# Data Analysis And Discussion Of The Results Obtained Business Essay

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## 4.1 Introduction

This chapter presents the data analysis and discussion of the results obtained in the context of the research question. The analysis and finding of this research are presented in descriptive analysis, reliability analysis using the Cronbach's Alpha, mean and percentage of respondent, multiple regression analysis, linear regression analysis and hypotheses testing. In this part, SPSS version 16.0 is used to analyze all the collected data. Thus, Pearson Coefficient correlation analysis used to measure the degree of relatedness of independent variables and dependent variables.

Within one month period, there are 220 questionnaires that have been distributed to the undergraduate students in Malacca. There are 200 questionnaire were completed and returned. The results are presented according to the statistical tests that had been done.

## 4.2 Descriptive Analysis

Descriptive analysis is a frequency analysis of demographic data which usually consists of age, gender, nationality, educational level and so on. The purpose of the analysis uses to provide an overview of the respondents and an insight into their behavioral patterns.

Frequency distributions were uses to obtain for all the respondent demographic and behavioral patterns. The sample consists of 200 respondents from the population undergraduate students in Malacca.

## Table 4.1 Respondent Profile

## Respondent's Demographic

## Frequency

## Percentage (%)

Gender

Male

Female

81

119

40.5

59.5

Age

17-20

21-24

25-28

40

158

2

20.0

79.0

1.00

Nationality

Malaysian

Others

196

4

98.0

2.00

Education

Bachelor's Degree

Pre U/ Foundation

Master's Degree

Diploma

Doctorate's Degree

177

8

0

15

0

88.50

4.00

0.00

7.50

0.00

Marital status

Single

Married

Divorce

Widow

Widower

200

0

0

0

0

100.00

0.00

0.00

0.00

0.00

Montly Income/ Allowance

<RM100

RM100 - RM500

RM500 - RM1000

Others

56

96

43

5

28.00

48.00

21.50

2.50

How many banks you currently deal with?

1

2

3

4

5

51

88

53

5

3

25.50

44.00

26.50

2.50

1.50

How often do you visit your transact bank?

Everyday

1-2 times per week

1-2 times per month

1-2 times per year

Others

3

78

110

8

1

1.50

39.00

55.00

4.00

0.50

How long have you been chosen your bank?

Less than 1 year

1 year to 3 years

4 year to 6 years

More than 6 years

17

85

65

33

8.50

42.50

32.50

16.50

## 4.2.1 Gender

As showed in table 4.1, there were 119 female respondents which is 40.5% and 81 respondents which is 59.5% from a total of 200 respondent. The respondent is randomly selected from the population undergraduate students in Malacca.

## 4.2.2 Age Group

Table 4.1 shows the respondent's age is range from 17 years old to 28 years old. The highest frequency of respondent the survey is from the range of 21 years old until 24 years old which is 158 respondents or 79% followed by the age group of 17 years old until 20 years old which is 40 respondents or 20%. However, there are only 2 respondents or 1% in the range of 25 years old until 28 years old which is the lowest frequency of respondent.

## 4.2.3 Nationality

As illustrated in table 4.1 above, there are 196 Malaysian respondents which are 98% from the questionnaire distributed. Thus, there are only 4 foreign respondents which are 2% who took part in the questionnaire. It showed that Malacca University has local students' more than international students.

## 4.2.4 Education

The undergraduate who respond to the questionnaire are majority taking the bachelor's degree in the Malacca University which is 88.5% or 177 respondents. Besides, there are 7.5% respondent which is 15 respondents are currently taking the diploma course. There are 8 respondents which is 4% taking the pre-U/ foundation course get the lowest frequency of respondent.

## 4.2.5 Marital Status

As the above table 4.1 showed, all 200 respondents are still single. They are all undergraduate still haven start their working or starting a family.

## 4.2.6 Monthly Allowance/Income

Table 4.1 shows the monthly allowance or income of respondent. There were 96 respondents which is 48% have monthly allowance or income in the range of RM100 until RM 500. It showed that majority of respondents monthly allowance is get from their parent or part time job. Besides, there were 56 respondents which are 28% have monthly allowance or income is less than RM100 and 43 respondents which is 21.5% respondent have monthly allowance or income in the range of RM501 until RM1000. Thus, there are only 5 respondent which is 2.5% have monthly allowance or income above RM1000.

## 4.2.7 How many banks you currently deal with?

As illustrated in table 4.1 above, there are 88 respondent which is 44% currently deal with two banks followed by 53 respondents which is 26.5% currently deal with three banks. Other than that, it showed that 51 respondents which is 25.5% currently deal with one bank. They show their loyalty to only one bank. However, there are only totally 8 respondents which is 4 % currently deal with four or five bank. It also showed that 100% of respondent deal with at least one bank.

## 4.2.8 How often do you visit your transact bank?

Table 4.1 shows that how often respondent have visit their transact bank. Majority respondent which is 55% visit their transact bank 1-2 times per month. There are 39% of respondent visit their transact bank 1-2 times per week. However, there are 4 % respondents visit their transact bank 1-2 times per year. There are only 1.5% respondents visit their transacting bank everyday. Lastly, the results shows that only 0.5% which is only 1 respondent do not visit their transact bank at all in a year.

## 4.2.9 How long have you been chosen your bank?

Table 4.1 represent that 42.5% which is 85 respondents have been with the bank in the range of one year to three years. There are 32.5% which is 65 respondents have been chosen their bank in the range of four year to six years. Besides, there are 16.5% which is 33 respondents have been with the bank more than six years. There are only 8.5% which is 17 respondents have been with the bank less than one years.

## 4.2.10 Descriptive Analysis for variables

Descriptive statistics for mean were obtained for the interval-scaled independent and dependent variables.

## Table 4.2 Descriptive Statistics for variables

## Variables

## N for cases

## Mean

Reliability

200

3.534

Responsiveness

200

3.439

Assurance

200

3.664

Empathy

200

3.332

Tangible

200

3.776

Consumer Satisfaction

200

3.629

Corporate Image

200

3.874

Commitment

200

3.436

Conflict handling

200

3.551

Customer Loyalty

200

3.630

Table 4.2 showed the resulting variables that are included in the analysis. All the variables get the mean above 3.00. This result shows that most of the respondents choose the answer of neither agree nor disagree or agree answer. However, tangible and corporate image get the highest mean which is 3.776 and 3.874. This two variables means are nearly to 4.00, it shows that majority respondents agree their transact bank have a good corporate image and physical facilities are visually appealing.

## 4.3 Reliability Analysis

Reliability estimates were determined for the scales based on Cronbach's coefficient Reliability is to test the consistency of respondents' answer to all the items in a measure. In general, reliabilities less than 0.6 are considered to poor. For those in the 0.7 range are considered as acceptable. Thus, reliabilities above 0.8 are good. (Sekaran, 2004).

## Table 4.3 Reliability Testing

## Variables

## N for cases

## N for Items

## Cronbach's Alpha

Reliability

200

5

0.724

Responsiveness

200

5

0.744

Assurance

200

5

0.773

Empathy

200

5

0.738

Tangible

200

5

0.724

Consumer Satisfaction

200

5

0.768

Corporate Image

200

5

0.714

Commitment

200

5

0.730

Conflict Handling

200

5

0.733

Customer Loyalty

200

5

0.812

Table 4.11 present the resulting variables that are included in the analysis. The reliability test had been done to all the variables namely customer satisfaction, commitment, conflict handling, corporate image, reliability, responsiveness, assurance, empathy, tangibles, and customer loyalty. The result shows that all the independent and dependent variables are above 0.7 which are accepted.

## 4.4 Multiple Regressions

Multiple regressions are done to examine the simultaneous effects of several independent variables into dependent variables. The analysis used to understanding how much of the variance in the dependent variable is explained by a set of predictors. (Sekaran, 2004).

## Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.669a

.448

.422

.48389

The result of the multiple regression analysis shows that the coefficient of determination (R square) of the model is 0.448, indicating that the variance in customer loyalty contributed by all the independent variable(reliability, responsiveness, assurance, empathy, tangibles, customer satisfaction, corporate image, commitment and conflict handling) up to 44.8 percent. The adjusted R square shows a value of 0.422 which is 42.2 percent.

## Table 4.4 Regression Analysis Results

Model

Unstandardized Coefficients

Sig

B

Std.Error

(Constant)

-.517

.346

.137

Reliability(X1)

.077

.080

.338

Responsiveness (X2)

.138

.080

.086

Assurance(X3)

.087

.075

.249

Empathy(X4)

.120

.069

.085

Tangible(X5)

.166

.084

.049

Customer Satisfaction(X6)

.210

.081

.010

Corporate Image(X7)

.236

.070

.001

Commitment(X8)

.188

.070

.007

Conflict Handling(X9)

-.075

.077

.328

Dependent variable: Customer Loyalty

From the table above, as we can see the result of beta level of reliability, responsiveness, assurance, empathy, tangible, customer satisfaction, commitment, and corporate is positive. It shows that there is a positive relationship between the independent variable and dependent variable. Thus, the result of beta level of corporate image is the highest among the variables with € 0.236. However, the beta level of conflict handling is -0.075. It shows that there is a negative relationship between customer loyalty and conflict handling. It means that when the bank conflict handling skills decrease, the level of customer loyalty will increase. It may be indicate that when all the variables determine together, the variables of conflict handling became not important when compare the other variables.

The multiple regression analysis shows that that there is no significant in term of the affects of tangible, customer satisfaction, conflict handling, reliability, assurance, empathy and responsibility towards the customer loyalty. It is not significant difference at 1% and 5%. However, corporate image and commitment get the significant value is 0.001 and 0.007 which is significant difference at 1%. The table above can conduct a formula which is:

## Customer loyalty(Y) = -0.157+0.077(X1)+0.138(X2)+0.087(X3)+0.120(X4)+0.166(X5)+0.210(X6)+

## 0.236(X7)+0.188(X8)+(-0.075) (X9)

Each coefficient (B) tells the average change in dependent variables (Y) given a unit change in each independent variable(X) while all of the others X are held constant. If customer loyalty increases by one unit, the reliability will increase by 0.077 units, holding all the others independent variables constant.

## 4.5 Linear Regression

Linear regression is used to examine the relationship between one dependent and one independent variable.

## Table 4.5: Coefficients Analysis of reliability

Model

Unstandardized Coefficients

Sig

B

Std.Error

(Constant)

1.924

.255

.000

Reliability

.483

.071

.000

Table 4.6 illustrates that the coefficients analysis between dependent variable (Customer loyalty) and independent variable (Reliability). The significant value of reliability is 0.000, which is significant difference at 1% in the analysis table. So, the variable of reliability will affect customer loyalty towards bank. If customer loyalty increases by one unit, the reliability will increase by 0.483 units. It shows that there is positive relationship between customer loyalty and reliability. The table above can conduct a formula which is:

## Customer Loyalty= 1.924+0.483 (Reliability).

## Table 4.6: Coefficients Analysis of Responsibility

Model

Unstandardized Coefficients

Sig

B

Std.Error

(Constant)

1.960

.235

.000

Responsiveness

.486

.067

.000

Table 4.6 represents the coefficients analysis between dependent variable (Customer loyalty) and independent variable (Responsiveness). The significant value of responsiveness is 0.000, which is significant difference at 1% in the analysis table. It shows that the variable of responsibility will affect customer loyalty towards bank. If customer loyalty increases by one unit, the responsiveness will increase by 0.486 units. It shows that there is positive relationship between customer loyalty and responsiveness. The table above can conduct a formula which is:

## Customer Loyalty= 1.960+0.486[Responsiveness]

## Table 4.7: Coefficients Analysis of Assurance

Model

Unstandardized Coefficients

Sig

B

Std.Error

(Constant)

1.936

.261

.000

Assurance

.462

.070

.000

Table 4.7 illustrates that the coefficients analysis between dependent variable (Customer loyalty) and independent variable (Assurance). The significant value of assurance is 0.000, which is significant difference at 1% in the analysis table. It shows that the variable of assurance will affect customer loyalty towards bank. If customer loyalty increases by one unit, the assurance will increase by 0.462 units. Therefore, there is positive relationship between customer loyalty and assurance. The table above can conduct a formula which is:

## Customer Loyalty= 1.936+0.462 [Assurance]

## Table 4.8: Coefficients Analysis of Empathy

Model

Unstandardized Coefficients

Sig

B

Std.Error

(Constant)

2.290

.225

.000

Empathy

0.402

.066

.000

Table 4.8 illustrates that the coefficients analysis between dependent variable (Customer loyalty) and independent variable (Empathy). The significant value of empathy is 0.000, which is significant difference at 1% in the analysis table. It shows that the variable of empathy will affect customer loyalty towards bank. If customer loyalty increases by one unit, the empathy will increase by 0.402 units. Therefore, there is positive relationship between customer loyalty and empathy. The table above can conduct a formula which is:

## Customer Loyalty= 2.290+0.402 [Empathy]

## Table 4.9: Coefficients Analysis of Tangible

Model

Unstandardized Coefficients

Sig

B

Std.Error

(Constant)

1.671

.295

.000

Tangible

.519

.077

.000

The Table 4.9 showed that the coefficients analysis between dependent variable (Customer loyalty) and independent variable (Tangible). The significant value of tangible is 0.000, which is significant difference at 1% in the analysis table. If customer loyalty increases by one unit, the tangible will increase by 0.519 units. Therefore, there is positive relationship between customer loyalty and tangible. It shows that the variable of tangible will affect customer loyalty towards bank. The table above can conduct a formula which is:

## Customer Loyalty= 1.671+0.519[Tangible]

## Table 4.10: Coefficients Analysis of Customer Satisfaction

Model

Unstandardized Coefficients

Sig

B

Std.Error

(Constant)

1.477

.263

.000

Customer Satisfaction

.593

.072

.000

Table 4.10 represents the coefficients analysis between dependent variable (Customer loyalty) and independent variable (Customer Satisfaction). The significant value of customer satisfaction is 0.000, which is significant difference at 1% in the analysis table. It shows that the variable of customer satisfaction will affect customer loyalty towards bank. If customer loyalty increases by one unit, the customer satisfaction will increase by 0.593 units. Therefore, there is positive relationship between customer loyalty and customer satisfaction. The table above can conduct a formula which is:

## Customer Loyalty= 1.477+0.593 [Customer Satisfaction]

## Table 4.11: Coefficients Analysis of Corporate Image

Model

Unstandardized Coefficients

Sig

B

Std.Error

(Constant)

1.729

.298

.000

Corporate Image

.491

.076

.000

Table 4.11 showed that the coefficients analysis between dependent variable (Customer loyalty) and independent variable (Corporate Image). The significant value of corporate image is 0.000, which is significant difference at 1% in the analysis table. It shows that the variable of corporate image will affect customer loyalty towards bank. If customer loyalty increases by one unit, the corporate image will increase by 0.491 units. Thus, there is positive relationship between customer loyalty and corporate image. The table above can conduct a formula which is:

## Customer Loyalty= 1.729+0.491 [Corporate Image]

## Table 4.12: Coefficients Analysis of Commitment

Model

Unstandardized Coefficients

Sig

B

Std.Error

(Constant)

2.054

.249

.000

Commitment

.459

.071

.000

Table 4.12 illustrates that the coefficients analysis between dependent variable (Customer loyalty) and independent variable (Commitment). The significant value of commitment is 0.000, which is significant difference at 1% in the analysis table. It shows that the variable of commitment will affect customer loyalty towards bank. If customer loyalty increases by one unit, the commitment will increase by 0.459 units. Thus, there is positive relationship between customer loyalty and commitment. The table above can conduct a formula which is:

## Customer Loyalty= 2.054+ [0.459 Commitment]

## Table 4.13: Coefficients Analysis of Conflict Handling

Model

Unstandardized Coefficients

Sig

B

Std.Error

(Constant)

2.269

.255

.000

Conflict handling

.383

.071

.000

Table 4.13 represents the coefficients analysis between dependent variable (Customer loyalty) and independent variable (Conflict Handling). The significant value of conflict handling is 0.000, which is significant difference at 1% in the analysis table. It shows that the variable of conflict handling will affect customer loyalty towards bank. If customer loyalty increases by one unit, the conflict handling will increase by 0.383 units. So, there is positive relationship between customer loyalty and conflict handling. The table above can conduct a formula which is:

## Customer Loyalty= 2.269+ [0.383 Conflict Handling]

## 4.6 Hypothesis Testing

This section is structured is such a way that it addresses the results for the hypotheses which were early presented. Hypothesis are been tested to determine whether each of the hypothesis is been supported. In order to test these hypotheses, Pearson coefficient correlation analysis had been use with the guideline of general rules concerning the strength of association.

Correlation test is conducted in this research to see whether there is a relationship between dependent and independent variables. A correlation describes the strength of an association between variables.

According to Franzblau (1958), it proposed that the rules of thumb about correlation coefficient are determined by the strength of the associate which is the significant level. Firstly, correlation coefficient ranging from zero to about regarded as indicating no or negligible correlation. Besides, correlation coefficient falls in between 0.21 to 0.40 may considered as a low degree of correlation. Thus, correlation coefficient ranging from about 0.41 to 0.60 may indicates that is a moderate degree of correlation. The range of coefficient of 0.61 to 0.80 indicates there is a marked degree of correlation. Lastly, correlation coefficient ranging from about .80 to 1.00 may be regarded as high correlation.

## Table 4.12: Correlation between the independent variables and the customer loyalty

Pearson Correlation(r)

Sig.

(2 tailed)

N

Reliability

0.434

0.000**

200

Responsiveness

0.456

0.000**

200

Assurance

0.423

0.000**

200

Empathy

0.395

0.000**

200

Tangible

0.430

0.000**

200

Customer Satisfaction

0.507

0.000**

200

Corporate Image

0.417

0.000**

200

Commitment

0.415

0.000**

200

Conflict Handling

0.359

0.000**

200

**Correlation is significant at the 0.01 level (2-tailed).

## 4.6.1 Correlation between customer loyalty and reliability

H1: There is a significant relationship between reliability and customer loyalty

According at the table 4.4 above, person correlation (r-value) showed a number of 0.434 and P-value is 0.000 which means there is moderate degree of correlation between customer loyalty and reliability. Thus, there is correlation between two variables since P-value is less than 0.01.The result shows that there is a significant correlation between customer loyalty and reliability. Therefore, hypothesis 1 will not be rejected.

## 4.6.2 Correlation between customer loyalty and responsiveness

H2: There is a significant relationship between responsiveness and customer loyalty

According at the table 4.4 above, person correlation showed a number of 0.456 and P-value is 0.000 which means there is moderate degree of correlation between customer loyalty and responsiveness. Besides, there is correlation between two variables because P-value is less than 0.01. The result shows that there is a significant correlation between customer loyalty and responsiveness. Therefore, hypothesis 2 will not be rejected.

## 4.6.3 Correlation between customer loyalty and assurance

H3: There is a significant relationship between assurance and customer loyalty

According at the table 4.4 above, person correlation showed a number of 0.423 and P-value is 0.000 which means there is moderate degree of correlation between customer loyalty and responsibility. Furthermore, there is correlation between two variables because P-value is less than 0.01. The result shows that there is a significant correlation between customer loyalty and assurance. Therefore, hypothesis 3 will not be rejected.

## 4.6.4 Correlation between customer loyalty and empathy

H4: There is a significant relationship between empathy and customer loyalty

According at the table 4.4 above, person correlation showed a number of 0.395 and P-value is 0.000 which means there is low degree of correlation between customer loyalty and empathy. Moreover, there is correlation between two variables since P-value is less than 0.01. The result shows that there is a significant correlation between customer loyalty and empathy. Therefore, hypothesis 4 will not be rejected.

## 4.6.5 Correlation between customer loyalty and tangible

H5: There is a significant relationship between tangible and customer loyalty

Table 4.1 represent that person correlation is 0.430 and P-value is 0.000 which means there is moderate degree of correlation between customer loyalty and tangible. In addition, there is correlation between two variables because the P-value is less than 0.01. The result shows that there is a significant correlation between customer loyalty and tangible. Therefore, hypothesis 5 will not be rejected.

## 4.6.6 Correlation between customer loyalty and customer satisfaction

H6: There is a significant relationship between customer satisfaction and customer loyalty

As illustrated in table 4.4 above, person correlation showed a number of 0.507 and P-value is 0.000 which means there is moderate degree of correlation between customer loyalty and customer satisfaction. Furthermore, there is correlation between two variables because P-value is less than 0.01. The result shows that there is a significant correlation between customer loyalty and customer satisfaction. Therefore, hypothesis 6 will not be rejected.

## 4.6.7 Correlation between customer loyalty and corporate image

H7: There is a significant relationship between corporate image and customer loyalty

According at the table 4.4 above, person correlation showed a number of 0.417 and P-value is 0.000 which means there is moderate degree of correlation between customer loyalty and corporate image. Besides; there is correlation between two variables since P-value is less than 0.01. The result shows that there is a significant correlation between customer loyalty and corporate image. Therefore, hypothesis 7 will not be rejected.

## 4.6.8 Correlation between customer loyalty and commitment

H8: There is a significant relationship between commitment and customer loyalty

According to the table 4.4 above, person correlation showed a number of 0.415 and P-value is 0.000 which means there is moderate degree of correlation between customer loyalty and commitment. Besides, there is correlation between two variables because P-value is less than 0.01. The result shows that there is a significant correlation between customer loyalty and commitment. Therefore, hypothesis 8 will not be rejected.

## 4.6.9 Correlation between customer loyalty and conflict handling

H9: There is a significant relationship between conflict handling and customer loyalty

Based on the table 4.4 above, person correlation showed a number of 0.359 and P-value is 0.000 which means there is low degree of correlation between customer loyalty and conflict handling. Besides, there is correlation between two variables since P-value is less than 0.01. The result shows that there is a significant correlation between customer loyalty and conflict handling. Therefore, hypothesis 9 will not be rejected.

## 4.7 Conclusion

The overall of the results has found out the answer for all the research question as shown in chapter 1.The Pearson correlation analysis shown there was significant relationship between nine independent variable (reliability, responsiveness, assurance, empathy, tangibles, customer satisfaction, commitment, conflict handling, and corporate image) and dependent variable(customer loyalty). Therefore, all hypotheses will not be rejected. Other than that, the Pearson correlation analysis also determines that customer satisfaction is most important factors affect customer loyalty towards bank.