CHAPTER V AN ANALYSIS OF CUSTOMERS SATISFACTION AND FACTORS INFLUENCING THE INTERNET BANKING 5.1 INTRODUCTION Banking industry is also one of the predominant industries adopting technologies which are helpful in providing better services to customers. Quality of service is improved by using technological innovations. Internet banking is time-saving. There will be huge acceptance of internet banking with the passage of time with growing awareness and education. A great many people are shifting to internet banking and are readily accepting the usefulness of this bounty. Many factors are attracting the public like perceived ease of use, perceived usefulness, security and privacy. Perceived ease of use is the degree to which using IT is free of effort for the user. Internet banking is the latest development that has added a new dimension to banking transactions by allowing customers to conduct financial transaction through the Internet while perceived usefulness is defined as the degree to which a person believes that using a particular technology would improve job performance. Banking institutions have taken several adequate measures to ensure complete security for internet banking. Hence, the present chapter deals with the 155
level of satisfaction regarding the internet services offered by the public and private sector banks, factors identifying the satisfaction of customers towards the internet banking services offered by the banks and the factors determining the customer satisfaction for public and private sector banks in Tirunelveli district. 5.2. LEVEL OF SATISFACTION Increased competition, slower growth and mature markets are also forcing many businesses to review their customer service strategy. Many businesses are channeling more efforts to retain existing customers rather than to acquire new ones. Moreover, banks carry on business with public money and therefore, customers expect better services from them. Hence the present section attempts to discuss the level of customers satisfaction towards the services on internet banking among the selected public and private sector banks in Tirunelveli district. The level of satisfaction has been determined by the score values calculated for nineteen statements which are associated with customers satisfaction/fulfillment towards the internet banking services offered by the banks by adopting 7-point scale (ranging from one indicating strongly disagree to seven indicating strongly agree ), namely Likert Type Scale. Thus, the total satisfaction score of a respondent is obtained by adding up the scores of all the nineteen statements. The level of satisfaction is classified into three categories namely low level, medium level and high level satisfaction for analytical purposes. The score values ³ `X + S.D. and the score values `X S.D. have been classified as high level of satisfaction and low level of satisfaction respectively. 156
The score values between (`X+S.D.) and (`X-S.D.) have been classified as medium level of satisfaction. `X and S.D. are the arithmetic mean and standard deviation calculated from the score value of six hundred respondents. The calculated values of `X and S.D. are 117.41 and 12.49 for public sector banks respectively. Therefore, `X + S.D. (117.41 + 12.49) = 129.90 = 130 and above `X S.D. (117.41 12.49) = 104.92 = 105 and below (`X - S.D) and (`X + S.D.) between 105 to 130 - High level of Satisfaction - Low Level of Satisfaction - Medium Level of Satisfaction In the case of private sector banks, the calculated values of `X and S.D. are 115.37 and 10.41 respectively. Therefore, `X + S.D. (115.37 + 10.41) = 125.78 = 126 and above `X S.D. (115.37 10.41) = 104.96 = 105 and below (`X - S.D) and (`X + S.D.) between 105 to 126 - High level of Satisfaction - Low Level of Satisfaction - Medium Level of Satisfaction For testing the relationship between respondents profile variables and level of satisfaction, Chi-square test is employed. For computing Chi-Square test, the following formula is used. (O E) 2 Chi-Square = å ---------- with (r-1) (c-1) degrees of freedom. E 157
Where, O = Observed frequency, E = Expected frequency, c = Number of column in a contingency table and r = Number of row in a contingency table. The calculated value of Chi-Square is measured with the table value of Chi-Square for given level of significance usually at 5 per cent level. If at the stated level, the calculated value (C.V.) is less than the table value (T.V.), the null hypothesis is accepted or otherwise it is rejected. 5.2.1. Levels of Satisfaction The levels of satisfaction of the six hundred sample respondents from public and private sectors in Tirunelveli district are given in Table 5.1. Sl. No. Levels of Satisfaction TABLE 5.1 LEVELS OF SATISFACTION Public Sector Banks No. of Percentage respondents Private Sector Banks No. of Percentage respondents 1. High 51 17.00 32 10.70 2. Medium 218 72.70 237 79.00 3. Low 31 10.30 31 10.30 Total 300 100.00 300 100.00 Source : Primary Data 158
FIGURE 5.1 LEVELS OF SATISFACTION 250 No. of Respondents 200 150 100 50 0 High Medium Low Levels of Satisfaction Public Sector Banks Private Sector Banks It is clear from Table 5.1 and Figure 5.1 that out of the 300 public sector banks, 51 respondents (17.00 per cent) come under the category of high level of satisfaction and 31 respondents (10.30 per cent) come under the category of low level of satisfaction. But nearly 218 respondents (72.70 per cent) of the sample from public sector banks have medium level of satisfaction. In the case of private sector banks, out of the 300 customers, 32 customers (10.70 per cent) are in the category of high level of satisfaction, 237 customers (79.00 per cent) come under the category of medium level of satisfaction whereas 31 respondents (10.30 per cent) only have low level of satisfaction. 159
5.2.2 Gender and Level of Satisfaction In determining the satisfaction of the respondents, gender plays a vital role. Table 5.2 shows the gender and level of satisfaction of the respondents. TABLE 5.2 GENDER OF THE RESPONDENTS AND LEVEL OF SATISFACTION Sl. No. Gender Public Sector Banks Private Sector Banks High Medium Low Total High Medium Low Total 1. Male 2. Female Total 31 (60.80) 20 (39.20) 148 (67.90) 70 (32.10) 21 (67.70) 10 (32.30) 200 (66.70) 100 (33.30) 25 (78.10) 7 (21.90) 174 (73.40) 63 (26.60) 20 (64.50) 11 (35.50) 219 (73.00) 81 (27.00) 51 218 31 300 32 237 31 300 Source: Primary data. Note : Figures in brackets represent percentage to total. From Table 5.2 and figure 5.1, it is inferred that in the case of public sector banks, out of 51 respondents with high level of satisfaction, 31 respondents (60.80 per cent) of the respondents are male and 20 respondents (39.20 per cent) are female. In case of medium level of satisfaction, out of 218 respondents, 148 (67.90 per cent) are male and 70 (32.10 per cent) are female. It also shows that out of 31 respondents with low level of satisfaction, 21 respondents (67.70 per cent) are male and 10 respondents (32.30 per cent) are female. In the case of private sector banks, out of 32 respondents with high level of satisfaction, 25 (78.10 per cent) are male and only 7 (21.90 per cent) are female. In the case of medium level of satisfaction, out of 237 respondents, 174 (73.40 per 160
cent) are male and 63 (26.60 per cent) are female, whereas in the case of low level of satisfaction, out of 31 respondents, 20 (64.50 per cent) are male and remaining 11 (3550 per cent) are female. In order to test the relationship between gender and the level of satisfaction of the respondents, the following null hypothesis is formulated: The level of satisfaction is independent of gender. The Chi-Square test is applied to examine the null hypothesis and the computed results are given in Table 5.3. TABLE 5.3 GENDER AND LEVEL OF SATISFACTION: CHI-SQUARE TEST Particulars Public Sector Banks Private Sector Banks Calculated Value 0.9570 1.5794 Table value at 5 per cent level 5.991 5.991 Degrees of freedom 2 2 Inference Not Significant Not Significant * Significant at 5 per cent level. Source : Primary Data It is inferred from Table 5.3 that for both the public sector and private sector banks, the calculated values are less than the table values. Hence, the null hypothesis is accepted. Therefore, it could be inferred that gender does not influence the satisfaction of respondents towards internet banking. 161
5.2.3 Age and Level of Satisfaction Age is one of the important factors in determining the satisfaction of the respondents. The age and level of satisfaction of respondents are shown in Table 5.4. TABLE 5.4 AGE OF THE RESPONDENTS AND LEVEL OF SATISFACTION Sl. No Age (in years) 1. Below 25 2. 25-45 3. 46-65 4. 65 and Above Total Public Sector Banks Private Sector Banks High Medium Low Total High Medium Low Total 6 (11.80) 15 (29.40) 26 (51.00) 4 (7.80) 51 34 (15.60) 113 (51.80) 69 (31.70) 2 (0.90) 218 7 (22.60) 19 (61.30) 2 (6.50) 3 (9.70) 31 47 (15.70) 147 (49.00) 97 (32.30) 9 (3.00) 300 6 (18.00) 20 (62.50) 5 (15.60) 1 (3.10) 32 51 (21.50) 148 (62.40) 19 (8.00) 19 (8.00) 237 9 (29.00) 20 (64.50) 66 (22.00) 188 (62.70) -- 24 (8.00) 2 (6.50) 22 (7.30) 31 300 Source: Primary data. Note : Figures in brackets represent percentage to total. From Table 5.4, it is observed that in the case of public sector banks, out of 51 respondents the high level of satisfaction is maximum with 26 (51.00 per cent) who belong to the age group between 46 65 years followed by 15 respondents (29.40 per cent) are of the age group between 25-45 years, 6 respondents(11.80 per cent) are in the age group below 25 years and 4 respondents (7.80 per cent) belong to the age group 65 years and above respectively. In the case of medium level of satisfaction, out of 218 respondents, maximum of 113 162
(51.80 per cent) of them belong to the age group between 25-45 years and 69 (31.70 per cent) belong to age group of 46 65 years respectively. Further it is also shown that, out of 31 respondents with low level of satisfaction, maximum of 19 (61.30 per cent) of them belong to the age group between 25-45 years and 7 (22.60 per cent) of them belong to the age group of below 25 years respectively. In the case of private sector banks, out of 32 respondents the high level of satisfaction, maximum of 20 (62.50 per cent) of them belong to the age group between 25-45 years. The table 5.4 also reveals that 6 (18.00 per cent) who belong to the age group of below 25 years, 5 (15.60 per cent) in the age group of 46-65 years and only one (3.10) customer in the age group of 65 years above is with the high level of satisfaction respectively. In the case of medium level of satisfaction, maximum of 148 (62.40 per cent) respondents belong to the age group between 25-45 years. The table also infers that 51 (21.50 per cent) respondents belong to the age group of below 25 years. Further, it also shows that in the case of low level of satisfaction, out of 31 respondents, maximum of 20 (64.50 per cent) respondents belong to the age group between 25-45 years and 9 (29.00 per cent) belong to the age group of below 25 years. In order to test the relationship between age and level of satisfaction of the respondents, the following null hypothesis is formulated: The level of satisfaction is independent of the age. The Chi-square test is applied to examine the null hypothesis and the computed results are given in Table 5.5. 163
TABLE 5.5 AGE AND LEVEL OF SATISFACTION: CHI-SQUARE TEST Particulars Public Sector Banks Private Sector Banks Calculated Value 30.4338 6.6566 Table value at 5 per cent level 12.592 12.592 Degrees of freedom 6 6 Inference Significant Not Significant * Significant at 5 per cent level. Source : Primary Data It is clearly evident from Table 5.5 that in the case of public sector banks, the calculated value is greater than the table value. Hence, the null hypothesis is rejected. Therefore, it could be inferred that the age influences the satisfaction of the customers towards internet banking services. In the case of private sector banks also the calculated value is less than the table value, and hence the null hypothesis is accepted. Therefore, it could be inferred that the age does not influence the satisfaction of the customers towards internet banking services. 5.2.4. Educational Qualification and Levels of Satisfaction Education is a vital factor which influences the satisfaction of the respondents. Independent identity of respondents can be proved only through education. Qualification of respondents and their level of satisfaction are shown in Table 5.6. 164
Sl. No TABLE 5.6 EDUCATIONAL QUALIFICATION OF THE RESPONDENTS AND Educational Qualification 1. Graduate 34 (66.70) 2. Post Graduate LEVELS OF SATISFACTION Public Sector Banks Private Sector Banks High Medium Low Total High Medium Low Total 13 (25.50) 3. Others 4 (7.80) Total 51 Source: Primary data. 125 (57.30) 56 (25.70) 37 (17.00) 218 15 (48.40) 9 (29.00) 7 (22.60) 31 174 (58.00) 78 (26.00) 48 (16.00) 300 (100.0) 15 (46.90) 16 (50.00) 1 (3.10) 32 Note : Figures in brackets represent percentage to total. 146 (61.60) 79 (33.30) 12 (5.10) 237 (100.0) 19 (60.30) 10 (32.30) 2 (6.40) 31 (100.0) 180 (60.00) 105 (35.00) 15 (5.00) 300 (100.0) It is revealed from Table 5.6 that in the case of public sector banks, out of 51 customers with high level of satisfaction, maximum of 34 (66.70 per cent) are in the category of graduate level followed by 13 (25.50 per cent) in the category of post graduate level and only 4 (7.80 per cent) in the category of others. In the case of medium level of satisfaction, out of 218 sample respondents, maximum of 125 (57.30 per cent) respondents are in the category of graduate level followed by 56 (25.70 per cent) in the category of post graduate level and 37 (17.00 per cent) in the category of others. Out of 31 respondents with low level of satisfaction, maximum of 15 (48.40 per cent) respondents are in the category of graduate level followed by 9 (29.00 per cent) in the category of post graduate level and 7 (22.60 per cent) in the category of others. 165
In the case of private sector banks, out of 32 respondents with high level of satisfaction, maximum of 16 (50.00 per cent) respondents are in the category of post graduate level followed by 15 (46.90 per cent) in the category of graduate level and only one (3.10 per cent) is in the category of others. In the case of medium level of satisfaction, out of 237 respondents, maximum of 146 (61.60 per cent) respondents are in the category of graduate level followed by 79 (33.30 per cent) in the category of post graduate level and 12 (5.10 per cent) in the category of others. Out of 31 respondents with low level satisfaction, maximum of 19 (60.30 per cent) respondents are in the category of graduate level followed by 10 (32.30 per cent) in the category of post graduate level and only 2 (6.40 per cent) are in the category of others. For finding out the relationship between educational qualification and level of satisfaction towards internet banking services, the following null hypothesis is formulated: There is no relationship between educational qualifications and level of satisfaction among the respondents. To test the above hypothesis, Chi-square test is applied. The computed results of Chi-Square test are presented in Table 5.7. 166
TABLE 5.7 EDUCATIONAL QUALIFICATIONS AND LEVELS OF SATISFACTION: CHI-SQUARE TEST Particulars Public Sector Banks Private Sector Banks Calculated Value 4.3823 3.6982 Table value at 5 per cent level 9.488 9.488 Degrees of freedom 4 4 Inference Not Significant Not Significant * Significant at 5 per cent level. Source : Primary Data It is clearly evident from Table 5.7 that, in case of public and private sector banks, the calculated Chi-Square values is less than the table values. Therefore, the null hypothesis is accepted. Hence, it could be inferred that the educational qualification does not influence the satisfaction of the respondents towards the internet banking services. 5.2.5. Profession and Levels of Satisfaction Level of satisfaction also depends upon the occupation or profession of the customers. The researcher has made an attempt to study the relationship between profession and level of satisfaction of the respondents. Profession of the respondents and their level of satisfaction are shown in Table 5.8. 167
TABLE 5.8 ASSOCIATION BETWEEN PROFESSION OF THE RESPONDENTS AND THEIR LEVELS OF SATISFACTION Sl. No. 1. 2. 3. 4. 5. 6. Occupation Business men Private Com-pany employees Govt. Employees Housewives Retired Persons Bank Employees 7. Doctors 8. Teachers 9. Students Total Public Sector Banks Private Sector Banks High Medium Low Total High Medium Low Total 6 (11.80) 1 (2.00) 7 (13.70) 3 (5.90) 6 (11.80) 23 (45.10) 2 (3.90) 2 (3.90) 1 (2.00) 51 51 (23.40) 16 (7.30) 35 (16.10) 9 (4.10) 7 (3.20) 69 (31.70) 4 (1.80) 15 (6.90) 12 (5.50) 218 3 (9.70) 8 (25.80) 7 (22.60) 2 (6.50) 60 (20.00) 25 (8.30) 49 (16.30) 14 (4.70) -- 13 (4.30) 7 (22.60) - 3 (9.70) 1 (3.20) 31 99 (33.00) 6 (2.00) 20 (6.70) 14 (4.70) 300 (100.0) 6 (18.80) 3 (9.40) 9 (28.10) 1 (3.10) 38 (16.00) 39 (16.50) 69 (29.10) 10 (4.20) -- 4 (1.70) 12 (37.50) -- 1 (3.10) -- 32 42 (17.70) 2 (0.80) 23 (9.70) 10 (4.20) 237 (100.0) -- 44 (14.70) 5 (16.10) 16 (51.60) 1 (3.20) -- 4 (12.90) -- 5 (16.10) -- 31 (100.0) 47 (15.70) 94 (31.30) 12 (4.00) 4 (1.30) 58 (19.30) 2 (0.7) 29 (9.70) 10 (3.30) 300 (100.0) Source: Primary data. Note : Figures in brackets represent percentage to total. From Table 5.8, it is revealed that in the case of public sector banks, out of 51 customers with high level of satisfaction, maximum of 23 respondents (45.10 per cent) who are bank employees followed by 7 respondents (13.70 per cent) private company employees and 6 respondents each (11.80 per cent) are 168
government employees and retired persons. In the case of medium level of satisfaction, out of 218 respondents, maximum of 69 (31.70 per cent) respondents are bank employees followed by 51 respondents (23.40 per cent) who are government employees and 35 (16.10 per cent) private company employees. Further, it also shows that out of 31 respondents with low level satisfaction, maximum of 8 (25.80 per cent) of them are businessmen followed by 7 (22.60 per cent) each of private company employees and bank employees respectively. In the case of private sector banks, out of 32 respondents with high level of satisfaction, maximum of 12 (37.50 per cent) are bank employees followed by 9 (28.10 per cent) private company employees and 6 (18.80 per cent) government employees. In the case of medium level of satisfaction, out of 237 respondents, maximum of 69 (29.10 per cent) are private company employees followed by 42 (17.70 per cent) bank employees, 39 (16.50 per cent) businessmen and 38 (16.00 per cent) government employees. It also shows that in the case of low level of satisfaction, out of 31 respondents, maximum of 16 (51.60 per cent) are private company employees followed by 5(16.10 per cent) each of businessmen and teachers respectively. For finding out the relationship between profession and level of satisfaction, the following null hypothesis is formulated: There is no relationship between profession and levels of satisfaction of the respondents. To test the above hypothesis, Chi-square test is applied. The computed results of Chi-Square test are presented in Table 5.9. 169
TABLE 5.9 PROFESSION AND LEVEL OF SATISFACTION: CHI-SQUARE TEST Particulars Public Sector Banks Private Sector Banks Calculated Value 35.9590 24.2556 Table value at 5 per cent level 26.296 26.296 Degrees of freedom 16 16 Inference Significant Not Significant * Significant at 5 per cent level. Source : Primary Data It is clearly evident from Table 5.9 that in the case of public sector banks, the calculated Chi-Square value is greater than the table value at 5 per cent level. Hence, the null hypothesis is rejected. Therefore, it could be inferred that there is a relationship between profession and levels of satisfaction of the customers towards the internet banking services. In the case of private sector banks, the calculated Chi-Square value is less than the table value at 5 per cent level. Hence, the null hypothesis is accepted. Therefore, it could be inferred that there is no relationship between profession and levels of satisfaction of the customers towards the internet banking services. 5.2.6 Monthly Income and Levels of Satisfaction Levels of satisfaction may also depend upon the monthly income of the respondents. Hence, an attempt is made to study the relationship between 170
monthly income and level of satisfaction of the respondents. The monthly income of the sample respondents and their level of satisfaction are shown in Table 5.10. TABLE 5.10 MONTHLY INCOME AND LEVELS OF SATISFACTION Sl. No. 1. 2. 3. 4. Monthly Income (`) Below 15000 15000-30000 30000-45000 Above 45000 Total Public Sector Banks Private Sector Banks High Medium Low Total High Medium Low Total 10 (19.60) 17 (33.30) 15 (29.40) 9 (17.60) 51 53 (24.30) 57 (26.10) 73 (33.50) 35 (16.10) 218 15 (48.40) 11 (35.50) 5 (16.10) -- 31 78 (26.00) 85 (28.30) 93 (31.00) 44 (14.70) 300 (100.0) 3 (9.40) 16 (50.00) 7 (21.90) 6 (18.80) 32 52 (21.90) 94 (39.70) 55 (23.20) 36 (15.20) 237 (100.0) 5 (16.10) 23 (74.20) 1 (3.20) 2 (6.50) 31 (100.0) 60 (20.00) 133 (44.30) 63 (21.00) 44 (14.70) 300 (100.0) Source: Primary data. Note : Figures in brackets represent percentage to total. From Table 5.10, it is revealed that in the case of public sector banks, out of 51 respondents with high level of satisfaction, maximum with 17 (33.30 per cent) respondents have monthly income between ` 15000 - ` 30000 followed by 15 (29.40 per cent) with monthly income between ` 30000 - ` 45000, 10 (19.60 per cent) with monthly income of below ` 15000 and 9 (17.60 per cent) with monthly income more than ` 45000. In the case of medium level of satisfaction, out of 218 respondents, 73 (33.50 per cent) respondents have monthly income between ` 30000 - ` 45000 followed by 57 (26.10 per cent) with monthly income between ` 15000 - ` 30000, 53 (24.30 per cent) with monthly income of below ` 171
15000 and 35 (16.10 per cent) with monthly income more than ` 45000. Further, it also shows that out of 31 respondents with low level of satisfaction, majority of 15 (48.40 per cent) respondents have monthly income below ` 15000 followed by 11 (35.50 per cent) with monthly income between ` 15000 - ` 30000 and 5 (16.10 per cent) with monthly income of ` 30000 - ` 45000. In the case of private sector banks, out of 32 respondents with high level of satisfaction, majority of 16 (50.00 per cent) respondents have monthly income between ` 15000 - ` 30000 followed by 7 (21.90 per cent) with monthly income between ` 30000 - ` 45000, 6 (18.80 per cent) with monthly income above ` 45000 and 3 (9.40 per cent) with monthly income of below ` 15000. In the case of medium level of satisfaction, out of 237 respondents, majority of 94 (39.70 per cent) respondents have monthly income between ` 15000 - ` 30000, followed by 55 (23.20 per cent) with monthly income between ` 30000 - ` 45000, 52 (21.90 per cent) with monthly income below ` 15000 and 36 respondents (15.20 per cent) with monthly income above ` 45000. Further it also shows that out of 31 respondents with low level of satisfaction, majority of 23 (74.20 per cent) respondents have monthly income between ` 15000 - ` 30000 followed by 5 respondents(16.10 per cent) with monthly income of below ` 15000, 2 respondents (6.50 per cent) with monthly income of more than ` 45000 and only one (3.20 per cent) with a monthly income of ` 30000 - ` 45000. In order to test the relationship between monthly income and level of satisfaction, the following null hypothesis is formulated: There is no relationship between monthly income and levels of satisfaction. To test the 172
above null hypothesis, Chi-Square test is applied. The results are presented in Table 5.11. TABLE 5.11 MONTHLY INCOME AND LEVELS OF SATISFACTION: CHI-SQUARE TEST Particulars Public Sector Banks Private Sector Banks Calculated Value 16.2230 17.1770 Table value at 5 per cent level 12.592 12.592 Degrees of freedom 6 6 Inference Significant Significant *Significant at 5 per cent level. Source : Primary Data Table 5.11 reveals that in case of both public sector and private sector banks, the calculated values of Chi-Square are greater than the table values. It implies that the null hypothesis is rejected. Hence, it could be inferred that there is no relationship between monthly income and levels of satisfaction towards internet banking services provided by the public and private sectors banks in Tirunelveli district. 5.2.7 Marital Status and Levels of Satisfaction The levels of satisfaction may also depend upon the marital status of the respondents. An attempt has been made to study the relationship between marital status and levels of satisfactions of the respondents. The marital status of the respondents and their levels of satisfactions are shown in Table 5.12. 173
TABLE 5.12 ASSOCIATION BETWEEN MARITAL STATUS OF THE RESPONDENTS AND LEVEL OF SATISFACTION Sl. No. Marital Status 1. Married 2. Unmarried Total Public Sector Banks Private Sector Banks High Medium Low Total High Medium Low Total 40 (78.40) 11 (21.60) 51 159 (72.90) 59 (27.10) 218 20 (64.50) 11 (35.50) 31 219 (73.00) 81 (27.00) 300 (100.0) 20 (62.50) 12 (37.50) 32 129 (54.40) 108 (45.60) 237 (100.0) 21 (67.70) 10 (32.30) 31 (100.0) 170 (56.70) 130 (43.30) 300 (100.0) Source: Primary data. Note : Figures in brackets represent percentage to total. Table 5.12 reveals that in the case of public sector banks, out of 51 respondents with high level of satisfaction, 40 (78.40 per cent) respondents are married while 11 (21.60 per cent) are unmarried. In the case of medium level of satisfaction, out of 218 respondents, 159 (72.90 per cent) are married while 59 (27.10 per cent) are unmarried. Out of 31 respondents with low level of satisfaction, 20 (64.50 per cent) are married while 11 (35.50 per cent) are unmarried. In the case of private sector banks, out of 32 respondents with high level of satisfaction, 20 (62.50 per cent) respondents are married while 12 (37.50 per cent) are unmarried. In the case of medium level of satisfactions, out of 237 respondents, 129 (54.40 per cent) are married while 108 (45.60 per cent) are unmarried. In the case of low level of satisfaction, out of 31 respondents, 21 (67.70 per cent) are married while 10 (32.30 per cent) are unmarried. 174
With a view to test the following null hypothesis namely, The levels of satisfaction is independent of the marital status, Chi-square test is applied and the results are shown in Table 5.13. TABLE 5.13 MARITAL STATUS AND LEVELS OF SATISFACTION: CHI-SQUARE TEST Particulars Public Sector Banks Private Sector Banks Calculated Value 1.8958 2.4746 Table value at 5 per cent level 5.991 5.991 Degrees of freedom 2 2 Inference Not Significant Not Significant *Significant at 5 per cent level. Source : Primary Data It is observed from Table 5.13 that in case of both public sector and private sector banks, the calculated Chi-Square values are less than the table values at 5 per cent level. Hence the null hypothesis is accepted. So, there is no relationship between marital status and level of satisfaction of the sample respondents among the public and private sector banks in Tirunelveli district. 5.2.8 Usage of Internet banking and Level of Satisfaction The usage of internet banking services by the sample customers and their level of satisfaction are shown in Table 5.14. 175
Sl. No. 1. TABLE 5.14 USAGE OF INTERNET BANKING AND LEVELS OF SATISFACTION Usage in Years Less than One year 2. 1 2 3. 2 3 4. More than 3 years Total Public Sector Banks Private Sector Banks High Medium Low Total High Medium Low Total 18 (35.30) 13 (25.50) 8 (15.70) 11 (21.50) 51 Source: Primary data. 64 (29.40) 63 (28.90) 45 (20.60) 46 (21.10) 218 13 (41.90) 9 (29.00) 6 (19.40) 3 (9.70) 31 95 (31.70) 85 (28.30) 59 (19.70) 61 (20.30) 300 (100.0) 6 (18.80) 10 (31.20) 13 (40.60) 3 (9.40) 32 Note : Figures in brackets represent percentage to total. 34 (14.30) 83 (35.00) 48 (20.30) 72 (30.40) 237 (100.0) 7 (22.60) 10 (32.20) 7 (22.60) 7 (22.60) 31 (100.0) From Table 5.14, it is inferred that in the case of public sector banks, out of 51 respondents with high level of satisfaction, maximum of 18 (35.30 per cent) respondents are using internet banking for less than one year followed by the respondents who use the internet banking for 1-2 years, more than 3 years and 2-3 years which constitute 25.50 per cent, 21.50 per cent and 15.70 per cent respectively. In the case of medium level of satisfaction, out of 218 respondents, maximum of 64 (29.40 per cent) are using internet banking for less than one year followed by 63 respondents (28.90 per cent) who use the internet banking for 1-2 years, more than 3 years (21.10 per cent) and 2-3 years which constitute 20.60 per cent. Out of 31 respondents with low level of satisfaction, maximum of 13 (41.90 per cent) of them are using internet banking for less than one year followed by the 47 (15.70) 103 (34.30) 68 (22.70) 82 (27.30) 300 (100.0) respondents who use internet banking for 1-2 years, 2-3 years and more than 3 176
years which constitute 29.00 per cent, 19.40 per cent and 9.70 per cent respectively. In case of private sector banks, out of 32 respondents with high level of satisfaction, maximum of 13 (40.60 per cent) are using internet banking for 2-3 years followed by the respondents who use the internet banking for 1-2 years, less than one year and more than 3 years which constitute 31.20 per cent, 18.80 per cent and 9.40 per cent respectively. In the case of medium level of satisfaction, out of 237 respondents, maximum of 83 (35.00 per cent) are using internet banking for 1-2 years followed by the respondents who use the internet banking for more than 3 years, 2-3 years and less than one year which constitute 30.40 per cent, 20.30 per cent and 14.30 per cent respectively. Further it also shows that, out of 31 respondents with low level of satisfaction, maximum of 10 (32.20 per cent) are using internet banking for 1-2 years followed 7 respondents each (22.60 per cent) by all those using internet banking for less than one year, 2-3 years and more than 3 years respectively. In order to test the relationship between usage of internet banking and level of satisfaction of the respondents, the following null hypothesis is formulated: There is no relationship between the usage of internet banking and levels of satisfaction. The above null hypothesis is tested by applying Chisquare test. The computed results are given in Table 5.15. 177
TABLE 5.15 USAGE OF INTERNET BANKING AND LEVELS OF SATISFACTION: CHI-SQUARE TEST Particulars Public Sector Banks Public Sector Banks Calculated Value 9.0333 11.8800 Table value at 5 per cent level 12.592 12.592 Degrees of freedom 6 6 Inference Not Significant Not Significant *Significant at 5 per cent level. Source: Primary Data Table 5.15 shows that in the case of both the public and private sector banks, the calculated Chi-Square values are less than the table values at 5 per cent level. Hence the established null hypothesis is accepted. It is concluded that there is no relationship between the usage of internet banking and levels of satisfaction of the respondents among the public and private sector banks in Tirunelveli district.. 5.3. FACTORS IDENTIFYING CUSTOMERS SATISFACTION TOWARDS INTERNET BANKING In this section, an attempt is made to identify the factors which are perceived by the customers towards the internet banking services offered by the banks. Nineteen statements relating to satisfaction of the customers towards the internet banking services of banks are selected, so as to identify the significant and important factors with the help of factor analytical technique. 178
5.3.1. Analytical Framework The technique adopted to identify and analyse the special attractions that galvanised the customers in public sector banks and private sector banks is factor analysis. The principal factor analysis method is mathematically satisfying because it yields a unique solution to a factor problem. Its major solution feature is the extraction of maximum amount of variation as each factor is calculated. In other words, the first extracts the most variance and so on. Most of the analytical methods produce results in a form that is difficult or impossible to interpret. Thurstone argued that it is necessary to rotate factor matrices if one wants to interpret them adequately. He pointed out that original factor matrices are arbitary in the sense that an infinite number of reference frames (axes) can be found to reproduce any given R Matrix. There are several methods available for factor analysis. But the principal factor method with orthogonal varimax rotation is mostly used and widely available in factor analysis computer programme. Further orthogonal rotations maintain the independence of factors that is, the angles between the axes are kept at 90 degrees. One of the final outcomes of a factor analysis is called rotated factor matrix, a table of co-efficient that expresses the ratios between the variable and the factors that have been prepared. The sum of squares of the factor loadings of variable is called communalities (h 2 ). 179
The communality (h 2 ) of a factor is its common factor variance. The factors with factor loadings of 0.5 or greater are considered as significant factors. This limit is chosen because it had been judged that factors with less than 50 per cent common variation with the rotated factor pattern are too weak to report. In the present study, the principal factor analysis method with orthogonal varimax rotation is used to identify the significant dimensions of satisfaction of customers towards the internet banking services provided by public sector banks and private sector banks. 5.3.2 Testing for Sampling Adequacy Public Sector Banks Before extracting the factors, to test the appropriateness of the factor model, Bartlett s test of sphericity is used to test the null hypothesis that the variables are intercorrelated in population. The test statistics of sphericity is based on a chi-square transformation of the determinant of the correlation matrix. Another useful statistic is the Kaiser-Meyer Oklin (KMO) test of sampling adequacy. Small value of the KMO statistic indicates that the correlation between parts of variable cannot be explained by other variables and that factor analysis may not be appropriate. Generally, a value greater than 0.5 is desirable. The correlation matrix is examined carefully and the two tests namely Bartlett s test of sphericity and Kaiser-Meyer Oklin test are undertaken to test if it is judicious to proceed with factor analysis in the present study. The computed results for public sector banks are given in Table 5.16. 180
TABLE 5.16 MEASURES OF SAMPLING INADEQUACIES PUBLIC SECTOR BANKS Measures Estimated Value Kaiser-Meyer Oklin Measure of Sampling Adequacy 0.8641 Bartlett s Test of Sphercity Appropriate Chi-Square 3023.7009 Significance 0.0000 Source : Primary Data From Table 5.16 it has been observed that the Bartlett s test is significant with P=0.000, being less than 0.05. Sampling adequacy measured using the Kaiser-Mayer Oklin (KMO) of 0.8641 is taken as acceptable. Thus the factor analysis may be considered an appropriate technique for analysing the data. Factor analysis is done with 19 variables (item) by orthogonal varimax rotation for the satisfaction of customers towards the internet services provided by public sector banks and private sector banks. 5.3.3 Customers Satisfaction towards internet services provided by Public Sector Banks The rotated factor matrix for the variables relating to the satisfaction of the customers in public sector banks in the study is given in Table 5.17. 181
TABLE 5.17 ROTATED FACTOR MATRIX PUBLIC SECTOR BANKS Sl. No. Variables Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 h 2 1. Internet banking is exactly what I need 0.7793 0.1215 0.0776-0.0128 0.0374 0.6296 2. I have truly enjoyed Internet banking 0.7548 0.0200 0.3406 0.0999-0.0474 0.6983 3. 4. 5. I am satisfied with my decision of purchasing using internet banking The website has adequate security features I will ask my family and friends to use internet banking facilities 0.7187 0.0928 0.2649 0.1433 0.0154 0.6160 0.6596 0.3879 0.0510 0.2418 0.2158 0.6930 0.5981 0.1313 0.4415 0.0665-0.1998 0.6141 6. Bank s servers perform well 0.5704 0.4148 0.0562 0.2476 0.2088 0.6054 7. 8. 9. 10. 11. 12. 13. 14. The service delivered through the bank s website is quick The bank s website makes accurate promises about the services delivered Customer s online transaction with the bank is always accurate When the bank promises to do something by a certain time, it does so If I had to do transaction again, I would choose the same internet banking service of my bank I am very committed to my relationship with my bank Internet banking at my bank has really pleased me The bank s site provides a confirmation of the service ordered 0.1693 0.8275 0.1551 0.2189-0.0694 0.7802 0.2310 0.7817 0.0812 0.1597-0.0369 0.6978 0.1545 0.7701 0.2751 0.1960 0.0344 0.7321 0.0092 0.6685 0.5001 0.2111 0.0628 0.7454 0.3235 0.2109 0.7066 0.1668-0.0556 0.6793 0.1708 0.1939 0.6912 0.3211 0.1185 0.6616 0.3925 0.2238 0.6521 0.1390-0.0824 0.6553 0.3182 0.1725 0.6275 0.2536 0.0237 0.5896 15. I trust this bank 0.0138 0.0464 0.5018-0.0527 0.1492 0.5887 16. 17. 18. 19. The bank s site provides quick confirmation Internet banking gives prompt services The bank s website performs the service in the first instance itself I am satisfied with the service of internet banking 0.1092 0.1613 0.1533 0.8872-0.0409 0.8501 0.1813 0.2234 0.0887 0.8341-0.0116 0.7864 0.0795 0.2475 0.1857 0.7590 0.0449 0.6801 0.0590-0.0221 0.1424-0.0037 0.9129 0.8576 Eigen Value 7.3656 1.9784 1.2632 1.1988 1.0163 Percentage Variance 38.80 10.10 6.60 6.30 5.30 Cumulative Percentage 38.80 48.90 55.60 61.90 67.20 182
Table 5.17 gives the loadings received by the factors under F1, F2, F3, F4 and F5 for public sector banks. From the above table, the rotated factor loadings for the nineteen statements (variables) of satisfaction of customers towards internet banking services provided by public sector banks are observed. It is clear from Table 5.17 that all the nineteen statements have been extracted into five factors namely F1, F2, F3, F4 and F5. The factors with identified new names which influence satisfaction of customers in public sector banks are discussed below: The first factor is designed as Fulfillment of Customers Needs on the basis of the loaded variables. Six variables in this category are important with high factor loading. It indicates that among the various performance scale, Internet banking is exactly what I need (0.7793), I have truly enjoyed Internet banking (0.7548), I am satisfied with my decision of purchasing using internet banking (0.7187), The website has adequate security features (0.6596), I will ask my family and friends to use internet banking facilities (0.5981) and Bank s servers perform well (0.5704) are important attributes in this category. Thus, the fulfillment of customers need is identified as an important factor to influence the customers satisfaction towards the internet banking services rendered by the public sector banks. The second factor is narrated as Fast and Accurate Services on the basis of the loaded variables. Four variables in this category are important with high factor loading. It indicates that among the various performance scale, The service delivered through the bank s website is quick (0.8275), The bank s website makes accurate promises about the services delivered (0.7817), Customer s online transaction with the bank is always accurate (0.7701) and 183
When the bank promises to do something by a certain time, it does so (0.6685) are important attributes in this category. Thus, the fast and accurate services of internet facilities is identified as an important factor to influence the customers satisfaction towards the internet banking services rendered by the public sector banks. The third factor is prescribed as Choice of Bank and their Services on the basis of the loaded variables. Five variables in this category are important with high factor loading. It indicates that among the various performance scale, If I had to do transaction again, I would choose the same internet banking service of my bank (0.7066), I am very committed to my relationship with my bank (0.6912), Internet banking at my bank has really pleased me (0.6521), The bank s site provides a confirmation of the service ordered (0.6275) and I trust this bank (0.5018) are the important attributes in this category. Thus, the choice of the bank and their internet services are identified as an important factor to influence the customers satisfaction towards the internet banking services rendered by the public sector banks. The fourth factor is highlighted as Quick Confirmation and Prompt Services on the basis of the loaded variables. Three variables in this category are important with high factor loading. It indicates that among the various performance scale, The bank s site provides quick confirmation (0.8872), Internet banking gives prompt services (0.8341) and The bank s website performs the service in the first instance itself (0.7590) are important attributes in this category. Thus, the quick confirmation of transaction and prompt services are identified as an important factor to influence the customers satisfaction towards the internet banking services rendered by the public sector banks. 184
The fifth factor is designed as Satisfaction with the services provided on the basis of the loaded variables. One variable in this category is important with high factor loading. It indicates that among the various performance scale, I am satisfied with the service of internet banking (0.9129) is an important attributes in this category. Thus, the satisfaction with the services of internet banking is identified as an important factor to influence the customers satisfaction towards the internet banking services provided by the public sector banks in Tirunelveli district. Table 5.18 presents the overall highest factor loadings for the satisfaction of the customers towards internet banking services provided by the public sector banks. TABLE 5.18 VARIABLES WITH THE HIGHEST FACTOR LOADINGS FOR THE SATISFACTION OF CUSTOMER TOWARDS INTERNET BANKING SERVICES PROVIDED BY PUBLIC SECTOR BANKS Factors Names of newly extracted dimensions (Factors) Selected Statements (Variables) Factor Loadings F1 Fulfillment of customers needs Internet banking is exactly what I need 0.7793 F2 Fast and accurate services The service delivered through the bank s website is quick 0.8275 F3 Choice of the banks and their services If I had to do transaction again, I would choose the same internet banking service of my bank 0.7066 F4 Quick confirmation and prompt services The bank s site provides quick confirmation 0.8872 F5 Satisfaction with the services provided I am satisfied with the service of internet banking 0.9219 185
It is clearly evident from Table 5.18 that the statements, Internet banking is exactly what I need (0.7793), The service delivered through the bank s website is quick (0.8275), If I had to do transaction again, I would choose the same internet banking service of my bank (0.7066), The bank s site provides quick confirmation (0.8872) and I am satisfied with the service of internet banking (0.9219) are the statements with highest factor loading under the dimensions namely, Fulfillment of customers needs (F1), Fast and accurate services (F2), Choice of the banks and their services (F3), Quick confirmation and prompt services (F4) and Satisfaction with the services provided (F5) respectively. Hence, it is concluded that these are the identified dimensions (factors) which influence the satisfaction of the customers towards the internet banking services provided by public sector banks in Tirunelveli district. 5.3.4 Testing for sampling adequacy Private Sector Banks The correlation matrix is examined carefully and the two tests namely Bartlett s test of sphericity and Kaiser-Meyer Oklin test are undertaken to test if it is judicious to proceed with factor analysis in the present study. The computed results for private sector banks are given in Table 5.19. TABLE 5.19 MEASURES OF SAMPLING INADEQUACIES PRIVATE SECTOR BANKS Measures Estimated Value Kaiser-Meyer Oklin Measure of Sampling Adequacy 0.8641 Bartlett s Test of Sphercity Appropriate Chi-Square 3023.7009 Significance 0.0000 Source: Primary Data 186
From Table 5.19 it has been observed that the Bartlett s test is significant with P=0.000, being less than 0.05. Sampling adequacy measured using the Kaiser-Mayer Oklin (KMO) of 0.8641 is taken as acceptable. Thus the factor analysis may be considered an appropriate technique for analysing the data. Factor analysis is done with 19 variables (item) by orthogonal varimax rotation for the satisfaction of customers towards the internet services provided by private sector banks. 5.3.3 Customers satisfaction towards internet services provided by Private Sector Banks The rotated factor matrix for the variables relating to the satisfaction of the customers in private sector banks in the study is given in Table 5.20. 187
Sl. No. TABLE 5.20 ROTATED FACTOR MATRIX PRIVATE SECTOR BANK Variables Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 1. I trust this bank 0.8346 0.1396 0.0352 0.2696 0.0085 0.7900 I am very committed to my 2. relationship with my bank 0.7675 0.1167 0.1325 0.2495 0.1199 0.6968 The bank s site provides a confirmation to the service ordered 3. 0.7031 0.0907 0.3063 0.0815 0.1616 0.6291 If I had to do transaction again, I 4. would choose the same internet banking service of my bank 0.6933 0.1737 0.2943 0.1131 0.1662 0.6378 Internet banking at my bank has 5. really pleased me 0.6631 0.1589 0.3714-0.0056 0.0995 0.6127 6. 7. 8. 9. 10. 11. 12. 13. The service delivered through the bank s website is quick Customer s online transaction with the bank is always accurate The bank s website makes accurate promises about the services delivered When the bank promises to do something by a certain time, it does do I am satisfied with the services of internet banking I have truly enjoyed internet banking I will ask my family and friends to use internet banking facilities I am satisfied with my decision of purchasing using internet banking 0.1779 0.8180 0.0074 0.1621 0.0920 0.7355 0.0888 0.7922 0.1091 0.1724 0.0496 0.6795 0.0190 0.7747 0.1796-0.0894 0.3100 0.7368 0.2987 0.6845 0.0768 0.0845 0.1676 0.5989 0.2597 0.1797 0.7588 0.2163-0.0299 0.7232 0.1963-0.0531 0.7333 0.3293 0.1655 0.7148 0.4114 0.2256 0.7218 0.0444 0.1374 0.7619 0.2135 0.1079 0.6660 0.4672 0.1071 0.7304 The website has adequate security 14. 0.2668 0.1450 0.1257 0.8248 0.0881 0.7961 features 15. Bank s servers perform well 0.1523 0.1333 0.2050 0.8158 0.2001 0.7885 Internet banking is exactly what I 16. 0.1056 0.0598 0.3440 0.7513 0.1412 0.7174 need 17. 18. 19. The bank s site provides quick confirmation The bank s website performs the service in the first instance itself Internet banking gives prompt service 0.1056 0.1329 0.0857 0.1802 0.8487 0.7889 0.1721 0.1035 0.0623 0.0773 0.8199 0.7223 0.0975 0.2826 0.1028 0.1446 0.7985 0.7885 Eigen Value 7.2711 2.2261 1.6759 1.3720 1.0747 Percentage Variance 38.30 11.70 8.80 7.20 5.70 Cumulative Percentage 38.30 50.00 58.80 66.00 71.70 h 2 188
Table 5.20 gives the loadings received by the factors under F1, F2, F3, F4 and F5 for private sector banks. Table reveals the rotated factor loadings for the nineteen statements (variables) of satisfaction of customers towards internet banking services provided in private sector banks. It is clear from Table 5.20 that all the nineteen statements are extracted into five factors namely F1, F2, F3, F4 and F5. The factors with identified new names which influence satisfaction of customers in private sector banks are discussed below: The first factor is designed as Confidence and Confirmation of Services on the basis of the loaded variables. Five variables in this category are important with high factor loading. It indicates that among the various performance scales, I trust this bank (0.8346), I am very committed to my relationship with my bank (0.7675), The bank s site provides a confirmation to the service ordered (0.7031), If I had to do transaction again, I would choose the same internet banking service of my bank (0.6933) and Internet banking at my bank has really pleased me (0.6631) are important attributes in this category. Thus, the confidence and confirmation of services provided by the bank is identified as an important factor to influence the customers satisfaction towards the internet banking services rendered by the private sector banks. The second factor is narrated as Fast and Accurate Services on the basis of the loaded variables. Four variables in this category are important with high factor loading. It indicates that among the various performance scale, The service delivered through the bank s website is quick (0.8180), Customer s online transaction with the bank is always accurate (0.7922), The bank s website makes accurate promises about the services delivered (0.7747) and When the bank promises to do something by a certain time, it does do (0.6845) are 189
important attributes in this category. Thus, the fast and accurate services of internet facilities is identified as an important factor to influence the customer satisfaction towards the internet banking services rendered by the private sector banks. The third factor is prescribed as Satisfaction with the services provided on the basis of the loaded variables. Four variables in this category are important with high factor loading. It indicates that among the various performance scales, I am satisfied with the services of internet banking (0.7588), I have truly enjoyed internet banking (0.7333), I will ask my family and friends to use internet banking facilities (0.7218) and I am satisfied with my decision of purchasing using internet banking (0.6660) are important attributes in this category. Thus, the satisfaction with the services provided by the bank is identified as an important factor to influence the customers satisfaction towards the internet banking services rendered by the private sector banks. The fourth factor is highlighted as Security and Fulfillment of Customers Needs on the basis of the loaded variables. Three variables in this category are important with high factor loading. It indicates that among the various performance scales, The website has adequate security features (0.8248), Bank s servers perform well (0.8158) and Internet banking is exactly what I need (0.7513) are important attributes in this category. Thus, the security and fulfillment of customers needs are identified as important factor to influence the customers satisfaction towards the internet banking services rendered by the private sector banks. 190