Aykac, D.s.o., Aydın, S., Ateş, M. & Tansel çetin, A., “effects Of Service Quality On Customer Satisfaction And Customer Loyalty: Example Of Marmara University Hospital,” International Congress On Performance And Quality In Health (uluslararası Sağlıkta Performans Ve Kalite Kongresi), March 19-21, 2009, Antalya, Turkey.

EFFECTS OF SERVICE QUALITY ON CUSTOMER SATISFACTION AND CUSTOMER LOYALTY: MARMARA UNIVERSITY HOSPITAL Dr. D. Selcen Ö.Aykaç1, Dr. Serkan Aydın2 , Doç. Dr. Metin Ateş3 , Dr. Ayşe Tansel Çetin4 Özet Bu çalışmada, Carmen (2000), ve Kara ve diğerleri (2005) tarafından geliştirilen hizmet kalitesi ölçeğindeki altı boyut dikkate alınarak, mükemmel bir hastaneden hastaların beklentileri, Marmara Üniversitesi hastanesinin sunduğu hizmetlerin kalitesi ve bu hizmet kalitesinin, müşteri memnuniyeti ve sadakati üzerindeki etkisi araştırılmaktadır. Tangibility, güvenilirlik, yanıt verme, güven, saygı, empati boyutları dikkate alınarak, hastaların mükemmel bir hastaneden beklentileri ve Marmara Üniversitesi hastanesinin bu boyutlar çerçevesinde sunduğu hizmet’in kalitesi ölçülmüş, mükemmel bir hastane ile Marmara Üniversitesi hastanesinin sunduğu hizmetler arasındaki gap ve Marmara üniversitesi hastanesinin sunduğu hizmetlerin kalitesinin müşteri memnuniyeti ve sadakati üzerindeki etkileri incelenmektedir. Bu amaçla, hastanede yatarak tedavi gören 183 hastadan anket yoluyla veri toplanmış ve toplanan bu veri regresyon analizi ile test edilmiştir. Anahtar Kelimeler: Hizmet kalitesi, Müşteri memnuniyeti, Sadakat, Sağlık hizmetleri Abstract This study employs six dimensions of service quality scale that is developed by Carman (2000) and Kara et al. (2005) to better understand the factors underlying healthcare customers’ perceptions of service quality. These dimensions investigated are namely tangibility, reliability, responsiveness, assurance, courtesy and empathy. Sampling has been conducted at the Marmara University Hospital between June 1st and July 15th 2007. Purposive convenient sampling has been employed to 183 inpatients. Through a 5 point Likert-type scale, healthcare customers’ expectations of a perfect service provider has been compared with the practices Marmara University Hospital to determine if there are any gaps. Quality of the Marmara University Hospital’s healthcare services has been analyzed together with its effects on customer satisfaction and customer loyalty through a regression analysis. Key Words: Service quality, Customer satisfaction, Customer loyalty, Healthcare services

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Özyeğin Üniversitesi, [email protected] Türk Telekom Veri Ambarı ve İş Zekası Grup Müdürlüğü, [email protected] 3 Marmara Üniversitesi, Sağlık Bilimleri Fakültesi, [email protected] 4 Gebze Yüksek Teknoloji Enstitüsü, [email protected] 2

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1. INTRODUCTION 1.1. Service Quality in Healthcare Turkey is listed among the big emerging countries by the Yale University Library resources (2007). Spillover effects of this factor is also seen in health expenditure per capita with 34% (Table 1) growth between years 2002 and 2007 (2009). Hospitals and other healthcare providers assume an important role in this fast growing service sector. Quality service provision, customer satisfaction, and customer loyalty has recently been emerging as important parameters for both researchers and practitioners in Turkey. For example, customer satisfaction is considered (1) amongst the main inducers of profitability, and (2) an important performance measure for firms, industries, and national economies (Anderson and Fornell 1994). Moreover, Press et al. (1991) indicate that improved customer satisfaction can help hospitals in cost reduction by resulting in fewer complaints. In addition, “patient satisfaction is a dominant concern that is intertwined with strategic decisions in the health services” (Gilbert, Lumpkin et al. 1992; Andaleeb 2001; Pakdil and Harwood 2005). Consumer’s satisfaction, choice of service provider and service quality evaluation are influenced by the expectations of the consumer (O’Connor, Trinh et al. 2000). Most healthcare consumers, namely patients, also have certain expectations about the service they demand prior to their visit to the hospital or clinic. Yet, 18-42% of the time health service provider fails to recognize or address these expectations (Jackson, Chamberlin et al. 2001).

Table 1. Total Health Expenditure per capita Turkey's Total Health Expenditure per capita ($)

2002

2003

2004

2005

2006

2007

484

514

562

586

614

647

Source: Euromonitor International (2009)

1.2. Measure of Service Quality Ducker (1991) defines service quality as “what the customer gets out and is willing to pay for” rather than “what the supplier (of the service) puts in”. Hence, service quality is often “conceptualized as the comparison of service expectations with actual performance perceptions” (Bloemer, Ruyter et al. 1999; Kara, Lonial et al. 2005). Service science literature often relies on SERVQUAL as an instrument to measure quality of service provided. SERVQUAL scale was developed based on a marketing perspective with the support of the 2

Marketing Science Institute (Parasuraman, Zeithaml et al. 1986). Previous research confirms its use as applicable to healthcare environment (Babakus 1992; Dean 1999; Arasli, Ekiz et al. 2008). For a thorough analysis of SERVQUAL see Nyeck et al. (2002). SERVQUAL principle primarily relies on a gap model (Parasuraman, Zeithaml et al. 1985) (Figure 1).

Every gap in SERVQUAL has a unique role as follows: • Gap 1: difference between consumer expectations and management perceptions of consumer expectations. • Gap 2: difference between management perceptions of consumer expectations and service quality specifications. • Gap 3: difference between service quality specifications and the service actually delivered. • Gap 4: difference between service delivery and what is communicated about the service to the consumer. • Gap 5: difference between consumer expectations and perceptions.

Figure 1. SERVQUAL gap analysis

Source: (Parasuraman, Zeithaml et al. 1985)

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Refined SERVQUAL defines five dimensions of service quality (Parasuraman, Zeithaml et al. 1988). These are: (1) Tangible – physical facilities, equipment, and appearance of personnel; (2) Reliability – ability to perform the promised service dependably and accurately; (3) Responsiveness – willingness to help customers and provide prompt service; (4) Assurance – knowledge and courtesy of employees and their ability to inspire trust and confidence; (5) Empathy – caring, the individualized attention the firm provides its customers. 1.3. Service Quality and Customer Satisfaction in Healthcare Sector SERVQUAL has been used in numerous sectors. The scale has also been applied to the healthcare field in numerous studies (Brown and Swartz 1989; Carman 1990; Babakus and Mangold 1992; Headley and Miller 1993; O’Connor, Shewchuk et al. 1994; Lam 1997; Lee, Delene et al. 2000). Its application to healthcare service quality demands an adaptation of the instrument (Carman 2000), e.g., 12 extra questions have been placed in the instrument in addition to original 22. The six dimensions named particularly applicable to healthcare are (1) nursing care, (2) accommodations, (3) physician care, (4) food service, (5) preparation for discharge, and (6) outcome (health status after hospitalization).

A more recent study in the context of a Turkish hospital by Kara et al. (2005) underlines that SERVQUAL should be used with 6 dimensions instead of the 5 that Parasuraman et al. has summarized (1988). In addition to tangible, reliability, responsiveness, assurance and empathy, their study includes courtesy. Here, courtesy refers to the kind behavior of employees to the customer.

We extend our work based on the model Kara et al. (2005) developed (Error! Reference source not found.). Therefore, our model does not only consider measuring service quality via SERVQUAL; but also investigates its effects on customer satisfaction and loyalty.

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Figure 2. Conceptual Model

H1 SERVICE QUALITY • Tangibility • Reliability • Responsiveness • Assurance • Empathy • Courtesy

SATISFACTION

LOYALTY

H2

Adapted from (Kara, Lonial et al. 2005)

We draw upon earlier work by Oliver (1980) and employ expectancy disconfirmation model to define customer satisfaction. According to the expectancy disconfirmation model, customer’s satisfaction is a function between his/her service performance perception and expectation (Pizam and Ellis, 1999), and illustrated as Satisfaction = f (PerceptionExpectation). Lastly, we explore loyalty concept, which is expected to result from satisfaction with the service encounter. Loyalty is defined as the likelihood that a customer of a healthcare service provider expects to do business with the organization in the future and engage in positive word-of-mouth communications about the service (Zeithaml, Berry et al. 1996). In this regard, following the earlier work and its confirming empirical evidence, we hypothesize that: H1 : Service quality has a positive effect on the patient satisfaction. H2 : Service quality has a positive effect on the patient loyalty.

2. METHODOLOGY In order to measure the constructs in the study, multi-item scales are employed and existing measures present in the literature are used. All items are measured on a five-point Likert – type scale, where 1 = strongly disagree and 5= strongly agree. In order to measure service quality, the scale, which is initially developed by Parasuraman et al. (1985, 1986, 1988) and 5

adapted by Carmen (2000) for further use within the context of healthcare, has been employed in identifying the critical factors of Service Quality. This scale has also been further improved by Kara et al. (2005) towards a better use at Turkish hospitals. In addition, for the purposes of measuring satisfaction and loyalty, scale used by Aydin (2005) is implemented. Two separate surveys have been distributed to impatients for measuring the quality of services. First survey explores what are the expectations regarding the perfect hospital, while the second seeks the actual service delivery of Marmara hospital’s evaluation. Data for this study were gathered using a questionnaire that was distributed to 250 impatients of the Marmara University hospital. In total, the response rate was 73% and there were 183 useable questionnaires, which forms a satisfactory dataset for subsequent analysis. Before evaluating the conceptual relationships of the proposed model, an assesment of internal consistency and reliability of the measurement scale were conducted. To test the internal consistency or reliability of a set of two or more scale indicators, Cronbach’s alpha is used (Nunnally, 1978). As suggested by Nunnally (1978), all of the Cronbach’s alpha values are detected as greater than 0.60. Our sample’s characteristics in terms of demographics are presented in Table 2. Table 2. Characteristics of the Sample

Gender

Education

Frequency

Percentile (%)

Female

64

35

Male

115

63

Primary

106

58

High School

43

24

Vocational School

4

2

Undergraduate

13

7

Graduate

2

1

No information

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2.1. Analysis and Findings As part of our preliminary analysis, we have followed earlier work by Kara et al. (2005) and conducted a GAP analysis to determine at which service factors Marmara University hospital deviates from a perfect hospital if it does at all. Results indicate that (Table 3) Marmara University hospital’s service quality is perceived to deviate from the perfect hospital on all 6

SERVQUAL dimensions. The largest gap is detected for tangibility, while the least is for courtesy.

Table 3. Results of GAP Analysis SERVQUAL

Deviation of Marmara University Hospital

Dimensions

from Perfect Hospital

Tangibility

1,144

Reliability

0,675

Responsiveness

0,642

Assurance

0,709

Courtesy

0,539

Empathy

0,612

Factors present in research model are analyzed in two groups. These are: (1) factors of the SERVQUAL scale, and (2) loyalty and satisfaction factors. Therefore, validity and reliability analysis have been conducted individually for both factor groups. Exploratory Factor Analysis (EFA) has been conducted to understand how data loads on factors. Results indicate a-6-factor structure. Yet, it is detected that some variables load to different factors. Therefore, analysis has been repeated after removal of these variables. Findings report a KMO (Kaiser-Meyer-Olkin) test value of 0.908 and a Bartlett test value of p<0.00. Therefore, results delivered by our study are significant (Hair et al., 1998). In total, 77.5% of the variation in our sample has been explained by 6 factors that 17 variables load to. Table 4. Factor Analysis and Cronbach Alpha Coefficient Factors

Factor loads

Factor 1:Courtesy (Cronbach α : 0.89 ) Nurses’ behavior should be very polite against patients in the hospital of Marmara University. 0.815 Visitors should be treated well in the hospital of Marmara University. 0.878 Doctors’ behavior should be very polite against patients in the hospital of Marmara University 0.864 Factor 2: Responsiveness (Cronbach α : 0.84) Discharging process is explained to the patients in the hospital of Marmara University 0.785 Employees of Marmara University hospital explain customer’ question appropriately about the any questions 0.675 Treatment is explained to the patient very clearly in the hospital of Marmara University 0.750 Factor 3: Tangibility (Cronbach α : 0.81) Physical facilities in the Marmara University hospital are visually appealing 0.577

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Bathrooms are very clean in the hospital of Marmara University 0.778 Rooms of the Marmara University hospital are very clean with fresh air. 0.784 Factor 4: Reliability (Cronbach α : 0.80) Food are delivered by a certain time in the hospital of Marmara University 0.855 When staff of the Marmara University hospital promise to do something by a certain time, they do it. 0.567 They keep patients’ records accurately in the hospital of Marmara University 0.598 Factor 5: Empathy (Cronbach α : 0.79) Doctors of the Marmara University hospital devote their time to discuss my fears 0.766 Doctors of the Marmara University hospital make me more comfortable even when they are not sure about the correctness of my treatment. 0.814 Nurses of the Marmara University hospital inform me as much as they can by talking. 0.580 Factor 6: Assurance (Cronbach α :0.78) Patients are trust doctors of Marmara University hospital 0.728 Patients are sure that they recovered well before they are discharged. 0.762 Factor 7: Loyalty (Cronbach α : 0.89) I am happy with the services of the Marmara University hospital. 0.904 My expectations from a hospital service are met by the Marmara University hospital. 0.885 Services of the Marmara University hospital are better than others. 0.791 Marmara University hospital provide me the exact service that I expect. 0.749 Factor 8: Satisfaction (Cronbach α : 0.79) I talk about Marmara University hospital positively with my friends and family. 0.844 I advise Marmara University hospital to people I know. 0.815 I’d prefer Marmara University hospital even if other hospitals are cheaper 0.806 If I need to go to a hospital again, I’d go to Marmara University hospital. 0.684

The dependent variable of the research model - loyalty and satisfaction construct - has also been subject to EFA. Results indicate a structure with 8 variables loading to 2 factors. In total, 75% of the variation in our sample has been explained by these two factors. Table 4 presents the details of the EFA analysis. The critical threshold value of 0.70 Cronbach’s α is captured (Nunnally, 1978). All factors analyzed have factor loads greater than 0.5, and cross loadings are less than 0.4. In brief, results indicate internal consistency (Kim et al, 2004). 2.2. Hypothesis Testing This study investigates the effects of service quality on satisfaction and loyalty. The relationships among the variables were tested via multiple regression analyses. Regression models are as follows: SAT= β0 + β1* TAN + β2*REL+ β3*RESP + β4*ASSU+ β5*EMP + β6*COUR +e LOY= = β0 + β1* TAN + β2*REL+ β3*RESP + β4*ASSU+ β5*EMP + β6*COUR +e (SAT:Satisfaction, LOY:Loyalty,TAN: Tangibility, REL: Reliability;RESP: Responsiveness, ASSU: Assurance, EMP: Empathy; COUR: Courtesy

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Linear regression analysis is conducted to test the research model. First, the regression model that explains the satisfaction variable via SERVQUAL factors is tested. Accordingly, tested regression model is meaningful (F1766: 18.185, p < 0.001) and independent variables can explain the 38.3% of change in the satisfaction variable. Closer analysis of the model parameters suggests that courtesy, assurance, responsiveness, empathy, tangibility and reliability variables have a significantly positive effect on satisfaction (<0.01). Second, effects of SERVQUAL factors on loyalty variable are investigated by testing the regression model. Results indicate that variables can satisfactorily explain 22.7% of the change in loyalty (F1766: 8.619, p < 0.001). Analysis of coefficients of the regression model shows that responsiveness and reliability variables and empathy variable have a positive and significant effect of 1% and 6%, respectively.

Table 5. Effects of service quality on satisfaction and loyalty Dependent variable Model 1 Model 2 Satisfaction Loyalty Independent variable Constant Tangibility Reliability Responsiveness Assurance Empathy Courtesy F R2 Adjusted R2

β 0.058 0.426 0.173 0.176 0.209 0.189 0.248 18.185** 0.383 0.362

T 0.000 7.191** 2.913** 2.970** 3.525** 3.184** 4.187**

β 0.032 0.024 0.261 0.376 0.000 0.125 0.032 8.619** 0.227 0.201

T 0.000 0.365 3.938** 5.680** -0.002 2.891* 0.479

Note: ** p< 0.001; * p< 0.005

3. LIMITATIONS Our study has certain limitations. First, cross sectional data could be helpful in improving the representativeness and generelizability of the results. Majority of the respondents in our sample have only lower levels of education. This shows a bias in their answers in addition to limiting the interpretation of our measurement tool by the respondents. Our survey has been conducted in polyclinics such as eye care and internal medicine. A sample with a balanced distribution among all polyclinics of the hospital would improve the representativeness significantly. Lastly, replication of this study at other hospitals would strengthen the implications and improve external validity. 9

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