Customer Attitude towards the CRM-Measures of Cell-phone ...

www.theinternationaljournal.org > RJCBS: Volume: 01, Number: 06, April-2012 Page 29

Introduction

Indian mobile phone industry has witnessed a

remarkable growth, in the recent years. Cheap mobile

handsets, availability of services at affordable rates, low

initial cost and reasonable recurring charges have motivated

several million people to become the customers of leading

service providers. Let it be business people, professionals,

employed, housewives, senior citizens, youth population

including the students, or any other category, everyone

considers cell-phone to be an integral part of their day to day

life.

In this context, it would be necessary and

interesting too, to analyze whether the mobile service

providers are successful in managing and retaining the

overwhelming customer strength, what are the strategies

they adopt to retain the existing customers and to attract the

new customers, and how do their CRM strategies work out.

Key words: CRM, Customer-in-absentia, Attitude,

Grievance-handling, Accessibility, Alpha-testing,

Customer relationship management (CRM)

CRM is a widely-implemented strategy for

managing a company’s interactions with customers, clients

and sales prospects. It involves using technology to

organize, automate, and synchronize business processes—

principally sales activities, but also those for marketing,

customer service, and technical support.

The relationship between customers and the

company authorities is peculiar in the mobile service

industry. In case of prepaid customers, the company people

and the clients do not mostly meet each other. But, still the

CRM concept exists in this relationship too. The efforts of

the cell-phone service providers to retain and attract these

customers-in-absentia are interesting. This paper attempts to

study the CRM measures adopted by the leading GSM

service providers like Aircel, Airtel and BSNL. It also

attempts to analyze the attitude of the customers towards the

CRM measures.

Objectives of the study

1. To analyze various CRM measures adopted by the

leading GSM service providers.

2. To analyze the attitude of the customers towards

the CRM measures.

Methodology

This is an empirical study which is based on the

fresh/first-hand data collected from the customers of the

GSM service providers, at Pollachi.

Sampling technique

A combination of ‘Quota sampling’ and ‘purposive

sampling’ was adopted for the purpose of data collection.

The population was divided into the strata like ‘College

Students’, ‘employed’ and ‘others’. A tool, designed and

standardized for the purpose of this study was used for data

collection.

Sampling unit and sample size

The sampling unit is consisting of two colleges in

Pollachi and the general public. The sample size is limited to

120 respondents.

Conceptual framework

The organizations can motivate and retain the

existing customers by various retention strategies and

selling techniques. One of those strategies is Customer

Relationship Management. The attitude of the customer is

formed, based on the experience of the customer that he has

had from various aspects of the company’s operations. The

attitude may be positive or negative. The direction and the

degree of attitude of the customers towards the CRM are

normally determined by the quality of CRM measures

adopted by the companies. Here, the researcher has taken

some variables to measures the CRM and also the attitude of

the customers.

Variables of the study

Two sets of variables ‘independent’ and ‘dependent’ are

taken up for the purpose of this study. The following

diagram shows the variables in detail.

Customer Attitude towards the CRM-Measures of

Cell-phone service providers (GSM)

– An empirical study at Pollachi Dr. C.K. Kotravel Bharathi Professor of Management & Principal,

Sri Kandhan College of Arts and Science, ERODE – 638 008 TAMILNADU

http://en.wikipedia.org/wiki/Customers

http://en.wikipedia.org/wiki/Sales

http://en.wikipedia.org/wiki/Marketing

http://en.wikipedia.org/wiki/Customer_service

http://en.wikipedia.org/wiki/Technical_support


Tools of Analysis

The following statistical tools have been used for

analyzing the data collected for the purpose of this study.

1. Cronbach’s Alpha testing (Test for internal-consistency

and reliability of data)

2. Correlation analysis

Implications of the Study

This study has brought out some interesting facts

about the CRM concept that is practiced by the GSM service

providers. Though the study has been carried on only in

Pollachi town, some of the findings can be generalized to

other areas also. This study would also give greater scope

for the similar research studies in the same line in future.

Cronbach's Alpha Testing

Cronbach's alpha will generally increase when the

correlations between the items increase. For this reason the

coefficient is also called the internal consistency or the

internal consistency reliability of the test. Cronbach's alpha

measures how well a set of items (or variables) measures a

single uni-dimensional latent construct. When data have a

multidimensional structure, Cronbach's alpha will usually be

low. Technically speaking, Cronbach's alpha is not a

statistical test - it is a coefficient of reliability (or

consistency). Cronbach's alpha can be written as a function

of the number of test items and the average inter-correlation

among the items.

α can take values between negative infinity and 1

(although only positive values make sense). Some

professionals, as a rule of thumb, require a reliability of 0.70

or higher (obtained on a substantial sample) before they will

use an instrument.

Case Processing Summary

N %

Cases Valid 120 100

Excluded 0 0

Total 120 100

Reliability Statistics

Cronbach's Alpha N of Items

0.7 14

As shown above, 14 variables leading to CRM

were taken for the Cronbach’s Alpha Testing. If the

Cronbach’s alpha value is 0.7 and above, it will indicate a

good amount of internal consistency and reliability of data.

Here, the alpha is exactly showing the highly positive and

encouraging value of “0.7”. It shows that the internal

consistency and reliability of data are good. If some of the

items are reduced, the alpha value may further go higher.

Results and Discussion

The cross-tabulation of Gender and Age shows that

the larger sector of the respondents is formed by the male

below 25 years of age (33.33%). Refer Table-1

It is to be noted that 76 respondents out of 120 are

degree holders. Thus it is assumed that majority of the

respondents are capable of well understanding the requisites

for a better CRM and they have given most appropriate

response. Refer Table 2

It was earlier decided to have quota sampling

consisting of three strata viz. the college students (50%),

employed (25%) and others (25%) which should have been

leading to collect data from 60, 30 and 30 respondents

respectively. But, during the field work, the researcher

could collect data only from 59 and 27 respondents

respectively from the first two categories. So, the response

was collected from 34 members of the third category. Refer

Table 3

As the researcher wanted to test whether there was

any impact of level of income on the perception of the

respondents regarding CRM measures, it was included in

the list of back-ground variables. Exactly two-third of the

respondents are in the ‘below 10000’ income category.

Refer Table 4

The longevity of the use of mobile phones by the

respondents was also considered to be a significant factor in

deciding the satisfaction over the CRM measure. To test

this aspect, it was added as one of the variables. More than

60 percent of the users have been using mobiles for more

than 3 years. This period is adequate to understand and rate

the CRM measures taken-up for the study. Refer Table 5

There are three leading GSM operators considered

for the study. Two-third of the respondents taken up for this

study, use AIRCEL. 25 percent of respondents use

AIRTEL, whereas BSNL mobile network is used by 10 out

of 120 respondents. Refer Table 6

The longevity of the use of network by the

respondents was also considered to be a significant factor in

deciding the satisfaction over the CRM measure. To test

this aspect, it was added as one of the variables. More than

60 percent of the users have been using mobiles for more

than 3 years. This period is adequate to understand and rate

the CRM measures of the network. Refer Table 7

The researcher had a hypothetical question whether

the type of network connection would have an impact on the

perception of CRM measures. So, it was added in the list of

Independent Variables

(CRM components)

Schemes

Rationality in tariff

Offers

Response to complaints

Grievance handling

Value-added services

Updating services

Reachability

Accessibility

Technology

Dependent Variable

Attitude towards CRM

http://en.wikipedia.org/wiki/Internal_consistency

www.theinternationaljournal.org > RJCBS: Volume: 01, Number: 06, April-2012 1

variables. It is interesting to note that 90.8 percent of the

respondents use pre-paid connections. If more number of

business men had been taken for the study, the percentage of

the post-paid connection would have been suppose

increased. Refer Table 8

Frequency of recharging is depending upon the

important factors like usage, tariff, etc. As the researcher

wanted to test its relationship with the company’s interest in

the customer relationship, this was added to the variables-

list. The table shows that nearly half of the respondents

recharge very frequently whenever required. Refer Table 9

The Table 10 shows that the network serves the

purpose for which it was chosen. This is endorsed by 98.4%

of the respondents.

Consistency in charging tariff is one of the

significant factors which help the networks to retain their

customers. 71.7 % of the respondents are happy with the

consistency in tariff. But 20.8 % of the respondents are not

happy with this. 20.8 % is considerably a big amount of

disagreement which the networks are to be really concerned

about. Refer Table 11

‘Offers’ that are availed from the network by a

customer after he has got the connection is one of the factors

that influence him in deciding whether to stick with the

same network or to switch over. Thus offers to certain

extent retain the customers and enable the network to

maintain a good relation with them. Here, as per the data,

89.2 % of the respondents are satisfied with the offers

provided by their network. Refer Table 12

As well as the validity and attractiveness of the

offers, how effectively they are communicated is very much

important. It shows to what extent the network is interested

to maintain the relationship with the customers and retain

them. Here, as per the data, 85% of the respondents are

happy with the way the offers are communicated. Refer

Table 13

In maintaining good relations with the customers,

the role of customer care officials is vital. For ensuring the

effective contribution of these officials, an effective

mechanism for having a prompt access to them is must. So,

it has been added as a significant variable in this study.

Exactly 70% of the respondents endorse that they are able to

have access to the customer-care officials when ever needed.

Refer Table 14

Queries from the customers, on various aspects of

the network services at any time are quite common in the

telecom industry. The satisfaction of the customers in this

aspect mainly depends on whether the queries are answered

in time. Nearly 65% of the respondents are satisfied in this

regard. But, 18.3 % of the respondents are not happy with

this. 18.3 % is considerably a big amount of disagreement

which the networks are to be really concerned about. Refer

Table 15

In the industries like telecommunications where

several millions of customers and hundreds of schemes are

involved, the issues and complaints relating to various

aspects are common. They are inevitable too, to certain

extent. But the question here is whether the companies have

made proper arrangements for the filing of such complaints.

Here, 78.3% of the respondents agree that there are adequate

provisions for the filing of complaints in time. Refer Table

16

Immediately after the complaint-filing mechanism,

the next question that arises in our minds is whether there is

a well evolved mechanism to sort and resolve the

complaints. According to 73.4% of the respondents, there

are adequate mechanisms evolved and maintained by the

networks to resolve the complaints in time. Refer Table 17

In spite of having the mechanisms for filing the

complaints and resolving the same, the networks may fail to

gain the confidence of the customers, if those complaints are

not resolved in time. This part of the issue is mainly

depending upon two things – number one: provision in the

system to monitor and ensure the complaint-resolution in

time and number two: the work-force that deals with the

process. 74.2% of the respondents endorse the view that the

complaints are resolved in time, where as another 15% do

not agree with this. Refer Table 18

Unlike other factors, the number of people having

negative attitude towards the networks are more (56.7%) in

case of “suffering from grievances”. Only 30.8% of the

respondents have denied the room for sufferings. This

shows that grievances are common phenomena in the

telecommunications irrespective of the colourful offers,

advanced technologies or other factors. But it is a serious

threat to the CRM efforts of the companies. So, it is

inevitable for the networks to systematically diagnose the

causes of grievances and resolve them suitably. Refer Table

19

Another important factor that may help the

networks to retain the customers and to improve the

relations with them is the value added services provided to

the customers. These services differ from network to

network. 80% of the respondents agree that the value

added services provided by the networks make them feel

comfortable and pleasant. Refer Table 20

Updating of services according to the change in the

trend and technology is an essential need and challenge for

the networks today. Any service-provider that fails to

update the technology and services lose the customers and

the market. But 80% of the respondents of this study say

that networks what they have chosen update the service.

This perception may be generalized to the entire population

too. Refer Table 21

One of the most significant factors that influence

the satisfaction and retention of the customers is the

coverage of the network. Here, 80% of the respondents are

satisfied with the coverage. But 14% of the dissatisfaction

should also be taken into consideration. Refer Table 22


Table 23 shows that 85% of the respondents are

satisfied with the overall services of their respective

network. It is assumed that this includes the satisfaction

over the CRM efforts of the network also.

CORRELATION ANALYSIS

In statistics, correlation indicates the strength and

direction of a linear relationship between two random

variables. That is in contrast with the usage of the term in

colloquial speech, which denotes any relationship, not

necessarily linear. In general statistical usage, correlation or

co-relation refers to the departure of two random variables

from independence. Here, the researcher has applied

correlation technique to test the association among some

selected variables.

The variable “offers satisfying the telecom needs”

is positively correlating with another variable

“communication of offers” (.311**

). This correlation

indicates that offers communicated in time serve the purpose

and satisfy the customers. It also correlates with “answering

queries in time” (.475**

). It indicates that the queries

relating to various offers are answered in time and thus the

customers are enabled to avail the offers in time. It further

correlates with “satisfaction with coverage” (.343**

). It

shows that the perfect coverage of network is essential for

availing and enjoying any offer and it happens in case of the

three networks taken up for this study. Refer Table 24

The variable “satisfaction with coverage”

positively correlates with another variable “queries

answered in time” (.345**

). It shows that better coverage

enables the answering of queries in time. It also correlates

with the “communication of offers” (.488**

). It indicates that

the prompt communication of offer needs better coverage

and this happens in case of all the three networks taken up

for this study.

There is a positive correlation between the

“updating of network services” and “satisfaction with

overall services” (.337**

). It shows that the updating of

services leads to avail a greater amount of benefits and

results in the overall satisfaction with the network. Refer

Table 25

The variable “access to the customer care officials”

is positively correlating with another variable “resolving

complaints in time” (.237**

). This correlation indicates that

the customers are able to access the customer care officials

in time, lodge the complaints and getting it resolved. It also

correlates with “answering queries in time” (.556**

). It

indicates that the customers are enabled to access to the

customer care officials in time and thus the queries relating

to various offers and issues are answered in time. It further

correlates with “satisfaction with overall services” (.363**

).

It shows that the perfect contribution and service of the

customer care officials are one among the important reasons

for the overall satisfaction with the network. Refer Table 26

In Table 27 correlation establishes that the

“network-coverage” is one among the few significant factors

that lead to the “overall all satisfaction” of the customers

with the network.

HYPOTHESIS TESTING

The following hypotheses were also formulated for

the purpose of the study. One way ANOVA was used to

test the hypothesis.

1. Ho = There is no significant relationship between

“Network chosen” and

“Access to customer care officials”.

2. Ho = There is no significant relationship between the


“Satisfaction with the coverage”.



“Satisfaction with overall services”.

The Table-28 shows that the calculated value of the

F-test in each case is higher than the table value of F. The

level of significance in each case also is below 0.05. So, all

the three null-hypotheses-1, 2 & 3 are rejected. So there is a

significant relationship between the variables shown in each

of the hypotheses taken up for the study.


“Income-level” and

“Satisfaction with overall services”.

Refer Table 29. The table value for the degree of

freedom ‘3’ at 95% confidence level is 3.95 and the

calculated value is 1.881. As the table value is higher than

the calculated value, the null-hypothesis-4 is accepted. So,

there is no significant relationship between the “Income-

level” and “Satisfaction with overall services”.

Conclusion

From all the above analysis, the researcher

concludes that, in general, the customers have a positive

attitude towards various ‘Customer Relationship

Management’ measures practiced by the GSM service-

providers. Except a very-few respondents, almost all feel

that the purpose for which they chose the particular network,

has been served. Some of the areas like “satisfying the

customers through offers”, “communicating the offers

promptly”, “providing value added services”, “updating of

services”, etc., are found well executed. These measures are

really helpful to the efforts made in retaining the customers

and in enhancing the customer-relationship.

But still lot of improvement is needed in some

other areas like “grievance handling”, “consistency in

charging tariff”, “access to customer care officials”,

“resolving the complaints in time”, etc. Further, a little bit

improvement is required in some areas like “answering

queries in time”, “provision for filing complaints”,

“mechanism to resolve complaints”, etc.

Scope for further study

The mobile-using population has been rapidly

increasing from time to time. This will further increase in

http://en.wikipedia.org/wiki/Statistics

http://en.wikipedia.org/wiki/Random_variables

http://en.wikipedia.org/wiki/Random_variables


the years to come. The future researchers may study the

impact of CRM measures on the retention and expanding of

the market exclusively for every individual GSM service

provider. Similar studies can be conducted with reference to

the service-providers who use CDMA-Technology also.

Some of the disagreements on the part of the customers like

“suffering from grievances” that have been found as an

outcome of this study may be further tested by the

researchers in their future studies.

References

Jahangir Karimi, Toni M. Somers and Yash P.

Gupta, “Impact of Information Technology

Management Practices on Customer Service”,

Journal of Management Information Systems, Vol.

17, No. 4 (Spring, 2001), pp. 125-158

Eugene W. Anderson, “Customer Satisfaction and

Price Tolerance”, Marketing Letters, Vol. 7, No. 3

(Jul., 1996), pp. 265-274

Nicholas C. Romano, Jr. and Jerry Fjermestad,

“Electronic Commerce Customer Relationship

Management: An Assessment of Research”,

International Journal of Electronic Commerce,

Vol. 6, No. 2 (Winter, 2001/2002), pp. 61-113

Sunil Mithas, M. S. Krishnan and Claes Fornell,

“Why Do Customer Relationship Management

Applications Affect Customer Satisfaction?”, The

Journal of Marketing, Vol. 69, No. 4 (Oct., 2005),

pp. 201-209

M. Tolga Akçura and Kannan Srinivasan,

“Research Note: Customer Intimacy and Cross-

Selling Strategy”, Management Science, Vol. 51,

No. 6 (Jun., 2005), pp. 1007-1012

John R. Hauser, Duncan I. Simester and Birger

Wernerfelt, “Customer Satisfaction Incentives”,

Marketing Science, Vol. 13, No. 4 (Autumn, 1994),

pp. 327-350

Frederick Hong-Kit Yim, Rolph E. Anderson and

Srinivasan Swaminathan, “Customer Relationship

Management: Its Dimensions and Effect on

Customer Outcomes”, The Journal of Personal

Selling and Sales Management, Vol. 24, No. 4,

Customer Relationship Management: Strategy,

Process, and Technology (Fall, 2004), pp. 263-278

Russell S. Winer, “A Framework for Customer

Relationship Management”, California

Management Review, Vol. 43, No. 4 (Summer

2001), pp. 89-105

Table-1

Gender * Age Cross-tabulation

Age Total

Below 25 25 to 35 35 to 45 45 to 60

Gender Male Count 40 5 4 34 83

Expected Count 45.6 4.2 9.7 23.5 83.0

Female Count 26 1 10 0 37

Expected Count 20.4 1.8 4.3 10.5 37.0

Total Count 66 6 14 34 120

Expected Count 66.0 6.0 14.0 34.0 120.0

Source: Primary Data

Table-2

Educational Qualification

Frequency Percent Valid Percent Cumulative Percent

Valid Below SSLC 32 26.7 26.7 26.7

SSLC 2 1.7 1.7 28.3

PUC/H.Sc./Diploma 10 8.3 8.3 36.7

Degree 58 48.3 48.3 85.0

PG 2 1.7 1.7 86.7

Professional Degree 16 13.3 13.3 100.0

Total 120 100.0 100.0



Table-3

Present Status


Valid Government Employee 4 3.3 3.3 3.3

Private Employee 23 19.2 19.2 22.5

Business 20 16.7 16.7 39.2

College Student 59 49.2 49.2 88.3

Retired Govt employee 2 1.7 1.7 90.0

House-Wife 12 10.0 10.0 100.0

Total 120 100.0 100.0


Table-4

Monthly Income


Valid Below 10000 80 66.7 66.7 66.7

10000 to 15000 27 22.5 22.5 89.2

15000 to 20000 4 3.3 3.3 92.5

30000 to 50000 9 7.5 7.5 100.0

Total 120 100.0 100.0 Source: Primary Data


Table-5

Longevity of using mobile phone


Valid 1 to 3 years 47 39.2 39.2 39.2

3 to 5 years 34 28.3 28.3 67.5

More than 5 years 39 32.5 32.5 100.0

Total 120 100.0 100.0


Table-6

Net work used


Valid AIRCEL 80 66.7 66.7 66.7

AIRTEL 30 25.0 25.0 91.7

BSNL 10 8.3 8.3 100.0

Total 120 100.0 100.0


Table-7

Longevity of using network


Valid 1 to 3 years 47 39.2 39.2 39.2

3 to 5 years 56 46.7 46.7 85.8

More than 5 years 17 14.2 14.2 100.0

Total 120 100.0 100.0


Table-8

Type of connection


Valid Pre-paid 109 90.8 90.8 90.8

Post-paid 11 9.2 9.2 100.0

Total 120 100.0 100.0


Table-9

Frequency of recharging


Valid Twice in a month 29 24.2 24.2 24.2

Once in a month 29 24.2 24.2 48.3

Once in three months 4 3.3 3.3 51.7

Very frequently 58 48.3 48.3 100.0

Total 120 100.0 100.0



Table-10

Purpose is served


Valid Disagree 2 1.7 1.7 1.7

Agree 59 49.2 49.2 50.8

Strongly Agree 59 49.2 49.2 100.0

Total 120 100.0 100.0


Table-11

Consistency in charging tariff


Valid Strongly Disagree 6 5.0 5.0 5.0

Disagree 19 15.8 15.8 20.8

Neither Agree Nor Disagree 9 7.5 7.5 28.3

Agree 62 51.7 51.7 80.0

Strongly Agree 24 20.0 20.0 100.0

Total 120 100.0 100.0


Table-12

Offers satisfy the telecom needs



Disagree 1 .8 .8 2.5


Agree 74 61.7 61.7 72.5

Strongly Agree 33 27.5 27.5 100.0

Total 120 100.0 100.0


Table-13

Offers are properly communicated



Disagree 5 4.2 4.2 5.8


Agree 41 34.2 34.2 49.2

Strongly Agree 61 50.8 50.8 100.0

Total 120 100.0 100.0


Table-14

Access to Customer care officials



Disagree 11 9.2 9.2 11.7


Agree 49 40.8 40.8 70.8

Strongly Agree 35 29.2 29.2 100.0

Total 120 100.0 100.0


Table-15

Queries are answered in time



Disagree 19 15.8 15.8 18.3


Agree 50 41.7 41.7 77.5

Strongly Agree 27 22.5 22.5 100.0

Total 120 100.0 100.0



Table-16

Provision to file complaints




Agree 45 37.5 37.5 59.2

Strongly Agree 49 40.8 40.8 100.0

Total 120 100.0 100.0


Table-17

Mechanism to resolve complaints




Agree 53 44.2 44.2 70.8

Strongly Agree 35 29.2 29.2 100.0

Total 120 100.0 100.0


Table-18

Complaints are resolved in time



Disagree 15 12.5 12.5 15.0


Agree 60 50.0 50.0 75.8

Strongly Agree 29 24.2 24.2 100.0

Total 120 100.0 100.0


Table-19

Suffering from grievances



Disagree 33 27.5 27.5 30.8


Agree 44 36.7 36.7 80.0

Strongly Agree 24 20.0 20.0 100.0

Total 120 100.0 100.0


Table-20

Network provides value added services



Disagree 5 4.2 4.2 5.8


Agree 59 49.2 49.2 69.2

Strongly Agree 37 30.8 30.8 100.0

Total 120 100.0 100.0


Table-21

Network updates services




Agree 54 45.0 45.0 65.0

Strongly Agree 42 35.0 35.0 100.0

Total 120 100.0 100.0



Table-22

Satisfied with the coverage



Disagree 10 8.3 8.3 14.2


Agree 49 40.8 40.8 60.8

Strongly Agree 47 39.2 39.2 100.0

Total 120 100.0 100.0


Table-23

Satisfied with the overall services



Disagree 9 7.5 7.5 11.7


Agree 57 47.5 47.5 62.5

Strongly Agree 45 37.5 37.5 100.0

Total 120 100.0 100.0


Table-24

Correlations

Offers satisfy the

telecom needs

Offers are properly

communicated

Queries are

answered in

time

Satisfied with

the coverage

Offers satisfy

the telecom

needs

Pearson Correlation 1 .311**

.475**

.343**

Sig. (2-tailed) .001 .000 .000

N 120 120 120 120

Satisfied with

the coverage

Pearson Correlation .343**

.488**

.345**

1

Sig. (2-tailed) .000 .000 .000

N 120 120 120 120

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

Table-25

Satisfied with overall services Network updates services

Satisfied with the

overall services


Sig. (2-tailed) .000

N 120 120

Network updates

services


1


N 120 120

Table-26

Correlations

Satisfied with the

overall services

Access to

Customer care

officials

Complaints are

resolved in

time

Queries are

answered in

time

Access to

Customer care

officials


1 .237**

.556**

Sig. (2-tailed) .000 .009 .000

N 120 120 120 120

Complaints are

resolved in time

Pearson Correlation .177 .237**

1 .269**

Sig. (2-tailed) .053 .009 .003

N 120 120 120 120

Queries are

answered in time


.556**

.269**

1

Sig. (2-tailed) .000 .000 .003

N 120 120 120 120



Table-27

Correlations

Satisfied with coverage Satisfied with the overall services

Satisfied with the

coverage



N 120 120

Satisfied with the

overall services


1


N 120 120


Table-28

ANOVA

Sum of Squares df Mean Square F Sig.

Satisfied with the overall services Between Groups 10.450 2 5.225 5.136 .007

Within Groups 119.017 117 1.017

Total 129.467 119

Satisfied with the coverage Between Groups 11.275 2 5.638 4.527 .013

Within Groups 145.717 117 1.245

Total 156.992 119

Access to Customer care officials Between Groups 7.046 2 3.523 3.486 .034

Within Groups 118.254 117 1.011

Total 125.300 119

Table-29

ANOVA

Satisfied with the overall services

Sum of Squares df Mean Square F Sig.

Between Groups 6.005 3 2.002 1.881 .137

Within Groups 123.462 116 1.064

Total 129.467 119

***

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