chapter-vii service quality analysis of indian general...

Chapter-VII

Service Quality Analysis of Indian General Insurance Companies

Indian general insurance industry has suddenly witnessed a major boom.

Being a globalized market, the customers seek and demand world class

products. In today's global market everything is benchmarked and compared.

The market for insurance business is found to be vast, the potential

policyholders are in a very good number, and their needs and requirements are

not identical (Banu, 2004). The success of insurance companies in the market

rests on the availability of customized product and also the service quality

offered to customers. At this juncture, the insurance companies should evaluate

their services and identify their distinction from others. The only way to

succeed in the market is the formulation of differentiated service to different

customer segments. (Vanniarajan and Jeyakumaran, 2007). Delivering of

quality services to the customers has become an indispensable factor for

success and survival in today's competitive insurance environment. General

insurance is a professional service which is characterized by high involvement

of the consumers due to the importance of tailoring to the specific needs, the

variability of the products available, the complexity involved in the policies

and processes, and the need to involve the consumer in every aspect of the

transaction (Mehta et al., 2002). The post-liberalized insurance industry in

India has been witnessing a discernible shift from the seller to the buyers'

market. The reformed insurance industry has offered a plethora of new

customer friendly products, new delivery channels like bancassurance,

corporate agents, brokers and direct selling through the internet, greater use of

computerization and information technology. The detariffing will be a major

reform of the insurance pricing regime and is likely to introduce a paradigm

change in the non-life sector. The customers‟ expectations have reached an all

time high. The opening up of the market has brought competition in the

market, and the customer decides the price of the product and service level

offered. So, the customer is the focus of the business, not only marketing

practices acquire critical importance, but the manner in which the customer is

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served also needs close attention. The customer is now better informed and his

expectations are on the rise in marketing. These changing circumstances are

exerting pressure on the existing players in the industry to rewrite their

strategies and policies. They will have to raise their level of customer services

to fight for survival in the market place. They will have to become much

sharper and more market savvy. General insurance companies themselves feel

the need to improve service quality. Under these circumstances, there is a need

to assess how far the public and private general insurance companies will be

able to satisfy their customers by providing quality service. Performance

evaluation of an individual insurance company will be insignificant for this

purpose. Inter-firm comparison within the general insurance companies as a

whole is required to examine how they are performing in the post-reform

period.

7.1 Service Quality: Conceptualization and Operationalization

Quality has come to be recognized as a strategic tool for attaining

operational efficiency and improved business performance (Babakus and

Boller, 1992; Garvin, 1983; Phillips et al., 1983). This is true for the service

sector too. Several authors have demonstrated its positive relationship with

profits, increased market share, return on investment, customer satisfaction and

future purchase intentions (Jain and Gupta, 2004). Service quality is a concept

that has around considerable interest and debate in the research literature

because of the difficulties in both defining it and measuring it with no overall

consensus emerging on either (Wisniewski, 2001). There are a number of

different "definitions" as to what is meant by service. Parasuraman et al. (1988)

defined service quality as a global judgment, or attitude, relating to the

superiority of the service and explicated it as involving evaluations of the

outcome (i.e., what the customer actually receives from services) and the

process of service act (i.e., the manner in which service is delivered).

Parasuraman et al. (1985, 1988) posited and operationalized service quality as a

difference between consumer expectations of 'what they want' and their

perception of 'what they get'. Cronin and Taylor (1992) controverted the

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framework of Parasuraman et al. with respect to the conceptualization and

measurement of service quality. They argued that the performance based

measure was an enhanced means of measuring the service quality constant.

Teas (1993) stated that the service quality is derived from a comparison of the

performance with the ideal standards. The service quality is produced in the

interaction between a customer and elements in the service organization. They

differentiated between quality associated with the process of service delivery

and quality service means confirming to the customer expectations on a

consistent basis. Gronroos (1984) explained service quality as a perceived

judgment, resulting from an evaluation process where customers compare their

expectations with the service they perceive to have received. The author also

suggested that service quality issues could be split into technical quality (what

is done) and functional quality (how it is done).

7.2 Measurement of Service Quality

Notwithstanding the recognized importance of service quality there have

been methodological issues and application problems with regard to its

operationalization. Quality in the context of service industries has been

conceptualized differently and based on different conceptualizations,

alternative scales have been proposed for service quality measurement.

SERVQUAL and SERVPERF constitute two major service quality

measurement scales. The consensus, however, continues to elude till date as to

which one is superior.

SERVQUAL Scale

The foundation for the SERVQUAL scale is the gap model proposed by

Parasuraman et al. (1985, 1988). According to the gap model, satisfaction is

related to the size and direction of disconfirmation of a person‟s experience vis-

a-vis his or her initial expectations. As a gap or difference between customer

expectations and perceptions, service quality is viewed as lying along a

continuum ranging from ideal quality to totally unacceptable quality with some

points along the continuum representing satisfactory quality. Parasuraman et al.

(1988) held that when perceived or experienced service is less than expected

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service, it implies less than satisfactory service quality. But, when the

perceived service is less than the expected service, the obvious inference is that

service quality is more than satisfactory. Parasuraman et al. (1988) pointed out

that while a negative discrepancy between perceptions and expectations – a

„performance gap‟ as they call it - causes dissatisfaction, a positive discrepancy

leads to consumer delight. Parasuraman et al. identified a set of 22

variables/items tapping five different dimensions of service quality construct.

Since service quality has been operationalized as being a gap between

customer‟s expectations and perceptions of performance on these variables, the

service quality scale comprised of total 44 items (22 for expectations and 22 for

perceptions). The higher the perception minus expectation score, the higher is

perceived to be the level of service quality. Several issues have been raised

with regard to use of (P-E) gap scores, i.e., disconfirmation model. Validity of

(P-E) measurement framework has also come under attack due to problems

with the conceptualization and measurement of expectation component of the

SERVQUAL scale.

In 1988, Parasuraman et al. developed SERVQUAL, a method to assess

customer loyalty for service industries. Their measurement involved the

difference between customers‟ perceptions and expectations based on five

generic dimensions:

Tangibility: appearance of physical facilities, equipment, personnel and

written materials.

Reliability: ability to perform the promised service dependably and

accurately.

Responsiveness: willingness to help customers and provide prompt

service.

Assurance: employees' knowledge and courtesy and their ability to

inspire trust and confidence.

Empathy: caring, individualized attention given to customers.

Parasuraman et al. (1985) proposed that service quality is a function of

the differences between expectation and performance along the quality

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dimensions. They developed a service quality model based on gap analysis.

This model of service quality is derived from the magnitude and direction of

five gaps which include consumer expectations-experiences discrepancies in

addition to the differences in service design, communications, management and

delivery. The first four gaps affect the way in which service is delivered, and

the existence of these four gaps leads to the extent of gap five.

The various gaps (Figure 7.1) visualized in the model are:

Gap 1: Difference between consumer expectations and management

perceptions of those expectations, i.e., not knowing what consumers

expect.

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Gap 2: Difference between management perceptions of consumer

expectations and service quality specifications, i.e., improper service

quality standards.

Gap 3: Difference between service quality specifications and service

actually delivered, i.e., the service performance gap.

Gap 4: Difference between service delivery and the communications to

consumers about service delivery, i.e., whether promises match

delivery?

Gap 5: Difference between consumer expectations and perceived

service. This gap depends on size and direction of the four gaps

associated with the delivery of service quality on the marketer‟s side.

According to this model, the service quality is a function of

perception and expectations and can be modelled as:

Where,

SQ=overall service quality; k= number of attributes.

Pij = Performance perception of stimulus i with respect to attribute j.

Eij = Service quality expectation for attribute j that is the relevant norm

for stimulus i.

SERVPERF Scale

Perception (P) is definable and measurable in a straightforward manner

as the consumer‟s belief about service is experienced, expectation (E) is subject

to multiple interpretations and as such has been operationalized differently by

different authors. It is because of the vagueness of the expectation concept that

some researchers like Babakus and Boller (1992) and Carman (1990) stressed

the need for developing a methodologically more precise scale. The

SERVPERF scale – developed by Cronin and Taylor (1992) – is one of the

important variants of the SERVQUAL scale. For being based on the perception

component alone, it has been conceptually and methodologically posited as a

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better scale than the SERVQUAL scale that has its origin in the

disconfirmation paradigm.

Cronin and Taylor (1992) opined that expectation component of

SERVQUAL scale be discarded and instead performance component alone be

used. They questioned the conceptual basis of the SERVQUAL scale. The

superiority of performance only instrument over disconfirmation model was

corroborated by conducting research across four industries, namely, banks, pest

control, dry cleaning and fast food. Being a variant of the SERVQUAL scale

and containing perceived performance component alone, performance only

scale is comprised of only 22 items. A higher perceived performance implies

higher service quality. Methodologically, the SERVPERF scale represents

marked improvement over the SERVQUAL scale. Not only is the scale more

efficient in reducing the number of items to be measured by 50 per cent, it has

also been found empirically superior to the SERVQUAL scale for being able to

explain greater variance in the overall service quality measured through the use

of single-item scale. They proposed what is referred to as the SERVPERF

scale. In equation form it can be expressed as

SQi = Pij

Where,

SQi = Perceived service quality of individual 'i'

P = Perception of Individual 'i' with respect to performance of a service firm

regarding attribute 'j'.

7.3 Comparison of SERVQUAL Vs. SERVPERF

SERVQUAL and SERVPERF scales were assessed in the Indian

context in terms of their ability to explain variance in the overall service

quality, power to distinguish among service objects/firms, convenience in data

collection and more importantly their diagnostic ability to provide insights for

managerial interventions in case of quality shortfalls.

Overall Service Quality

The scales could be employed to measure the overall service quality of a

service firm vis-à-vis multiple variables of the scales. By regressing

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perceptions of overall service quality on its corresponding multi-item service

quality scale, the ability of a scale to explain the variation in the overall service

quality could be assessed. It has been suggested in the previous research studies

that SERVPERF scale explained higher variance in the overall service quality

than the SERVQUAL scale.

Convenience in Data Collection

The SERVQUAL scale requires data on perceptions as well as customer

expectations, whereas the performance only measure, i.e., SERVPERF requires

data on customers‟ perceptions alone, thus, considerably obviating the data

collection task. While the number of items required for the data is only 22 for

the SERVPERF scale, it is 44 for the SERVQUAL scale. The requirement of

additional data could result in making the questionnaire lengthy and

compounds data editing and coding tasks. In SERVPERF scale the number of

items to be measured is reduced by 50 per cent. So, in this regard also,

SERVPERF shows superiority to SERVQUAL scale.

Diagnostic Ability of Scales in Providing Insights for Managerial

Intervention and Strategy Formulation

A major reason underlying the use of a multi-item scale vis-à-vis its

single item counterpart is its ability to provide information about the attributes

where a given firm is deficient in providing service quality and thus needs to

evolve strategies to remove such quality shortfalls with a view to enhance

customer satisfaction in future. In SERVPERF scale it is performance

component only that is acting as a reference point whereas it is customer

expectation for each of the service areas that is acting as a yardstick under the

SERVQUAL scale. Ideally speaking, management should strive for attaining

the maximum possible performance level in all those service areas where the

performance level is lacking. This is exactly what the SERVPERF scale-based

analysis purports to do. However, this is tenable only under the situations when

there are no time and resource constraints and it can be assumed that all the

areas are equally important to customers and they want maximum possible

quality level in respect of each of the service attributes. But, in a situation

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where the management works under the resource constraints and consumers do

not attribute equal importance to possible service quality provisions, the

management needs to find areas which are more critical from the consumers‟

point of view and call for immediate attention. This is exactly what

SERVQUAL scale does by pointing to areas where firm‟s performance is

below the customers‟ expectations.

So long as perceived performance equals or exceeds customer

expectations for a service attribute, the SERVQUAL scale does not point to

managerial intervention despite performance level in respect to that attribute

falling short of the maximum attainable service quality score. The SERVPERF

scale could indicate that the service attribute under study is a fitting area for

managerial intervention because the perceived performance level is below

maximum attainable service quality score. This may, however, not be the case

with the SERVQUAL scale. Since the customer perceptions of an insurer's

performance could be above their expectation level, there seems to be no

ostensible justification in further trying to improve the performance in this area.

Any such effort, moreover, is unlikely to add to the customers‟ delight, as the

customers themselves might not be desirous of having more of the service

attribute. Since (P-E) entails a direct comparison of performance perceptions

with customer expectations, it provides a more pragmatic diagnosis of service

quality shortfalls. Especially in the event of time and resource constraints, the

SERVQUAL scale is able to direct managerial attention to service areas that

are critically deficient from the customers‟ viewpoint and require immediate

attention. No doubt, the SERVQUAL scale entails greater data collection work,

but employing direct rather than computed expectation, disconfirmation

measures can ease it out. So, in this study, SERVQUAL scale is used to assess

the service quality of both the public and private sector general insurance

companies due to its better diagnostic ability in providing an insight into

managerial intervention and strategy formulation.

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7.4 A Descriptive Analysis of Customer Profile

Section-I

The descriptive analysis presents a demographic profile of the

respondents. To be successful in the present market environment, the general

insurers have to provide the products and services according to the needs of

customers. The demands of the customers vary as per their age, income,

occupation, education level etc. For formulating effective marketing strategies

companies need to maintain an up-to-date profile of the customers in the form

of customer based data. The customers selected for the study belonged to

different categories made on the basis of city/village, sex, age, education,

occupation, monthly income, policy and duration. The study aims to have a

comparative service quality analysis of the public and private sector general

insurance companies. The customers belonging to different categories may

have different perceptions regarding the same product of a particular company.

It may lead to draw wrong conclusions regarding the comparative service

quality of the public and private sector insurers. To overcome this problem, the

questionnaires have been filled by the identical customers of the public and

private sector general insurance companies to the maximum possible extent.

The Chi-square test has been used to investigate the significant difference

between the customers profile belonging to different categories for both the

public and private sector general insurance companies.

Table 7.1

Location Profile of the Customers

Demography Public Sector Private Sector Total

Frequency Per cent Frequency Per cent Frequency Per cent

City 112 93.3 166 92.2 278 92.7

Village 8 6.7 14 7.8 22 7.3

Total 120 100.01 180 100.01 300 100.01

Chi-square value =0.131, d.f. = 1, P- value = 0.718, not significant at 5% level of significance.

Table 7.1 highlights the sector-wise location profile of the respondents.

As per the table majority of the respondents 112 (93.3%) and 166 (92.2%) from

the public and private sectors respectively lived in cities. Only a small number

of respondents i.e., 8 (6.7%) and 14 (7.8%) from the public and private sectors

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respectively resided in villages. The Chi-square test (P > .05) reveals that

location-wise there is no significant difference between the customers of public

and private sector general insurance companies.

Table 7.2

Gender Profile of the Customers

Sex Public Sector Private Sector Total


Male 86 71.7 112 62.2 198 66.0

Female 34 28.3 68 37.8 102 34.0

Total 120 100.0 180 100.0 300 100.0

Chi-square value = 2.862, d.f. = 1, P-value =0.091, not significant at 5% level of significance.

The table reveals that the numbers of male respondents are more than

the females in both the public and private sector general insurance companies

under study. In the public sector companies, 86 (71.7%) of the customers are

male and 34 (28.3%) are female. However, in the private sector companies, 112

(62.2%) respondent customers belong to male category and the remaining 68

(37.8%) belong to female category. The Chi-square test results (P > 0.05)

exhibit that sex-wise, there is no significant difference between the respondents

from the public and private sector general insurance companies.

Table 7.3

Age Profile of the Customers

Age Public Sector Private Sector Total


Below 30 yrs. 37 30.8 76 42.2 113 37.7

30 to 45 yrs. 54 45.0 69 38.3 123 41.0

45 to 60 yrs. 24 20.0 28 15.6 52 17.3

Above 60 yrs. 5 4.2 7 3.9 12 4.0

Total 120 100.0 180 100.0 300 100.0

Chi-square value = 4.094, d.f. = 3, P- value = 0.251, not significant at 5% level of significance.

The age-wise distribution of the respondents from both the public and

private sector general insurance companies is exhibited in Table 7.3. As is

evident from the table as many as 37 (30.8%) and 76 (42.2%) respondents from

both the public and private sector companies respectively are below the age of

30 years. Similarly, as many as 54 (45%) and 69 (38.3%) respondents fall in

the age category of 30 to 45 years, 24 (20%) and 28 (15.6%) in 45 to 60 years,

whereas 5 (4.2%) and 7 (3.9%) above 60 years in the public and private sector

companies respectively. The table reflects that majority of the respondents are

up to the age of 45 years in both the sectors. The Chi-square test shows that

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there is an insignificant difference among the respondents belonging to

different age categories in the public and private sector insurance companies.

Table 7.4

Education Profile of the Customers

Education Public Sector Private Sector Total


Below Matric 11 9.2 17 9.4 28 9.3

Under Graduate 14 11.7 29 16.1 43 14.3

Graduate 26 21.7 61 33.9 87 29.0

Postgraduate 49 40.7 53 29.5 102 34.1

Professional

Degree

20 16.7 20 11.1 40 13.3

Total 120 100.0 180 100.0 300 100.0


Table 7.4 presents the education-wise distribution of the respondents of

public and private sector insurance companies separately. However, majority of

the respondents from the private sector insurance companies, i.e., 61 (33.9%)

belong to the graduate category, whereas 53 (29.5%), 29 (16.1%), 20 (11.1%)

and 17 (9.4%) respondents represent the postgraduate, undergraduate,

professional degree, and below matric categories respectively. An analysis of

the table reveals that maximum number of respondents from the public sector

insurance companies, i.e., 49 (40.7%) belong to the postgraduate category,

while 26 (21.7%), 20 (16.7%), 14 (11.7%) and 11 (9.2%) respondents represent

the graduate, professional degree, under graduate and below matric categories

respectively. The Chi-square test (P > 0.05) shows that an insignificant

difference lies between the education status of the respondents from the public

and private sector insurance companies.

Table 7.5

Occupation Profile of the Customers

Occupation Public Sector Private Sector Total

Frequency Per cent Frequency Percent Frequency Per cent

Businessman 31 25.8 37 20.6 68 22.7

Serviceman 66 55.0 83 46.1 149 49.6

Professional 8 6.7 15 8.3 23 7.7

Agriculturist 7 5.8 16 8.9 23 7.7

Any Other 8 6.7 29 16.1 37 12.3

Total 120 100.0 180 100.0 300 100.0


Table 7.5 presents the occupation-wise distribution of respondents from

the public and private sector insurance companies separately. An analysis of

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the table provides that maximum number of respondents from the public sector

general insurance companies under study, i.e., 66 (55.0%) belong to

serviceman category, whereas 31 (25.8%) and 7 (5.8%) respondents represent

the businessman and agriculturist categories respectively. Further, an equal

number of respondents, i.e., 8 (6.7%) belong to both the professional and any

other categories. However, majority of the respondents from the private sector

general insurance companies, i.e., 83 (46.1%) belong to the serviceman

category, while 37 (20.6%), 29 (16.1%), 16 (8.9%), and 15 (8.3%) respondents

represent the businessman, any other, agriculturist and professional categories

respectively. The results of Chi-square test (P > 0.05) reveal that there is an

insignificant difference between occupation-wise respondents of both the

public and private sector insurance companies.

Table 7.6

Monthly Income Profile of the Customers

Monthly Income Public Sector Private Sector Total

Frequency Per cent Frequency Percent Frequency Percent

Below Rs.10000 21 17.5 49 27.2 70 23.3

Rs.10000 to 25000 51 42.5 72 40.0 123 41.1

Rs.25000 to 50000 36 30.0 43 23.9 79 26.3

Rs.50000 to 75000 3 2.5 10 5.6 13 4.3

Above Rs.75000 9 7.5 6 3.3 15 5.0

Total 120 100.0 180 100.0 300 100.0


Table 7.6 exhibits monthly income-wise distribution of the respondents

belonging to the public and private sector general insurance companies. As is

evident from the table, majority of the respondents, i.e., 51 (42.5%) belong to

monthly income group of Rs.10,000 to Rs.25000, while 36 (30%), 21 (17.5%),

9 (7.5%) and 3 (2.5%) respondents represent the categories of Rs. 25,000-

50,000, below Rs.10,000, above Rs.75,000 and Rs.50,000-75,000 respectively.

However, maximum number of respondents from the private sector insurance

companies, i.e., 72 (40%) belong to monthly income group of Rs.10,000-

25,000, whereas 49 (27.2%), 43 (23.9%), 10 (5.6%) and 6 (3.3%) respondents

represent the income categories of below Rs.10,000, Rs.25,000-50,000,

Rs.50,000-75,000 and above Rs.75,000 respectively. The Chi-square test

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indicates that there is an insignificant difference between income profile of the

respondents from both the public and private sector insurance companies.

Table 7.7

Time Period of Policy

Duration of Customer Public Sector Private Sector Total


Less than 1 year 29 24.2 48 26.7 77 25.7

1 year but less than 3 years 40 33.3 69 38.3 109 36.3

3 years but less than 6 years 22 18.3 41 22.8 63 21.0

Above 6 years 29 24.2 22 12.2 51 17.0

Total 120 100.0 180 100.0 300 100.0


The table reflects that among the public sector insurance companies,

majority of the respondents, i.e., 40 (33.3%) have been the customers of their

respective companies for one year but less than three years, while 22 (18.3%)

respondents have been the customers for three years but less than six years.

Similarly, an equal number of customers i.e., 29 (24.2%) have been the

customers of their companies for less than one year and above six years.

However, maximum number of respondents from the private sector insurance

companies, i.e., 69 (38.3%) have been the customers of their respective

companies for one year but less than three years, whereas the other

respondents, i.e., 48 (26.7%), 41 (22.8%) and 22 (12.2%) have been the

customers for less than one year, three years but less than six years, and above

six years respectively. The Chi-square test indicates that there is an

insignificant difference between duration of customer profile of the

respondents from both the public and private sector insurance companies.

7.5 Service Quality Level of the Public and Private Sector General

Insurance Companies Using SERVQUAL Model

The analysis of the gap between consumers‟ expectations and their

perceptions of service quality delivery provides the management an

opportunity to know how well is actual service performance compared with the

expectations of the consumers. Thus, the study of this gap is extremely useful

for the management in monitoring the service delivery by testing

policyholders‟ perception. It helps to ascertain whether the service quality

provided by the insurers is up to the expectations of the policyholders.

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Tangibility

Table 7.8

Sector-wise Gap Analysis of Customers’ Expectations and Perceptions

Regarding Tangible Dimension

Tangibility Public Sector Private Sector

Statements P

mean

E

mean

Gap

(P-E)

t-

value

p-

value

P

mean

E

mean

Gap

(P-E)

t-

value

p-

value

Modern equipment and

technology

3.94 4.27 -0.33 -3.6 0.000 4.17 4.35 -0.18 -2.77 0.006

Physical facilities

visually appealing 3.63 4.06 -0.43 -4.9 0.000 3.79 3.98 -0.19 -2.93 0.004

Employees and

agents neat in

appearance

3.67 3.99 -0.33 -3.2 0.000 3.82 4.02 -0.19 -2.41 0.017

Materials

associated with

the services

appealing

3.79 4.07 -0.28 -2.7 0.010 3.87 3.96 -0.09 -1.21 0.229

It is evident from the table that both the sectors have shown a negative

SERVQUAL score on all the four items of tangible dimensions. However, the

private sector has exhibited a lower negative value which means lesser gap

between customers‟ perceptions and expectations. The P-values indicate that

there is a significant gap between customers‟ perceptions and expectations in

all the four items of tangible dimension in the case of public sector general

insurance companies and the first three items in the case of private sector

companies. The significant negative SERVQUAL scores against all the items

of tangibility except materials associated with the services appealing in the case

of private insurers demand substantial investment on the said elements of

tangibility which may improve the service quality to a great extent. The public

sector companies need to show sincere interest in adopting new technology,

computerization, internet and intranet based services, etc.

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Reliability

Table 7.9


Regarding Reliability Dimension

Reliability Public Sector Private Sector

Statements P

mean

E

mean

Gap

(P-

E)

t-

value

p-

value

P

mean

E

mean

Gap

(P-

E)

t-

value

p-

value

Promise to do something by a

certain time, they

do so.

3.58 4.03 -0.46 -4.5 0.000 3.66 4.14 -0.48 -5.15 0.000

Show sincere

interest in solving

customers‟

problem.

3.52 4.18 -0.67 -6.1 0.000 3.77 4.14 -0.38 -4.53 0.000

Perform the service

right in the first

instance.

3.55 4.08 -0.53 -4.4 0.000 3.67 4.06 -0.38 -4.22 0.000

Provide their

services at the time

they promise to do

so.

3.53 4.13 -0.60 -5.6 0.000 3.67 4.11 -0.43 -4.47 0.000

Error free record. 3.62 4.19 -0.58 -5.5 0.000 3.69 4.18 -0.49 -5.83 0.000

Sound financial

strength. 3.92 4.18 -0.26 -2.9 0.000 3.93 4.20 -0.27 -3.38 0.001

Goodwill. 3.83 4.15 -0.32 -3.1 0.000 3.97 4.02 -0.06 -0.72 0.472

Table 7.9 carries the data showing variation in SERVQUAL scores of

both the public and private insurers under study on all elements of reliability.

The SERVQUAL scores against all the seven items of reliability dimension in

the case of both public and private sector general insurance companies are

negative, but the gap between perceptions and expectations of customers of the

private insurers is lesser than that of the public insurers. The P-value (<.05) for

all the items of reliability dimension except Godwill of the private insurers

show that there is a significant gap between the customers‟ perceptions and

their expectations. It is evident that the insurers are not doing well in meeting

the customers‟ expectations about reliability dimension. The study implies that

managements of both the public and private insurers should emphasize on

improving quality of reliability dimension to improve overall service quality

and to meet customers‟ expectations.

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Responsiveness

Table 7.10


Regarding Responsiveness Dimension

Responsiveness Public Sector Private Sector

Statements P

mean

E

mean

Gap

(P-E)

t-

value

p-

value

P

mean

E

mean

Gap

(P-E)

t-

value

p-

value

Employees and agents tell customers

exactly when services

performed.

3.64 3.98 -0.33 -3.0 0.00 3.73 3.96 -0.22 -2.68 0.008

Employees and

agents provide

prompt service to

customers.

3.53 4.02 -0.49 -4.7 0.00 3.81 4.05 -0.24 -3.14 0.002

Employees and

agents willing to help

customers.

3.66 4.04 -0.38 -3.7 0.00 3.82 4.01 -0.19 -2.49 0.014

Employees and

agents remain ready

to respond to

customers' requests.

3.58 3.92 -0.33 -3.0 0.00 3.72 3.91 -0.18 -1.9 0.059

Employees and agents communicate

with customers

regularly.

3.64 3.97 -0.33 -3.3 0.00 3.89 3.68 0.22 2.55 0.012

Method of

communication suits

the needs of

customers.

3.69 4.08 -0.38 -4.2 0.00 3.76 4.08 -0.32 -4.08 0.000

Table 7.10 carries the data showing the customers‟ perceptions and

expectations regarding items of responsiveness dimension of both the public

and private sector general insurance companies. The results show that the mean

scores of expectations are higher than those of the perceptions which means

that both the public and private general insurers are unable to meet the

expectations of their customers. The negative SERVQUAL scores of both the

insurers speak about their poor service quality standards on the responsiveness

dimension except the statement employees and agents communicate with

customers' regularly, where SERVQUAL score has a positive value in the case

of private sector insurance companies. The P- value of all the items of

responsiveness dimension is <0.05 except for the statement that “employees

and agents remain ready to respond to customers requests” of the private

insurers. It exhibits that there is a significant gap between customers‟

222

perception and expectations. So, the results suggest that it is necessary for both

the public and private insurers to enhance their level of service for improving

their overall service quality. The negative SERVQUAL score of the private

sector general insurance companies on the item called "employees and agents

remain ready to respond to customers requests" is insignificant which implies

that the private insurers are required to concentrate on the other items of

responsiveness dimension.

Assurance

Table 7.11


Regarding Assurance Dimension Assurance Public Sector Private Sector

Statements P

mean

E

mean

Gap

(P-E)

t-

value

p-

value

P

mean

E

mean

Gap

(P-E)

t-

value

p-

value

The behaviour of

employees and agents

instills confidence in

customers.

3.68 4.05 -0.38 -3.6 0.000 3.83 4.06 -0.23 -2.81 0.006

Customers feel safe

in that their

transactions are safe.

3.78 4.17 -0.39 -3.7 0.000 3.81 4.17 -0.37 -4.63 0.000

Employees and

agents are courteous

with customers.

3.67 3.90 -0.33 -2.9 0.01 3.79 3.82 -0.03 -0.37 0.714

Employees and

agents have

knowledge to render

professional service

to customers.

3.74 4.12 -0.38 -3.4 0.00 3.88 4.24 -0.36 -4.62 0.000

Employees and agents give accurate

presentation of

products and

services.

3.74 3.9 -0.16 -1.5 0.15 3.81 4.02 -0.22 -2.93 0.004

Table 7.11 describes the mean value of customer perceptions and

expectations regarding items of assurance dimension of both the public sector

and the private sector general insurance companies are shown in table 7.11.

The results reveal that the mean values against all the items of expectations are

higher than those of the perceptions which implies that both the public and

private general insurers have failed to meet the expectations of their customers.

The negative SERVQUAL scores of both the insurers speak about their poor

service quality standards on assurance dimension. The P-values against the four

items of assurance dimension in the case of public insurers depicts a significant

223

gap between the perceptions and expectations of the customers of these

companies. The P-value against the item called "employees and agents give

accurate information about the products and services" in the case of public

insurers reveals an insignificant gap between the perceptions and expectations

of customers. The P-values against the four items out of five under assurance

dimension in the case of private insurers depict that there is significant gap

between the perceptions and expectations of customers. The P-value for the

item called "employees and agents are courteous with customers" under

assurance dimension, in the case of private insurers implies that there is

insignificant gap between perceptions and expectations of the customers. So,

the analysis reveals that public and private insurers must improve all those

items under assurance dimension where the gap between (P-E) is significant.

Empathy

Table 7.12


Regarding Empathy Dimension

Empathy Public Sector Private Sector

Statements P

mean

E

mean

Gap

(P-E)

t-

value

p-

value

P

mean

E

mean

Gap

(P-E)

t-

value

p-

value

Customer's individual

attention. 3.49 3.93 -0.43 -3.9 0.000 3.60 3.87 -0.27 -3.22 0.002

Operating hours

convenient to all their customers.

3.64 4.04 -0.40 -4.4 0.000 3.85 4.00 -0.15 -1.77 0.078

Employees and agents

who give customer

personal attention.

3.63 3.93 -0.29 -2.6 0.010 3.78 3.89 -0.11 -1.37 0.172

The customers' best

interests at heart. 3.41 3.8 -0.39 -3.5 0.000 3.54 3.78 -0.24 -2.94 0.004

Understand the specific

needs of their customers. 3.50 3.93 -0.43 -3.8 0.000 3.76 3.84 -0.08 -1.05 0.296

Welcome complaints and

criticism and respond

positively.

3.48 3.88 -0.41 -3.7 0.000 3.66 3.98 -0.32 -3.95 0.000

Organise consumer

awareness programmes

under CRM.

3.59 3.96 -0.37 -4.1 0.000 3.75 4.02 -0.27 -3.48 0.001

Commit to ethics and

promote ethical

behaviour.

3.51 3.89 -0.38 -3.3 0.000 3.77 3.81 -0.04 -0.53 0.594

The data regarding the perceptions and expectations of customers from

both the public and private sector general insurance companies for all the eight

items under empathy dimension is presented in Table 7.12. The results reveal

224

that the mean scores against all the eight items under empathy dimension of

expectations are higher than those of the perceptions which means that both the

general insurers are unable to meet the expectations of their customers. The P-

values for the gap between the perceptions and expectations of all eight items

of the public insurers indicate that there is a significant gap between

perceptions and expectations of the customers. It speaks about their poor

service quality standard in all the eight items under empathy dimension in the

case of public insurers. The P-values of four items, namely, customer's

individual attention, customers' best interests at heart, welcome complaints, and

organizing consumer awareness programmes under CRM in the case of private

insurers have shown a significant gap between P & E which speaks about the

poor service quality standard on these items under empathy dimension which

need to be improved. However, the P-values of other four items under empathy

dimension, namely, convenient operating hours, employees and agents give

personal attention, understand the specific needs of customers and ethical

behaviour of the private insurers have shown insignificant gap between P & E.

Product Availability

Table 7.13


Regarding Product Availability Dimension

Product Availability Public Sector Private Sector

Statements P

mean

E

mean

Gap

(P-E)

t-

value

p-

value

P

mean

E

mean

Gap

(P-E)

t-

value

p-

value

Products and Services

of utmost quality. 3.90 4.15 -0.25 -2.4 0.02 4.03 4.12 -0.09 -1.16 0.247

Diversified Products

and Policies. 3.75 4.07 -0.32 -3.3 0.00 3.87 4.08 -0.22 -3.00 0.003

Competitive price of

their products and

services.

3.78 4.14 -0.36 -3.5 0.00 3.74 4.11 -0.37 -4.86 0.000

Customers assured of highest product/services

through appropriate

guarantees.

3.76 4.06 -0.30 -2.9 0.01 3.75 4.11 -0.36 -3.82 0.000

Differentiate adequately

their products and

services.

3.78 4.00 -0.23 -2.1 0.04 3.87 3.98 -0.11 -1.35 0.179

225

Table 7.13 exhibits the mean values, gap (P-E), t-values and P-values of

customers' perceptions and expectations regarding five items under product

availability dimension of both the public and private sector general insurance

companies. The companies from both the sectors have shown negative

SERVQUAL scores against all the five items of product availability dimension.

However, the private sector companies have exhibited lesser negative values

which indicates lesser gap between perceptions and expectations of their

customers. The P-values of the gap (P-E) in the case of public insurers

regarding all the five items under product availability dimension have shown a

significant gap between perceptions and expectations of their customers. These

companies need to bridge this gap. The P-values in the case of private sector

companies against the items called product and services of utmost quality, and

differentiate adequately their products and services have shown an insignificant

gap on these items. The results indicate that the private insurers need to

emphasize on improving quality of other three attributes of product availability

dimension, while the public insurers need to improve quality on all the five

items of product availability dimension.

Product Convenience

Table 7.14


Regarding Product Convenience Dimension

Product Convenience Public Sector Private Sector

Statements P

mean

E

mean

Gap

(P-E)

t-

value

p-

value

P

mean

E

mean

Gap

(P-E)

t-

value

p-

value

Contract of insurance

policies with clear and

transparent terms.

3.63 4.16 -0.53 -5.0 0.000 3.85 4.32 -0.47 -5.54 0.000

Settle customers' claims

without any delay. 3.58 4.18 -0.60 -4.9 0.000 3.78 4.19 -0.41 -4.63 0.000

Formalities for taking a

policy of the company

are simple.

3.65 3.98 -0.33 -3.3 0.000 3.69 3.86 -0.17 -1.63 0.106

Table 7.14 displays the data regarding customers' perceptions and

expectations on three items under product convenience dimension in both the

public and private sector general insurance companies. It is evident from the

table that in both the sectors SERVQUAL scores on all the items have been

226

negative but the public sector has higher negative value than the private sector

which implies that the service provided by the public sector is of poor quality

than the private sector. The P- value shows that the gap between the

perceptions and expectations of the public insurers regarding all the three

attributes is significant, whereas in the case of private insurers it is significant

in the first two items only. The gap of "formalities for taking a policy" item of

the private insurers is insignificant.

The study found that customers are satisfied to have an insurance policy

from the private sector general insurance companies due to lesser and simple

formalities. An attempt has been made to examine the inconsistencies between

customers‟ expectations and experiences with services of the insurers.

Inconsistencies in expectations and experiences may have an adverse effect on

the evaluation of service performance. Once inconsistencies have been

identified, strategies and tactics for achieving more congruent expectations and

experiences can be initiated. Greater consistency would lead to a more positive

service encounter and enhances the likelihood that the experience will evolve

into a long-term client-provider relationship.

Further, it was found that in the case of public insurers the difference

between customers' actual perception of service quality and their expectations

was insignificant in only one out of 38 items which emphasize upon improving

service quality in all 37 items. In the case of private insurers the gap between

perception and expectation was insignificant in only 11 (eleven) out of 38 items

which implies that irrespective of their negative gap scores management should

focus on improving quality of other 26 items. The analysis brought out that the

negative gap of public insurers is more and the significant negative gap in

number of items is also higher than that of the private insurers.

227

7.6 Comparative Service Quality Analysis of the Public and Private

Sector General Insurance Companies Using SERVQUAL Model

The previous analysis of the service quality based on the gap (P-E)

analysis shows negative SERVQUAL score of both the public and private

sector general insurance companies on all the dimensions which demands

substantial improvement on those attributes where the gap is significant.

Another objective of the study is to investigate the comparative service quality

level of the public and private sector general insurance companies. No doubt,

Tables 7.8 to 7.14 reveal that the negative scores of gap (P-E) of the private

sector is lesser than that of the public sector which exhibits that the service

quality of the private sector is better as compared to the public sector on most

items of the seven dimensions. Now, an attempt has been made to examine the

significant gap between the service quality of public and private sector general

insurance companies by using t-test on the gaps (P-E) on all the items of seven

dimensions.

Tangibility

Table 7.15

Test of Significance of Sector-wise Gap Regarding Tangible Dimension

Tangibility Public Sector

Gap (P-E)

Private Sector

Gap (P-E) t-value p-value

Modern equipment and technology -0.33 -0.18 -1.368 0.172

Physical facilities visually appealing -0.43 -0.19 -2.138 0.033

Employees and agents neat in appearance -0.33 -0.19 -1.007 0.315

Materials associated with the services appealing -0.28 -0.09 -1.432 0.153

The table reveals that the difference between gap (P-E) regarding item

numbers 1, 3 and 4 under tangible dimension of the public and private sector is

insignificant. The item called "physical facilities visually appealing" shows a

significant difference between gap (P-E) of the public and private sector

general insurance companies. The analysis provides that the service quality of

the private sector is significantly higher than that of the public sector as far as

the second item is concerned.

228

Reliability

Table 7.16

Test of Significance of Sector-wise Gap Regarding Reliability Dimension

Reliability

Public

Sector

Gap (P-E)

Private

Sector

Gap (P-E)

t-

value

p-

value

Promise to do something by a certain time, they do so. -0.46 -0.48 0.139 0.890

Show sincere interest in solving customers problems -0.67 -0.38 -2.124 0.035

Perform the service at the first instance. -0.53 -0.38 -1.007 0.315

Provide their services at the time they promise to do so. -0.60 -0.43 -1.130 0.260

Error free record -0.58 -0.49 -0.643 0.520

Sound financial strength -0.26 -0.27 0.113 0.910

Goodwill -0.32 -0.06 -2.064 0.040

As is evident from the table that the service quality on two items of

reliability, namely, "show sincere interest in solving customers problems" and

"goodwill" of the private sector is significantly higher than that of the public

sector. There is no significant gap between service quality level on the other

five attributes of reliability among the private and public sector general

insurance companies.

Responsiveness

Table 7.17

Test of Significance of Sector-wise Gap Regarding

Responsiveness Dimension

Responsiveness

Public

Sector

Gap (P-E)

Private

Sector

Gap (P-E)

t-

value

p-

value

Employees and agents tell customers exactly when services

performed. -0.33 -0.22

-

0.820 0.413

Employees and agents give prompt services to customers. -0.49 -0.24 -

1.927 0.055

Employees and agents willing to help customers. -0.38 -0.19 -

1.540 0.125

Employees and agents never busy to respond to customers'

requests. -0.33 -0.18

-

1.012 0.312

Employees and agents constantly communicate with

customers. -0.33 0.22

-

4.109 0.000

Method of communication suits the needs of customers. -0.38 -0.32 -

0.501 0.617

Table 7.17 highlights the variation in comparative service quality level

of the public and private sector general insurance companies. The results

indicated that the service quality of the private sector general insurance

companies on the item "employees and agents constantly communicate with

229

customers" is significantly better than that of the public sector. There is no

significant gap between the service quality level of both the public and private

sector companies on the other five items of responsiveness dimension under

study.

Assurance

Table 7.18

Test of Significance of Sector-wise Gap Regarding Assurance Dimension

Assurance

Public

Sector

Gap (P-E)

Private

Sector

Gap (P-E)

t-

value

p-

value

The behaviour of employees and agents instils

confidence in customers. -0.38 -0.23

-

1.131 0.259

Customers feel that their transactions are safe. -0.39 -0.37 -

0.192 0.848

Employees and agents are courteous with customers. -0.33 -0.03 -

2.278 0.023

Employees and agents have knowledge to render

professional service to customers. -0.38 -0.36

-

0.149 0.881

Employees and agents give accurate presentation of

products and services. -0.16 -0.22 0.462 0.645

The analysis of the table reveals that the service quality of private sector

on the items called "employees and agents are courteous with customers" is

significantly higher than that of the public sector. There is no significant gap

between the service quality level of the public and private sector general

insurance companies on the other four items of assurance dimension.

Empathy

Table 7.19

Test of Significance of Sector-wise Gap Regarding Empathy Dimension

Empathy

Public

Sector

Gap (P-E)

Private

Sector

Gap (P-E)

t-

value p-value

Customers' individual attention. -0.43 -0.272 -1.170 0.243

Operating hours convenient to all their customers. -0.40 -0.150 -1.958 0.049

Employees and agents who give customer personal

attention. -0.29 -0.111 -1.331 0.184

The customers' best interests at heart. -0.39 -0.239 -1.126 0.261

Understand the specific needs of their customers. -0.43 -0.083 -2.570 0.011

Welcome complaints and criticism and respond positively.

-0.41 -0.317 -0.683 0.495

Organize consumer awareness programmes under

CRM. -0.37 -0.272 -0.786 0.432

Commit to ethics and promote ethical behaviour. -0.38 -0.039 -2.655 0.008

230

As is evident from the table that the service quality of the private sector

general insurance companies on three items under empathy dimension, namely,

operating hours convenient to all their customers, understand the specific needs

of their customers, and commit to ethics and promote ethical behaviour is

significantly higher than that of the public sector general insurance companies.

There is no significant gap between the public and private sector general

insurance companies regarding other five attributes under empathy dimension

of service quality.


Table 7.20

Test of Significance of Sector-wise Gap Regarding Product

Availability Dimension


Public

Sector

Gap (P-E)

Private

Sector

Gap (P-E)

t-value p-

value

Products and services of utmost quality. -0.25 -0.089 -1.270 0.205

Diversified products and policies. -0.32 -0.217 -0.845 0.399

Competitive price of their products and

services. -0.36 -0.367 0.067 0.947

Customers assured of highest product/services

through appropriate guarantees. -0.30 -0.361 0.424 0.672

Differentiate adequately their products and

services. -0.23 -0.106 -0.927 0.354

Table 7.20 shows that there is no significant difference between service

quality level of the public and private sector general insurance companies on all

the five attributes under product availability dimension.

Product Convenience

Table 7.21

Test of Significance of Sector-wise Gap Regarding Product

Convenience Dimension

Product Convenience

Public

Sector

Gap (P-

E)

Private

Sector

Gap (P-E)

t-

value

p-

value

Contract of insurance policies with clear and transparent

terms. -0.53 -0.47 -0.492 0.623

Settle customers' claims without any delay. -0.60 -0.41 -1.278 0.202

Formalities for taking a policy of the company are simple.

-0.33 -0.17 -1.112 0.267

231

Table 7.21 reveals that there is no significant difference between service

quality level of the public and private sector general insurance companies on all

the three dimensions under product convenience dimension.

The analysis reveals that the service quality of the private sector general

insurance companies on 8 out of 38 items is significantly higher than that of the

public sector companies. The service quality of the public and private sector is

insignificantly different regarding the other thirty items. The SERVQUAL

score of negative gap of the private sector is higher only in four items out of

thirty-eight than the public sector, whereas negative the gap of public sector is

higher than the private sector in thirty-four out of thirty-eight items. Therefore,

the study accepted the hypothesis that the service quality of the private sector is

higher than that of public sector general insurance companies.

7.7. Customers' Perceptions Towards Overall Service Quality,

Customer Satisfaction and Purchase Intention of General Insurance

Industry in India

Favourable perceptions lead to a favourable buying decision. These

reflect the intention for buying a product or service. The perception of a

customer towards any product or service is the vital influence on buying

behaviour. The target of a company, in attracting its customers in view of

capturing potential markets and meeting the competition, is to create customers'

favourable perception. Like any other business, general insurance companies

are also trying to capture high market share. Creating favourable customers'

perceptions towards the organization means gaining more business. The main

focus of this chapter is to examine customers perceptions towards the overall

service quality, customer satisfaction and purchase intention behaviour of the

customers of both the public and private sector general insurance companies.

On the basis of the problem and the variables used, the following five null and

alternative hypotheses are to be tested:

Ho1 XOS=YOS Ha1 XOS=YOS

Ho2 XCS=YCS Ha2 XCS=YCS

Ho3 Xag=Yag Ha3 Xag=Yag

232

Ho4 XRC=YRC Ha4 XRC=YRC

Ho5 XCh=YCh Ha5 XCh=YCh

Where x and y denote the customers' perceptions on public and private

insurance companies respectively and OS=overall service quality of the

company, CS=customer satisfaction, ag = use this facility again.

Rc=Recommened this company to a friend.

Ch=make the same choice.

Table 7.22

Respondents' Perception Regarding Overall Service Quality

Perception Public Sector Private Sector

Frequency Per cent Frequency Per cent

Low Quality 13 10.8 12 6.7

Average 60 50.0 81 45.0

High Quality 38 31.7 65 36.1

Extremely High Quality 9 7.5 22 12.2

Total 120 100.0 180 100.0

Table 7.22 shows that 39.2% customers have favourably perceived the

overall service quality of the public sector general insurance companies of

whom 7.5% customers ranked extremely high quality, and 31.7% ranked high

quality regarding the overall service quality of the public insurers. Half of the

customers, i.e., 50% ranked average and 10.8% ranked low quality regarding

the overall service quality perception. On the other hand, 48.3% customers

favourably perceived the overall service quality of the private sector general

insurance companies of whom 12.2% ranked extremely high quality and 36.1%

ranked high quality regarding the overall service quality perception. However,

45% customers ranked average and 6.7% customers ranked low quality

regarding the overall service quality perception of the private sector general

insurance companies. Mean values of customers' perceptions towards overall

service quality of the public and private insurers are 3.36 and 3.54 respectively

which lie between average and high quality categories.

233

Customers' Satisfaction Measure

Table 7.23

Respondents' Perception Regarding Customers' Satisfaction



Dissatisfied 11 9.2 12 6.7

Average 40 33.3 50 27.8

Satisfied 58 48.3 95 52.7

Highly Satisfied 11 9.2 23 12.8

Total 120 100.0 180 100.0

Table 7.23 shows that 57.5% respondents have favourably perceived the

customers' satisfaction of the public sector general insurance companies of

whom 9.2% are highly satisfied and 48.3% satisfied. As many as 33.3%

respondents ranked average and 9.2% ranked dissatisfied regarding the

customer satisfaction perception. On the other hand, 65.5% customers

favourably perceived the customers' satisfaction of the private sector general

insurance companies of whom 12.8% ranked highly satisfied, 52.7% ranked

satisfied, 27.8% ranked average and 6.7% ranked dissatisfied regarding the

customers' satisfaction. Mean values of customers' perceptions towards

customer satisfaction of the public and private insurers are 3.58 and 3.72

respectively which fall between average and satisfied categories.

Purchase Intention Measures

Table 7.24

Respondents Perception Regarding Purchase Intention Measures

Perception Again use this facility Recommend Again make same choice

Public

Sector

Private

Sector

Public

Sector

Private

Sector

Public Sector Private

Sector

Very Low - 2

(1.1)

- - - -

Low 7

(5.8)

19

(10.6)

10

(8.3)

15

(8.3)

12

(10.0)

16

(8.9)

Average 61

(50.9)

83

(46.1)

50

(41.7)

72

(40.0)

60

(50.0)

70

(38.9)

High 40

(33.3)

58

(32.2)

45

(37.5)

66

(36.7)

36

(30.0)

81

(45.0)

Extremely

High

12

(10.0)

18

(10.0)

15

(12.5)

27

(15.0)

12

(10.0)

13

(7.2)

Total 120

(100.0)

180

(100.0)

120

(100.0)

180

(100.0)

120

(100.0)

180

(100.0)

Note: The figures given in parentheses indicate the percentages.

234


probability to use this facility - services again of the public sector general

insurance companies of whom 10% ranked probability very high, 33.3%

ranked high, 50.9% ranked average and 5.8% ranked low. On the other hand,

42.2% customers have favourably perceived regarding the probability to use

this facility - services again of the private sector general insurance companies

of whom 10% ranked probability very high, 32.2% high, 46.1% ranked

average, 10.6% ranked low and 1.1% ranked very low. Mean values of

customers' perceptions towards again use this facility services of the public and

private insurers are 3.48 and 3.39 respectively which lie between average and

high categories. It shows that half of the customers, i.e., 50% have favourably

perceived to recommend this company to a friend as far as the public sector

general insurance companies are concerned, of whom 12.5% per cent ranked

very high, 37.5% ranked high, 41.7% ranked average and 8.3% ranked low

regarding the perception of recommending this company to a friend. On the

other hand, 51.7% customers have favourably perceived to recommend to a

friend the private sector general insurance companies, of whom 15% ranked

very high, 36.7% ranked high, 40% ranked average and 8.3% ranked low

regarding the perception of recommending this company to a friend. Mean

values of customers' perceptions towards 'recommended this company to a

friend' of the public sector and private sector general insurance companies are

3.54 and 3.58 respectively which lie between average and high categories. It

shows that 40% customers have favourably perceived to 'again make the same

choice' of the public sector general insurance companies, of whom 10% ranked

very high, 30% ranked high, 50% ranked average and 10% ranked low. On the

other hand, 52.2% customers have favourably perceived to again make the

same choice of the private sector general insurance companies of whom 7.2%

ranked very high, 45% ranked high, 38.9% ranked average and 8.9% ranked

low regarding the perception of 'again make the same choice' of the private

sector general insurance companies. Mean values of customers' perceptions

235

towards 'again make the same choice' of the public and private insurers are 3.40

and 3.51 respectively, which fall between average and high categories.

Table 7.25

Comparative Sector-wise Analysis of Overall Service Quality, Customers’

Satisfaction and Purchase Intention Measure

S. No. Perception Public

Sector

Mean

Private

Sector

Mean

t-value d.f. Sig.

(2-tailed)

1. Overall service quality 3.36 3.54 -1.948 298 0.520

2. Customers satisfaction 3.58 3.72 -1.547 298 0.123

3. Again use this facility-services 3.48 3.39 0.841 298 0.401

4. Recommend to a friend 3.54 3.58 -0.424 298 0.672

5. Again make the same choice 3.40 3.51 -1.153 298 0.250

It is evident from the table that all the five null hypotheses stand

accepted, i.e.,

Ho1 : There is no significant gap of the overall service quality between

the public and private sector general insurance companies.

Ho2 : There is no significant gap of customer satisfaction between the

public and private sector general insurance companies.

Ho3 : There is no significant gap of the probability to use these facilities

- services again between the public and private sector general insurance

companies.

Ho4 : There is no significant gap of the perception to 'recommend this

company to a friend' between the public and private sector general insurance

companies.

Ho5 : There is no significant gap of the perception of 'again make the

same choice' between the public and private sector general insurance

companies.

7.8 Relationship Between the Service Quality, Customer Satisfaction,

Purchase Intention and Customer Retention

A service organization‟s long-term success in a market is essentially

determined by its ability to expand and maintain a large and loyal customer

base. Despite the fact that customer loyalty is essential for business survival,

236

the relationship between perceived service quality and customer loyalty

remained relatively underdeveloped. Customer loyalty has been generally

described as occurring when customers repeatedly purchase a good or service

over time and hold favourable attitude towards a good or service or towards the

company supplying the good or service. Loyal customers are less likely to

switch to a competitor due to a given price inducement, and these customers

make more purchases compared to less loyal customers. Loyalty is determined

by combination of repeat patronage behaviour and level of attachment. These

overall service quality would be employed to measure their relation to

customer loyalty by applying them on various customer loyalty items. The

various customer loyalty items that should be considered are: customers say

positive things about the service firm to other people, whether they recommend

the service firm to someone who seeks advice, encourage friends and relatives

to use the services of that particular firm, consider the service firm to make the

same choice in the next few years switch to a competitor if there are problems

with the service and shifted to another company. To examine the relationship

between the service quality and the customer satisfaction, customer satisfaction

and customers' purchase intention and service quality and customers' purchase

intention, correlation and regression have been used.

Relationship Between Overall Service Quality and Customer Satisfaction:

Table 7.26

Correlation Matrix of Public Sector General Insurance Companies

Overall Service Quality Satisfaction

Overall Service Quality 1

Satisfaction 0.680** 1

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

Table 7.27

Correlation Matrix of Private Sector General Insurance Companies

Overall Service Quality Satisfaction

Overall Service

Quality

1

Satisfaction .670** 1

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

237

Table 7.28

Regression Analysis of General Insurance Companies Between Overall

Service Quality and Customer Satisfaction

Sector R R-

Square

Adjusted

R- Square

Std.

Error of

the

Estimate

Change Statistics

R-

Square

Change

F-

Change d.f.1 d.f.2

Sig. F-

Change

Public

Sector 0.680(a) 0.463 0.458 0.578 0.463 101.547 1 118 0.00

Private

Sector 0.670(a) 0.450 0.446 0.574 0.450 145.381 1 178 0.00

1. Constant : overall service quality

2. Dependent variable: customer satisfaction

Tables 7.26 to 7.28 show that there is the strongest association between

the overall service quality and customer satisfaction of both the public and

private sector general insurance companies. The correlation coefficients of the

public and private insurers between overall service quality and customers'

satisfaction are 0.680 and 0.670 respectively which indicates significant

positive correlation. As reported in Table 7.28, the values of adjusted R2 in the

case of both public and private sector are 0.458 and 0.446 respectively which

show a strong relationship between the two constructs. The results indicated

that the regression model explained 45.8% and 44.6% variation in the customer

satisfaction due to service quality of the public and private sector companies

respectively. The analysis provides that the overall service quality level has a

strong effect on customer satisfaction.

Relationship Between Overall Service Quality and Purchase Intention

Table 7.29


Overall Service

Quality

Purchase

Intention


Purchase Intention 0.663** 1 ** Correlation is significant at the 0.01 level (2-tailed).

238

Table 7.30


Overall Service Quality Purchase

Intention


Purchase Intention 0.631** 1 ** Correlation is significant at the 0.01 level (2-tailed).

Table 7.31

Regression Analysis of General Insurance Companies Between Overall

Service Quality and Purchase Intention Measures

Sector Model R R-

Square

Adjusted

R-

Square

Std.

Error of

the

Estimate

Change Statistics

R-

Square

Change

F-

Change d.f.1 d.f.2

Sig. F-

Change

Public

Sector 1 0.663(a) 0.440 0.439 0.594 0.440 281.506 1 358 0.00

Private

Sector 1 0.631(a) 0.398 0.397 0.637 0.398 356.125 1 538 0.00

1. Constant: Overall service quality

2. Dependent variable: Purchase intention measures

As is evident from the table that there is a strong association between the

overall service quality and purchase intention behaviour of the customers of

both the public and private sector general insurance companies. The values of

correlation coefficients of the public and private insurers between overall

service quality and purchase intention are 0.663 and 0.631 respectively which

indicates significant positive correlation. As reported in the table, the values of

adjusted R2, i.e., 0.439 and 0.397 in the case of public and private sector

general insurance companies respectively show a strong relationship between

the two constructs. The results revealed that the regression model explained

43.9% and 39.7% variation in the purchase intention due to service quality of

the public and private sectors respectively. The analysis provides that the

overall service quality has a strong effect on purchase intention. In the present

study, three items which are similar to those commonly utilized in the service

literature to measure purchase intention have been used to operationalize the

purchase intentions construct (Cronin and Taylor, 1992; Babakus and Boller,

239

1992). The study further analysed the effect of overall service quality on all the

three measures of purchase intention individually.

Table 7.32


Between Overall Service Quality and Purchase Intention

Item Overall Service

Quality

Purchase

Again

Recommend Again

Choice

Overall service

quality

1

Purchase again 0.668** 1

Recommend 0.684** 0.749** 1

Again choice 0.645** 0.709** 0.677** 1 ** Correlation is significant at the 0.01 level (2-tailed).

Table 7.33


Between Overall Service Quality and Purchase Intention Measure

Overall service

Quality

Purchase

again

Recommend Again

Choice

Overall service

quality

1


Recommend 0.637** 0.706** 1

Again choice 0.659** 0.730** 0.671** 1 ** Correlation is significant at the 0.01 level (2-tailed).

Tables 7.32 and 7.33 show that there is a significant correlation between

overall service quality with 'again use this facility', 'recommend to a friend' and

'again make the same choice' of both the public and private sector general


Table 7.34

Regression Analysis Between Overall Service Quality and Again Use This

Facility Services

Sector R R-

Square

Adjusted

R-

Square

Std. Error

of the

Estimate

Change Statistics

R-

Square

Change

F-

Change d.f.1 d.f.2

Sig. F-

Change

Public

Sector

0.668

(a) 0.446 0.441 0.565 0.446 95.027 1 118 0.00

Private

Sector

0.611

(a) 0.374 0.370 0.674 0.374 106.314 1 178 0.00

1. Constant: overall service quality 2. Dependent variable: Again use this Facility services

240

Table 7.34 describes that the variation in probability of a customer to

'again use this facility' of the public and private sector is 44.1% and 37%

respectively due to the overall service quality which is statistically significant.

So, it is evident from the analysis that overall service quality has strong impact

on 'again use this facility' service of both the public and private sector

respectively.

Table 7.35

Regression Analysis Between Overall Service Quality and Recommend

This Company to a Friend

Sector R

R-

Square

Adjuste

d R-

Square

Std. Error

of the

Estimate

Change Statistics

R-

Square

Change

F-

Change d.f.1 d.f.2

Sig. F-

Change

Public

Sector

0.684

(a) 0.468 0.464 0.600 0.468 103.829 1 118 0.00

Private

Sector

0.637

(a) 0.405 0.402 0.653 0.405 121.408 1 178 0.00

1. Constant : overall service quality

2. Dependent variable: Recommend this company to a friend.

Table 7.35 shows that the variation in probability of a customer to

'recommend this company to a friend' of the public and private sector is 46.4%

and 40.2% respectively due to the overall service quality which is statistically

significant. So it is evident from the results that overall service quality has

strong impact on 'recommend this company to a friend' of both the public and

private sector respectively.

Table 7.36

Regression Analysis Between Overall Service Quality and Again Make the

Same Choice

Sector R R-

Square

Adjusted

R- Square

Std.

Error of

the

Estimate

Change Statistics

R-

Square

Change

F-

Change d.f.1 d.f.2

Sig. F-

Change

Public

Sector 0.645(a) 0.416 0.411 0.617 0.416 83.902 1 118 0.00

Private

Sector 0.659(a) 0.434 0.431 0.572 0.434 136.325 1 178 0.00

1. Constant: Overall service quality.

2. Dependent variable: Again make the same choice.

Table reveals that the variation in 'again make the same choice' measure

of the public and private sector general insurance companies is 41.1% and

241

43.1% due to overall service quality. The analysis provides that the overall

service quality has a significant effect on all the three measures of purchase

intention.

Relation Between Customers' Satisfaction and Purchase Intention

It has been found earlier that customer satisfaction has potential

influence on consumer purchase intentions and customer retention (Anderson

and Fornell, 1994). So, the consumer satisfaction has also been the subject of

much attention in the marketing literature. Satisfaction is described as "an

evaluation of an emotion" (Brady et el., 2002) which suggests that the

measurement of the satisfaction construct should be related to whether a

consumer feels that a good or service provides positive utility. In the present

scenario, both the public and private insurers want to enhance the consumer

satisfaction which ultimately increases the purchasing behaviour towards their

company which, in turn, resulted into increase of their market share and

profitability.

Table 7.37


Customer

Satisfaction

Purchase

Again

Recommend Again Choice

Customer

satisfaction

1


Recommend 0.610** 0.749** 1

Again choice 0.538** 0.709** 0.677** 1

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

Table 7.37 shows that all the three variables of purchase intention, viz.

'again use the same facility', 'recommend to a friend' and 'again make the same

choice' have a significant and positive relationship with customer satisfaction

of the public insurers and the coefficients for these variables are 0.612, 0.610

and 0.538 respectively.

242

Table 7.38


Customer

Satisfaction

Purchase

Again

Recommend Again Choice

Customer

satisfaction

1


Recommend 0.598** 0.706** 1

Again choice 0.523** 0.730** 0.671** 1 **Correlation is significant at the 0.01 level (2-tailed)

Table 7.38 presents the correlation matrix of the three purchase intention

measures with customer satisfaction of the private sector general insurance

companies. The results indicated that all the three variables have a significant

and positive correlation with customer satisfaction and the co-efficient of these

three variables, namely, 'again use same facility', 'recommend to a friend' and

'again make the some choice' are 0.624, 0.598 and 0.523 respectively.

Table 7.39

Sector-wise Regression Analysis Between Customer Satisfaction and Again

Use the Same Facility

Sector R R-

Square

Adjusted

R-Square

Std. Error

of the

Estimate

Change Statistics

R-

Square

Change

F-

Change d.f.1 d.f.2

Sig. F-

Change

Public

Sector 0.612(a) 0.375 0.370 0.600 0.375 70.841 1 118 0.00

Private

Sector 0.624(a) 0.389 0.386 0.665 0.389 113.308 1 178 0.00

1. Constant: customer satisfaction.

2. Dependent variable: Again use the same facility.

Table 7.39 reveals that the values of adjusted R2 of the public and

private sector general insurance companies are 0.370 and 0.386 respectively

which show a strong relationship between the two constructs. The regression

model explained statistically significant variation of 37% and 38.6% in the

public and private sector general insurance companies' dependent variable

called 'again use the same facility' which can be mainly ascribed to customer

satisfaction.

243

Table 7.40

Sector-Wise Regression Analysis Between Customer Satisfaction and

Recommend this Company to a Friend

Sector R R-

Square

Adjusted

R-Square

Std. Error

of the

Estimate

Change Statistics

R-

Square

Change

F-

Change d.f.1 d.f.2

Sig. F-

Change

Public

Sector

0.610

(a) 0.372 0.366 0.652 0.372 69.766 1 118 0.00

Private

Sector

0.598

(a) 0.357 0.354 0.679 0.357 99.007 1 178 0.00

1. Constant: customer satisfaction

2. Dependent variable: Recommend this company to a friend

The adjusted R2 values of 0.366 and 0.354 against the public and private

sector respectively given in Table 7.40 reveal that the dependent variable called

'recommend this company to a friend' has established a strong relationship with

'customer satisfaction' which is a second measure of purchase intention.

Table 7.41

Sector-wise Regression Analysis Between Customer Satisfaction and Again

Make the Same Choice

Sector R R-

Square

Adjusted

R-Square

Std. Error

of the

Estimate

Change Statistics

R-

Square

Change

F-

Change d.f.1 d.f.2

Sig. F-

Change

Public

Sector 0.538(a) 0.290 0.284 0.680 0.290 48.158 1 118 0.00

Private

Sector 0.523(a) 0.273 0.269 0.648 0.273 67.004 1 178 0.00

1. Constant: customer satisfaction

2. Dependent variable: Again make the same choice.

Table 7.41 explains the variation in the third measure of purchase

intention i.e. 'again make the same choice' due to customer satisfaction. As per

regression analysis, the adjusted R2 values of 0.284 and 0.269 against the

public and private sectors respectively given in Table 7.41 explain that the

dependent variable called 'again make the same choice' has established a

significant relationship with 'customer satisfaction' which is a third measure of

purchase intention. The variation of 28.4% and 26.9% on this purchase

244

intention measure due to customer satisfaction also shows a strong effect of

customer satisfaction on purchase intention.

The above analysis indicates that overall service quality has a

statistically significant effect on both customer satisfaction and purchase

intention. The customer satisfaction has also a statistically significant effect on

purchase intention. It has also been found that overall service quality has more

effect on purchase intention than the customer satisfaction. Given the influence

of service quality on customer loyalty, it is important for the service managers

to focus their attention on developing positive feelings in customers towards

the service firm. An unsatisfactory service encounter can obviously lead to a

lost sale and potentially to diminish customer loyalty. Thus, management can

play a crucial role in enhancing contact employees‟ service delivery process by

setting high performance standards, enabling contact employees to meet these

standards, and appraising and rewarding them accordingly.

7.9 Comparative Analysis of Customers' Retention in the Public and

Private Sector General Insurance Companies

It is believed that customer retention is a more efficient and cost

effective mechanism for revenue and profitability growth (Saini and Arora,

2008). So, in this competitive era, every general insurance company tries to

retain all its customers by providing superior service quality. However, it is

seen that some customers shift from one general insurance company to another.

In this chapter, an attempt has been made to analyse the reasons which

contribute towards shifting of customers from one general insurance company

to another.

Table 7.42

Sector-wise Customer Shifting from one Insurance Company to another

Public Sector Private Sector


Yes 24 20.0 32 17.8

No 96 80.0 148 82.2

Total 120 100.0 180 100.0

245

Table 7.42 depicts that 24 (20%) customers belonging to the public

sector general insurance companies and 32 (17.8%) customers from the private

sector companies have shifted to other companies.

Table 7.43

Sector-wise Distribution of Customers Regarding Reasons of Shifting to

Other Insurance Companies

Table 7.43 highlights the reasons for shifting of customers from one

general insurance company to another. Among the public sector companies, as

many as 9 customers have shifted the company due to delay in claim settlement

followed by 7 customers due to lesser amount of claim settlement, 5 customers

due to higher price of policy, 2 customers due to unsuitablity of product, and 1

customer due to the behaviour of employees. However, among the private

sector companies as many as 15 customers have shifted due to delay in claim

settlement, followed by 7 customers due to higher price of policy, 5 customers

due to lesser amount of claim settlement, etc. It is evident from the table that

most of the customers from both the public and private sector companies

shifted from one company to another due to delay in their claim settlement. So,

to improve customers' retention and loyalty these companies need to focus

more on improving procedures and formalities of claim settlement so that it can

be settled as early as possible. Further, the amount of claim settlement needs to

be paid reasonably.

Reasons For Shifting


Frequency

Per

cent Frequency Per cent

Customers not Shifted 96 80.0 148 82.2

Delay in Claim Settlement 9 7.5 15 8.3

Lesser Amount of Claim Settlement 7 5.8 5 2.8

Higher Price of Policy 5 4.2 7 3.9

Unsuitability of Product 2 1.7 1 0.6

Behaviour of Employees 1 0.8 3 1.7

Any Other 0 0.0 1 0.6

Total 120 100.0 180 100.0

246

7.10 Customers' Perception Regarding Claim Settlement by the General

Insurance Companies

In today‟s customer-focused market place, service is a critical driver of

customer retention and profitable growth. A key to ensuring the loyalty of

customers lies in creating a predictably positive experience for them. By

delivering on their service promise successfully at every opportunity, effective

organizations go beyond “customer satisfaction” and ultimately earn customer

loyalty. Since insurance is a contractual promise to indemnify the insured when

a loss occurs, how fast a claim is settled is an important component of the

insurance product. It has also been established in many previous studies that

majority of the customers shift to other general insurance companies mainly

because of delay in claim payment by their companies. In this respect,

respondents‟ perception has been analyzed on various aspects, such as type of

availing claim, time taken to settle the claim, role played by employees during

the claim settlement, claim settlement formalities, influence and source used to

settle the claim, and customers' perception regarding overall service quality of

both who availed claim and those who did not avail claim.

Table 7.44

Type of Availing Claim

Type of Claim



Not Availed any Claim 83 69.2 159 88.3

Fire 1 0.8 - -

Motor 26 21.7 20 11.1

Health 10 8.3 1 0.6

Total 120 100.0 180 100.0

Firstly, the respondents were asked whether they have availed any claim

or tried to avail claim from general insurance company or not. The sector-wise

responses of the respondents in this regard have been presented in Table 7.44.

It has been observed that 37 (30.8%) customers of the public sector and 21

(11.7%) customers of the private sector have availed claim from their

respective companies. The proportion of customers availing claim is

247

comparatively higher in the case of public sector than the private sector general

insurance companies. The table also deals with the type of claim availed by

customers of both the public and private sector general insurance companies. It

has been seen that majority of the customers, i.e., 26 from the public sector

companies availed claim under motor insurance followed by 10 customers

under health insurance and 1 customer under fire insurance policy. Similarly,

majority of the customers, i.e., 20 from the private sector companies availed

claim under motor insurance and 1 under health. It has been found that

maximum customers availed claim under motor insurance policy. The claim

ratio of this portfolio is also the highest in both the sectors.

Table 7.45

Respondents' Perception Regarding Claim Settlement

Perception

Time Taken to Settle the

Claim

Employees' Role in Claim

Settlement

Claim Settlement Formalities

Public

Sector

Private

Sector

Public Sector Private

Sector


Not Availed

any Claim

83 69.2% 159 88.3% 83 69.2% 159 88.3% 83 69.2% 159 88.3%

Highly

Dissatisfactory

2 1.7% - - - - - - 2 1.7% - -

Dissatisfactory 4 3.3% - - 2 1.7% - - 3 2.5% - -

Neutral 13 10.8% - - 7 5.8% 3 1.7% 15 12.5% 6 3.3%

Satisfactory 12 10% 13 7.2% 24 20% 15 8.3% 14 11.7% 13 7.2%

Highly

Satisfactory

6 5% 8% 4.4% 4 3.3% 3 1.7% 3 2.5% 2 1.1%

Total 120 100% 180 100% 120 100% 180 100% 120 100% 180 100%

Table 7.45 carries the data showing sector-wise responses of

respondents regarding claim settlement. It is evident from the table that

majority of the customers (13) from the public sector are neutral followed by

12 customers who are satisfied, 6 customers are highly satisfied, 4 customers

are dissatisfied and 2 customers are very dissatisfied with the time taken to

settle the claim. Among the private sector companies, majority of the

customers (13) are found to be satisfied followed by 8 customers who are

248

highly satisfied with the time taken to settle the claim. The mean scores of the

public and private sector companies regarding this are 3.43 and 4.38

respectively which shows that satisfaction level regarding time taken to settle

claim of the customers of the public sector lies between neutral and

satisfactory, whereas that of the private sector lies between satisfactory and

highly satisfactory. The analysis provides that the private sector general

insurance companies take lesser time to settle the claim as compared to their

counterparts and the satisfaction level of the private sector customer is higher

than that of the public sector regarding the time taken to settle the claim. The

table reveals that in the public sector majority of the customers, i.e., 24 are

satisfactory followed by 7 customers who are neutral, 4 customers are highly

satisfactory, and 2 customers are dissatisfied with regard to the role played by

employees during the claim settlement process. However, in the private sector

majority of the customers, i.e., 15 are satisfactory followed by 3 customers who

are highly satisfactory, and 3 customers are neutral. The mean scores of the

public and private sectors regarding satisfaction level in relation to the role

played by the employees during the claim settlement process are 3.81 and 4.00

respectively which indicates that the customers of the private sector are more

satisfied than the public sector regarding the role of the employees during the

claim settlement process. It has been found that the employees of the private

sector general insurance companies take keen interest to help the customers in

completing the formalities of the claim.

As reported in the table, 15 customers of the public sector are neutral, 14

are satisfied, 3 are highly satisfied, 3 are dissatisfied and 2 are highly

dissatisfied regarding claim settlement formalities. On the other hand, 13

customers of the private sector are satisfied, 6 are neutral, and 2 are highly

satisfied. The mean scores of the public and private sector customers regarding

claim settlement formalities are 3.35 and 3.81 respectively which implies that

the customers belonging to the private insurance companies are more satisfied

than the public sector companies. It has been found that the private insurers

249

have less formalities to follow while making a claim settlement, and also have

an easy and quick process to complete the formalities.

Table 7.46

Source Used to Settle the Claim by Respondents

Source



Source Not Used 105 87.5 174 96.5

Employee 6 5.0 3 1.7

Senior Officer 2 1.7 1 0.6

Agent 6 5.0 1 0.6

Politician 1 0.8 1 0.6

Total 120 100.0 180 100.0

Table 7.46 highlights the different sources used by the respondents

while settling their claim. As is evident from the table that as many as 15

customers from the public and only 6 customers from the private sector used

influence to settle their claim. It is also clear from the table that more number

of customers from the public sector used influence to settle their claim as

compared to the customers from the private sector general insurance

companies. The respondents were further asked to explain their exact source

which they used to settle their claim. The customers belonging to the public

sector reported that they mainly used employees and agents to settle their

claim. On the other hand, the customers from the private sector mainly used

employees to settle the claim.

The analysis provides that the procedure laid down by the private

sector general insurance companies for settling any claim is simple, less time

consuming and favourable to the interest of the claimants. The role of

employees is also positive in this regard. As stated earlier, the claim settlement

is the most important factor to retain a customer. It has been established in

many studies that the customers' perception regarding the overall service

quality of their company is changed when they actually avail the claim from

their company. It has been observed that the service provided by a general

insurance company at the time of taking a policy is, no doubt, of better quality

250

than that provided at the time of settling a claim. On the basis of this problem,

the following hypotheses are formulated:

1. There is no significant gap of public sector customers who avail claim

and those who do not avail claim regarding overall service quality of the

company.

2. There is no significant gap of private sector customers who availed

claim and those who do not avail claim regarding overall service quality.

3. The private sector provides better service quality than the public

sector to these customers who avail claim.

4. The private sector provides better service quality than the public

sector to those customers who do not avail claim.

Table 7.47

Sector-wise Perception of Respondents Regarding Overall Service Quality

Sector

Availed

Claim N Mean Std. Deviation

Public Sector

Yes 37 2.92 0.595

No 83 3.55 0.769

Private Sector

Yes 21 3.67 0.966

No 159 3.52 0.77

Test of Significance

Sector

t-test for Equality of Means

t d.f. Sig. (2-tailed

Public Sector -4.46 118 0

Private Sector 0.784 178 0.434

Table 7.47 analysed the perceptions of customers from both the public

and private sector general insurance companies, who availed the claim and

those who did not avail the claim regarding the overall service quality. The

results indicated that the mean values of the customers' perception of the public

insurers who availed the claim and those who did not avail the claim regarding

overall service quality are 2.92 and 3.55 respectively which indicates that the

customers of the public insurers who did not avail the claim perceived better

service quality than the customers who availed the claim. The t-test (P < .05)

also reveals that the claim significantly changes the perception of the customers

251

regarding overall service quality of the public insurers. So, the public general

insurance companies must improve their claim settlement process to enhance

overall service quality level. In the case of private insurers, the mean values of

both the customers' perception, who availed the claim and those who did not

avail the claim are 3.67 and 3.52 respectively which indicates that the

customers of the private insurers who availed the claim perceived marginal

better service quality than those customers who did not avail the claim. The t-

test (P > .05) shows that there is no significant gap between the perception of

both type of customers, who availed the claim and those who did not avail the

claim regarding overall service quality of the private insurers.

Table 7.48

Respondents' Perception Regarding Overall Service Quality

Availed

Claim Sector N Mean Std. Deviation

Yes

Public Sector 37 2.92 0.595

Private Sector 21 3.67 0.966

No

Public Sector 83 3.55 0.769

Private Sector 159 3.52 0.77


Availed

Claim

t-test for Equality of Means

t d.f. Sig. (2-tailed)

Yes -3.654 56 0.001

No 0.309 240 0.758

Table 7.48 investigates the comparative service quality of the public and

private sector general insurance companies under two different situations;

firstly, customers availing claim and secondly, customers not availing claim.

The comparative service quality analyses when customers' availed claim

showed that the private insurers provide better service quality than the public

insurers. The t-test (P < .05) indicates that the private insurers deliver

significantly better service quality than the public insurers.

252

The mean values of the service quality of the public and private insurers

when customers did not avail claim are 3.55 and 3.52 which exhibits that

public sector‟s service quality is better than the private sector. The t-test

indicates that there is no significant gap in the service quality of the public and

private insurers when the customers did not avail claim. The results suggested

that the claim settlement process of the public sector has adversely affected

their service quality level. So, the public insurers must improve their claim

settlement process to enhance service quality.

7.11 Customer Awareness and Perception Regarding Ombudsman in

General Insurance Industry

The Ombudsman system is a unique scheme as it provides cost-free and

expeditious redressal of grievances for policyholders. Although, in effect, the

Ombudsman would be offering policyholders an alternative for going to court,

the insurers saw the schemes as a kind of extension of their own internal

complaint handling arrangements (Hampton, 2003). It is aptly said,

"Consumers are now in need of weapons to fight insurers for justice and the

legal process at present is too costly for them in terms of money and time. In

terms of equity and fairness, one has to devise newer procedures to redress and

restore a little bit of power to customers to make insurers answerable to some

authority other than courts. The Ombudsman is one such institution. The

unique feature of the insurance Ombudsman scheme is that the awards and

orders of the Ombudsman are binding on the insurance companies while the

insured, if not satisfied with the award or order can approach other redressal

forums. This scheme provides a time-bound, free and independent method of

dispute resolution for the individual consumer (Gopalakrishna, 2007). This

chapter investigates the customers' awareness about availability of Ombudsman

and their perception regarding the working of Ombudsman.

253

Respondents' Perceptions Regarding Awareness and Working of

Ombudsman.

Table 7.49

Respondents Having Knowledge of Ombudsman

Chi-square value = 6.483, d.f. = 1, P- value =0 .011, not significant at 5% level of

significance.

Table 7.49 depicts that as many as 34 (28.30%) and 29 (16.10%)

customers of the public and private sector general insurance companies

respectively are aware of the Ombudsman to redress their complaints. As is

evident from the table that only a small number of customers have knowledge

regarding Ombudsman. The Chi-square test (P < .05) indicates that there is a

significant gap between the customers of both the public and private sector

general insurance companies regarding the knowledge of Ombudsman.

Table 7.50

Filing of Complaints to Ombudsman by the Respondents

Filing of

Complaint Frequency/Percentage

Sector

Total

Public

Sector

Private

Sector

Don‟t have

knowledge of

Ombudsman

Count 86 151 237

% within Sector 71.70% 83.90% 79.00%

Yes

Count 7 5 12

% within Sector 5.80% 2.80% 4.00%

No

Count 27 24 51

% within Sector 22.50% 13.30% 17.00%

Total

Count 120 180 300

% within Sector 100.00% 100.00% 100.00% Chi-square value = 6.601, d.f. =2, P- value = 0.037, not significant at 5% level of

significance.

Knowledge Frequency/Percent

Sector

Total Public

Sector

Private

Sector

Yes

Count 34 29 63

% within Sector 28.30% 16.10% 21.00%

No

Count 86 151 237

% within Sector 71.70% 83.90% 79.00%

Total

Count 120 180 300

% within Sector 100.00% 100.00% 100.00%

254

Table 7.50 investigates whether the customers of the public and private

sector general insurance companies having knowledge about Ombudsman have

ever filed a complaint to the said authority. The results reveal that 7 customers

out of 34 and 5 customers out of 29 of the public and private sectors

respectively who had knowledge about the Ombudsman filed complaint against

the insurers. It is clear from the table that only a few customers filed a

complaint to the Ombudsman. The Chi-square test results also indicate that

there is significant gap between the customers of the public and private sector

general insurance companies regarding filing of complaint to the Ombudsman.

Table 7.51

Sector-wise Details Regarding Nature of Complaints Filed by the

Respondents

Nature of Complaint Frequency/Percentage

Sector

Total

Public

Sector

Private

Sector

Do not File Complaint

Count 113 175 288

% within Sector 94.20% 97.20% 96.00%

Non-payment of Claim

Count 2 0 2

% within Sector 1.70% 0.00% 0.70%

Lesser Amount of Claim

Payment

Count 2 0 2

% within Sector 1.70% 0.00% 0.70%

Delay in Payment of

Claim

Count 3 3 6

% within Sector 2.50% 1.70% 2.00%

Wrongly stated by

Employees

Count 0 2 2

% within Sector 0.00% 1.10% 0.70%

Total

Count 120 180 300

% within Sector 100.00% 100.00% 100.00%

Table 7.51 describes the nature of complaints filed by the customers to

Ombudsman against the insurers. Among the public sector, a total of seven

customers filed complaints, out of which three customers filed complaints for

delay in payment of claim, followed by two customers each for non-payment of

claim and lesser amount of payment of claim. Among the private sector, a total

of five customers filed complaints out of which three filed complaints for delay

in payment of claim and two customers filed for wrongly stated by employees

255

and agents regarding features of product and policies. The analysis brought out

that most of the complaints filed to the Ombudsman related to claims.

Table 7.52

Time Taken to Dispose of a Complaint by Ombudsman

Chi-square value = 5.173, d.f. = 4, P- value =0.27, not significant at 5% level of significance.

Table 7.52 shows the perception of customers who filed complaint to the

Ombudsman regarding time taken to dispose it of. It is evident from the table

that majority of the customers, i.e., 5 from the public sector and 2 from the

private sector are highly satisfied with the time taken to dispose of complaints

by Ombudsman. The mean values of perception of the public and private sector

customers regarding time taken to dispose of complaints by the Ombudsman

are 4.3 and 4.0 respectively which fall in the satisfactory category of both the

public and private sector general insurance companies. The Chi-square test (P >

.05) explains that there is no significant gap between the perception of

customers from both the public and private sector general insurance companies

regarding the time taken to dispose of the complaints by the Ombudsman.

Perception

Frequency/Percentage

Sector

Total

Public

Sector

Private

Sector

Don‟t File

Complaint

Count 113 175 288

% within Sector 94.20% 97.20% 96.00%

Dissatisfactory

Count 1 0 1

% within Sector 0.80% 0.00% 0.30%

Neutral

Count 1 2 3

% within Sector 0.80% 1.10% 1.00%

Satisfactory

Count 0 1 1

% within Sector 0.00% 0.60% 0.30%

Highly

Satisfactory

Count 5 2 7

% within Sector 4.20% 1.10% 2.30%

Total

Count 120 180 300

% within Sector 100.00% 100.00% 100.00%

256

Table 7.53

Handling of Complaints by Ombudsman

Perception Frequency/Percentage

Sector

Total Public

Sector

Private

Sector

Don‟t File Complaint

Count 113 175 288

% within Sector 94.20% 97.20% 96.00%

Dissatisfactory

Count 1 0 1

% within Sector 0.80% 0.00% 0.30%

Neutral

Count 0 3 3

% within Sector 0.00% 1.70% 1.00%

Satisfactory

Count 2 0 2

% within Sector 1.70% 0.00% 0.70%

Highly satisfactory

Count 4 2 6

% within Sector 3.30% 1.10% 2.00%

Total

Count 120 180 300

% within Sector 100.00% 100.00% 100.00%

Table 7.53 carries the data showing the experience of customers

regarding handling of complaints by the Ombudsman. From the public sector, 4

customers had expressed high satisfaction, 2 customers expressed satisfaction,

and 1 customer showed dissatisfaction regarding handling of the complaints by

the Ombudsman. On the other hand, from the private sector, 2 customers

showed high satisfaction, and 3 expressed neutral views regarding handling of

complaints by the Ombudsman. The mean scores of the public and private

sector customers regarding experience of handling of complaints by the

Ombudsman are 4.3 and 3.8 respectively which indicates that public sector

customers are more satisfied than those of private sector regarding handling of

complaints by the Ombudsman.

The analysis brought out that Ombudsman provides time bound, free

and independent method of dispute resolution for the individual customers. In

India, only a limited number of customers have the knowledge regarding

Ombudsman, as majority of them were found to have never heard about

Ombudsman in the insurance sector. Among Award customers, only a few filed

complaints to Ombudsman and most of the complaints related to claims. It has

been found that the working of Ombudsman with respect to handling and time

257

taken to dispose of complaints is satisfactory. So, it is in the greater interest of

the customers that they first approach the Ombudsman for any problem during

the whole process of insurance.

7.12 Customers' Awareness Regarding Websites of General Insurance

Companies'

Initially, the internet was perceived as a medium of communication, but

now it is slowly metamorphosing into a powerful business medium. It provides

direct reach to end users, which is being exploited by the corporate to gain a

cost competitive edge (Sakkthivel, 2006). The emergence of the internet is

creating new values for both customers and companies, which has in a way

compelled insurance companies to explore their potential as a new distribution

Channel (Rao, 2006). The use of internet related services in the insurance

industry has been increasing at a rapid speed in India. The general insurance

companies in India have started their own websites to give the facility of on-

line insurance and to provide information regarding their products, prices,

policies, services, branches etc.

Table 7.54

Respondents Having Knowledge Regarding Websites of General

Insurance Companies

Knowledge Frequency/Percentage

Sector

Total

Public

Sector

Private

Sector

Yes

Count 59 88 147

% within Sector 49.20% 48.90% 49.00%

No

Count 17 43 60

% within Sector 14.20% 23.90% 20.00%

Not Aware

Count 44 49 93

% within Sector 36.70% 27.20% 31.00%

Total Count 120 180 300

% within Sector 100.00% 100.00% 100.00% Chi-square value = 5.476, d.f. =2, P- value = 0.065, not significant at 5% level of significance.

The awareness of the respondent customers was checked by way of

asking them a question whether their insurance company has a website or not.

Table 7.54 depicts sector- wise response of the respondents in this regard. The

table reveals that as many as 59 (49.2%) customers from the public sector and

88 (48.9%) from the private sector are aware about the websites of their

258

companies. As many as 17 (14.2%) and 43 (23.9%) customers from the public

and private sector insurance companies respectively have clearly stated that

their companies have no website, while rest of the respondents, i.e., 44 (36.7%)

and 49 (27.20%) from the public and private sector companies respectively

have no knowledge in this regard. So, in both the public and private sector

companies less than 50% respondent customers have the awareness regarding

such websites. The Chi-square test results (P- value > .05) also indicated that

there is no significant gap between the awareness level of the customers from

the public and private sector general insurance companies.

Table 7.55

Sector-wise Distribution of Website Users

Website Used Frequency/Percentage

Sector

Total

Public

Sector

Private

Sector

Don‟t have

knowledge

Count 61 92 153

% within Sector 50.80% 51.10% 51.00%

Yes

Count 38 51 88

% within Sector 31.7% 28.30% 29.30%

No

Count 21 37 59

% within Sector 17.40% 20.60% 19.70%

Total

Count 120 180 300

% within Sector 100.00% 100.00% 100.00% Chi-square value = .335, d.f. = 2, P- value = 0.846, not significant at 5% level of significance.

The customers knowing about the websites of their companies were

further asked to tell whether they had ever used the website of their company or

not. Table 7.55 reveals that 38 customers from out of 59 the public sector and

51 customers out of 88 from the private sector having awareness about such

websites, made use of this facility. However, as many as 21 and 37 customers

from the public and private sector insurance companies respectively despite

having the knowledge about such websites did not avail this facility. The Chi-

square test results indicated that there is no significant gap between the usage

of websites of the public and private sector general insurance companies by

their customers. The results also reveal that the use of websites is not common

259

among the customers of both the public and private sector general insurance

companies.

Table 7.56

Purpose of Using Website by the Respondents

Purpose

Frequency/

Percentage

Sector Total

Public

Sector

Private

Sector

Don‟t use website

Count 82 129 211

% within Sector 68.30% 71.70% 70.30%

To know about the

product/Policies

Count 16 19 35

% within Sector 13.30% 10.60% 11.70%

To know about services of

company

Count 5 9 14

% within Sector 4.20% 5.00% 4.70%

To know about price of policies

Count 9 3 12

% within Sector 7.50% 1.70% 4.00%

Take online policies

Count 2 1 3

% within Sector 1.70% 0.60% 1.00%

To know the status of policies

Count 6 19 25

% within Sector 5.00% 10.60% 8.30%

Total

Count 120 180 300

% within Sector 100.00% 100.00% 100.00% Chi-square value = 10.378, d.f. =5, P-value =0.065, not significant at 5% level of significance.

The respondent website users were asked about the purpose for which

they used it most frequently. The table reveals that majority of the customers,

i.e., 16 from the public sector are using websites to know about the product and

policies, followed by those who use it to know about the price of policies, to

know the status of policies, to know about services of company, and to take

online policies. On the other hand, 19 customers from the private sector general

insurance companies have used websites to know about the product and

policies, followed by those who use it to know the status of policies, to know

about price of policies, and to take online policies. The Chi-square test results

(P>.05) indicate that there is no significant difference between the purpose of

using website by the customers of the public and private sector general


260

Perception Frequency/Percentage

Sector

Total Public Sector Private Sector

Don‟t use website

Count 82 129 211

% within Sector 68.30% 71.70% 70.30%

Yes

Count 22 16 38

% within Sector 18.30% 8.90% 12.70%

No

Count 7 19 26

% within Sector 5.80% 10.60% 8.70%

Not Aware

Count 9 16 25

% within Sector 7.50% 8.90% 8.30%

Total

Count 120 180 300

% within Sector 100.00% 100.00% 100.00%

Table 7.57

Respondents’ Perception Regarding Information Displayed on Website

Perception


Sector

Total

Public

Sector

Private

Sector

Don‟t Use Website

Count 82 129 211

% within Sector 68.30% 71.70% 70.30%

Quite insufficient

Count 1 0 1

% within Sector 0.80% 0.00% 0.30%

Insufficient

Count 1 1 2

% within Sector 0.80% 0.60% 0.70%

Average

Count 8 18 26

% within Sector 6.70% 10.00% 8.70%

Sufficient

Count 17 30 47

% within Sector 14.20% 16.70% 15.70%

Very Sufficient

Count 11 2 13

% within Sector 9.20% 1.10% 4.30%

Total

Count 120 180 300

% within Sector 100.00% 100.00% 100.00% Chi-square value = 13.689, d.f. = 5, P- value = 0.018, significant at 5% level of significance.

Table 7.57 depicts that majority of the customers, i.e., 17 and 30 from

the public and private sectors respectively opined that information displayed on

the website is sufficient. The mean values of the customers' perception of the

public and private sector are 3.95 and 3.65 which indicate that the information

displayed on websites of the public sector companies is more sufficient than the

private sector general insurance companies. The Chi-Square test results

(P<.05) show that there is a significant gap between the information displayed

on the websites of the public and private sector general insurance companies.

Table 7.58

Respondents’ Perception about Updating Website Regularly


261

The customers were further asked to comment with respect to update of

websites.

Table 7.58 shows that majority of the website users, i.e., 22 belonging to

the public sector general insurance companies perceived that the website is

regularly updated by their company. However, only 7 customers perceived that

website is not regularly updated, whereas 9 customers showed their ignorance.

In the case of customers from private sector general insurance companies, 16 of

them perceived that the website is regularly updated. However, 19 customers

perceived that website is not regularly updated. The Chi-square test (P > .05)

indicated that statistically there is no significant gap between the customers'

opinion of the public and private sector general insurance companies about

updating the websites.

Table 7.59

Respondents' Perception Regarding Access of Site


Sector

Total Public Sector Private Sector

Don‟t Use

Website

Count 82 129 211

% within Sector 68.30% 71.70% 70.30%

Easy

Count 35 43 78

% within Sector 29.20% 23.90% 26.00%

Time

Consuming

Count 3 8 11

% within Sector 2.50% 4.40% 3.70%

Total

Count 120 180 300

% within Sector 100.00% 100.00% 100.00% Chi-square value = 1.628, d.f. = 2, P- value = 0.443, not significant at 5% level of

significance.

The respondents were further asked to comment with respect to access

to the website. Majority of the respondents from both the public and private

sectors have confirmed an easy access to their companies' website. The Chi-

square test (P>.05) also proved that there is no significant gap between the

customers' perception regarding access to the website of the public and private

sector general insurance companies.

It has been found that internet is creating new values for both the

customers and companies, which has in a way compelled insurance companies

262

to explore their potential as a new distribution. The analysis revealed that less

than 50% of the customers have awareness regarding website of their company,

and most of them from both the public and private sector general insurance

companies do not generally access it. Majority of the customers used website to

know about the product and policies of the company, and they perceived that

access to site is easy. The public sector customers are found to be more

satisfied with the information displayed on the site than those from the private

sector. The analysis reveals that the insurance companies need to emphasize

more on popularizing internet usage by their customers which may help to

improve customer satisfaction and also cost reduction.

7.13 Customers' Awareness Regarding their Meetings arranged by the

General Insurance Companies

The general insurance companies organise customer meetings at

different intervals of time and place to get the feedback about their working

style, to solve and know the problems of their customers, and to provide latest

information regarding the products, policies and services. To check their

awareness and effectiveness about such meetings, the customers were asked

whether their general insurance company holds any customer meeting or not or

they know nothing about such meetings.

Table 7.60

Respondents’ Awareness Regarding Arrangement of Customer's Meeting

Awareness Frequency/Percentage

Sector

Total

Public

Sector

Private

Sector

Yes

Count 20 47 67

% within Sector 16.70% 26.10% 22.30%

No

Count 44 44 88

% within Sector 36.70% 24.40% 29.30%

Not Aware

Count 56 89 145

% within Sector 46.70% 49.40% 48.30%

Total

Count 120 180 300

% within Sector 100.00% 100.00% 100.00% Chi-square value = 6.657, d.f. =2, P- value =0.036, significant at 5% level of significance.

263

Table 7.60 depicts that 20 (16.70%) and 47 (26.10%) customers from

the public and private sector general insurance companies respectively are

aware about the holding of customer meetings by their companies. As many as

44 (36.70%) and 44 (24.40%) customers from the public and private sector

respectively opined that their companies do not hold customer meetings. The

remaining respondents are not aware about the holding of customer meetings

by their general insurance company. The proportion of such respondents in the

case of public and private sector companies is 46.70% and 49.40%

respectively. It is evident from the table that the customers of private sector

general insurance companies have more awareness regarding customer

meetings than those from the public sector. The Chi-square test (P < .05) also

implies that the awareness of customers from the private sector general

insurance companies is significantly higher than that of the public sector

customers regarding such meetings.

Table 7.61

Respondents’ Participation in Customer's Meetings

Reason Public Sector Private Sector Total

Yes 11 14 25

No 9 33 42

Total 20 47 67

The respondents having the knowledge about holding of customer

meetings by their general insurance companies were further asked about their

participation in these meetings. The data reveals that 11 customers from the

public sector and 14 from the private sector general insurance companies have

participated in customers meetings. It is evident from the table that the

awareness is more in the case of private sector customers, but the participation

in customer's meetings is higher in the public sector than the private sector.

264

Table 7.62

Reasons for Not Participating in Customer's Meetings

Reason Public Sector Private Sector Total

No time to go to meetings - 5 5

No information about date, time and

venue 5 8 13

It is just wastage of time 3 7 10

Meeting place is not suitable - 5 5

Unsuitability of time/date 1 8 9

Total 9 33 42

In table 7.62 the reasons for not participating in customer's meetings,

have been investigated. Majority of the respondents admitted that they could

not attend such customer's meetings as they were never informed by their

companies about the date and time of such meetings followed by the reason

that participating in such a meetings is just wastage of time. So, the companies

need to inform their customers well in advance regarding the date and time of

such meetings. The problems of customers also need to be carefully listened

and solved accordingly. The analysis depicts that there is a lack of awareness in

majority of the customers regarding holding of customer meetings by their

respective companies.

Respondents Gone Through Details of Documents While Signing

Table 7.63

Details of Documents



Never 10 8.3 11 6.1

Rare 14 11.7 13 7.2

Sometimes 33 27.5 56 31.1

Often 23 19.2 49 27.2

Always 40 33.3 51 28.3

Total 120 100.0 180 100.0

In response to the question whether the respondents go through the

details of each document before signing it, 40 (33.3%) and 51 (28.3%)

customers from the public and private sector companies respectively responded

that they always read details of all the documents. However, 23 (19.2%) and 49

265

(27.2%) customers from the public and private sector companies respectively

responded that they often read the details of the documents before signing

them. The remaining respondents were not bothered about reading the details

of all the documents before signing them.

Problems Faced by the Respondents’

Table 7.64

Problems Faced by the Respondents’


Perception Frequency Per cent Frequency Per cent

Yes 24 20.0 27 15.0

No 96 80.0 153 85.0

Total 120 100.0 180 100.0

Table 7.64 reveals that as many as 24 (20%) and 27 (15%)

customers belonging to the public and private sector general insurance

companies faced certain problems during the whole process of insurance.

However, majority of the customers faced no problem at all during the whole

process of insurance.

7.14 Comparative Analysis of Impact of Privatization on the Public and

Private Sector General Insurance Companies

Table 7.65

Respondents' Perception Regarding Impact of Privatization on Overall

Working of the Company



Badly Deteriorated - - 5 2.8

Deteriorated 15 12.5 10 5.6

Remained Same 23 19.2 3 1.7

Improved 72 60.0 139 77.1

Highly Improved 10 8.3 23 12.8

Total 120 100.0 180 100.0


Test Public Sector

Mean

Private Sector

Mean

t-value d.f. Sig.

(2-tailed)

t- test 3.64 3.92 -2.943 298 0.004

266


impact of privatization on the overall working of the public sector general

insurance companies, of whom 8.3% ranked highly improved, 60% ranked

improved, 19.2% ranked remained same and 12.5% ranked deteriorated. On the

other hand, 90% customers have favourably perceived the impact of

privatization on the overall working of the private sector general insurance

companies, of whom 12.8% ranked highly improved, 77.1% ranked improved,

1.7% ranked remained same, 5.6% ranked deteriorated and 2.8% ranked badly

deteriorated. The table further reveals that mean values of the responses

towards the impact of privatization on the overall working of the public and

private sector general insurance companies are 3.64 and 3.92 respectively

which indicates that the impact of privatization on improving the overall

working of the private sector is better than the public sector. The results of t-

test (P < .05) also indicate that the working of private insurers has improved

more than the public insurers over the period of reforms.

Table 7.66

Respondents' Perception Regarding Time Taken to Settle the Claim



Very Slow - - 5 2.8

Slow 4 3.3 3 1.7


Fast 59 49.2 125 69.4

Very Fast 16 13.3 25 13.9

Total 120 100.0 180 100.0


Test Public Sector

Mean

Private

Sector Mean

t-value d.f. Sig. (2-tailed)

t-test 3.73 3.90 -1.989 298 0.048

Table 7.66 depicts the perception of customers regarding the impact of

privatization on the time taken to settle the claim by the public and private

sector general insurance companies. The results highlight that 62.5%

respondents from the public sector have favourably perceived the impact of

267

privatization on the time taken to settle the claim, of whom 13.3% ranked very

fast, 49.2% ranked fast, 34.2% ranked remained same and 3.3% ranked slow.

However, majority of the respondents, i.e., 83.4% from the private sector have

favourably perceived the impact of privatization on the time taken to settle the

claim, of whom 13.9% ranked very fast, 69.4% ranked fast, 12.2% ranked

remained same, 1.7% ranked slow and 2.8% ranked very slow. The results

further indicate that the mean values of the responses towards the impact of

privatization on the time taken to settle the claim of the public insurers and

private insurers are 3.73 and 3.90 respectively. The higher mean value of the

private insurers exhibits that the private insurers take lesser time to settle the

claim than the public insurers. The t-test (P < .05) further shows that the

process to settle the claim of the private insurers is significantly quicker than

the public insurers.

Table 7.67

Respondents' Perception Regarding Procedure and Formalities of Claim

Settlement



Very Complicated 3 2.5 2 1.1

Complicated 11 9.2 14 7.8


Simple 65 54.2 95 52.7

Very Simple 7 5.8 32 17.8

Total 120 100.0 180 100.0


Test Public Sector

Mean

Private Sector

Mean


t-test 3.52 3.78 -2.642 298 0.009

Table 7.67 reveals that 60% customers have favourably perceived the

impact of privatization on the procedures and formalities of claim settlement of

the public sector general insurance companies, of whom 5.8% ranked very

simple, 54.2% ranked simple, 28.3% ranked remained same, 9.2% ranked

complicated and 2.5% ranked very complicated. Among the customers of the

private sector general insurance companies, 70.6% have favourably perceived

268

the impact of privatization on the procedures and formalities of claim

settlement, of whom 17.8% expressed very simple, 52.8% ranked simple,

20.6% expressed remained same, 7.8% ranked complicated, and 1.1% ranked

very complicated. The results show that mean values of the responses towards

the impact of privatization on simplifying the procedures and formalities of

claim settlement of the public and private sectors are 3.52 and 3.78 respectively

which exhibits that the private insurers have more simplified procedure and

formalities of claim settlement. The t-test (P < 0.05) further exhibits that the

procedure and formalities of the private insurers are significantly lesser than

the public insurers.

Table 7.68

Respondents' Perception Regarding Procedure and Formalities of Taking

Insurance Policies



Very Complicated 2 1.7 1 0.6

Complicated 9 7.5 11 6.1

Remained same 25 20.8 52 28.9

Simple 72 60.0 87 48.3

Very Simple 12 10.0 29 16.1

Total 120 100.0 180 100.0


Test Public

Sector Mean

Private

Sector Mean

t-value d.f. Sig. (2-

tailed)

t-test 3.69 3.73 -0.431 298 0.667

Table 7.68 exhibits that 70% respondents have favourably perceived the

impact of privatization on the procedure and formalities of taking insurance

policy of the public sector general insurance companies. Among the

respondents of the public sector, 10% ranked very simple, 60% ranked simple,

20.8% ranked remained same, 7.5% ranked complicated and 1.7% ranked very

complicated. However, 64.4% respondents of the private sector have

favourably perceived the impact of privatization on the procedure and

formalities of taking insurance policy. However, among the respondents of the

private sector, 16.1% ranked very simple, 48.3% ranked simple, 28.9% ranked

remained same, 6.1% ranked complicated, and 0.6% ranked very complicated.

269

The table further reveals that mean values of responses of the respondents

towards the impact of privatization on procedure and formalities of taking

insurance policy of the public and private sector companies are 3.69 and 3.73

respectively, which exhibits that privatization has impacted positively on

simplifying the procedure and formalities of taking insurance policy from the

companies belonging to both the sectors up to some extent. The t-test (P >

0.05) further depicts that there is no significant gap between the public and

private sector companies regarding impact of privatization on simplifying the

procedure and formalities while taking an insurance policy.

Table 7.69

Respondents' Perception Regarding Price of Policy after Detarrification



Very high 2 1.7 1 0.6

High 5 4.2 22 12.2

Remained same 48 40 46 25.6

Low 59 49.2 80 44.4

Very low 6 5.0 31 17.2

Total 120 100 180 100


Test Public

Sector Mean

Private

Sector Mean


tailed)

t-test 3.52 3.66 -1.382 298 0.168

Table 7.69 presents that 54.2% respondents of the public sector general

insurance companies have favourably perceived the impact of privatization on

reducing the prices of the policies of the public sector general insurance

companies. Among the respondents of the public insurers, 5% ranked very low,

49.2% ranked low, 40% ranked remained same, 4.2% ranked high and 1.7%

ranked very high. On the other side, 61.6% respondents of the private sector

have favourably perceived the impact of privatization on reducing the prices of

policies of the private sector general insurance companies, of whom 17.6%

ranked prices very low, 44.4% ranked low, 25.6% ranked remained same,

12.2% ranked high and .6% ranked very high. The table 7.69 further shows

270

mean value of responses of the respondents of the public sector and the private

sector towards the impact of privatization on reducing the prices of their

policies is 3.52 and 3.66 respectively which depicts that little prices have been

reduced after detarification of both the insurers but the prices of the policies of

the private insurers are more reduced than the public insurers. The t-test (P >

.05) indicates that there is no significant difference of reduction in prices of

policies of the public and the private sector general insurance companies after

detarrification.

Table 7.70

Respondents' Perception Regarding Innovation of New Policy and Product





Improved 60 50.0 70 38.9

Highly improved 11 9.2 13 7.2

Total 120 100.0 180 100.0


Test Public

Sector Mean

Private

Sector Mean


tailed)

t-test 3.61 3.33 2.803 298 0.005

Table 7.70 explains that 59.2% customers of the public sector general

insurance companies have favourably perceived the impact of privatization on

innovation of new policies/products as per the requirement of customers.

Among the respondents of the public sector companies, 9.2% ranked 'highly

improved', 50% ranked 'improved', 33.3% ranked 'remained same' and 7.5%

ranked 'deteriorated'. Among the respondents of the private sector 7.2% ranked

'highly improved', 38.9% ranked 'improved', 33.9% ranked 'remained same' and

20% ranked deteriorated. The mean values for the response obtained from the

respondents belonging to both the public and private sector companies are 3.61

and 3.33 respectively which show that privatization has little impact on the

products and policies as per the requirement of customers. The t-test (P <.05)

proves that the improvement in innovation of products and policies of the

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public sector companies is significantly higher than that of the private sector

general insurance companies.

Table 7.71

Respondents' Perception Regarding Behaviour and Efficiency of

Employees and Agents



Badly deteriorated 1 0.8 5 2.8



Improved 71 59.2 117 65.0

Highly improved 13 10.8 18 10.0

Total 120 100.0 180 100.0


Test Public Sector

Mean

Private Sector

Mean


t-test 3.78 3.77 0.032 298 0.975

Table 7.71 exhibits the impact of privatization on the improvement of

behaviour and efficiency of the employees and agents of general insurance

companies. As is evident from the table that 70% respondents of the public

sector companies have perceived favourably towards behaviour and efficiency

of the employees and agents. Among the respondents of the public sector

companies, 10.8% ranked 'highly improved', 59.2% ranked 'improved', 27.5%

ranked 'remained same', 1.7% ranked 'deteriorated' and 0.8% ranked 'badly

deteriorated'. Among the respondents of the private sector companies, 75%

have perceived favourably, of whom 10% ranked 'highly improved', 65%

ranked 'improved', 20% ranked 'remained same', 2.2% ranked 'deteriorated' and

2.8% ranked 'badly deteriorated'. The mean values for the response obtained

from the respondents belonging to the public and the private companies are

3.78 and 3.77 respectively, which contains that there has been almost similar

improvement in the efficiency and behaviour of employees and agents in both

the sectors due to privatization. The t-test also proves that there is no

significant gap between efficiency improvement and behaviour of the public

and private sector general insurance companies.

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It has been found that privatization has contributed towards improving

the overall working of both the public and private sector general insurance

companies. The private sector general insurance companies have comparatively

shown more improvement than the public sector companies in terms of overall

working, time taken to settle claim, procedure and formalities to settle claim,

etc. However, the public sector companies have recorded greater improvement

than the private sector companies in relation to innovation of new policies and

products. There is no significant gap in the impact of privatization on the public

and private sector companies regarding procedure and formalities of taking

policy, price of policies after detarrification, behaviour and efficiency of

employee and agents.

273