PREDICTORS OF CUSTOMER RETENTION IN ONLINE HEALTH CARE SYSTEM OHCS by iaemedu

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									 INTERNATIONAL JOURNAL OF MANAGEMENT (IJM)
  International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 –
  6510(Online), Volume 4, Issue 1, January- February (2013)
ISSN 0976-6502 (Print)
ISSN 0976-6510 (Online)
Volume 4, Issue 1, January- February (2013), pp. 243-257
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    PREDICTORS OF CUSTOMER RETENTION IN ONLINE HEALTH
    CARE SYSTEM (OHCS) - STRUCTURAL EQUATION MODELLING
                       (SEM) APPROACH

                                             1                         2
                          R. Thiru Murugan , Dr. J Clement Sudhahar
      1
          Ph. D Scholar, School of Business Leadership and Management, Karunya University,
                                   Coimbatore, Tamil Nadu, India.
           2
             Professor in Marketing Area , School of Business Leadership and Management,
                          Karunya University, Coimbatore, Tamil Nadu, India


  ABSTRACT

  Purpose
        The purpose of this study is to identify the predictors of customer trust and
  customer satisfaction, and to empirically test the relationship among customer trust,
  customer satisfaction, customer commitment and customer retention in online health care
  system in Indian context.

  Design/ Methodology and approach
         This paper stems from a conceptual framework grounded on the theory
  concerning customer trust and retention. The predictors of customer trust, customer
  satisfaction, customer commitment and customer retention in online health care are
  identified through literature support. After conceptual underpinnings, a questionnaire was
  developed and survey conducted among the patients of the Hospitals who use online
  health care system. To empirically test this, Exploratory Factor Analysis (EFA),
  Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM) were
  carried out. These analyses done through SPSS and AMOS software.

  Findings
           The study shows that Perceived usefulness, Information quality, Responsiveness,
  Security and User interface are predictors of customer trust and customer retention.
  It a l s o empirically prove the relationship between customer trust, customer satisfaction,
  customer commitment and customer retention happening through Online Health Care
  System in India.

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Research Limitations/ Implications
      The data is collected from just one district in Tamil Nadu. Further testing of the
proposed conceptual model across different sections of customer is needed to
determine the generalisability of this study s findings.

Practical Implications
       The online health providers shall concentrate these factors to give better service to
the people. This paper gives a suggestion to the government to have more number of
online health centres that saves time and cost of the people.

Keywords: Customer trust, customer commitment, customer retention, Online Health Care
System, Structural Equation Modelling

INTRODUCTION

       In the past two decades there are plenty of studies taken place in e-commerce and
customer retention. But in the burgeongoing digital world, studies in Online Health Care
System (OHCS) received very less attention from the researchers. OHCS can be a best
substitute for a country like India having very huge population and less number of
health professionals. OHCS will cut down the cost, and reduce the geographical
barriers. Increasingly, therefore, OHCS is unavoidable in this ever expanding internet era.
In this realm needless to emphasise that customer retention is paramount factor for
ensuring profitability and performance. Based on this seminal idea this research first
focuses on the predictor of customer trust and customer satisfaction. Second, it focuses on
unravelling the relationship among customer trust, customer satisfaction, customer
commitment and customer retention using Structural Equation Modelling (SEM).

CONCEPTUAL UNDERPINNINGS INFORMATION QUALITY (IQ)

        Information quality is measuring the quality of the e-commerce information. (Huan-
Ming Chuang and Chwei-Jen Fan, 2011). The quality of accurate information and
its presentation about the services offered by a service provider (Nusair and Kandampully,
2008). E-commerce information quality dimensions are                 accuracy,   Reliability,
completeness, interpretability and ease of understanding (Wang and Strong 1996). In
OHCS information quality delivered by service provider place a important role in customer
trust. Information quality is to deliver confidence and inspire trust in the OHCS
transactions. (Huan-Ming Chuang and Chwei-Jen Fan, 2011). Seyed et al, (2011) revealed
that information quality is the best predicting factor for trust attitude. OHCS information
quality leads to higher level of satisfaction (Bliemel and Hassanein, 2007).

RESPONSIVENESS

            Parasuraman et al. (1985) e x p l a i n e d t h a t R e s p o n s i v e n e s s r e f e r s t o t h e
w i l l i n g n e s s o f service providers to help customers and provide prompt service. Online
health care service needs immediate response (Wu, 2000, Thae Min Lee 2005) from the
service providers because it deals with human life. When problems occurred people always
expect from the service provider to handle the problems successfully (Parasuraman et
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al., (2005).It is important to the service provider to give prompt communication and timely
support (Kim et al., 2004) in the case of any questions or problems of the customers
(Semeijn et al, 2005, Moorman et al. 1993, Clement and Selvam 2009). This will lead to
reduce the distrust of the customer. OHCS responsiveness is positively related to customer
trust (Chao-Min Chiu et. al 2008, Kineta Hung et al., 2011).

USER INTERFACE (UI)

        Gummerus et al., (2004) define the user interface as the channel through which
customers are in contact with the OHCS system provider. The quality of user interface
have impact on customer satisfaction (Park and Kim, 2003). Alam and Yasin [2009]
echoed that when the customer feel better instructiveness thorough good user interface, it
will guide to make the customers satisfied. User interface have direct impact on customer
trust and customer satisfaction (Gummerus, et al., 2004)

PERCEIVED USEFULNESS (PU)
        Perceived Usefulness is defined as the degree to which a person believes that
using a particular system would enhance his or her transaction performance (Davis,
1989). Perceived usefulness has positive influence on customer satisfaction (Flavian and
Carlos 2006). Perceived usefulness has significant impact on trust in OHCS. Cyr
(2008) illustrated that perceived usefulness has a significant effect on customer loyalty
intention.

SECURITY
        OHCS have all the medical and personal data of the customer. Hence security is the
major concern for OHCS trust. The customer does not have panic about the confidentiality
while giving data about the ill. Because, security is closely associated with trustfulness of
online health providers. OHCS should encompass with low risk and high safety (Zhilin
Yang 2004). Security positively influences e-satisfaction (Szymanski and Hise 2000).
The perceived lack of security on in online health system is major a block (Balfour et
al., 1998). The main barrier to the development of online health care system is lack of
security as perceived by the customers.

CUSTOMER SATISFACTION
        Customer satisfaction is a measure which eases the organisation with abundant
information about customer retention, customer satisfaction helps the organisation to
develop a successful policies to bring good service to the customer (Shah Ankit, 2011). In
health care sector, organisations should focus on customer satisfaction to fulfil the
emotional and psychological needs of the customers (Pairot, 2008). In OHCS satisfied
customers have the will give repeat business to the organisation compare to the dissatisfied
customers (Soheila ghane et al. 2011). Customer satisfaction is a predictor of customer
retention (Janet Sim et al, 2006, Zeithaml, 2000, Garbarino and Johnson, 1999). It leads
to the organisation to build loyalty in the mindset of the customers and they pay less
attention to the competitors (Kotler, 2000). Yu (2007) analysed the impact of customer
satisfaction on customer retention, customer cost and customer profitability. Customer
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satisfaction have positive relationship with customer retention (Gummesson, 1987). Higher
satisfaction will lead to have long-term relationship with the organisation (Seyed et al, 2011).
Park and Kim (2003) and Chiou (2004) argued that customer commitment is a result of customer
satisfaction.

CUSTOMER TRUST

        A consumer's willingness to rely on the service provider and take action in
circumstances where such action makes the customer vulnerable to the service provider.
(Jarvenpaa and Tractinsky, 1999). In electronic commerce customer trust is also defined that
confidence in the reliability on a person or a system (Meng, 2004). Customer trust is closely
related to customer satisfaction and it is measured as antecedent of customer satisfaction
(Yau, 2007). Customer trust is a paramount for customer satisfaction (Gummerus, et. Al,
2004). In OHCS customer trust have direct impact on customer satisfaction. (Seyed et al,
2011 Flavian and Carlos 2006). Customer trust in health care is the key factor for organisational
performance (Gounaris et al. 2005). Trust is a latent construct for retention (Reichheld 1993;
Ranaweera and Prabu, 2003). Pavlou and Fygenson (2006) illustrated through their research
that trust plays a important role in driving customer repurchase intention. Gummesson,
(1987), Teichert and Rost (2003), Garbarino and Johnson, (1999), Yau, (2007) and
Zeithaml, (2000) found that trust has positive relationship with customer retention and
also it is a key element of customer retention. Trust has strong relationship with customer
commitment (Yau, 2007).

CUSTOMER COMMITMENT

        Commitment is defined as a psychological attachment or an affective attachment
which produced an enduring wish to uphold long-term relationships. (Fullerton, 2005, Morgan
and Hunt, 1994). Moorman et al., (1993) explained that commitment means that customer in a
relationship feels motivated to some extent to do business with service provider.
Commitment is positively related to repurchase intentions (Fullerton, 2005). Commitment in
an e-commerce goes beyond satisfaction and commitment is a crucial predictor of retention
(Gustafsson et al. 2005 and Wilson, et al, 1995). Health care services performance
depends on the relationship with the customer. Commitment guides to maintain long-
term relationships between the services provider and the customer (Wilson et al. 1995). In
OHCS committed customers give positive feedback about the service providers to others
(Gustafsson et al. 2005). Gummesson, (1987) and Zeithaml, (2000) reveals that commitment
have positive effects on customer behavioural intention and retention.

CUSTOMER RETENTION

        Zeithaml, (2000) Retention referred to a service provider s capability adapt the
                                                                      ‟
existing customers into repeat customers to ensure long-term relationship. “Deeply
held commitment to rebuy or repatronize a preferred product or service consistently in the
future, despite situational influences and marketing efforts having the potential to cause
switching behaviour” (Oliver, 1999). In service industry cost of acquiring new customer is
higher than retaining a current customer (Anonymous, 1997, Reichheld and Sasser (1990).
Customer retention is directly affecting profitability (Kotler (2000), Zeithaml, (2000), Ross
(1995) and performance of the service provider. (Yau, 2007)

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            Author                                       Factors affecting Retention
   Hennig-Thurau and Klee, (1997)                  Customer satisfaction and Relationship
                                                   quality

   Garbarino and Johnson, (1999)                   Trust and Commitment
   Lee et al. (2001), Ranaweera and Prabhu, Switching cost
   (2003)

STRUCTURAL MODEL AND HYPOTHESISES

H1-1 – Responsiveness has a positive impact on customer trust
H1-2 – Security has a positive impact on Customer trust
H1-3 – User Interface has a direct impact on Customer trust
H1-4 – Information Quality has a positive impact on trust
H1-5 – Perceived usefulness has direct impact on customer trust
H2-1 – Responsiveness has a positive impact on customer satisfaction
H2-2 – Security has a positive influence on Customer satisfaction
H2-3 – User Interface has a direct impact on Customer satisfaction
H2-4 – Information Quality has a positive impact on satisfaction
H2-5 – Perceived usefulness has direct impact on customer satisfaction
H3 – Customer trust has a direct impact on customer satisfaction
H4 – Customer trust has a positive impact on customer commitment
H5 – Customer trust has influence on customer retention
H6 – Customer satisfaction has a direct influence on customer commitment
H7 – Customer satisfaction has positive impact on customer retention
H8 – Customer commitment has a direct impact on customer retention

                                   Figure1: Proposed Model




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SAMPLING AND DATA COLLECTION

         Pilot study has been conducted on 54 respondents who have taken treatment from
the online health care centre for the past one year in Coimbatore city, Tamilnadu. The
respondents were asked to fill up the questionnaire when they came for second
consultation. The size of the population for this study was unknown. It has been suggested that
a sample of between 200 and 1,000 respondents for populations of 10,000 or more is
preferable (Alreck and Settle, 1985). After considering such resources budget, time and
accessibility to respondents, this survey targeted 461 respondents in order to provide
sufficient power for the statistical analyses.
         The population for the study is the patients of online health care patients in
Coimbatore city and the stratified random sampling technique was used for choosing the sample
size of the study. There are 5 hospital are providing OHCS through 13 centres in Coimbatore
city. In the first stage of sampling (using stratified sampling method), one top ranked centre
from each hospital in terms of size of the patients base chosen. Accordingly, from the
chosen set of 5 top OHCS centres, the administrators of and doctors of centres were
approached for obtaining details of the patients who have taken the OHCS from each centre
in the past one year. The list, thus obtained from administrators and doctors of the centre from
each hospital 341, 902, 719, 570 and 997 numbers of patients respectively.
         In the second stage (using simple random sampling method), from this
parsimonious list of patients provided by the administrator and doctors, using random table,
50% from each of the above mentioned total was drawn and arrived at the sample size of
170, 401, 360, 285 and 498 in each hospitals respectively. These 1714
(170+401+360+285+498) patients were then approached for collecting responses for the
study through questionnaire. Subsequently, 825 out of 1714 patients approached gave their
consent for responding, after many contacts established in person and over phone. Upon
conducting interviews with these favourably inclined patients, the sample size for this
investigation turned out to be 83, 73, 91, 113, and 101 from each hospital respectively,
constituting a final sample size of 461 in numbers and thereby yielding a response rate of
55.87%.
                                       Table1: Sample Profile
                   Variable                Measure                 Frequency
                                             Male                     298
                    Gender                  Female                    163
                                          Less than 25                143
                                             25-35                    107
                                             36-45                    159
                     Age                     45-60                    41
                                           Above 60                   11
                                          School level                275
                  Education                Graduate                   126
                    Level
                                         Post graduate                49
                                             None                     11
                                             Urban                    162
                   Location                  Rural                    299



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DATA ANALYSIS

       To prove the theoretical model, Structural Modelling Equation (SEM) is
used for data analysis. Two step modelling approach will give improved reliability
and reduce problems of inter correlation of constructs in the path model (Anderson
and Gerbing, 1988). In the first step, Exploratory Factor Analysis (EFA) was used
to explore the factors from the variables and Confirmatory Factor Analysis (CFA)
was deployed to verify the fitness of the factors.

EXPLORATORY FACTOR ANALYSIS (EFA) RESULTS

        Kaiser Meyer Olkin measure of sampling adequacy refers the sample size for
the study is good enough to perform the factor analysis. The value is 0.768. The table
below shows that the factor loadings were above 0.5 which underlines the convergent
validity of the factors. Based on the results of EFA, nine factors were formed and
they were named as Perceived Usefulness (PU), Information quality (IQ), User
Interface (UI), Security, Responsiveness, Customer Trust, Customer Satisfaction,
Customer Commitment and Customer Retention.

                    Table2: Exploratory Factor Analysis (EFA) Results

                                                                  Factor
         Variables                                   Extraction   Loadings      Factor
 Through OHCS I Can get variety of information       .523           .684          PU
 The OHCS is easy to use                             .691           .752          UI
 The information on the OHCS is easy to
 understand                                          .645           .734          UI
 I am able to get the required information through
 OHCS at any time                                    .498           .629     Responsiveness
 The OHCS provides prompt attention to my
 request and questions                               .615           .579     Responsiveness
 The OHCS has mechanism to ensure the safe
 transmission of its customers information           .566           .552        Security
 The OHCS facilitates to get my health information   .502           .586          IQ
 The OHCS is trustworthy                             .645           .716         Trust
 The OHCS insists the confidence in its customers    .570           .657         Trust
 The OHCS provides the relevant the services         .490           .534          IQ
 information
 I have a personal attachments with this OHCS        .492           .567      Commitment
 It is easy to complete the transaction on the
 OHCS                                                .511           .578          IQ
 I am confident that OHCS does not misuse any
 information about me                                .572           .639        Security
 OHCS provides good quality of information
 through online                                      .554           .614          PU


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 I am committed to my relationship
 with OHCS                                                .571         .663      Commitment
 OHCS will Save time                                      .519         .536           PU
 The information available in the OHCS is visually
 appealing                                                .520         .702            UI
 I OHCS service provider fulfils my needs                 .534         .583          Trust
 The OHCS does not behave opportunistically               .515         .544          Trust
 The OHCS has technical capacity to ensure that
 the data I send cannot be modified by others             .659         .711         Security
 Changing my preference from the OHCS requires
 major rethinking.                                        .524         .682      Commitment
 Information provided by OHCS                 is easy
 to                                                       .548         .655            IQ
 understand
 The payment through OHCS is safe                         .526         .577         Security
 I continue to use OHCS                                   .542         .555        Retention
 I feel that the risk associated with OHCS is low         .522         .582         Security
 OHCS will save money                                     .495         .527           PU
 I definitely recommend OHCS to my friends                .512         .600        Retention
 In the future I will continue to use OHCS                .540         .627        Retention
 Using the OHCS makes it easier to get the
 information needed                                       .498         .512           PU
 Using the OHCS requires a lot of skills                  .723         .541            UI
 The OHCS has Flexibility                                 .546         .560     Responsiveness
 I find that using the OHCS is useful for collecting
 information                                              .574         .607           PU
 The OHCS is effective in resolving my problems           .673         .583     Responsiveness
 I prefer to use traditional health care system rather
 than OHCS.                                               .572         .584        Retention
 The OHCS is effective in handling complaints             .499         .711     Responsiveness
 Overall I am satisfied with the performance of
 OHCS                                                     .639         .757       Satisfaction


After identifying the factors the reliability check were done through using Cronbach s         ‟
alpha and the reliability coefficients of the factors were higher than the cut-off level of 0.70
(Nunnally, 1978) which shows the internal consistency. The following table shows the
reliability analysis results.




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                       Table3: Reliability Coefficient of the Factors
                 No.           Factor                      Cronbach’s α
                 1.    Perceived Usefulness                   0.74
                 2.    Information Quality                    0.78
                 3.    User Interface                         0.82
                 4.    Security                               0.72
                 5.    Responsiveness                         0.71
                 6.    Customer Trust                         0.85
                 7.    Customer Satisfaction                  0.71
                 8.    Customer Commitment                    0.79
                 9.    Customer Retention                     0.77

MEASUREMENT MODEL

The related fit indicators of the measurement model were achieved the acceptable level.
This explains the measurement model factors have established discriminant validity.
Except customer satisfaction which has only one variable in the factor. The following table
will show the measurement model fit statistics

                        Table4: Fit indices of Measurement model

           Fit statistics               Acceptable level          Obtained level
     Chi-Square                                -                     1483
     Df                                        -                      938
     Chi-Square significance               P ≤ 0.05                 < 0.01
     Chi-Square/ df                           3                      1.58
     GFI                                    > 0.90                   0.91
     AGFI                                   >0.90                    0.91
     NFI                                    > 0.90                   0.93
     RFI                                    > 0.90                   0.92
     CFI                                    > 0.90                   0.94
     TLI                                    >0.90                    0.94
     RMSEA                                  < 0.05                   0.01
     RMR                                    <0.02                    0.01




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HYPOTHESES EXAMINATION

For hypothesises examination and to know the direct and indirect effect of the related
factors is shown in the below table.

                    Table5: Results of Hypothesises examination
   Hypothesis           Model fit                           Coefficient (β)       P
     H1-1     Responsiveness › Customer trust                   0.158             < .01
     H1-2     Security › Customer trust                         0.232             < .01
     H1-3     User interface › Customer trust                   0.422             0.05
     H1-4     Information quality › Customer trust              0.241             < .01
     H1-5     Perceived usefulness › Customer trust             0.211             0.04
     H2-1     Responsiveness › Customer satisfaction            0.238             0.01
     H2-2     Security › Customer satisfaction                  0.144             0.02
     H2-3     User interface › Customer satisfaction            0.212             < .01
     H2-4     Information quality › Customer satisfaction       0.442             0.05
     H2-5     Perceived usefulness › Customer satisfaction      0.132             < .01
      H3      Customer trust › Customer satisfaction            0.399             < .01
      H4      Customer trust › Customer commitment              0.354             0.03
      H5      Customer trust › Customer retention               0.305             < .01
      H6      Customer satisfaction › Customer commitment       0.280             < .01
      H7      Customer satisfaction › Customer retention        0.142             0.02
      H8      Customer commitment › Customer retention          0.343             < .01


                           Table6: Structural Model Fit Indices
                       Fit Statistics                                 Value
           Chi-Square                                                 2270
           Df                                                          929
           Goodness of fit index(GFI)                                  0.92
           Adjusted Goodness of Fit Index (AGFI)                       0.91
           Normed Fit Index (NFI)                                      0.90
           Relative Fit Index (RFI)                                    0.89
           Comparative Fit Index (CFI)                                 0.88
           Incremental Fit Index (IFI)                                 0.91
           Tucker Lewis Index (TLI)                                    0.01
           Root mean Square Error of Approximation ( RMSEA)            0.02

       The above table shows the examination of SEM results shows that the
influence of responsiveness, security, user interface, information quality and perceived
usefulness on customer trust. It explains: Responsiveness (γ = 0.158, P < .01), Security (γ
= .232, P < .01), User interface (γ = 0.422, P = .05), Information quality (γ = 0.241, P <
.01) and Perceived usefulness (γ = 0.211, P = .04) has positive impact on customer trust.
Therefore, Hypothesises H1-1, H1-2, H1-3, H1-4, and H1-5 are supported.


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        This research also found that the impact of responsiveness, security, user
interface, information quality and perceived usefulness on customer satisfaction.
Responsiveness (γ = 0.238, P = .01), Security (γ = .144, P = .02), User interface (γ =
0.212, P < .01), Information quality (γ = 0.442, P = .05) and Perceived usefulness (γ = 0.132,
P < .01) has positive impact on customer trust. Based on the empirical results, the
Hypothesises H2-1, H2-2, H2-3, H2-4, and H2-5 are supported. After analysing the
factor influence on customer trust and customer satisfaction the researchers analysed the
cause and effect relationship between customer trust, customer satisfaction, customer
commitment and customer retention. This analysis shown that customer trust have impact
on customer satisfaction (β = 0.399, P = <0.01). Customer trust have positive influence on
customer commitment (β = 0.354, P = 0.03). Customer trust have direct impact on
customer retention (β = 0.305, P = <0.01). Customer satisfaction have direct impact on
customer commitment (β = 0.280, P = <0.01). Customer commitment have positive impact
on customer retention. As a result of this H3, H4, H5, H6, H7 and H8 has been supported.
                                 Figure 2: Structural Model




DISCUSSION

        The SEM result shows that responsiveness, security, and information quality are the
most important predictors of customer trust. Comparatively, User interface and perceived
usefulness have influence on customer trust. This situation happened, due to the
respondents are more familiar to the traditional health care system. This indicate that the
online health service providers should focus more on user interface and also should create
awareness about OHCS to create trust in customer mind.
        From the empirical research, the researcher found the factors affecting
customer satisfaction. Responsiveness, security, user interface and perceived usefulness are
highly influence than information quality. This happened because of their education and
location.
The researcher also found that the relationship between customer trust, customer
satisfaction, customer commitment and customer retention.

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MANAGERIAL IMPLICATIONS
       Since the results suggest that responsiveness, security, information quality,
perceived usefulness and user interface are the determinants of customer trust, the service
providers has to concentrate on these factors to seed customer trust. Also the mentioned
constructs contributed to customer satisfaction stemming from customer trust. This
research has facilitated the health care service providers to understand the predictors of
customer trust, customer satisfaction, customer commitment and customer retention. It is
very imperative that the traditional health service providers have to adopt the suggested
model in OHCS in due course. The marketer may follow this model to retain their
customers rather than appointing strategic planners to do the task. The government can
also adopt OHCS effectively in rural areas so as to reduce the prevalent health barriers.
CONCLUSION, LIMITATIONS AND FUTURE DIRECTIONS
       The purpose of this study is to create a conceptual model framework and empirically
prove the model. This study also found the direct and indirect effect of the related factors.
The measurement model and structural model were found to be fit through the scores
obtained in fit indices. Hence it is important that the customers of OHCS need these factors
from the service providers to return to the service. Also this model can be applied in other
service sectors. This research was done in only a small geographical area in India. The
sample size chosen for the study is relatively small. Further the study can be extended with
some more demographic variables, new geographical area, more sample size and
also include organisational performance in the model.
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