis results show that the Cronbach's Alpha coefficient of the scale is 0.924, satisfying the condition of being greater than 0.6. In the model's scale, there are 2 variables that are eliminated from the model because they do not satisfy the condition of the total correlation of variables being greater than 0.3, which are "There are many modern equipments inside the bank" and "Friends and colleagues recommend customers to choose Maritime Bank". Below are the specific results of the 3rd Cronbach's Alpha test

Table 8: Cronbach's Alpha of the scale after the third run


Observation variable

Total variable correlation

Cronbach's Alpha coefficient if variable is removed

C6

0.521

0.923

C7

0.612

0.920

C8

0.613

0.920

C10

0.606

0.920

C11

0.442

0.923

C12

0.641

0.919

C13

0.689

0.919

C14

0.544

0.921

C15

0.619

0.920

C16

0.631

0.919

C17

0.662

0.919

C18

0.535

0.921

C19

0.346

0.924

C20

0.552

0.921

C21

0.636

0.919

C22

0.504

0.922

C23

0.395

0.924

C25

0.642

0.919

C26

0.581

0.920

C27

0.613

0.920

C28

0.664

0.919

C29

0.585

0.920

Cronbach's Alpha = 0.924

(Source: Results of survey data processing)

As a final result, we have 22 observations to process in the next steps.

2.3.2.2 Testing the normal distribution of observations

Testing for normal distribution is the first condition that needs to be performed to ensure the level of satisfaction of the factor analysis variables. To perform this test, the study also uses two quantities to measure the characteristics of the data distribution, which are the Skewness coefficient and the Kurtosis concentration coefficient. The Skewness coefficient tells us the distribution shape of the observed values, a Skewness distribution is considered a normal distribution when the Standard error Skewness is in the range from -2 to 2. Similarly, for the Kurtosis concentration coefficient, this coefficient is used to compare the observed curve with the normal distribution curve, a Kurtosis distribution is considered a normal distribution when the Standard error Kurtosis is in the range from -2 to 2.

Table 9: Normal distribution test


Observations

Std. Error of Sknewness

Std. Error of Kurtosis

Reputable and branded bank

0.214

0.425

Large scale bank

0.214

0.425

Because Maritime Bank is a group 1 bank

0.214

0.425

Because the bank has convenient working hours

0.214

0.425

Convenient transaction points and ATMs

0.214

0.425

Because the procedure is simple and not complicated

0.214

0.425

Because the interest rate at Maritime Bank is suitable

0.214

0.425

Interest rates at Maritime Bank have outstanding advantages

0.214

0.425

Because of the many amenities included

0.214

0.425

Due to reasonable service fees

0.214

0.425

Bank has 24/7 hotline

0.214

0.425

By dedicated and professional staff

0.214

0.425

By enthusiastic and attentive staff

0.214

0.425

Because the staff can answer all questions

0.214

0.425

Maritime Bank regularly has promotional programs.

0.214

0.425

MSB's unique and attractive promotion program

0.214

0.425

Referred by family member

0.214

0.425

KM program is an active activity of NH.

0.214

0.425

Customers are interested in the promotion program

0.214

0.425

Customers know about promotions

0.214

0.425

Customers are aware of the MSB brand

0.214

0.425

Customers love the MSB brand

0.214

0.425

(Source: Results of survey data processing)

Looking at the analysis table, we see that Std. Error Skewness and Std. Error Kurtosis are both in the range of -2 to 2, so we can confirm that the sample has a normal distribution. Satisfy the conditions to enter the next processing steps.

2.3.3 Exploratory factor analysis EFA

2.3.3.1 KMO test

After analyzing the Cronbach's Alpha reliability coefficient and testing the normal distribution, the scales were evaluated by exploratory factor analysis. The purpose of this analysis is to group related variables into new factors. On the one hand, factor analysis helps reduce the number of variables participating in the regression equation, on the other hand, through factor analysis, it is also possible to evaluate the convergent validity and discriminant validity of the scale.

Table 10: KMO and Bartlett's test


KMO Index

0.708


Bartlett test results

Approx. Chi-Square

2.420E3

Df

231

Sig.

0.000

(Source: Results of survey data processing) The extraction method used is “Principle component” with Varimax rotation. The standard of this method is that the KMO value must be between 0.5 and 1 and the Barlett's test must have a significance level of Sig. < 0.05 to prove that the data used for EFA analysis is completely appropriate and there is correlation between the variables. In addition, the Eigenvalues ​​must be greater than 1, the total extracted variance must be greater than 50% and the factor loading must be greater than 0.5. Cases that do not satisfy the above conditions will be

removed

The results of factor analysis show that the KMO coefficient = 0.708, and the Barlett's test has a significance level of Sig. = 0.000. This proves that the data used for exploratory factor analysis is completely appropriate and there is a correlation between these variables.

2.3.3.2 Factor analysis

Table 11: Factor analysis corresponding to observed variables


Rotated Component Matrix a


Factor


1

2

3

4

5

6

Customers are interested in the promotion program

0.860






Attractive MB promotion program

unique

0.830






Maritime Bank regularly has programs

KM program

0.823






Customers know the programs well

promotion

0.790






KM program is an active activity.

of NH

0.779






Referred by family member

0.608






Interest rates at Maritime Bank have outstanding advantages


0.829





Due to reasonable service fees


0.790





Because the interest rate at Maritime Bank is suitable


0.759





Bank has 24/7 hotline


0.629





Because of the many amenities included


0.587





Reputable and branded bank



0.907




Because Maritime Bank is a group 1 bank



0.866




Large scale bank



0.850




By dedicated and professional staff




0.865



By enthusiastic and attentive staff




0.852



Because the staff can answer all questions




0.801



Convenient transaction points and ATMs





0.881


Because the bank has convenient working hours





0.793


Because the procedure is simple and not complicated





0.741


Customers love the MB brand






0.816

Customer brand awareness

Strong MB






0.666

Evaluations

0.865

2,570

2.012

1,735

1,342

1,007

Eigenvaluaes explained %

39.34

11.68

9.14

7.88

6.10

4.57

Cumulative explained %

39.34

51.02

60.16

68.05

74.15

78.73

(Source: Results of survey data processing) After rotating the factors for the first time, we see that the concentration of variables according to each factor is quite clear. The analysis results table shows that there are 22 variables in total but only

There are 6 factors with Eigenvalues ​​greater than 1. The results show that these 6 factors have a total cumulative variance of 78.73%, meaning that the 6 factors explain 78.73% of the variation in observed variables.

2.3.3.3 Naming and explaining factors

Based on the correlation and significance of the observations, we proceed to name the groups of factors that influence customers' decision to choose a bank. After reviewing the groups from factor analysis, we proceed to name the groups of factors as follows:

Table 12: Factor naming and explanation



Factor name


Observations

Eigenvalues

Variance

extract

Cronbach's

alpha


Promotion

Customers are interested in the promotion program


0.865


39.34


0.902

MB's promotion program is attractive and unique.

Maritime Bank regularly has promotional programs.

Customers know about promotions

KM program is an active activity of NH.

Referred by family member


Product

service

Interest rates at Maritime Bank have outstanding advantages


2,570


51.02


0.876

Due to reasonable service fees

Because the interest rate at Maritime Bank is suitable

Bank has 24/7 hotline

Because of the many amenities included


Reputation

Reputable and branded bank


2.012


60.16


0.915

Because Maritime Bank is a group 1 bank

Large scale bank


Staff

By dedicated and professional staff


1,735


68.05


0.869

By enthusiastic and attentive staff

Because the staff can answer all questions

Ability

approach

Convenient transaction points and ATMs


1,342


74.15


0.878

Because the bank has convenient working hours

Because the procedure is simple and not complicated

Recognize

trademark

Customers love the MB brand

1,007

78.73

0.860

Customers perceive the MB brand as strong

(Source: Results of survey data processing)

These six factors will represent all observations in the model to be carried out in the next processing steps, which is multivariate regression analysis to determine which important factors have a direct impact on customers' decision to choose a bank and the level of influence of that factor.

2.3.4 Building a regression model

The regression model chosen to be built is a multiple linear regression function model.

has the form:

Y= ß 0 + ß 1 *X 1 + ß 2* X 2 + ß 3 *X 3 + ß 4 *X 4 + ß 5 *X 5 + ß 6 *X 6

Where: Y is the dependent variable, ß k are the partial regression coefficients, X i are the independent variables in the model and e i is the random independent variable.

The independent variables used for regression analysis include:

- X 1 is Bank Promotional Activities

- X 2 is the quality of bank products and services

- X 3 is the Bank's reputation

- X 4 is a Bank employee

- X 5 is Customer Accessibility to Banking

- X 6 is Brand Awareness.

The regression results with the variable selection method enter give the result of assessing the model's suitability R 2 is 0.81, the adjusted R 2 index (Adjuster R square) is 0.80. Because the adjusted R 2 is smaller than R 2 , choosing the adjusted R 2 index to consider the model's explanation level is safer because it is less inflated than R 2. The adjusted R 2 index is 0.80, which means that the variables included in the model explain 80% of the variation in factors affecting customers' decision to choose a bank in Hue city.

In addition, the Sig. F Change value is 0.000 (<0.05), which means that with a confidence level of 95%, the hypothesis H 0 is rejected (H 0 : ß 1 =ß 2 =ß 3 =ß 4 =ß 5 =ß 6 =0). This means that the partial regression coefficients of the variables included in the model are different from zero. The data in the table shows that "Bank employee" has a significance level of sig. > 0.05 and the remaining factors all have a significance level of sig. < 0.05. Therefore, in addition to the above factor, the ß coefficients of the other factors are all statistically significant.

Table 13: Results of regression model of factors affecting

customer choice of bank



Coefficient not yet

standardize


level of intention

meaning

Statistical

multicollinearity

ß

Deviation

standard

Coefficient

Tolerance

VIF

coefficient of freedom

-0.933

0.236

0.000



Promotion

0.462

0.055

0.000

0.726

1,377

Product quality

0.259

0.063

0.000

0.515

1,941

Bank reputation

0.132

0.041

0.002

0.678

1.475

Bank employee

7.5E-5

0.056

0.999

0.716

1,397

NH Accessibility

0.194

0.055

0.001

0.616

1,622

Brand awareness

0.253

0.052

0.000

0.554

1,806

(Source: Results of survey data processing)

From the above results, we build a regression model describing the relationship between the variables.

Factors affecting customers' decision to choose a bank are as follows: Decision -0.933 + 0.462*Promotion + 0.259*Quality of selected products and services = + 0.132*Bank reputation + 0.194*Accessibility

Bank + 0.253*Brand Awareness.

The estimated multiple regression equation above shows that “Promotion program”, “Product and service quality” and “Brand awareness” are the variables with the best level of explanation for customers' decision to choose a bank.

Explanation of regression model:

- The regression coefficients ß reflect the positive or negative proportion to the choice decision.

customer bank

- ß 1 = 0.462 reflects that customers' decision to choose a bank will increase.

0.462 units when promotion activity increases by 1 unit.

- ß 2 = 0.259 reflects that customers' decision to choose a bank will increase.

0.0.259 units when the quality of bank's services increases by 1 unit.

- ß 3 = 0.132 reflects that customers' decision to choose a bank will increase.

0.132 units when bank reputation increases by 1 unit.

- ß 5 = 0.194 reflects that customers' decision to choose a bank will increase.

0.0.194 units when banking accessibility increases by 1 unit.

- ß 6 = 0.253 reflects that customers' decision to choose a bank will increase.

0.253 units when customer's bank brand recognition increases by 1 unit.

The acceptance criteria (Tolerance) of the variables included in the model are all greater than 0.1 and the variance inflation factor (VIF) is less than 10, so multicollinearity between independent variables is unlikely to occur. On the other hand, the Durbin-Watson coefficient is 1.924, which is in the acceptable range from 1 to 3, so it is possible to accept that autocorrelation between independent variables does not occur (Hoang Trong & Chu Nguyen Mong Ngoc, 2008). Therefore, the above regression model is accepted. From the results of analysis and testing of regression coefficients, the official research model is supplemented with regression coefficients to form a complete model as follows:


Promotion

0.462


Product quality


Bank reputation

0.259


0.132


Decision to choose

bank


Accessibility

0.194


Brand awareness

0.253


Figure 5: Complete research model after regression analysis

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