# Introduction ervices sector is the fastest growing sector in India and is projected to have high growth in future. A major contributor among huge service sector is the insurance sector which plays an important role in enhancing financial intermediation, creating liquidity and mobilizing savings in the country. The Indian life insurance industry remained a monopoly of Life Insurance Corporation of India (LIC) till it was liberalized in 1999. At present, there are 24 life insurance companies operating in India with LIC being the only public sector life insurer and the balance being private players. Presently, there are 36 crore life insurance policies in India making it the biggest player in the world for life insurance. India's insurable population is anticipated to touch 75 crore in 2020. India was ranked 10th among 147 countries in the life insurance business in financial year 2013 with a share of 2.03 percent. The life insurance industry in India is projected to increase at a compound annual growth rate (CAGR) of 12-15 per cent in the next five years. The industry has the potential to top the US$ 1 trillion mark over the next seven years (IBEF, 2014). According to Insurance Regulatory & Development Authority (IRDA), insurance services sector grew by 8.6 percent and the total premium for the life insurance sector was Rs. 2.87 lakh crore (IRDA Annual Report 2012 -13). With most life insurance companies offering similar policies, product differentiation is tough in increasingly competitive market. As a result, Insurance companies in India are now moving from a productcentered approach to a customer-centered strategy. The focus is on enhancing customer satisfaction through improved service quality which leads to improved customer retention, loyalty and profitability. In order to survive and thrive in the competitive insurance industry, life insurers are actively engaged in developing new strategies for customer satisfaction through proper improvement of service quality. With increased awareness level, the consumers demand higher standard of services and insurance sector is getting more and more competitive. Customers are becoming increasingly aware of the options on offer in relation to the rising standards of service (Kris hnaveni et al, 2004). They demand better quality service. Delivering quality service is considered an essential strategy for success and survival in today's competitive environment (Dawkins and Reich held, 1990; Parasuraman et al., 1985; Reich held and Sasser 1990; Zeithaml et al., 1990). More specifically, the cost of retaining existing customers by enhancing the products and services that are perceived as being important is significantly lower than the cost of winning new customers (Krishnan et al, 1999). Hence, to remain competitive, Life insurance companies need to focus on service quality. Studies have shown that it costs six times more to attract new customers than to retain the existing ones (Rosenberg & Czepiel, 1983). It has also been suggested that service quality has a direct effect on organizations' profits as it is positively associated with customer retention and customer loyalty (Baker & Crompton, 2000;Zeithaml & Bitner, 2000). Customer dissatisfaction has been found to have a greater psychological impact and a greater longevity compared to good experiences. As per estimates, two out of three times an unhappy customer will speak about a bad experience than relate to a good experience. Hence, there is a multiplier effect of poor service hurting not just the bottom line of an insurance company but bringing additional costs of losing potential customers in addition to existing ones. The purpose of the present study is to measure customer's perception towards service quality of life insurance companies. The framework developed by Tsoukatos and Rand, (2006), Durvasula et al. (2004) and Mittal et al. (2013) has been used to find out customer's perception towards service quality dimensions of Life Insurance providers. # II. # Literature Review a) Service Quality Extensive research has been undertaken on different aspects of service quality providing a sound conceptual foundation. Authors (Parasuraman et al., 1988;1991;Carman, 1990) agree that service quality is an abstract and elusive concept, difficult to define and measure. Empirically, various service quality models and instruments have been developed for measuring service quality. According to Gronroos (1982), there are two dimensions of customer's perceptions of any service, namely technical quality (what is provided) and functional quality (how the service is provided). Sasser et al. (1978) suggested three different attributes (levels of material, facilities, and personnel) all dealing with the process of service delivery. Subsequently, Gronroos (1990) identified six specific dimensions viz., professionalism and skills, reliability and trustworthiness, attitudes and behavior, accessibility and flexibility, recovery, and reputation and credibility, on which service quality could be measured. Lehtinen and Lehtinen (1982) discussed three dimensions viz., physical quality, involving physical aspects; corporate quality, involving a service firm's image and reputation; and interactive quality, involving interactions between service personnel and customers. Perceived service quality has been defined as a global judgment or attitude relating to the superiority of a service (Zeithaml and Bitner, 2000). There are three types of customer expectations predicted service, desired service, and adequate service which presents a comparison between customer evaluation of service quality and customer satisfaction (Valerie A. Zeithaml, Lonard L. Berry, and A. . It has been found that investments in service quality, customer satisfaction and customer relationships result in increased profitability and market share (Rust and Zahorik, 1993). High-quality service and customer satisfaction often lead to more repeat purchases and market share improvements (Buzzell and Gale, 1997). Service quality is one of the effective means in building a competitive position in the service industry (Lewis, 1991). Customer satisfaction leads to customer loyalty and this leads to profitability (Hallowell, 1996). The most widely used service quality measurement tools include SERVQUAL (Parasuraman et al.,1988;Boulding et al., 1993) and SERVPERF (Cronin and Taylor, 1992). The SERVQUAL model suggests that service quality can be measured by identifying the gaps between customers' expectation and perceptions of the performance of the service using 22 items and five-dimensions: reliability, assurance, tangible, empathy, and responsiveness. In the SERVPERF scale, service quality is measured through performance on score based on the same 22 items and five dimensional structure of SERVQUAL. The SERVQUAL have been used to measure service quality in the insurance industry (Stafford et al., 1998 Experts have claimed that the number of service dimensions is dependent on the particular service being offered. According to Babakus and Boller (1992), the domain of service quality may be factorially complex in some industries and very simple and uni-dimensional in others. The SERVQUAL scale has been presented in different dimensions in various studies -singledimensional (Babakus et al., 1993;Lam, 1997) (Headley and Miller, 1993), seven-dimensional (Sasser et al., 1978;Freeman and Dart, 1993), nine-dimensional (Carman, 1990), and nineteen-dimensional (Robinson and Pidd, 1998) construct. Also, several scales have been replicated, adapted and developed to measure services by taking SERVQUAL as a base, viz., SERVPERF Taylor, 1992, 1994) for hotels, clubs and travel agencies; DINESERV (Stevens et al., 1995) for food and beverage establishments; LODGSERV (Knutson et al., 1990) for hotels; SERVPERVAL (Petrick, 2002) for airlines; SITEQUAL (Yoo and Donthu, 2001) for Internet shopping; E-S-QUAL (Parasuraman et al., 2005) for electronic services; SELEB (Toncar et al., 2006) for educational services; HISTOQUAL (Frochot and Hughes, 2000) for historic houses; LibQUAL (Cook et al., 2001) for library ; and ECOSERV (Khan, 2003) for ecotourism. # b) Service Quality in Life Insurance Life insurance is a high credence service (Lynch and Mackay, 1985), very abstract, complex and focused on future benefits that are difficult to prove (financial protection etc.). Life insurance products provide very little signs to signal quality. It has been suggested that consumers usually rely on extrinsic signs like brand 20 # Global Journal of Management and Business Research Volume VII Issue IX Version I Year ( ) image to ascertain and perceive service quality (Gronroos, 1982). Customer satisfaction in insurance is both difficult to measure and ascertain. The future benefits of the "product" purchased are difficult to foresee and take a long time to "prove" its effects (Crosby and Stephens, 1987). An extended period of time may be required in this industry for a fully informed evaluation (Devlin, 2001). As the premium amount typically invested in an insurance policy is high, customers seek long-term relationships with their insurance companies and respective agents in order to reduce risks and uncertainties (Berry, 1995). Research have indicated that the key parameters, e.g. past experience, personal needs, external communication, word of mouth, and active clients significantly influence service quality of the insurance sector (Barkur et al., 2007). In Indian context, measuring service quality on six dimensions, namely assurance, competence, personalized financial planning, corporate image, tangibles and technology dimensions, it was found that the priority areas of service were assurance followed by competence and personalized financial planning (Siddique & Sharma, 2010). Perceived service quality of life insurance services is a multi-dimensional secondorder construct consisting of the primary dimensions of Service Delivery, Sales Agent Quality, Tangibles, Value and Core Service (Mittal et al. 2013). Cultural factors were found to have significant influence on the expectation on service quality in Indian Insurance market (Meharajan and Vanniarajan, 2011). Three factors namely, proficiency; physical and ethical excellence; and functionality were found to have significant impact on the overall service quality of Life Insurance Corporation of India in a study based on seven-factor construct (Sandhu and Bala, 2011). Strong relationship is found between satisfaction level and the service quality dimensions (Gayathri et al., 2005). Perceived service quality and customer satisfaction are dependent on information technology (Choudhuri, 2014). SERVQUAL construct cannot be applied to Indian Life Insurance sector and further research is needed to understand and improve life insurance service quality within Indian context (Bala et al., 2011). Demographic variables are related to eight service service quality factors namely, employee competence, creditability, timeliness and promptness, convenience, accessibility, communication, customer orientation and responsiveness (Bishnoi and Bishnoi, 2013). Product innovation, increased interaction level between agents and customers and technological upgradation affect the service quality perceptions of Life Insurance policyholders in Northern India (Chawla and Singh, 2008). An insurance policy is almost always sold by an agent who, in most cases, is the customer's only contact (Richard and Allaway, 1993; Clow and Vorhies, 1993; Crosby and Cowles, 1986). Customers are, therefore, likely to place a high value on their agent's integrity and advice (Zeithaml et al., 1993). Service quality depends to a large extent on the information gathering and processing activities of agents (Eckardt and Doppner, 2010). The quality of the agent's service and strength of his relationship with the customer play a major role in customer purchasing the life insurance product. Putting the customer first, and, exhibiting trust and integrity have found to be essential in selling insurance (Slattery, 1989). According to Sherden (1987), high quality service (defined as exceeding "customers' expectations") is rare in the life insurance industry but increasingly demanded by customers. In Insurance Industry, high retention rates are closely related to the economic performance of companies (Diacon and O Brien, 2002). The insurance industry considers that understanding consumer behaviour after the initial purchase will help insurers to maintain longer customer-insurer relationship (Harrison, 2003). Toran (1993) points out that quality should be at the core of what the insurance industry does. Customer surveys by Prudential have identified that customer want more responsive agents with better contact, personalized communications from the insurer, accurate transactions, and quickly solved problems (Pointek, 1992). A different study by the National Association of Life Underwriters highlighted other important factors like financial stability of the company, insurer's reputation, integrity of agent and the quality of information and guidance from the agent (King, 1992). Clearly, understanding consumers' expectations of life insurance agent's service is crucial as expectations serve as standards or reference points against which service performance is assessed (Walker and Baker, 2000). In a study conducted in Germany, the duration of counseling interviews is found to be the single most important factor that has a positive effect both on the information quality and on the total service quality provided (Eckardt and Doppener, 2010). Consumers tend to rate service quality higher if they are aware of their right to complain to the regulator (Wells and Stafford, 1995). Technology has also become an important factor in how the agent operates in the field including other functions such as distribution, claim costs and administration (Anonymous, 2004). Communication, ICT, customer's knowledge and prior experience influence the service quality in insurance industry (Saad et al., 2014). Research has shown that the quality of service and the achievement of customer satisfaction and loyalty are fundamental for the survival of insurers. The quality of after sales services, in particular, can lead to very positive results through customer loyalty, positive word-of-mouth, repetitive sales and cross-selling (Taylor, 2001). However, many insurers appear unwilling to take the necessary actions to improve their image. This creates problems for them as the market is # Global Journal of Management and Business Research Volume VII Issue IX Version I Year ( ) extremely competitive and continuously becomes more so (Taylor, 2001). Previous studies, notably those of Wells and Stafford (1995), the Quality Insurance Congress (QIC) and the Risk and Insurance Management Society (RIMS) (Friedman, 2001a(Friedman, , 2001b)), and the Chartered Property Casualty Underwriters (CPCU) longitudinal studies (Cooper and Frank, 2001), have confirmed widespread customer dissatisfaction in the insurance industry, stemming from poor service design and delivery. Ignorance of customers' insurance needs (the inability to match customers perceptions with expectations), and inferior quality of services largely account for this. The American Customer Satisfaction Index shows that, between 1994 and 2009, the average customer satisfaction had gone down by 2.5% for life insurance. However, post 2010 till 2014 there have been continuous improvement in the index as Insurers are now realizing the importance of service quality and its impact on customer satisfaction (www.theacsi.org, 2014). It is therefore not surprising that measurement of service quality has generated, and continues to generate, a lot of interest in the industry (Wells and Stafford, 1995). Several metrics have been used to gauge service quality. In the United States, for example, the industry and state regulators have used "complaint ratios" in this respect (www.dfs.ny.gov, 2014). The "Quality Score Card", developed by QIC and RIMS, has also been used. However, both the complaints ratios and the quality scorecards have been found to be deficient in measuring service quality and need for a more robust metric is strongly felt. Although service quality structure is found rich in empirical studies on different service sectors, service quality modeling in life insurance services is not adequately investigated. Further, for service quality modeling, a set of dimensions is required, but there seems to be no universal dimension; it needs to be modified as per the service in consideration. Thus, the dimensions issue of service quality requires reexamination in context of life insurance services. # III. # Objectives of the Study The objective of the study was to find out the factors that affect the service quality of Life Insurance providers. It also studied the effect of demographic factors on customer perception and service delivery. In order to achieve these objectives, the following hypotheses have been formulated: H o1 -There is no relationship between the age of respondents and perception of service quality of Life Insurance providers H o2 -There is no relationship between the gender of respondents and perception of service quality of Life Insurance providers H o3 -There is no relationship between the education level of respondents and perception of service quality of Life Insurance providers H o4 -There is no relationship between the income of respondents and perception of service quality of Life Insurance providers IV. # Research Methodology a) Data Collection Method The main instrument used for data collection in this research was the questionnaire. The responses have been collected through online survey using google docs and email. Prior to the final survey, the questionnaire was pre tested using a sample of respondents similar in nature to the final sample. The goal of pilot survey was to ensure readability and logical arrangements of questions. The questionnaire was sent to 25 respondents having a life insurance policy through email. The responses of pilot study were thoroughly analyzed. The questionnaire was reviewed in light of comments and shortcomings and then it was revised accordingly. The final questionnaire was uploaded on Google docs and the link was sent to 200 customers and 139 usable responses were received, thereby making a response rate of 69.5%. The perception of the respondents towards the service delivery quality was gauged using a questionnaire containing close-ended questions, which were designed to ascertain perception of the respondents using a five point Likert scale with following options: Highly Agree, Agree, Neutral, Disagree and Highly Disagree. # c) Research and Statistical Tools Employed The research and statistical tools employed in this study are factor analysis and correlation. SPSS 16 was used to perform statistical analysis. The reliability of the data was carried out by using Cronbach's Alpha Value. The factor analysis was used to examine the underlying or latent dimensions within variables of overall customer perception (Hair et al, 1998). Both Bartlett's test of spherecity and measure of sampling adequacy (MSA) were also carried out to ensure that the requirements of factor analysis were met. V. # Data Analysis and Interpretation The analysis of this data was divided into following section: # a) Demographic profile of Respondents The respondent profile as displayed in table 2 indicates the current scenario of life insurance sector and its user's profile. Most of the respondents (75.5%) were males and post-graduate (89.2%). Majority of respondents are in the age group of 25-35 years (42.4%) and between 35-50 years (43.2%). Most of the respondents have income above 5 laksh (5-10 lakhs at 25.2% and above 10 lakhs at 30.9%). The profile of respondents indicates they are young, urban, educated and have high income which is a right demographic composition from life insurance provider's context. # Global Journal of Management and Business Research Volume VII Issue IX Version I Year ( ) The study highlighted that majority of respondents hold a policy by Life Insurance Company (49.6%) followed by ICICI Pru (10.8%). This is in line with market share position of major insurers in India with LIC leading at 72.7% share followed by ICICI Pru at 4.7% market share. The lowest number of respondents had a policy from Kotak Mahindra (1.4%) followed by Aegon Religare (2.2%). 4 shows the result of reliability analysis-Cronbach's Alpha Value. This test measured the consistency between the survey scales. The Cronbach's Alpha score of 1.0 indicate 100 percent reliability. Cronbach's Alpha scores were all greater than the Nunnaly's (1978) generally accepted score of 0.7. In this study, the score was 0.871 for the service quality provided by the life insurance companies. Overall, the set of data meets the fundamental requirements of factor analysis satisfactorily (Hair et al, 1998). In analyzing the data given, the 20 response items were subjected to a factor analysis using the principal component method. Using the criteria of an Eigen value greater than one, four clear factors emerged accounting for 73.71% of the total variance. As in common practice, a Varimax rotation with Kaiser Normalization was performed to achieve a simpler and theoretically more meaningful factor solution. The Cronbach's alphas score for all the factors was 0.871 (Table 4). # Global Journal of Management and Business Research Volume VII Issue IX Version I Year ( ) It is clear from the factor loadings as highlighted in Table 6 that clear four factors have emerged representing 73.71% of total variance. These four factors represent different elements of services quality that form the underlying factors from the original 20 scale response items. Referring to the Table 6 above, first factor represents elements of the service quality directly related to responsiveness and assurance; it is therefore labeled "Responsiveness and Assurance Factors". These elements are timely service, agent's recommendation, timely claim, sympathy, courteous behavior of employees, individual attention to customers, wide range service and availability of adequate information. Second factor is directly related to convenience provided to customers, it is therefore labeled as "Convenience Factors". These elements are agent's communication skills, agent's trust, premium rates, convenient location and convenient working hours. Third factor is directly related to tangibility of services and therefore named as "Tangible Factor". These elements are modern office, attractive office, employee's dress and understanding of customer needs. Fourth factor represent empathy, therefore it is named as "Empathy Factor". These elements are best interest of customers, availability of employee assistance and trustworthiness of employees. # e) Correlation To measure the impact of demographic factors on customer perception of service quality of life insurers, correlation technique was used. Table 7 shows the correlation between age and the 20 items of service quality. Since in case of majority of attributes of service quality the significance level is lower than .05, we reject the null hypothesis (Ho1) that there is no relationship between the age of respondents and perception of service quality of Life Insurance providers. In other words, the age has significant relationship which determines the service quality perception. Similar findings were there in the study of Bishnoi and Bishnoi (2013). Table 8 shows the correlation between gender and service quality. Since in case of majority of attributes of service quality the significant level is greater than .05, we accept the null hypothesis (Ho2) that there is no relationship between the gender of respondents and perception of service quality of Life Insurance providers. In other words, gender does not affect the service quality perception and both male and female customers share similar perception towards service quality of life insurers. 9 shows the correlation between educational qualification and service quality. Since in case of majority of attributes of service quality the significant level is greater than .05, we accept the null hypothesis (Ho3) that there is no relationship between the education level of respondents and perception of service quality of Life Insurance providers. In other words, education does not affect the service quality perception. If we look at the demographic profile we find that majority of the respondents are post-graduates (89.2%) and have the knowledge about the different life insurance products. Similar response may be there in other metro cities of India. Table 10 shows the correlation between income levels and service quality. Since in case of majority of attributes of service quality the significant level is greater than .05, we accept the null hypothesis (Ho3) that there is no relationship between the income level of respondents and perception of service quality of Life Insurance providers. In other words, income does not affect the service quality perception. If we look at the demographic profile we find that majority of the respondents (56.1%) have high income (above 5 lakh). # Discussion The research examined the impact of different demographic characteristics on customer perception of service quality of life insurance providers. The factor analysis has brought four clear factors related with the service quality of life insurers. These factors are Responsiveness and Assurance Factors, Convenience Factors, Tangible Factors and Empathy Factors. These factors represent 73.71% of total variance. The life insurers may take note of these factors which significantly determines the customer's perception of service quality. They may take care of these factors and ensure proper availability of tangible factors which will positively enhance the customer perception of service quality. The test of correlation between demographic characteristics and service quality parameters have found out that the age of respondents significantly determine the customer perception of service quality of life insurance companies. Therefore, the life insurance providers may keep in mind the age factor while designing their product offerings and promotions. The other demographic characteristics such as gender, education and annual income does not have significant impact on customer perception towards service quality of life insurance providers. The study has been carried out in the metropolitan area of Delhi NCR. The findings can be generalized for other metropolitan areas as the demographic profile of major metropolitan cities shows similar trends. The managers of life insurance service providers can use these findings to further improve their product offering and marketing strategies incorporating these findings. This will help them to enhance their brand image as well as customer loyalty and retention resulting in increased sales of their products. The managers of life insurance industry may utilize the findings of this study to minimize the service quality gap caused by the difference between the customer's actual expectation and the management's estimation of customer's expectations. Similar research can be carried out by the life insurance providers for rural and semi-urban areas so that the reach of these companies can be expanded into the majority of Indian population. ![b) Development of Research Instrument In order to develop a questionnaire, in depth literature review on service quality dimension in Life Insurance sector was carried out. The constructs of the questionnaire are based on the framework developed by Tsoukatos and Rand, (2006), Durvasula et al. (2004) and Mittal et al. (2013).](image-2.png "") 1Year22Volume VII Issue IX Version I)(Global Journal of Management and Business ResearchItem My Life Insurer has best interest of customers at heart My Life Insurer's employees are available for assistance My Life Insurer provides services in timely manner My Life Insurer's employees are trustworthyCode SQ1 SQ2 SQ3 SQ4My Life Insurer's agents recommend policy as per customer needsSQ5My Life Insurer's agents have good communication skillsSQ6My Life Insurer's agents are trustworthySQ7 2DemographicCharacteristics Freq.%FactorsAge25-35 years5942.435-50 years6043.250 aboveyears&2014.4GenderMale10575.5Female3424.5EducationalGraduate1510.8QualificationPost Graduate12489.2Annual IncomeUpto 2 lakhs2014.42-5 lakhs4129.55-10 lakhs3525.2Above 10 lakhs4330.9Total139100b) Respondent's Share of Life Insurers 3InsurerFrequencyPercentLIC6949.6ICICI Pru1510.8HDFC Life64.3Birla Sun life42.9SBI Life107.2Reliance Life42.9Tata AIA42.9Max Life42.9Bajaj Allianz85.8Kotak Mahindra21.4Aegon Religare32.2Others107.2Total139100.0c) Reliability and ValidityTable 4d) Factor AnalysisCronbach's AlphaN of Items.87120 5Kaiser-Meyer-Olkin Measure of Sampling Adequacy..830Bartlett's Test of SphericityApprox. Chi-Square2556.710df190Sig..000Table 6 : Rotated Component MatrixRotated Component Matrix aComponent1234SQ1.212-.002.389.755SQ2.261.103.015.737SQ3.534.455.263.094SQ4.571.201-.006.648SQ5.643.165.569.025SQ6.346.652.379-.181SQ7.321.726.226.007SQ8.201.353.811-.103SQ9.055.112.836.286SQ10.125.391.723.341SQ11.299.776.180.205SQ12.136.881.113.176SQ13.219.806.283.123SQ14.691.280.075.426SQ15.720.263.266.212SQ16.711.083.279.327SQ17.492.296.445.316SQ18.509.304.619-.032SQ19.703.391.125.273SQ20.771.337.021.201 7SQ1SQ2SQ3SQ4SQ5PC-0.160-0.072-0.2640.157-0.370Sig.0.0600.3990.0020.0650.000SQ6SQ7SQ8SQ9SQ10PC-0.329-0.223-0.421-0.271-0.195Sig.0.0000.0080.0000.0010.021SQ11SQ12SQ13SQ14SQ15PC-0.125-0.130-0.2650.020-0.258Sig.0.1430.1280.0020.8190.002SQ16SQ17SQ18SQ19SQ20PC0.069-0.282-0.333-0.127-0.018Sig.0.4220.0010.0000.1350.833PC = Pearson CorrelationSig. = Significance (2-tailed) 8Year26Volume VII Issue IX Version I)(Global Journal of Management and Business ResearchPC Sig. PC Sig. PC Sig.SQ1 -0.124 0.145 SQ6 0.129 0.131 SQ11 -0.063 0.465 SQ16SQ2 0.046 0.593 SQ7 0.079 0.357 SQ12 -0.101 0.236 SQ17SQ3 0.112 0.189 SQ8 0.084 0.327 SQ13 -0.081 0.341 SQ18SQ4 -0.163 0.055 SQ9 -0.106 0.214 SQ14 -0.219 0.010 SQ19SQ5 0.077 0.367 SQ10 -0.025 0.774 SQ15 -0.194 0.022 SQ20PC-0.005-0.1640.194-0.0590.096Sig.0.9490.0530.0220.4870.260PC = Pearson CorrelationSig. = Significance (2-tailed) 9SQ1SQ2SQ3SQ4SQ5PC0.1230.0540.1220.289-0.019Sig.0.1480.5270.1530.0010.825SQ6SQ7SQ8SQ9SQ10PC0.0360.1720.1190.2280.306Sig.0.6710.0430.1640.0070.000SQ11SQ12SQ13SQ14SQ15PC0.0620.073-0.0060.0860.109Sig.0.4660.3910.9420.3110.202SQ16SQ17SQ18SQ19SQ20PC0.2090.0420.3000.1530.069Sig.0.0140.6230.0000.0730.421PC = Pearson CorrelationSig. = Significance (2-tailed) 10YearVolume VII Issue IX Version I( )PC Sig. PC Sig. PC Sig.SQ1 0.057 0.504 SQ6 0.097 0.255 SQ11 .176* 0.038 SQ16SQ2 -0.062 0.467 SQ7 0.116 0.172 SQ12 .321** 0.000 SQ17SQ3 -0.093 0.279 SQ8 -0.133 0.117 SQ13 0.045 0.601 SQ18SQ4 .259** 0.002 SQ9 -.182* 0.032 SQ14 .307** 0.000 SQ19SQ5 -0.068 0.425 SQ10 0.011 0.896 SQ15 .181* 0.033 SQ20Global Journal of Management and Business ResearchPC0.1080.099-0.0980.128.230**Sig.0.2050.2480.2520.1320.006PC = Pearson CorrelationSig. = Significance (2-tailed)** = Correlation is significant at the 0.01 level (2-tailed). * = Correlation is significant at the 0.05 level (2-tailed). © 2014 Global Journals Inc. (US) 1 © 2014 Global Journals Inc. (US) * American Customer Satisfaction Index 2014 * Seizing the initiative Anonymous Life Insurance International 2004. April * An empirical assessment of the SERVQUAL scale EBabakus GWBoller Journal of Business Research 24 3 1992 * Empirical examination of a direct measure of perceived service quality using SERVQUAL items EBabakus DLPedrick MInhofe 1993 TN Memphis State University unpublished manuscript * Quality, Satisfaction and Behavioral Intentions DBaker JCrompton International Journal of Economics and Finance 2 4 2000 Annals of Tourism Research. * Measuring Life Insurance Service Quality: An Empirical Assessment of SERVQUAL Instrument NBala HSSandhu NNagpal International Business Research 4 4 2011 * Insurance sector dynamics: towards transformation into learning organization GBarkur KV MVarambally LL RRodrigues The Learning Organization 2007 14 * Relationship marketing of services-Growing interest, emerging perspectives LLBerry Journal of the Academy of Marketing Science 23 1995 Fall * Service Quality of Life Insurance Companies VKBishnoi MBishnoi BVIMR Management Edge 6 1 2013 * A Dynamic Process Model of Service Quality: From Expectations to Behavioural Intentions WBoulding AKarla RStaelin VAZeithaml Journal of Marketing Research 30 1 1993 * Measuring service quality in the car service industry: building and testing an instrument MBouman TVan Der Wiele International Journal of Service Industry Management 3 4 1992 * RDBuzzell BTGale The PIMS Principles: Linking Strategy to Performance New York Free Press 1997 * Consumer perceptions of service quality: An assessment of the SERVQUAL dimensions JMCarman Journal of Retailing 66 1990 * Service Quality Perceptions of Life Insurance Policyholders in Northern India: Pre-privatization vs. Postprivatization SChawla FSingh The ICFAI University Journal of Marketing Management 4 2008 * Information Technology enabled Service Quality Model for Life Insurance Services PSChoudhuri International Journal of Management 5 2014 * Building a Competitive Advantage for Service Firms KFClow DWVorhies Journal of Services Marketing 7 1 1993 * Users' Perceptions of Library Service Quality: A LibQUAL+? Qualitative Study CCook FHeath Library Trends 49 4 2001 * Key ethical issues facing the property and casualty insurance: References Références Referencias has a decade made a difference? RWCooper GLFrank Journal 54 2 2001 * SERVPERF versus SERVQUAL, reconciling performance-based and perceptions-minus-expectations measurement of service quality JJCronin SATaylor Journal of Marketing 58 1994. January * Measuring Service Quality: A Reexamination and Extension JJCroninJr SATaylor Journal of Marketing 56 3 1992 * Life Insurance Agents as Financial Planners: A Matter of Role Consensus LACrosby DCowles Journal of Professional Services Marketing 1 1986 * Effects of relationship marketing on satisfaction, retention, and prices in the life insurance industry LACrosby NStephens Journal of Marketing Research 24 1987. November * Consumer as a Competitive Weapon PDawkins FReichheld Directors and Boards 14 1990 * Department of Financial Services New York State * Consumer Evaluation and Competitive Advantage in Financial Services: a Research Agenda JDevlin European Journal of Marketing 35 2001 * Persistency in UK longterm insurance: Customer satisfaction and service quality SDiacon CO'brien 2002 Nottingham CRIS Discussion Papers, III, University of Nottingham * Forging relationships with services: The antecedents that have an impact on behaviourial outcomes in the life insurance industry SDurvasula SLysonski SMehta BPeng Tang Journal of Financial Services Marketing 8 4 2004 * The Quality of Insurance Intermediary Services -Empirical Evidence from Germany MEckardt SRDoppner The Journal of Risk and Insurance 77 3 2010 * Service quality in Cretan accommodations: marketing strategies for the UK holiday market YEkinci PProkopaki CCobanoglu International Journal of Hospitality Management 22 1 2003 * Quality improvement in the Greek and Kenyan insurance industries TEvangelos MSimmy RKGraham archives of economic history 16 2 2004 * Measuring the perceived quality of professional business services KDFreeman JDart Journal of Professional Services Marketing 9 1 1993 * RIMS plans to have third quality SFriedman National Underwriter 18 2001a. 2002 * RIMS launches quality process SFriedman National Underwriter 19 2001b * HISTOQUAL: the development of a historic houses assessment scale IFrochot HHughes Tourism Management 21 2 2000 * Customer expectations and perceptions of service quality in apparel retailing KBGagliano JHathcote Journal of Services Marketing 8 1 1994 * A pilot study on the service quality of insurance companies HGayathri MCVinaya KLakshmisha Journal of Services Research 5 2 2005 * Customer satisfaction with service quality in the life insurance industry in India PGoswami ICFAI Journal of Services Marketing 5 1 2007 * Service Management and Marketing CGronroos 1990 Lexington Books, Lexington, MA * A service-oriented approach to marketing of services CGronroos European Journal of Marketing 12 8 1982 * Multivariate Data Analysis JFHairJr REAnderson RLTatham WCBlack 1998 Prentice Hall Upper Saddle River, NJ 5th Edition * The relationships of customer satisfaction, customer loyalty, and profitability: an empirical study RHallowell International Journal of Service Industry Management 7 4 1996 * Understanding the behaviour of financial services consumers: a research agenda THarrison Journal of Financial Service Marketing 8 1 2003 * Measuring service quality and its relationship to future consumer behavior DEHeadley SJMiller Insurance Regulatory and Development Authority 13 4 1993. 2014. 2014 Journal of Health Care Marketing * Measuring service quality in the hotel industry: evidence from Northern Cyprus OMKaratepe TAvci Anatolia: An International Journal of Tourism and Hospitality Research 13 1 2002 * ECOSERV: ecotourists quality expectations MKhan Annals of Tourism Research 30 1 2003 * The applicability of SERVQUAL in crossnational measurements of health-care quality WEKilbourne JADuffy MDuffy GGiarchi Journal Of Services Marketing 18 6 2004 * Agents/policy owners split on service CKing National Underwriter 7 1992. October * LODGSERV, a service quality index for the lodging industry BKnutson PStevens CWullaert FYokoyoma Hospitality Research Journal 14 2 1990 * Customer Satisfaction for Financial Services: The Role of Products, Services, and Information Technology MSKrishnan VenkatramRamaswamy MaryCMeyer PaulDamien Management Science 45 9 1999 * RKrishnaveni DDivya Prava 2004 * Measuring Service Quality in Banking Sector Prajnan: Jr. of Social and Management Sciences 23 1 * SERVQUAL: a tool for measuring patients opinions of hospital service quality in Hong Kong SS KLam Total Quality Management 8 4 1997 * Service quality: a study of quality dimensions JLehtinen ULehtinen 1982 Helsinki Unpublished working paper, Service Management Institute * The interactive approach to service quality and management MRLeste WVittorio 1997 * Deuxième Congres International Franco-Quebecois de Génie Industriel 1997 ALBI * Service quality: an international companion of bank customers' expectations and reception BRLewis Journal of Marketing Management 7 1991 * Life Insurance Products and Consumer Information MichaelPLynch Robert Mackay 1985 Washington DC US Government Printing Office FTC Staff Report * Cultural Influences on GIQUAL: An Empirical Study in Insurance Sector TMeharajan TVanniarajan Global Management Review 5 2011 * MSS, MSA and zone of tolerance as measures of service quality: A Study of the Life Insurance Industry SCMehta ALobo Second International Services Marketing Conference 2002 University of Queensland * Analysing service quality in the hospitality industry AW OMei AMDean CJWhite Managing Service Quality 9 2 1999 * Developing and Testing a Hierarchical Model of Customer Perceived Service Quality for Life Insurance Services SMittal RGera SRSinghvi Asia-Pacific Journal of Management Research and Innovation 9 2013 * Diagnosing the zone of tolerance for hotel services HNadiri KHussain Managing Service Quality 15 3 2005 * E-S-QUAL: a multiple-item scale for assessing electronic service quality JNunnaly AParasuraman VZeithaml AMalhotra Journal of Service Research 64 3 1978. 2005 McGraw-Hill Psychometric theory * Refinement and reassessment of the SERVQUAL scale AParasuraman LLBerry VAZeithaml Journal of Retailing 67 4 1991 * A conceptual model of service quality and its implications for further research AParasuraman VAZeithaml LLBerry Journal of Marketing 48 1985 * Multipleitem scale for measuring consumer perceptions of service quality AParasuraman VAZeithaml LLBerry Journal of Retailing 64 1 1988 * Development of a multidimensional scale for measuring the perceived value of a service JFPetrick Journal of Leisure Research 34 2 2002 * Outside interests: Making the move from lip service to real service SPointek National Underwriter 44 34 1992 * Zero defections: quality comes to services FFReichheld WESasser Harvard Business Review 1990. Sept.-Oct. * Service Quality Atrributes and Choice Behaviour MDRichard AWAllaway Journal of Services Marketing 7 10 1993 * Provider and customer expectations of successful simulation projects SRobinson MPidd Journal of the Operational Research Society 49 3 1998 * A Marketing Approach for Consumer Retention LRosenberg JCzepiel Journal of Consumer Marketing 1 1983 * Customer satisfaction, customer retention and market share RTRust AJZahorik Journal of Retailing 69 2 1993 * Antecedents of Service Quality in Insurance Industry AMSaad RZYusoff RIslam Advances in Natural and Applied Sciences 2014 8 * Customers' Perception towards Service Quality of Life Insurance Corporation of India -A Factor Analytic Approach HSSandhu NBala International Journal of Business and Social Science 2 18 2011 * Management of service operations WESasser RPOlsen DDWyckoff 1978 Allyn and Bacon Boston, MA * The erosion of service quality WSherden Best's Review 88 5 22 1987 * Measuring the customer perceived service quality for life insurance services: an empirical investigation MasoodHSiddiqui VKhand TGSharma International Business Research 2010 * Special report: Nichols: we've forgotten the consumer TSlattery National Underwriter 48 11 1989. November * Determinants of service quality and satisfaction in the auto casualty claims process MRStafford TFStafford BPWells Journal of Services Marketing 12 1998 * DINESERV: a tool for measuring service quality in restaurants PStevens BKnutson MPatton Cornell Hotel and Restaurant Administration Quarterly 36 2 1995 * Assessing the use of regression analysis in examining service recovery in the insurance industry: relating service quality, customer satisfaction and customer trust SATaylor Journal of Insurance Issues 24 1 2001 * Uniform assessment of the benefits of service learning, the development, evaluation, and implementation of the SELEB scale MFToncar JSReid DJBurns CEAnderson HPNguyen Journal of Marketing Theory and Practice 14 3 2006 * Quality service (quality everything!) DToran 1993 12 LIMRA'S Market Facts * Path analysis of perceived service quality, satisfaction and loyalty in Greek insurance. Managing Service Quality ETsoukatos GKRand 2006 16 * The nature and determinants of customer expectations of service ValerieAZeithaml LonardLBerry AParasuraman Journal-of-the-Academy-of-Marketing-Science. Winter 1993 * v21n1 * An exploratory study of a multi-expectation framework for services JWalker JBaker Journal of Services Marketing 14 5 2000 * Service quality in the insurance industry: Consumer perceptions versus regulatory perceptions BPWells MRStafford Journal of Insurance Regulation 13 1995 * Business-to-business selling determinants of quality KWWestbrook RMPeterson Industrial Marketing Management 27 1 1998 * Developing a scale to measure the perceived quality of internet shopping sites (SITEQUAL) BYoo NDonthu Quarterly Journal of Electronic Commerce 2 1 2001 * Services Marketing: Integrating Customer Focus Across the Firm VAZeithaml MJBitner 2000 McGraw-Hill New York, NY * The nature and determinants of customer expectations of service VAZeithaml LLBerry AParasuraman Journal of the Academy of Marketing Science 21 1 1993 * Delivering Quality Service ValerieAZeithaml AParasuraman LeonardLBerry 1990 The Free Press New York, N.Y