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The relationship between independent variables and dependent variables

This chapter is presents the data analysis and discuss about the results obtained. The purpose for this chapter is to study the relationship between independent variables and dependent variable. In this chapter, the data was be determined and discussed by using few analyses. The analysis has included descriptive analysis, reliability analysis, Pearson’s Product-Moment Correlation, ANOVA, and regression. In addition, there are two types of the regression was being mention in this chapter which are linear regression and multiple regression. Linear regression uses only two variables which are one dependent variable and one independent variable. However, multiple regression are uses three or more variables which are one dependent variable and two or more independent variables.

4.2 Frequency Analysis

Frequency analysis is use to describe the population or sample being studied. The purpose of doing frequency analysis is to summarize and describe the data. In the frequency analysis section, the respondents’ gender, age, race, income level, occupation, and others were being conducted. In this section, the frequency and percent were being discussed. Besides, frequency analysis also has measure of central tendency such as mean and dispersion such as standard deviation. The result also can be show by using bar graphs, histogram, pie charts, line charts, and others.

What is your gender?

Frequency

Male

51

Female

49

Total

100

Mean: 1.49

Standard Deviation: 0.502

Table 4.2.1 Gender of Respondent

Figure 4.2.1 Gender of Respondent

Table 4.2.1 is show the gender of the respondents. From the table, we can know that the mean of the gender is 1.49 and the standard deviation of gender is 0.502. Besides, the pie chart is show about the percentage of the gender of respondent. The respondents are randomly selected. The highest respondents that responded to the survey are male which is 51% whereas the lowest percentage of respondents is female which is 49%.

What is your age?

Frequency

Below 20

1

20 to 30

46

31 to 40

33

41 and above

20

Total

100

Mean: 2.72

Standard Deviation: 0.792

Table 4.2.2 Age Group of Respondent

Figure 4.2.2 Age Group of Respondent

Table 4.2.2 is show the age of the respondents. Pie chart also can be show in this section. Figure 4.2.2 is show the percentage for the age of respondent. The highest respondents that responded to the survey are from the range of 20 to 30 years old which is 46% whereas the lowest percentage of respondents that respond falls to the group of below 20 years old which is 1%. There were 33 respondents are 31 to 40 years old and 20 respondents are 41 years old and above. The frequency is not same for each age group because the respondents are being selected randomly. In addition, the mean value for age group of respondent is 2.72 and the standard deviation is 0.792.

What is your race?

Frequency

Malay

29

Chinese

43

Indian

28

Total

100

Mean: 1.99

Standard Deviation: 0.759

Table 4.2.3 Race of Respondent

Figure 4.2.3 Race of Respondent

Table 4.2.3 shows the race of the respondents who took part in this survey. The mean value for race of respondent is 1.99 and the standard deviation is 0.759. Figure 4.2.3 is show the percentage of race of respondent. It is shown that the Chinese population occupies 43% which is 43 respondents from the questionnaires distributed. The second will be the Malay population with 29 respondents which is 29%. In addition, there are 28 respondents is Indian which occupies 28%.

What is your income level?

Frequency

RM1001 to RM2000

8

RM2001 to RM3000

34

RM3001 to RM4000

37

RM4000 above

21

Total

100

Mean: 3.71

Standard Deviation: 0.891

Table 4.2.4 Income Level of Respondent

Figure 4.2.4 Income Level of Respondent

Table 4.2.4 is show the income level of the respondents. The mean has obtained 3.71 and the standard deviation has obtained 0.891. From the figure 4.2.4, we can know that there are 37 respondents are earn RM3001 to RM4000 each month which is occupies 37% among the respondents. Besides, the income level of RM1001 to RM2000 are occupies 8%. In addition, there are 34% of respondents’ income level are RM2001 to RM3000 and 21% of respondents’ income level are RM4000 above. The respondents which randomly selected are come from different industry so that their monthly income level might different.

What is your occupation?

Frequency

Manager

20

Operator

25

Salesperson

32

Others

23

Total

100

Mean: 2.58

Standard Deviation: 1.056

Table 4.2.5 Occupation of Respondent

Figure 4.2.5 Occupation of Respondent

Table 4.2.5 is show the occupation of the respondents. The mean for occupation of respondent is 2.58 and the standard deviation is 1.056. From the figure above, we can know that there are 32% of respondents are work as salesperson. 25% of respondents are work as operator, and 20% of respondents are work as manager. Besides, there are 23% of respondents are choosing others which has included businessman, lawyer, and accountant.

Do you aware the important of mobile banking nowadays?

Frequency

Yes

53

No

47

Total

100

Mean: 1.47

Standard Deviation: 0.502

Table 4.2.6

Figure 4.2.6

Table 4.2.6 is showed the respondents’ point of view toward awareness of the important of mobile banking nowadays. The mean has obtained 1.47 and the standard deviation has obtained 0.502. The figure show that there are 53% of respondents aware to the important of mobile banking might because they feel that using mobile banking can give them a lot of benefit. Besides, there are 47% of respondents are not aware to the important of mobile banking. It might because they are not familiar with mobile banking services.

Do you have a good experience when using the mobile banking services?

Frequency

Yes

54

No

46

Total

100

Mean: 1.46

Standard Deviation: 0.501

Table 4.2.7 Experience of Respondent

Figure 4.2.7 Experience of Respondent

Table 4.2.7 is show the experience of respondents when they using the mobile banking services. The mean for experience of respondent is 1.46. Besides, the standard deviation for experience of respondent is 0.501. In addition, figure 4.2.7 has showed that there are 54% of respondents have the good experience when they are using mobile banking services. Besides, there are 46% of respondents do not have good experience when using mobile banking services. The screen of the mobile phone might give negative experience to the respondents.

Have you applied the value package that provide by mobile banking telecommunications company such as Maxis and Digi to got the benefit on the fees on internet service?

Frequency

Yes

36

No

64

Total

100

Mean: 1.64

Standard Deviation: 0.482

Table 4.2.8 Percentage of Respondent has Applied for Value Package

Figure 4.2.8 Percentage of Respondent has Applied for Value Package

Table 4.2.8 is show the percentage of how many respondents has applied for the value package that provide by mobile telecommunications to got the benefit on fees on internet service. From the table above, we can know that the mean for this question is 1.64 and the standard deviation is 0.482. Besides, figure 4.2.8 has showed that there are 64% of respondents have not applied for this kind of package. It is because the respondents feel that this package is not useful and they are seldom using mobile banking services. But there are 36% of respondents have applied for this value package because they think that it can help them reduce in cost and it is valuable.

I have used the mobile banking services,

Frequency

Below 2 times per month

42

2 to 10 times per month

44

11 to 20 times per month

13

Above 20 per month

1

Total

100

Mean: 1.73

Standard Deviation: 0.723

Table 4.2.9 Times per Month that Respondents Used Mobile Banking Services

Figure 4.2.9 Times per Month that Respondents Used Mobile Banking Services

Table 4.2.9 is show the frequency of respondents that used the mobile banking services. The mean for this question has obtained 1.73 and the standard deviation has obtained 0.723. From the figure 4.2.9, we can determine that there are 44% of respondents are used this mobile banking services 2 to 10 times per month and 1% of the respondents are used this services above 20 times per month. Besides, there are 42% of respondents are used mobile banking services below 2 times per month and 13% of respondents are used this services 11 to 20 times per month.

What type of mobile banking products that you usually use?

Frequency

Make bill payment (utility bills, credit cards etc)

30

Make transaction

8

Check the account balance or latest transaction

46

Request services (cheque book request)

16

Total

100

Mean: 2.48

Standard Deviation: 1.087

Table 4.2.10 Type of Mobile Banking Products that Respondents Usually Use

Figure 4.2.10 Type of Mobile Banking Products that Respondents Usually Use

Table 4.2.10 is showing the types of mobile banking products that respondents are usually used. This question has the mean value of 2.48 and the standard deviation of 1.087. From figure 4.2.10, we can know that the most popular mobile banking services that respondents used is to check their account balance or latest transaction by using mobile banking which is occupies 46%. Besides, there are only 8% of respondents are using mobile banking to make the transaction. In addition, there are 30% of the respondents are using mobile banking to make the bill payment and 16% of the respondents are using mobile banking to request for services.

4.3 Descriptive Analysis

Descriptive analysis is used to describe the data in quantitative terms. In the descriptive analysis, Mean and Standard Deviation of the dependent variable and independent variables has been discussed.

4.3.1 Summary of Descriptive Statistics

Descriptive Statistics

N

Mean

Demographic

100

3.4100

Trust

100

3.1920

Convenient

100

3.3020

Save Time and Cost

100

3.3900

Services and service Quality

100

3.5020

Perceived Ease to Use

100

3.3440

Complexity

100

3.4660

Customers’ Perception

100

3.5386

Table 4.3.1 Summary of Descriptive Statistics

Table 4.3.1 show the mean and standard deviation of the independent variables and dependent variable. Table 4.3.1 has show that the mean for all variables has above 3. It means that the respondents are more choosing either disagree or agree of the question.

4.3.2 Descriptive Analysis of Demographic

Mean

Std. Deviation

Customers who live in development countries are more familiar with using mobile banking services.

3.31

1.368

Young generations are more confident and have interest to use mobile banking.

4.49

0.559

Customers who have high income level are more willing to use the mobile banking because they not much worried that they will lose their money due to the error occur when they using mobile banking.

2.99

1.367

People who have professional jobs (eg: lawyer, accountant, etc) are more using mobile banking services.

3.19

1.440

Male are more using mobile banking services compare to female because male are more willing try to use new products or services.

3.06

1.448

Table 4.3.2 Descriptive Analysis of Demographic

Table 4.3.2 has showed that the highest mean in demographic is the young generations are more confident and have interest to use the mobile banking which is 4.49. It means customers feel that young generations have high self-confidence in using mobile banking. Besides, customers who have high income level are more willing to use mobile banking have lowest mean which is 2.99. It mean that customers who have high income level also will worried that they will lose their money due to the error occur when they using mobile banking.

4.3.3 Descriptive Analysis of Trust

Mean

Std. Deviation

Hacker or intruders will not get in to my private profile easily, because I fully trust the bank.

3.25

1.533

Connection is breaks or disconnect will pose the risks to mine banking actions.

3.56

1.388

I do not trust my skills and worry that I might miss or choose the wrong options when using the mobile banking because the screen of mobile phone is smaller.

2.82

1.373

I worried that I would loss due to the wrong option.

3.14

1.436

I do not trust the functionality of banking services by using the mobile phone.

3.19

1.285

Table 4.3.3 Descriptive Analysis of Trust

Table 4.3.3 has show that the highest mean in trust is customers believe that connection breaks or disconnect will pose the risks to their banking actions which is 4.49. It means customers feel that they will lose their money when using mobile banking if suddenly disconnected. Besides, customers also trust their skills and believe that they will not choose the wrong options when using the mobile banking because the screen of mobile phone is smaller and its mean value is 2.99.

4.3.4 Descriptive Analysis of Convenient

Mean

Std. Deviation

Mobile banking had made my life more easier compare with the traditional banking.

3.47

1.039

I think that mobile banking system is a user friendly which help me a lot in doing transactions such as transfer funds, make bills payment, checking the account balance and etc.

4.15

0.857

I was become less willing to visit the traditional branches and more receptive to the mobile banking because mobile banking offers 24 hours service.

2.76

1.084

I prefer to use the mobile banking because it is free access and faster.

3.08

1.107

I feel that the keypad and display of the mobile phone will not affect me when using the mobile banking.

3.05

1.258

Table 4.3.4 Descriptive Analysis of Convenient

Table 4.3.4 has show that the highest mean in the convenient is customers feel that mobile banking system is user friendly which is 4.15. It means customers feel that mobile banking system can help them do a lot of transaction such as transfer fund, make bill payments and others. Besides, the lowest mean in convenient is customers become less willing to visit the traditional braches which is 2.67. It means that customers has will continue to visit the traditional branches although it do not offer 24 hours services.

4.3.5 Descriptive Analysis of Save Time and Cost

Mean

Std. Deviation

I think that using mobile banking can help me to save time.

3.25

1.473

I am not preferred to visit traditional banking to make transaction because I do not want to queue for long time.

4.49

0.559

I think that using mobile banking cannot help me to save cost because I need to purchase the high-end / advance mobile phone before I get the benefits of using the mobile banking.

2.97

1.389

I think that mobile banking perceives expensive to the low income customers.

3.18

1.452

I think that mobile banking is fast to use.

3.06

1.448

Table 4.3.5 Descriptive Analysis of Save Time and Cost

Table 4.3.5 has showed that the highest mean in save time and cost is 4.49. It means customers feel that they are not preferred to visit the traditional branches to make the transaction because they do not want to queue for long time. Besides, customers who think that mobile banking cannot help them save cost have the lowest mean which is 2.99. It mean that customers has think that using mobile banking can help them to save cost although they need to purchase the smart phone before they get the benefit.

4.3.6 Descriptive Analysis of Service and Service Quality

Mean

Std. Deviation

I think that using the mobile banking can improve the living standard and quality of life.

3.40

1.491

I can avoid over spend because I can check the account balance anytime and anywhere.

4.45

0.500

I think that mobile banking can give me greater control over my banking transactions.

2.94

1.399

I am willing to use mobile banking and sacrifice with the new technology.

3.20

1.470

I can enjoy the benefits of using the mobile banking and sacrifice with that services.

3.52

1.306

Table 4.3.6 Descriptive Analysis of Service and Service Quality

Table 4.3.6 has show that the highest mean in the service and service quality is customers can avoid over spend which obtained 4.49. It is because customers can check the account balance anytime and anywhere. Besides, customers have thought that mobile banking can give them greater control over the banking transaction has the lowest mean which obtained 2.94. It means that customers were also over spending although they are able to check the account balance by using mobile banking.

4.3.7 Descriptive Analysis of Perceived Ease to Use

Mean

Std. Deviation

I choose to use the mobile banking because of its benefits.

3.33

1.231

I am not willing to change the banking system because I am satisfied with the previous banking experience.

3.87

1.212

I still prefer to use the familiar banking services.

3.02

1.128

I do not have confident to use the mobile banking services because I do not have experience with this new technology.

3.29

1.183

I can do the budgeting and tracing spending without waiting for monthly paper statement.

3.21

1.113

Table 4.3.7 Descriptive Analysis of Perceived Ease to Use

Table 4.3.7 has show that the highest mean in the perceived ease to use is customers are not willing to change their current banking system which has obtained 3.87. It is because they are satisfied with the previous banking experience. Besides, customers has prefer to use the familiar banking services has the lowest mean which obtained 3.02. It means that customers might change their current banking services in future.

4.3.8 Descriptive Analysis of Complexity

Mean

Std. Deviation

The complex design of the banks’ web page is make me difficult to utilize their web page via hand phone.

4.29

0.946

I need more time to adapt the mobile banking services because of the complex design.

3.14

1.189

I feel that mobile banking is complex and it need better skill and effort needed for adopting and using it.

3.31

1.228

My negative experience of using mobile banking services will decrease my usage intention of mobile banking.

3.64

1.059

I think that mobile banking requires knowledge and learning.

2.95

1.403

Table 4.3.8 Descriptive Analysis of Complexity

Table 4.3.8 has show that the highest mean in the complexity is the complex design of the bank’s web page is make customers feel difficult to utilize via using smart phone which obtained 4.29. It means customers do not prefer to the complex design. Besides, mobile banking is requires knowledge and learning has the lowest mean which obtained 2.95. It means that customers feel that using mobile banking is not requires knowledge and learning.

4.3.9 Descriptive Analysis of Customers’ Adoption

Mean

Std. Deviation

I think that demographic will affect customers in using mobile banking.

3.31

1.398

I think that trust will affect me to use mobile banking.

4.49

0.559

I feel that convenient might influence me to use mobile banking.

2.99

1.367

Save time and cost will affect me in using the mobile banking service.

3.19

1.440

Because of the service and service quality of using mobile banking, so I am willing to use mobile banking.

3.06

1.448

I think that perceived ease to use will affect me to use mobile banking.

3.24

1.485

The complexity of using mobile banking will affect me in choosing to use the mobile banking.

4.49

0.559

Table 4.3.9 Descriptive Analysis of Customers’ Adoption

Table 4.3.9 has showed that trust and complexity are most affect customers in choosing and using mobile banking services. The mean value that trust and complexity obtained is 4.49. Besides, service and service quality has the lowest mean which has obtained 3.06. It means customers have think that service and service quality would not much affect them in using mobile banking services.

4.4 Reliability Analysis

Reliability analysis is a technique to determine the reliability of the scale with multiple items. Reliability was determined for the scale based on Cronbach’s coefficient alpha. Cronbach’s coefficient alpha is one of the most used reliability statistics to test the reliability of each variable. In addition, Cronbach’s alpha also measure that how closely a set of the items are as a group. When the Cronbach’s alpha has equaled or greater than 0.7, that means the variables are acceptable. According to Sekaran (2003), Cronbach’s alpha is computed in terms of average intercorrelations among the items measuring the concept. Furthermore, Sekaran (2003) also has stated that the closer of the Cronbach’s alpha is to 1, the higher the internal consistency reliability. There are eight variables have been tested in reliability. Each independent variable has consisted of five questions. However, dependent variable has consisted seven questions.

Reliability Statistical

Cronbach’s Alpha

Independent Variables

Demographic

.902

Trust

.898

Convenient

.901

Save Time and Cost

.897

Services and service Quality

.889

Perceived Ease to Use

.896

Complexity

.900

Dependent Variable

Customers’ Perception

.778

Table 4.4.1 Reliability Analysis

From the table 4.4.1, we can determine that the Cronbach’s alpha of all dependent variable and independent variables which have being selected are higher than 0.7. It means that all the dependent variable and independent variables are acceptable. Independent variables of demographic, convenient and complexity have obtained very high Cronbach’s alpha score which is 0.902, 0.901, and 0.900. Those can indicate that the scale has very high internal consistency.

Besides, independent variables of trust, save time and cost, services and service quality, and perceived ease to use have obtained good Cronbach’s alpha score which is 0.898, 0.897, 0.889, and 0.896. In addition, customers’ perception also is accepted which has obtained 0.778.

4.5 Hypothesis Testing

4.5.1 Multiple Regression

Multiple regression is used to determine the relationship between dependent variable and several possible of independent variables. According to Jacob et al (2003), multiple regression are used to determine the minimum set of the variables which data have been collected. Gerard (2008) has defined that in model summary table, R is representing the multiple correlation coefficient that can determine how strongly the independent variables are related to the dependent variable and R2 is show the coefficient of the determination. Moreover, adjusted R2 is to takes into account the sample size and the number of independent variables. Adjusted R2 are always being equal to or less than R2.

Model Summary

Model

R

R Square

Adjusted R Square

1

.993a

.986

.984

Predictors: (Constant), Demographic, Trust, Convenient, Save Time and Cost, Services and Service Quality, Perceived Ease to Use, Complexity

Table 4.5.1 Model Summary

Table 4.5.1 has shows that R is 0.993. Besides, it also shows that R2 is 0.986. It means that the variance in customers’ perception contributed by all the seven variables up to 98.6%. Besides, the adjusted R2 is 0.984. It also can determine that those variables have accounts for 98.4% of variance in the customers’ perception. In addition, the standard error of the estimate is 0.10448.

ANOVA table is show the overall significance on the research model. According to Gerard (2008), the model is known as regression and the error is known as residual. In addition, Gerard (2008) also stated that the formula to calculate the mean square is the sum of squares divided by the corresponding degrees of freedom. According to David (1996), it is significance when p < 0.05, while any value which is greater than this will define as non-significance effects. Besides, David (1996) also stated that the F value is measurement of how different the means are relative to variability within the variables.

ANOVAb

Model

Sum of Squares

df

Mean Square

F

1

Regression

Residual

Total

68.622

1.004

69.627

7

92

99

9.803

.011

898.037

Predictors: (Constant), Demographic, Trust, Convenient, Save Time and Cost, Services and Service Quality, Perceived Ease to Use, Complexity

Dependent Variable: Customers’ Perception

Table 4.5.2 ANOVA

As the table 4.5.2 showed that the F ratio for this research model is 898.037. Besides, it also shows that the significance value is 0.000, which is p < 0.05; it means that there is a relationship between the dependent variable and independent variables. Thus, we can conclude that demographic, trust, convenient, save time and cost, service and service quality, perceived ease to use, and complexity have the relationship between affect the customers’ perception toward mobile banking.

Coefficients is to test the relationship between dependent variable and independent variables. According to Roberta (2010), if the significance level (p value) is more than 0.05, it should accept null hypothesis (H0). However, if the significance level is less than 0.05, it should reject null hypothesis (Ha).

Coefficientsa

Unstandardized Coefficients

Standardized Coefficients

Model

B

Std. Error

Beta

t

1

(Constant)

.268

.086

3.112

Demographic

.207

.010

.269

20.201

Trust

.046

.012

.049

3.710

Convenient

.061

.020

.049

3.126

Save Time and Cost

.681

.012

.902

55.784

Service and Service Quality

-.040

.011

-.046

-3.469

Perceived Ease to Use

.072

.019

.060

3.747

Complexity

-.057

.019

-.048

-2.971

Dependent Variable: Customers’ Perception

Table 4.5.3 Coefficients

Table 4.5.3 has shows that all the independent variables are significance which is p< 0.005. Therefore, we can determine that all the independent variables have the relationship between the dependent variables. Table 4.5.3 has shows that demographic (β= 0.207) is significance (p=0.000). Thus, the null hypothesis has been rejected. In others words, customers had feel that demographic will affect them in using the mobile banking. According to Howcroft et al. (2002), the younger consumers have felt that using mobile banking is convenient. However, adult consumers are mobile banking is lack of communication and it has bring the inconvenient when they make the transaction.

From the table 4.5.3, we can define that trust (β=0.046) is significance (p= 0.000). Thus, we can conclude that null hypothesis has to be rejected. It shows that there is the relationship between customers’ perception and trust. Customers are worried that they will lose their money due to the disconnected or errors when they are using mobile banking (Laukkanen et al 2007). Besides, Luarn and Lin (2005) also have stated that customers are very concern about the security and privacy issues.

In addition, we also can determine that convenient (β= 0.061) is significance (p= 0.002). It means that there is a relationship between customers’ perception and convenient and we should rejected null hypothesis. According to Karjaluoto (2002), mobile banking has offer a lot of services such as bill payment, make transaction, transfer fund and others and those services has make customers feel convenient when they want to conduct the banking activities.

Moreover, save time and cost also has the relationship on the mobile banking services. Save time and cost (β= 0.681) is significance (p= 0.000) and it should reject null hypothesis. Customers have felt that using mobile banking can help them to save time and cost. According to Suoranta (2003), one of the reasons that customer willing to use mobile banking service is because mobile banking are related to time and cost saving.

Service and service quality (β= -0.040) is significance (p= 0.001) and it should reject null hypothesis. Therefore, we can state that customers’ perception has the relationship between service and service quality. Black et al. (2001) has define that people will use mobile banking is because the high quality of the services.

Moreover, perceived ease to use (β= 0.072) is significance (p=0.000). It shows that there is the relationship between customers’ perception and perceived ease to use. So, we should reject null hypothesis. According to Davis (1989), customers have felt that mobile banking is easy to use and customers can enjoy the benefits when using the mobile banking services.

Complexity (β= -0.057) is significance (p= 0.004) and it shows that there is a relationship between customers’ perception and complexity. Thus, we need to reject null hypothesis. Complexity can affect the customers’ perception toward mobile banking (Lee et al, 2003). Complexity design of the banks’ web page will make customers difficult to utilize their web site. Besides, complexity web page might decrease the customers’ satisfaction when using the mobile banking services.

4.6 Pearson Correlation Analysis

Pearson Correlation is use to study the relationship between dependent variable and independent variable either in the same or reverse direction. According to Amit (2009), when the significance value (r value) > 0, it is indicate positive relationship. However, when r < 0, it is indicate negative relationship.

4.6.1 Correlations between Customers’ Perception and Demographic

Correlations

Demographic

Demographic

Pearson Correlation

Sig. (2-tailed)

N

1

100

Customers’ Perception

Pearson Correlation

Sig. (2-tailed)

N

0.370**

0.000

100

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

Table 4.6.1 Correlations between Customers’ Perception and Demographic

From table 4.6.1, the Pearson Correlation Analysis has shows the relationship between demographic and customers’ perception. It shows that the significance value (p= 0.000) and Pearson Correlation value (r= 0.370). Given that p value is lower than 0.01, so it can conclude that there is significance correlation between customers’ perception and demographic. Besides, we also can conclude there is a moderate positive relationship between customers’ perception and demographic. It means that customers who have different demographic background will have the different point of views on mobile banking services. So, we can conclude that demographic can affect the customers’ perception toward mobile banking.

4.6.2 Correlations between Customers’ Perception and Trust

Correlations

Trust

Trust

Pearson Correlation

Sig. (2-tailed)

N

1

100

Customers’ Perception

Pearson Correlation

Sig. (2-tailed)

N

0.201*

0.045

100

*. Correlation is significant at the 0.05 level (2-tailed)

Table 4.6.2 Correlations between Customers’ Perception and Trust

Table 4.6.2 has shows that the significance value (p= 0.045) which is lower than 0.01 and Pearson Correlation value (r= 0.201). Therefore, it can conclude that there is significance correlation between customers’ perception and trust. Besides, we also can conclude there is a weak positive relationship between customers’ perception and trust. It means that when customers are confident and believe the function of the mobile banking, they willing to use mobile banking services.

4.6.3 Correlations between Customers’ Perception and Convenient

Correlations

Convenient

Convenient

Pearson Correlation

Sig. (2-tailed)

N

1

100

Customers’ Perception

Pearson Correlation

Sig. (2-tailed)

N

0.604**

0.000

100

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

Table 4.6.3 Correlations between Customers’ Perception and Convenient

Table 4.6.3 has shows that the significance value (p= 0.000) which is lower than 0.01 and Pearson Correlation value (r= 0.604). Thus, it can conclude that there is significance correlation between customers’ perception and convenient. Besides, we also can conclude there is a strong positive relationship between customers’ perception and convenient. It means that when customers feel that using mobile banking is convenient, they will be willing to use this service.

4.6.4 Correlations between Customers’ Perception and Save Time and Cost

Correlations

Save Time and Cost

Save Time and Cost

Pearson Correlation

Sig. (2-tailed)

N

1

100

Customers’ Perception

Pearson Correlation

Sig. (2-tailed)

N

0.954**

0.000

100

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

Table 4.6.4 Correlations between Customers’ Perception and Save Time and Cost

Table 4.6.4 is shows the correlations between customer’ perception and save time and cost. From this table, we can determine that the significance value (p= 0.000) which is lower than 0.01 and Pearson Correlation value (r= 0.954). Therefore, it can conclude that there is significance correlation between customers’ perception and save time and cost. Besides, we also can conclude there is a strong positive relationship between customers’ perception and save time and cost. It means that when customers feel that using mobile banking can help them save time and cost, they will be willing to use this service.

4.6.5 Correlations between Customers’ Perception and Service and Service Quality

Correlations

Service and Service Quality

Service and Service Quality

Pearson Correlation

Sig. (2-tailed)

N

1

100

Customers’ Perception

Pearson Correlation

Sig. (2-tailed)

N

0.257**

0.000

100

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

Table 4.6.5 Correlations between Customers’ Perception and Service and Service Quality

Table 4.6.5 is shows the correlations between customers’ perception and service and service quality. From this table, we can determine that the significance value (p= 0.000) which is lower than 0.01 and Pearson Correlation value (r= 0.257). Therefore, it can conclude that there is significance correlation between customers’ perception and save time and cost. Besides, we also can conclude there is a weak positive relationship between customers’ perception and service and service quality. It means that when customers feel that they can enjoy the service and service quality when using mobile banking, they will be willing to use this service.

4.6.6 Correlations between Customers’ Perception and Perceived Ease to Use

Correlations

Perceived Ease to Use

Perceived Ease to Use

Pearson Correlation

Sig. (2-tailed)

N

1

100

Customers’ Perception

Pearson Correlation

Sig. (2-tailed)

N

0.165

0.000

100

Table 4.6.6 Correlations between Customers’ Perception and Perceived Ease to Use

Table 4.6.6 is shows the correlations between customers’ perception and service and service quality. From this table, we can determine that the significance value (p= 0.000) which is lower than 0.01 and Pearson Correlation value (r= 0.165). Therefore, it can conclude that there is significance correlation between customers’ perception and perceived ease to use. Besides, we also can conclude there is a weak positive relationship between customers’ perception and perceived ease to use. It means that when customers feel that they can enjoy the benefits when using mobile banking, they will be willing to use this service.

4.6.7 Correlations between Customers’ Perception and Complexity

Correlations

Complexity

Complexity

Pearson Correlation

Sig. (2-tailed)

N

1

100

Customers’ Perception

Pearson Correlation

Sig. (2-tailed)

N

0.232*

0.020

100

*. Correlation is significant at the 0.05 level (2-tailed)

Table 4.6.7 Correlations between Customers’ Perception and Complexity

Table 4.6.7 is shows the correlations between customers’ perception and complexity. From this table, we can determine that the significance value (p= 0.020) which is lower than 0.05 and Pearson Correlation value (r= 0.232). Therefore, it can conclude that there is significance correlation between customers’ perception and complexity. Besides, we also can conclude there is a weak positive relationship between customers’ perception and complexity. It means that when customers feel that mobile banking is difficult to use due to the complexity of the design on the banks’ web page, they will not willing to use this service.


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