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February 2015

An Assessment of Service Quality, Customer Satisfaction and Customer Loyalty in Life Insurance Corporation of India with Special Reference to Srinagar District of Jammu and Kashmir

 

 

Prof. M. Nasir Zamir Qureshi

Professor, Department of Commerce, Aligarh Muslim University, Aligarh, India, 202002,

Javaid Ahmad Bhat

Ph. D Research Scholar, Department of Commerce,Aligarh Muslim University

 


 

Abstract

Insurance services in India are passing through a sea change, opening up of the industry has placed numerous severe threats andchallenges to Life Insurance Corporation of India (LIC), the only public sector life insurance service provider in the country. For success and survival in today’s competitive environment, delivering quality service is of paramount importance for any economic enterprise. Therefore, service quality has become a highly influential co-efficient in the aggressive competitive marketing. Life Insurance Corporation of India, the leading insurance company has set up ‘benchmarks’ in enervating the whole concept of service quality.The present study aims to measure customers’ expectations and perceptions towards service quality of LIC in Srinagar district of Jammu and Kashmir by applying a framework adopted from earlier studies. Moreover, Customer Satisfaction and Customer Loyalty with the services of LIC have also been examined.Data has been collected from 273 LIC customers from Srinagar, the capital city of J&K. The data were analysed with the help of statistical techniques including Cronbach’s alpha, correlations, t-statistics and ANNOVA. The findings of the study indicate that there is a service quality shortfall i.e. perceptions are lower than expectations in all the six service quality dimensions of the study with Personalized financial planning followed by Competence and Assurance being more concerned dimensions.

Keywords: Service quality, LIC, Perceptions, Expectations.

___________________________________________________________________________

Introduction: Today’s businesses are facing fierce and aggressive competition while operating in a market characterised by global competition. Most managers and marketers would of course agree that establishing long-term business relationship is essential for developmentand survival. According to Lewis, the world has never been so interdependent (Mittal & Kumar,2007). All trends point to co-operation as a fundamental, growing force in business (Buttle, 1996). Today marketing is not just developing, delivering and selling, it is moving towards developing and maintaining mutually long-term relationships with customers (Johnston, Connor &Zultowski, 1984). This new business philosophy is called “relationship marketing”, which has attracted considerable interest both from marketing academics and practitioners (Sethi, 2004). As stated above that today’s business is characterised by stiff competition, consequently, delivering quality services becomes absolutely pivotal for attracting and retaining the customers. Service Quality is the consumers’ judgement about an entity’s overall excellence or superiority (Zeithmalet al. 1986). It is a form of attitude and results from a comparison of expectations to perceptions of performance received.

In the recent years, service firms like other sectors have realized the significance of customer centred philosophies. They are also using Service Quality as an important differentiator and a path to success. Rai and Medha (2013) stated that Service Quality is an important antecedent of customer loyalty. Services business success has been associated with the ability to deliver superior service (Gale, 1990; Rudie and Wansely, 1984). Therefore, delivering superior service quality than the competitors is the key for the success of any organization. But, the companies face difficulties in measuring the quality of services offered to the customers. Because unlike measuring the quality of goods, the measurement of the quality of services offered by the companies is difficult due to the unique features of the services, viz. intangibility, heterogeneity, and inseparability. Hence, the only way of measuring the quality of services offered by the service provider is the measurement of the customer’s perception of the quality of service they are experiencing from their service providers. Academicians and researchers have proposed several approaches to service quality. Some of them are dimensions of service quality, gap analysis, the design approaches and direct application of quality know-how from goods to services.

The life insurance industry in India is one of the hard-core parts of the service sector. It not only provides safety against risk for individuals, but also creates the savings and investment habits among the individuals. The life insurance sector by its nature attracts long-term funds, which are invested in productive heads for the development of the Indian economy. It is pertinent to mention that Insurance industry reforms began in India following the report of R.N. Malhotra Committee, which was set up in 1993. In the pre-reform phase, the government had a monopoly in the life insurance industry. However, since 2000, whenthe insurance industry was opened to the private players, the competition has increased many folds. As the private sector insurers ventured into the country, the industry got a taste of market-driven competition. In the post reform phase, the Life insurance Corporation of India (LIC) is facing challenges from the new competitors entering the market. Therefore, delivering quality service is the only viable strategy for LIC inorder to be successful and survive in today's competitive environment. Research has shown that the quality of services and the achievement of Customer Satisfaction and Loyalty are elementary for the survival of insurers. The quality of after sales services, in particular, can lead to very positive results through Customer Loyalty, positive WOM, repetitive sales and cross-selling (Chakrabaraty, 2006). It is therefore not surprising that measurement of service quality has generated, and continues to generate, a lot of interest in the industry (Prakash, Jha&Kallurkar, 2011). Thus, the service quality requires an assessment in context of life insurance services.

Literature survey

Service is “an activity, benefit, or satisfaction offered for sale that is essentially intangible and does not result in the ownership of anything.” There are certain characteristics of services distinct from goods such as: (i) Intangibility (i.e. services cannot be tasted, seen, heard, smelled, felt) (ii) Inseparability (simultaneous production and consumption) (iii) Heterogeneity (service quality depends on who provides service, when, where and how) (iv) Perishability, i.e. services cannot be inventoried (Kotler and Armstrong, 2012).

Now the point is how customers evaluate the quality of services rendered to them by their service provides. The answer is provided by SERVQUAL model developed by (Parasuraman, Zeithmal and Berry, 1988) which describes five determinants of service quality in terms of Tangibility, Reliability, Responsiveness, Assurance and Empathy. The SERVQUAL instrument has been extensively applied for assessing the service quality across variety of service settings including life insurance services (Bhat, J. A. 2014). It is worth to mention that different Researchers have modified the generic SERVQUAL instrument in order to make it specific to the nature of services investigated, the scheme of operationalization remaining the same as the original SERVQUAL. In this context, Mehta and Lobo, (2004), identified six dimensions for assessing service quality in life insurance; which included Assurance, Corporate image, Tangibles, Personalized financial planning, Similarity with agent and Competence. Sureshchandaret. al(2001) prescribed a framework for assessing life insurance service quality that consisted of five dimensions of Service Quality, those were: Core service/ Service Product, Human element of service delivery, Systemization of service delivery/ Non-Human element, Tangibles of services/ Services capes and Social Responsibility. Ahmed and Sungip (2008) reported that insures in Malaysia need to initiate quality improvement efforts towards the component of Reliability. Siddiqui and Sharma (2010) in their study on life insurance service quality concluded that ‘Assurance’ was the best predictor of Service Quality followed by ‘Competence’ and ‘Personalized financial planning. Sandhu and Bala (2011) while assessing the service quality of LIC reported that Proficiency, Physical and ethical excellence and Functionality had significant impact on Overall service quality. Dar et.al (2012) examined the customer perception of Service Quality offered by the Insurance Companies in Srinagar (J&K) and reported that culture was one of the important dimensions of Service Quality in their study, thus SERVQUAL need to be modified under different study contents.

Kotler and Armstrong (2012) have defined customer satisfaction as “the extent to which product’s perceived performance matches a buyer’s expectations.” Oliver (1980) mentioned three positions as negative disconfirmation when customers are highly dissatisfied, zero disconfirmation when performance matches expectations and positive disconfirmation when customers are highly satisfied. Borah (2012) assessed the Customer Satisfaction with the Services provided by private life insurance Companies in Assam and concluded that dimensions of Tangibility, Accessibility and Understanding had the maximum impact on Customer Satisfaction. Kotler and Armstrong (2012) stated that the aim of customer relationship management is to create not only satisfied customer but also the loyal customer who in turn not only practices repeated purchases but also spreads favourable word of mouth. Rai and Medha (2013) assessed the loyalty status of life insurance customers in India and thereby reported that Indian customers considered the public sector status of financial service provider as it provided a sense of security and stability and thus created a difference between Customer Loyalty of public sector and private sector life insurance.

Objectives of the study

The study is intended to fulfil the following objectives:

1. To measure Customer’s expectations and perceptions of Service Quality in Life Insurance Corporation of India in Srinagar.

2. To determine the gap between expectations and perceptions of Service Quality.

3. To measure the Satisfaction and Loyalty perceptions of Customers towards the Services of Life Insurance Corporation of India.

4. To offer suggestions for the improvement of Service Quality in Life Insurance Corporation of India.

Hypotheses development

This study draws the hypotheses as follows.

H01: There is no significant difference in Overall Service Quality across Gender.

H02: There is no significant difference in Overall Service Quality across Age categories.

H03: There is no significant difference in Overall Service Quality across Education levels.

H04: There is no significant difference in Overall Service Quality across Income groups.

H05: There is no significant difference in Customer Satisfaction across Gender.

H06: There is no significant difference in Customer Satisfaction across Age categories.

H07: There is no significant difference in Customer Satisfaction across Education levels.

H08: There is no significant difference in Customer Satisfaction across Income groups.

H09: There is no significant difference in Customer Loyalty across Gender.

H010: There is no significant difference in Customer Loyalty across Age categories.

H011: There is no significant difference in Customer Loyalty across Education levels.

H012: There is no significant difference in Customer Loyalty across Income groups.

Instrument development and scale reliability

The scales that are used in this study measuring Service Quality, Customer Satisfaction and Customer Loyalty have been adoptedfrom earlier studies. The service quality attributes are SERVQUAL type and are based on Mehta and Lobo, (2004). The service quality attributes consisted of six dimensions: Assurance, Personalized financial planning, Tangibles, Corporate image, Similarity with agent and Competence. Customer Satisfaction consisted of five items and is based on Westbrook and Oliver (1991). Customer Loyalty also consisted of five items adopted from Parasuramanet al. (1996).

Table 1: Reliability Statistics

Scale Dimension

Observed variables

Indicators/ items

Reliability

(Cronbachalpha)

Overall

Reliability

 

 

Expectations of Service Quality

Assurance

09

.929

 

 

.962

Personalized financial planning

04

.914

Tangibles

03

.723

Corporate image

03

.764

Similarity with agent

03

.712

Competence

06

.842

 

Perceptions of Service Quality

Assurance

09

.927

 

 

.958

Personalized financial planning

04

.853

Tangibles

03

.711

Corporate image

03

.688

Similarity with agent

03

.725

Competence

06

.894

Satisfaction

05

.924

 

Loyalty

05

.800

Source: SPSS output (based on Survey)

A 5-point likert scale was used for measurement of Service Quality, Satisfaction and Loyalty latent variables with end anchors 1 for “strongly disagree” to 5 for “strongly agree”. Cronbach’s alpha values were calculated to check the reliability of the scales and are depicted in Table 1.The overall reliability was found to be .962 and .958 for expectations and perceptions respectively. The high alpha values above 0.7 indicates that the measures are reliable and internally consistent (Nunnally, J. C. 1978). The reliability of each dimension of service quality were measured for both expectations and perceptions separately which were: Assurance (expectations .929, perceptions .927), Personalized financial planning (expectations .914, perceptions .853), Tangibles (expectations .723, perceptions .711), Corporate image (expectations .764, perceptions .688), Similarity with agent (expectations .712, perceptions .725) and Competence (expectations .842, perceptions .894). Moreover, reliability coefficients of Satisfaction and Loyalty were .924 and .800 respectively. This shows high internal consistency. Hence the scale items are reliable and internally consistent.

Sample and Data collection:A convenient sampling technique was practiced and questionnaires were distributed among LIC policy holders in the Srinagar district of Jammu & Kashmir. A total of 273 questionnaires were distributed to different policy holders out of which 215 valid responses were received making a response rate of 78.75%.

 

Results

As per Table 2, out of a total of 215 respondents, 176 were males and 39 were females. This shows 81.9% and 18.1% for males and females respectively. In terms of age, 48.8% of respondents belong to the age range of 30-45, and 40.9% belong to 46-60 while 10.2% were below 30 years. 81.4% of the respondents were post graduates and 15.3% of the respondents were graduates, meanwhile 3.3% were under graduates. Out of 215 respondents, 28.4% of

Table2: Demographics of respondents

Variable

Frequency

 

Percentage

 

Gender

 

Male

176

81.9

Female

39

18.1

Total

215

100.0

Age

 

Under 30

22

10.2

30-45

105

48.8

46-60

88

40.9

Above 60

nil

0.00

Total

215

215

Education

 

High school

7

3.3

Graduate

33

15.3

Post Graduate

175

81.4

Total

215

100.0

Income

 

Under 30000

21

9.8

30000-50000

51

23.7

50001-70000

61

28.4

70001-90000

31

14.4

Above 90000

51

23.7

Total

215

100.0

Source: Field Survey

respondents had monthly income between 50001-70000, 23.7% fall in the income slab of 30000-50000, 23.7% had monthly income of above 90000, 14.4% respondents fall in the range of 70001-90000 and 9.8% of the respondents income was under 30000 I.N.R.


Table 3: GAP Analysis

Observed variable

 

Indicators/items

Perception

(P)

Expectati-on

(E)

Gap

 

(P-E)

Mean

Perception

(SD)

Mean

Expectation

(SD)

Average

gap

 

Assurance

 

 

 

 

 

 

 

 

 

 

1.       Employees of insurance company being consistently courteous during service contact.

3.58

 

4.31

 

-0.73

 

 

 

 

 

 

 

 

 

 

 

3.39

(.920)

 

 

 

 

 

 

 

 

 

 

 

4.26

(.802)

 

 

 

 

 

 

 

 

 

 

 

-0.87

2.       Agents’ being Trustworthy when explaining policy’s terms and conditions.

3.26

 

4.21

 

-0.95

3.       Agents’ conducting assessment of risk profile/situation for their customers.

3.35

 

4.18

 

-0.83

4.       Employees consciously listening to customer requests and queries.

3.52

 

4.33

 

-0.8

5.       Insurance company understanding intimately specific needs of their customers’.

3.26

 

4.18

 

-0.91

6.       Insurance company having trained and well informed agents.

3.51

 

4.34

 

-0.83

7.       Agents’ clearly explaining policy terms and conditions.

3.43

 

4.39

 

-0.97

8.       Insurance company having customer’s best interests at heart.

3.15

 

4.34

 

-1.19

9.       Agents’ and employees approaching from customer’s point of view.

3.43

 

4.03

 

-0.6

Personalized

Financial planning

 

 

 

1. Insurance company arranging for periodical meetings with its customers.

2.31

 

3.92

 

-1.61

 

 

 

 

2.83

(.997)

 

 

 

 

4.07

(.982)

 

 

 

 

-1.24

2. Insurance company restructuring policies as customer’s life changes.

3.01

 

4.13

 

-1.12

3. Insurance company keeping customers updated on new products.

3.09

 

4.2

 

-1.1

4. Insurance company taking due care of customers life style preferences

2.92

 

4.03

 

-1.1

 

Tangibles

 

 

 

1. Agents’ and employees being neat and professional in appearance.

3.69

 

4.25

 

-0.57

 

 

 

3.67

(.80)

 

 

 

4.39

(.704)

 

 

 

-0.72

2. Insurance company possessing good certification and credentials.

3.76

 

4.42

 

-0.66

3. Insurance company using modern aids and technology in servicing their customers.

3.64

 

4.48

 

-0.84

 

Corporate image

 

 

 

1. Insurance company being a financially stable company.

4.10

 

4.46

 

-0.37

 

 

3.91

(.703)

 

 

4.40

(.583)

 

 

-0.49

2. Insurance company being innovative in introducing new products.

3.61

 

4.23

 

-0.62

3. Simple & Less time consuming Procedure for purchasing a policy.

4.03

 

4.50

 

-0.47

 

Similarity with agent

1. Agents’ sharing similar view points and beliefs as that of customers.

3.31

 

3.92

 

-0.61

 

 

 

3.52

(.804)

 

 

 

4.07

(.717)

 

 

 

-0.55

2. Agents’ relating well with customers due to similar traits and characteristics.

3.41

 

3.86

 

-0.45

3. Customer being able to easily communicate with the agent.

3.83

 

4.44

 

-0.61

 

Competence

 

 

 

 

 

 

1. Insurance company providing the services at the promised time.

3.39

 

4.52

 

-1.12

 

 

 

 

 

 

 

3.40

(.920)

 

 

 

 

 

 

 

4.31

(.671)

 

 

 

 

 

 

 

-0.91

 

2. Employees being dependable in handling customer’s problems.

3.4

 

4.06

 

-0.66

3. Employees being able to respond promptly to need or emergency.

3.26

 

4.31

 

-1.05

4. Employees showing willingness to help customers even when busy.

3.13

 

4.28

 

-1.15

5. Agents’ on behalf of customers settling administration matters efficiently.

3.30

 

4.04

 

-0.74

6. Insurance company having a good reputation

3.89

 

4.64

 

-0.75

Source: SPSS output (based on Survey)


The Table 3 furnishes the results of service quality gap analysis (perceptions – expectations) performed in respect of six service quality variables i.e. Assurance, Personalized financial planning, Tangibles, Corporate image, Similarity with agent and Competence. The results indicate that there is a service quality gap in respect of all the service quality variables under study. It is quite evident from the results that Personalized financial planning has the highest gap of -1.24 followed by competence -0.91 and Assurance -0.87. Moreover, Tangibles, Corporate image and Similarity with agent have service quality gaps of -0.72, -0.49 and -0.55 respectively.

Descriptive and Correlation Analysis:It reveals from Table 4that Overall Service Quality has a mean score of -0.79 indicating that the gap in Service Quality is not excessively wide. While as it is apparent in the Table that Satisfaction has a mean value of 3.64 indicating that customers were satisfied on an average. Since, Loyalty perceptions has a mean score of 3.45, it indicates that on an average customers were loyal to LIC.

Table 4: Descriptive and Correlation statistics (Service Quality attributes, Satisfaction and Loyalty)

Variables

Mean

SD

AS

PFP

TAN

CI

SWA

COPT

SAT

LOY

AS

-.87

1.12

 

 

 

 

 

 

 

 

PFP

-1.24

1.31

.752**

 

 

 

 

 

 

 

TAN

-0.72

.863

.848**

.620**

 

 

 

 

 

 

CI

-0.49

.659

.494**

.356**

.502**

 

 

 

 

 

SWA

-0.55

.755

.628**

.596**

.492*

.521**

 

 

 

 

COPT

-0.91

1.07

.884**

.733*

.793**

.602**

.698**

 

 

 

OSQ

-0.79

.816

 

 

 

 

 

 

 

 

SAT

3.64

.964

.423**

.263**

.342**

.238**

.553**

.431**

 

 

LOY

3.45

.875

.275**

.107

.203**

.171*

.446**

.305**

.858**

 

Source:SPSS output (based on Survey)

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

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

AS- Assurance, PFP- Personalized financial planning, TAN- Tangibles, CI- Corporate image, SWA- Similarity with agent, COPT- Competence, SAT- Satisfaction, LOY- Loyalty, OSQ- Overall Service Quality.

 

A correlation analysis has been performed to check the relationships between all Service Quality variables, Customer Satisfaction and Customer Loyalty. The results are shown in Table 4. The results indicate that all the six dimensions of Service Quality as well as Customer Satisfaction and Customer Loyalty have significant positive relationship between each other.

T-test and ANNOVA:To test the hypotheses from H01 to H012 (to find out the significant differences in Overall Service Quality, Customer Satisfaction and Customer Loyalty across particular demographic attributes) independent sample t-test and one way ANNOVA have been performed. It is clear from the statistics presented in Table 5 that there existed no significant difference in Overall Service Quality across Gender (t= -1.724, p= .089) and Education levels (f=1.218, p= .298). Moreover, significant difference in Overall Service Quality existed across Age categories (f= 12.872, p= .298) and Income groups (f= 7.522, p= .000).

Statistics presented in Table 6 pertain to examination of difference in Customer Satisfaction across particular demographic attributes. It is quite evident that there existed no significant difference in Customer Satisfaction as far as Gender (t= .955, p= .344) and Age Categories (f= 1.826, p= .164) are concerned. Meanwhile, significant difference in Customer Satisfaction was observed across Education levels (f= 3.307, p= .039) and Income groups (f= 6.728, p= .000).

As per the statistics shown in Table 7, no significant difference in Customer Loyalty was observed across gender (t= -.712, p= .480). Consequently, significant difference in Customer Loyalty across Age Categories (f= 2.664, p= .072), Education levels (f= 2.387, p= .094) and Income groups (f= 8.631, p= .000) was observed.

Table 5: t- test and ANNOVA statistics (Overall Service Quality and Demographics)

 

Variable

T value

F value

sig

 

Gender

 

-1.724

-

.089

 

Age

 

-

12.872

.000

 

Education

 

-

1.218

.298

 

Income

 

-

7.522

.000

Source: SPSS output (based on Survey)

Table 6: t- test and ANNOVA statistics (Customer Satisfaction and Demographics)

 

Variable

T value

F value

sig

 

Gender

 

.955

-

.344

 

Age

 

-

1.826

.164

 

Education

 

-

3.307

.039

 

Income

 

-

6.728

.000

Source: SPSS output (based on Survey)

 

 

 

 

Table 7: t- test and ANNOVA statistics (Customer Loyalty and Demographics)

 

Variable

T value

F value

sig

 

Gender

 

-.712

-

.480

 

Age

 

-

2.664

.072

 

Education

 

-

2.387

.094

 

Income

 

-

8.631

.000

Source: SPSS output (based on Survey)

 

 

Hypothesis Results:On the basis of above statistical findings, hypotheses results can be drawn which are shown in Table. 8.

Table 8: Result of hypotheses

Hypotheses

t

f

P

Results

H01:There is no significant difference in Overall Service Quality across Gender.

 

-.1724

 

-

 

.089

 

Supported

H02: There is no significant difference in Overall Service Quality across Age categories.

 

-

 

12.872

 

.000

 

Not supported

H03: There is no significant difference in Overall Service Quality across Education levels.

 

-

 

1.218

 

.298

 

Supported

H04: There is no significant difference in Overall Service Quality across Income groups.

 

-

 

7.522

 

.000

 

Not supported

H05: There is no significant difference in Customer Satisfaction across Gender.

 

.955

 

-

 

.344

 

Supported

H06: There is no significant difference in Customer Satisfaction across Age categories.

 

-

 

1.826

 

.164

 

Supported

H07:There is no significant difference in Customer Satisfaction across Education levels.

 

-

 

3.307

 

.039

 

Not supported

H08:There is no significant difference in Customer Satisfaction across Income groups.

 

-

 

6.728

 

.000

 

Not supported

H09:There is no significant difference Customer Loyalty across Gender.

 

-.712

 

-

 

.480

 

Supported

H010:There is no significant difference Customer Loyalty across Age categories.

 

-

 

2.664

 

.072

 

Not supported

H011:There is no significant difference Customer Loyalty across Education levels.

 

-

 

2.387

 

.094

 

Not supported

H012:There is no significant difference Customer Loyalty across Income groups.

 

-

 

8.631

 

.000

 

Not supported

Source: SPSS output (based on Survey)

Discussion

Based on the statistical results, hypotheses H01, H03, H05, H06, and H09, are supported whereas remainder of the hypotheses are not supported. Personalized financial planning showed highest service quality gap followed by competence and Assurance. Moreover, significant differences in Overall Service Quality were found across Age groups and Income levels. Furthermore, significant difference in Customer Satisfaction was found across Education levels and Income groups. In addition, significant difference in Customer Loyalty was observed across Age categories, Education levels and Income groups.

Assurance: Results of the study showed that Assurance is positively correlated with Satisfaction and Loyalty. Service quality gap of -0.87 has been observed on this dimension which is slightly on the higher side.

Personalized financial planning: Service quality gap of -1.24 which is highest of the service quality gaps observed on all dimensions. Results indicated that Personalized financial planning positively correlated with Satisfaction and Loyalty.

Tangibles: Service quality gap of -0.72 has been observed. Statistics depicted that Tangibles positively correlated with Satisfaction and Loyalty.

Corporate Image: Service quality gap of -0.49 has been observed on this dimension. Results depicted that Corporate image positively correlated with Satisfaction and Loyalty

Similarity with Agent: Service quality gap of -0.55 has been observed. Results indicated that Similarity with agent positively correlated with Satisfaction and Loyalty.

Competence: Service quality gap of -0.91 has been observed on this dimension. Results showed that Competence positively correlated with Satisfaction and Loyalty.

Customer satisfaction: The average perception of 3.64 has been observed on Customer Satisfaction, indicating that customers were satisfied on an average. Significant correlations between Satisfaction and Service Quality dimensions along with Loyalty attribute have been found.

Customer loyalty: The average perception of 3.45 has been observed on Customer Loyalty, indicating that customers were average loyal to their service provider. Significant correlations between Loyalty and Service Quality dimensions along with Satisfaction construct have been found.

Managerial implications:This study demonstrated interrelationships among Service Quality, Customer Satisfaction and Customer Loyalty in Life Insurance Corporation of India (LIC). As evident from correlation matrix service quality attributes are positively correlated with Customer Satisfaction as well as Customer Loyalty, so LIC should be focused upon the provision of efficient and effective quality services. Personalized financial planning showed highest service quality gap, so LIC should concentrate on providing effective personalized service. Assurance and Cmpetence attributes also showed significant service quality gaps. As, these attributes are related with agents and employees, LIC should focus on employee and agent training programmes so as to fill these gaps. It is also revealed from the study that there is a strong correlation between Customer Satisfaction and Customer Loyalty. Hence LIC should concentrate not only on maintaining existing services but also enhancing the service standards as the Customer Satisfaction mean score is just above the threshold point. Therefore, it must be made sure that that there is prompt delivery of services to customers and with high service standards for which LIC should arrange complete training to their agents and employees for addressing the concerns of the customers so that the customers are satisfied as ultimately making the customers satisfied is pivotal for securing their loyalty.

Limitations and directions for future research:There are certain limitations of this study. First the sample size is small to represent the overall population and secondly convenience sampling technique was used to collect data from LIC customers. In future, researchers may include a large sample and may practice a random sampling which is the basis for generalizability of the findings. Thirdly, in this study the data were collected only from the Srinagar district of J&K while customers from other areas of the country may have different perceptions. Moreover, the impact of service quality variables on Customer Satisfaction and Customer Loyalty has not been studied. In future researchers may study the mediating effect of Customer Satisfaction between Service Quality and Customer Loyalty.

 

 

 

 

 

 

References

Ahmad, A. &Sungip, Z. (2008). An Assessment on Service Quality in Malaysia Insurance Industry. . Communications of the IBlMA, 1, 13-26.

Alok Mittal and Akash Kumar (2007). An Exploratory Study of Affecting Selection of Life Insurance Products, in NaliniParavaTripathy and Prabir Bal (Eds), Insurance Theory and Practice. New Delhi, Prentice-Hall India Private Limited.

Amit Kumar Chakrabaraty (2006). The Efficiency of LIC during the Post-Liberalization and Globalization Period: A Case Study of West Bengal. Business Perspectives,8(2), July-December.

Anand Prakash, Sanjay Kumar Jha and Kallurkar (2011). Attitudes of Indians towards Service Quality for Life Insurance in India. International Journal of Research In Computer Application & Management,1(9), November, pp.57-63.

Anjor, P., et al. (2014). Service quality assessment: A study of consumer satisfaction in Indian insurance sector. IOSR Journal of Business and Management (IOSR-JBM), 16 (3), 34-41

Baron, R. M., and Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.

Bhat, J. A. (2014). Antecedents of service quality in Life insurance. Online International Interdisciplinary Research Journal, 4(3), 237-249.

Bodla, B. S., & Chaudhary, P. (2012). A study of service quality expected and perceived by the customers of ICICI prudential life insurance company. International Journal of Computing and Business Research.ISSN (Online) : 2229-6166.

Buttle, F (1996). Relationship Marketing: Theory and Practice. London, Paul Chapman Publishing.

Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of applied psychology, 78(1), 98.

Dar, A., Malik, M., & Mir, R. (2012). Customer Satisfaction on Service Quality in Life insurance. International Journal of Scientific Research, 1(6), 118-23.

Hassan, M. U., et al.(2013). Relationships amoung customers’ perceived service quality, satisfaction and loyalty in retail banking sector of Pakistan. World Applied Sciences Journal, 24(8), 1020-1030.

Johnston, E. O, O’Connor, R. J and Zultowski, W. H (1984). The Personal Selling Process in the Life Insurance Industry, in Jacoby, J and Craig, C.S (Eds.), Personal Selling: Theory, Research and Practice, pp.136-164.

Kotler, P., and Armstrong, G. (2012). Principles of Marketing. Pearson Prentice Hall.

Mehta, S. C. & Lobo, A. (2004). MSS, MSA and zone of tolerance as measures of service quality: A Study of the Life Insurance Industry. Second International Services Marketing Conference, University of Queensland.

NeerajSethi (2004). Insurance Regulator: Hindrance for Growth? in Jawaharlal, Insurance Industry Trends and Regulations (eds.). Hyderabad, ICFAI University Press.

Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.

Oliver, R. (1980). A cognitive model of antecedents and consequences of satisfaction decisions. Journal of Marketing Research. 17(4), 460.

Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality. Journal of Retailing, 64(1), 12-40.

Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1996). The behavioral consequences of service quality. The Journal of Marketing, 60(2), 31-46.

Rai, A. K., &Medha, S. (2013). The Antecedents of Customer Loyalty: An Empirical Investigation in Life Insurance Context. Journal of Competitiveness, 5(2), 139-163.

Sandhu, D. H., &Bala, M. N. (2011). Customers’ Perception towards Service Quality of Life Insurance Corporation of India: A Factor Analytic Approach.International Journal of Business and Social Science, 2(18), 123-138.

Siddiqui, M. H., & Sharma, T. G. (2010). Measuring the Customer Perceived Service Quality for Life Insurance Services: An Empirical Investigation. International Business Research, 3(3), 171-186.

Sureshchandar, G. S., Rajendran, C., &Kamalanabhan, T. J. (2001). Customer perceptions of service quality: a critique. Total quality management, 12(1), 111-124.

Westbrook R.A. and Oliver R.L. (1991). The Dimensionality of Consumption Emotion Patterns and Consumer Satisfaction. Journal of Consumer Research, 18, 84-91. 147

 

 

 
 

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