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ISSN 1913-0341 [Print] ISSN 1913-035X [Online] www.cscanada.net www.cscanada.org Management Science and Engineering Vol. 7, No. 2, 2013, pp. 1-15 DOI:10.3968/j.mse.1913035X20130702.1718 Developing a Service Quality Measurement Model of Public Health Center in Indonesia Tri Rakhmawati [a], *; Sik Sumaedi [a] ; I Gede Mahatma Yuda Bakti [a] ; Nidya J Astrini [a] ; Medi Yarmen [a]; Tri Widianti [a] ; Dini Chandra Sekar [a] ; Dewi Indah Vebriyanti [a] [a] Indonesian Institute of Sciences, Indonesia * Corresponding author. Received 16 March 2013; accepted 14 April 2013 Abstract Many researches were conducted in order to develop service quality measurement model for health service. However, the majority of the researches were conducted in hospital service context and only small numbers of the researches were done in developing countries. Furthermore, the previous researches also have not tested the stability of service quality measurement model because of the differences in socio-demographic profiles (sex, age, and income) of the users. Therefore, this research tried to develop a new service quality measurement model for public health center (PHC) in Indonesia, a developing country. In order to build the model, research data were gathered from 800 PHC users using survey method. The authors applied some statistical analysis, such as: exploratory factor analysis to identify the dimensions of service quality; confirmatory factor analysis to test the goodness of fit, discriminant validity, and convergent validity; Cronbach Alpha analysis to ensure the reliability, and stability analysis based on socio-demographic profles of the respondents. The result shows that service quality measurement model of PHC in Indonesia consists of 24 indicators which are divided into four dimensions, namely the quality of healthcare delivery, the quality of healthcare personnel, the adequacy of healthcare resources, and the quality of administration process. This service quality measurement model has not only met the criteria of goodness of fit, discriminant validity, convergent validity, and reliability but also proved to be stable tested against respondents sexes, ages, and incomes. Key words: Service quality; Public Health Center; Measurement instrument; Developing countries Tri Rakhmawati, Sik Sumaedi, I Gede Mahatma Yuda Bakti, Nidya J Astrini, Medi Yarmen, Tri Widianti, Dini Chandra Sekar, Dewi Indah Vebriyanti (2013). Developing a Service Quality Measurement Model of Public Health Center in Indonesia. Management Science and Engineering, 7(2), 1-15. Available from: http://www.cscanada. net/index.php/mse/article/view/j.mse.1913035X20130702.1718 DOI: http://dx.doi.org/10.3968/j.mse.1913035X20130702.1718 1. INTRODUCTION 1.1 Background In service sectors, quality is already identifed as a variable with important roles (Yusoff and Ismail, 2008). Many researches proved that service quality is an antecedent factor of satisfaction (Lai and Chen, 2011; Olorunnivo et al., 2006; Ojo, 2010; Ravinchandran et al, 2010; Salazar et al, 2004; Hasan et al, 2008; Ishaq, 2011; Sumaedi et al., 2011) and customer loyalty (Bunthuwun et al., 2010; Kheng et al., 2010; Al-Rousan et al., 2010; Bloomer et al., 1999). Furthermore, service quality also determines the value of products/ services in the eyes of customers (Omar et al., 2010; Ismail et al., 2009; Wen et al., 2005; Kuo et al., 2009; Jen and Hu, 2003; Zeithaml, 1998). In the context of health service, customer perception on service quality is also believed to be a success factor for healthcare organizations. For example, Donabedian (2005) stated that hospital profitability and user satisfaction is affected by users perceptions on service quality. Furthermore, perceived service quality is also said to have an impact on customer loyalty and word-of-mouth (Andaleeb, 2001). Therefore, user perception on service quality must always be considered and improved in health service context. Health is an important aspect of national development since it infuences the quality of human resources (Act No. 36 of 2009 concerning Health). In this particular context, healthcare service in Indonesia is a part of public services 2 Copyright Canadian Research & Development Center of Sciences and Cultures Developing a Service Quality Measurement Model of Public Health Center in Indonesia that must be provided by the Government. In Indonesia, Government develops public health centers (PHC) to ensure the availability of healthcare service for its citizens (The Decree of Indonesian Minister of Health No.279/ MENKES/SK/IV/2006 concerning the Guideline for Implementing Public Healthcare Effort in Public Health Center). Unfortunately, until now, harsh complaints and criticisms towards PHC in Indonesia are still vibrantly heard. Given this, PHC service quality improvement must be a mandatory agenda. With that in mind, user perception of public health center in Indonesia, especially the way they measure service quality, is essential, urgent and interesting to be studied. This because the knowledge on quality measures (quality dimensions) will help practitioners and policy makers in public health center clearly assess what needs to be monitored, analyzed, maintained, and fxed regarding to service quality. 1.2 Literature Review and Research Gaps Service quality is one of the most discussed topics among practitioners and scholars in the field of service management (Yusoff and Ismail, 2010). Many researchers try to defne service quality. Although different, generally, researchers agree that service quality must be seen from the view of users/customers (Clemes et al., 2008). Zeithaml (1988) defned it as the consumers judgment about a [service]s overall excellence or superiority. Hence, we can conclude that healthcare service quality is referred as consumer overall evaluation on healthcare service performance given by health care service provider. Quality is an abstract concept, making it hard to be measured and it is currently seen using various points of view (Lee et al., 2000). It is more complex in service context because of the unique characteristics of service quality, which are intangibility, inseparability, variability, and perishability (Kotler and Keller, 2012). Hence, many researchers have tried to develop ways to measure service quality including in the context of healthcare service. Surprisingly, until now, there is no agreement on how to measure service quality (Jain and Gupta, 2004; Parasuraman, 1985; 1988; 1994; Cronin and Taylor, 1992; Clewes, 2003), including in the context of healthcare service (Pai and Chary, 2012). Service quality measurement model, which consists of dimensions and indicators of the dimensions, illustrates how service quality is evaluated by service consumers. Service quality dimension is aspects that are deemed as relevant by consumers in evaluating service performance (Clemes et al., 2008). Literatures show that service quality has been agreed as a multidimensional concept (Berry et al., 1985 and Parasuraman et al., 1985), but there is no consensus on what are the dimensions of the construct (Brady and Cronin, 2001). Many researchers have proposed service quality measurement model that is specific to the context of healthcare service. For examples, Lim and Tang (2002) suggested seven service dimensions of healthcare service quality, namely reliability, assurance, tangible, empathy, responsiveness, accessibility and affordability. Other researchers, Reidenbach and Sadifer-Smallwood (1990), argued that service quality should be consisted of seven dimensions, which are patient confidence, empathy, quality of treatment, waiting time, physical appearance, support services, and business aspects. Haddad et al. (1998) saw that service quality dimension only has three dimensions, namely delivery, personnel, and facilities. Van Duong et al. (2004) mentioned that service quality has four dimensions (healthcare delivery, health facility, interpersonal aspects of care, and access to services). More completely, Table 1 summarizes studies that proposed service quality dimensions that are specific to the context of healthcare service. Referring to previous explanation, the majority of the researches on health care service quality measurement model was in the context of developed countries, while researches in developing countries are fairly limited (van Duong et al., 2004). To our knowledge, there was no empirical study in Indonesia that specifically conducted to develop healthcare service quality measurement model. Meanwhile, it is generally known that culture in a country can infuence service quality dimensions that are appropriate for service context in that country (van Duong et al., 2004; Herbig and Genestre, 1996; Witkowski and Wolfinbarger, 2002). Thus, service quality measurement model generated from studies on certain countries needs to be tested and adjusted for others (Malhotra et al., 1994; Cui et al., 2003). Previous researches that developed healthcare service quality measurement model were also mostly carried out for hospital service while similar researches for PHC are small in numbers. That was indicated by the difficulty in looking for PHC service quality measurement model in some large data bases and publisher (Emeraldinsight, Science Direct, JSTOR, Taylor & Francis Online). Service characteristics in PHC are different with the ones in hospitals. In Indonesia, public health center focuses on basic health treatments. Besides, public health center is the responsibility of Indonesian Government so that it is more social-oriented than profit-oriented (Deber, 2002). These characteristics create implication that service mix, marketing programs, and even resources managed by PHC are different with hospital. This condition will differentiate the user perceptions of roles and functions between PHC and hospitals. Therefore, it becomes important to build an appropriate model for the context of healthcare service in PHC in Indonesia. Besides above gaps, from the methodology aspect, the previous researches utilized the method proposed by Parasuraman et al. (1988; 1991) in developing healthcare service quality measurement models. Researchers generally did some explorations to identify the dimensions of service quality using factor analysis. After that, every 3 Copyright Canadian Research & Development Center of Sciences and Cultures Tri Rakhmawati; Sik Sumaedi; I Gede Mahatma Yuda Bakti; Nidya J Astrini; Medi Yarmen; Tri Widianti; Dini Chandra Sekar; Dewi Indah Vebriyanti (2013). Management Science and Engineering, 7(2), 1-15 dimension was tested for its validity and reliability (for examples, see Reidenbach and Sandifer-Smallwood, 1990; Haddad et al., 1998; Baltussen et al., 2002; Van Duong et al., 2004; Narang, 2011). Related to the use of factor analysis, Hair et al. (2006) pointed out some important points for considerations as follows: [t]he researcher must ensure that the sample is homogeneous with respect to the underlying factor structure. It is inappropriate to apply factor analysis to a sample of males and females for a set of items known to differ because of gender. When the two subsamples (males and females) are combined, the resulting correlation and factor structure will be a poor representation of the unique structure of each group. Thus, whenever differing groups are expected in the sample, separate factor analyses should be performed, and the results should be compared to identify differences not refected in the results of the combined sample. (Hair et al., 2006) Unfortunately, the previous researches have not tested whether service quality dimensions used in the model were stable across various socio-demographic profiles, such as sex, age, and income. Meanwhile, literature on consumer behavior discusses that socio-demographic characteristics of consumers can affect their attitude and purchasing behavior (Al-Khayri and Hassan, 2012; Farah et al., 2011; Akman and Rehan, 2010; Abreu and Lins, 2010). For example, women tend to consider hedonic service elements as more important than functional utilitarian elements and men tend to think the other way around (Jen-Hung and Yi-Chun, 2010; Alreck and Settle, 2002). More specifcally, in the context of service quality, Zeithaml (1993) and Joseph et al (2005) argued that consumer evaluation on service quality will be affected by their socio-demographic profile. Thus, the results of previous researches are questionable since they have not considered the possibility of different service quality dimensions among respondents with different socio- demographic profles. 1.3 Research Objective In order to fll the gaps in the literature, this research aims to build service quality measurement model that is both stable and appropriate for PHC in Indonesia, a developing country. More specifically, this research tries to answer the question of what are the appropriate dimensions and indicators to measure service quality of PHC in Indonesia. After the introduction, this paper is organized as follows. First section is a literature review related to service quality and service quality measurement model in healthcare service. Second part will confer about research methodology and the third will present research results and the implications. The last section of this paper will discuss the conclusion, limitations, and next research agenda. 2. RESEARCH METHODOLOGY 2.1 Research Design This research was designed as exploratory study using quantitative approach. Following the footsteps of previous researchers (e.g. van Duong, 2004; Vandamme and Leunis, 1993; Narang 2011; Haddad et al., 1998; Ygge and Arnetz, 2001), research was begun with identifying service quality indicators believed to be relevant with the characteristics of PHC. After that, data of consumer perceptions were gathered in a survey using questionnaire as research instrument. Exploratory and confrmatory factor analyses were applied to form service quality dimensions and ensure the validity. Cronbach alpha analysis conducted to test the reliability of the dimensions. Unlike previous researches, service quality dimensions formed were tested for their stability against socio-demographic profles (sex, age, and income). Research design can be seen in Figure 1. 2.2 Service Quality Indicators PHC service quality indicators used in this study were gathered from review on scientifc literature, government regulations, and documents currently used by PHC to measure user perception towards PHC performance and the performance of healthcare service in general. Indicators were chosen based on several considerations, which are (1) their appropriateness to be used as evaluation indicators for healthcare service providers that only offer basic medical treatment; (2) their compatibility with social oriented healthcare organizations; (3) their suitability with service providers that serve citizens with lower-middle income. Based on above method, authors chose 29 indicators suspected as PHC service quality indicators. For more details, those indicators can be seen in Table 2. 2.3 Data Collection The respondents of this study were 800 PHC users. The number of sample was bigger than previous researches, such as van Duong et al. (2004) with sample size 396, Narang (2011) with sample size 396, Haddad et al. (1998) with sample size 241, and Ygge and Arnetz (2001) with sample size 624. This sample size also exceeds the requirements of factors analysis and Structural Equation Modelling (Hair et al., 2010). Demographic profiles of respondentss will be discussed in the result and discussion section. Data collection was done by using survey method with questionnaire as the instrument. The questionnaire consists of two parts, respondent demographic profle and PHC service quality measurement. In the second part, PHC service quality measurement, respondents were asked to express their perception on 29 positive statements regarding the indicators of service quality (see Table 3). The questionnaire used 7-points Likert where 1 represents totally disagree and 7 represents totally agree. 4 Copyright Canadian Research & Development Center of Sciences and Cultures Developing a Service Quality Measurement Model of Public Health Center in Indonesia
Result : 29 service quality indicators
Method : factor analysis
4th Step Confirmatory Factor Analysis Purpose: verify dimensions formed from previous step Method : Structural Equation Modeling
1st Step Identification of Service Quality Indicators Purpose: obtain service indicators that compatible with the characteristics of PHC service Method : review on literature and relevant documents Result : 29 service quality indicators 2nd Step Data Gathering Purpose: obtain user perception data Method : survey using questionnaires (800 respondents) 3rd Step Exploratory Factor Analysis Purpose: classify some indicators which have similar characteristics into one dimension Method : factor analysis 5th Step Model Stability Analysis Purpose: check the consistency of dimensiosns validity and reliability across segments (age, sex, and income) Obtain service quality dimensions which have stable validity and reliability across segments. Figure 1 Research Design To ensure that respondents were the users of PHC service, survey was carried out in the location of PHC. There were five PHC chosen in Jabodetabek. The sites were prefered because the area is located in Indonesia central government area and considered as metropolitan area which has residents that are highly critical towards healthcare service. Table 1 Service Quality Dimensions in Healthcare Service Context Authors Country Object Sample Service quality dimensions Lim and Tang (2000) Singapore Hospital 252 patients Tangibility, Reliability, Responsiveness, Assurance, Empathy, Accessibility and Affordability Reidenbach and Sandifer- Smallwood (1990) Hospital 300 patients from three service area (ER, inpatients service, outpatients service) Patient confdence, empathy, quality of treatment, waiting time, physical appearance, support services and business aspects Jabnoun and Chaker (2003) United Arab emirates Hospital 205 inpatients empathy, tangibles, reliability, administrative responsiveness, and supporting skills" Maxwell (1984) United Kingdom Hospital - Accessibility, relevance, effectiveness, equity, social acceptability and effciency To be continued 5 Copyright Canadian Research & Development Center of Sciences and Cultures Tri Rakhmawati; Sik Sumaedi; I Gede Mahatma Yuda Bakti; Nidya J Astrini; Medi Yarmen; Tri Widianti; Dini Chandra Sekar; Dewi Indah Vebriyanti (2013). Management Science and Engineering, 7(2), 1-15 Authors Country Object Sample Service quality dimensions Tomes and Ng (1995) England Hospital 132 patients Tangible (empathy, understanding of illness, relationship of mutual respect, dignity, religious needs) and Intangible (food and physical). Haddad et al. (1998) Upper Guinea Hospital, Urban and Rural health centers 241 patients health care delivery, personnel, and facilities Baltussen et al (2002) Burkina Faso 1 Urban Hospital and 10 rural health care centers 1081 visitors health personnel and conduct; adequacy of resources and services; healthcare delivery, and fnancial; and physical accessibility Van Duong, et al (2004) Vietnam Pregnant and postnatal care 196 pregnant women and 200 women in maternity care heal t hcar e del i ver y, heal t h f aci l i t y, interpersonal aspects of care, and access to services Narang (2011) India Public Health Care Center 396 patients health care delivery; interpersonal and diagnostic aspect of care; Facility; health personnel conduct and drug availability; Financial and physical access to care Ygge and Arnetz (2001) Sweden The Pediatric Care 624 patients and parents information-illness; information-routine; accessibility; medical treatment; caring process; staff attitude; participation; work environment Zineldin (2006) Egyptian & Jordanian Medical Clinic 244 inpatients Object, processes, infrastructure, interaction and atmosphere quality Lynn (2007) - Nursing care 1.470 patients Individualization, nurse characteristics, caring, Environment, Responsiveness Badri, et al (2008) UAE Public Hospital 244 inpatients quality of care, process and administration and information Karassavidou (2009) Greek NHS Hospital 137 patients Huma n As pe c t ; Ac c e s s ; Ph ys i c a l environment and infrastructure Choi et al (2005) South Korea A general hospital in Sungnam, Seoul 557 outpatients phys i c i a n c onc e r n, s t a f f c onc e r n, convenience of the care process, and tangible, reflecting aspects of technical, functional, environment and administration quality Wellstood et al (2005) Ontario, Canada The emergency room (ER) 41 men and women from two socially distinct neighborhoods in Hamilton, Ontario, Canada Physician-patient interaction, information/ communication between the physician and patient, and wait time Sower et al. (2001) Texas Hospital 663 recently discharged patients Respect and Caring, Effectiveness and Continuity, Appropriateness, Information, Efficiency, Effectiveness-Meals, First Impression, Staff Diversity Yeilada and Direktr (2010) Northern Cyprus Public and Private Hospital in Northern Cyprus 806 users Reliability/confdence, empathy, tangibles Teng et al. (2007) Taiwan Hospital 271 patients in surgical wards Needs management, assurance, sanitation, customization, convenience and quiet, attention Table 2 Service Quality Indicators No Service Quality Indicators Reference 1 SQ1 Conditions of healthcare facilities and equipment Lim and Tang (2000), 2 SQ2 Comfort and cleanliness of the environment Lim and Tang (2000), Narang (2011), Zineldin (2006) 3 SQ3 Suffciency of medical equipment Haddad et al. (1998), Baltussen and Ye (2005), Duong, et al (2004), Narang (2011) 4 SQ4 Suffciency of available room Haddad et al. (1998), Duong, et al (2004), Narang (2011) 5 SQ5 Suffciency of personnel (doctors, nurses, and administrative staff) Haddad et al. (1998), Baltussen and Ye (2005), Duong, et al (2004), Narang (2011) 6 SQ6 Suffciency of available medicines Haddad et al. (1998), Baltussen and Ye (2005), Narang (2011) 7 SQ7 Staff appearance (doctors, nurses, and administrative staff) Lim and Tang (2000), 8 SQ8 Employee hospitality and courtesy Lim and Tang (2000), Tomes and Ng (1995), Zineldin (2006) 9 SQ9 Employees sense of respect towards the patients Baltussen and Ye (2005), Tomes and Ng (1995), Duong, et al (2004), Haddad et al. (1998), Narang (2011) Continued To be continued 6 Copyright Canadian Research & Development Center of Sciences and Cultures Developing a Service Quality Measurement Model of Public Health Center in Indonesia No Service Quality Indicators Reference 10 SQ10 Employees sense of care towards the patients Baltussen and Ye (2005), Haddad et al. (1998), ), Duong, et al (2004), Narang (2011) 11 SQ11 Employees genuine desire to help patients Baltussen and Ye (2005), Narang (2011), Haddad et al. (1998), Duong, et al (2004) 12 SQ12 Willingness of employees to listen to patients problems Lim and Tang (2000), Zineldin (2006), 13 SQ13 Doctors/ nurses professionalities in diagnosing patients Haddad et al. (1998), Baltussen and Ye (2005), Duong, et al (2004), Narang (2011) 14 SQ14 Doctors/ nurses professionalities in examining patients Baltussen and Ye (2005), Duong, et al (2004), Narang (2011), Haddad et al. (1998), 15 SQ15 Doctors/ nurses professionalities in determining medicines Haddad et al. (1998), Baltussen and Ye (2005) 16 SQ16 Guarantee the availability of doctors in operational hours Haddad et al. (1998), Baltussen and Ye (2005), Duong, et al (2004), Narang (2011) 17 SQ17 The quality of medicines Baltussen and Ye (2005), Narang (2011), Haddad et al. (1998), Duong, et al (2004) 18 SQ18 The ease of registration procedures Zineldin (2006), The Decree of Indonesian Minister of Administrative Reform (MENPAN) No. 81 Year 1993 concerning guideline for Management of Public Services. 19 SQ19 The speed of registration process Zineldin (2006), The Decree of Indonesian Minister of Administrative Reform (MENPAN) No. 81 Year 1993 concerning guideline for Management of Public Services. 20 SQ20 The ease of payment procedures Zineldin (2006), The Decree of Indonesian Minister of Administrative Reform (MENPAN) No. 81 Year 1993 concerning guideline for Management of Public Services. 21 SQ21 The speed of payment process Zineldin (2006), The Decree of Indonesian Minister of Administrative Reform (MENPAN) No. 81 Year 1993 concerning guideline for Management of Public Services. 22 SQ22 Conformity between health services of health center with the expectations of patients to be healthier than ever Baltussen and Ye (2005), Haddad et al. (1998) 23 SQ23 The effectiveness of health center services in treating patients Baltussen and Ye (2005), Haddad et al. (1998) 24 SQ24 The effcacy of drugs given Baltussen and Ye (2005), Duong, et al (2004), Narang (2011), Haddad et al. (1998) 25 SQ25 The conformity of medicines and the illness Baltussen & Ye (2005), Duong, et al (2004), Narang (2011), Haddad et al. (1998) 26 SQ26 Doctors competence in treating disease Tomes and Ng (1995), Lim and Tang (2000), Zineldin (2006) 27 SQ27 Doctors effectivity in treating disease Tomes and Ng (1995) 28 SQ28 The effectivity of treatment method Baltussen and Ye (2005), Haddad et al. (1998) 29 SQ29 The conformity of treatment with the disease Baltussen and Ye (2005), Haddad et al. (1998) Continued 2.4 Data Analysis Data analysis consists of three phases, which are: exploratory factor analysis, confrmatory factor analysis, and stability analysis of service quality measurement model. Exploratory factor analysis was conducted to identify the number of service quality dimensions and their respective indicators. It was done using software SPSS 16 with confidence level of 95%. Confirmatory factor analysis was carried out in order to test goodness of fit, construct validity (discriminant and convergent validity), and the stability of the model was confirmed using Structural Equation Modelling (LISREL 8.80). In addition, Cronbach Alpha Analysis was also done to test the reliability of service quality measurement model. 3. RESULT AND DISCUSSION 3.1 Respondent Profle The respondent of this study was 800 PHC service users. The respondent comprised of 403 males (50.4%) and 397 females (49.6%). Their age are below or equal 20 years old (22.41%), 21-30 years old, (29.97%), 31-40 years old (21.03%), and equal or above 41 years old (26.57%). Most of the respondents are unemployed (29.10%), some of them are students (23.08%), workers at prive sectors (18.20%), day labor (12.56%), entrepreneurs (12.18%), civil servants (4.23%), and military personnel (0.64%). Respondents profile also shows that 57.56% of them graduated from high school. The rest of them graduated from junior high school (19.77%), university (12.1%), elementary school (8.94%), and small number of respondents did not go to school or did not finish elementary school (1.7%). Forty five point five percent (45.5%) of respondents has no income, 40% has income below or equal with Rp1,800,000, and the rest of them has income of more than Rp1,800,000. 3.2 The Result of Explortory Factor Analysis The result of Kaiser-Meyer-Olkin (KMO) test was 0.942 which means that the sample size of this test was adequate for factor analysis (Hair et al., 2010). In addition, Bartletts Test of Sphericity (BTS) shows the significance number of below 0.05 which indicates this study use an appropriate model for factor analysis (Gupta & Bansal, 2012). Exploratory factor analsysis was done by using principal component analysis in order to extract indicators and categorize them into minimum numbers of dimensions (Gupta & Bansal, 2012). Varimax rotation procedures use 7 Copyright Canadian Research & Development Center of Sciences and Cultures Tri Rakhmawati; Sik Sumaedi; I Gede Mahatma Yuda Bakti; Nidya J Astrini; Medi Yarmen; Tri Widianti; Dini Chandra Sekar; Dewi Indah Vebriyanti (2013). Management Science and Engineering, 7(2), 1-15 to obtain simple factors structure (Hair et al., 2010). The result of exploratory factor analysis can be seen in Table 3. Refering to Table 3, there are four factors that have eigenvalue of more than 1 and able to represent 65.98% of variance in indicators. Those four factors could be seen as a group of indicators which illustrates the quality of healthcare delivery (SQ22, SQ23, SQ24, SQ25, SQ26, SQ27, SQ28, SQ29), the quality of healthcare personnel (SQ8, SQ9, SQ10, SQ11, SQ12, SQ13, SQ14, SQ15), the adequacy of healthcare resources (SQ3, SQ4, Q5, SQ6), and the quality of administration process (SQ18, SQ19, SQ20, SQ21). Furthermore, there were five indicators removed. Four indicators (SQ1, SQ2, SQ7, SQ17) were removed since their communalities value is less than 0.5 while one indicator (SQ16) was removed because its factor loading is less than 0.5 (Hair et al., 2010). 3.3 The Results of Confrmatory Factor Analysis To see the goodness of fit of the model, some criteria, which are Root Mean Square Error of Approximation (RMSEA), Normed Fit Index (NFI), Non-Normed Fit Index (NNFI), Comparative Fit Index (CFI), Incremental Fir Index (IFI), Relative Fit Index (RFI), were employed. Table 4 shows the results of the analysis. Referring to Table 4, Confirmatory Factor Analysis shows that the model met the criteria. Thus, four dimensions emerged from exploratory factor analysis are fit to become the building block of PHC service quality measurement model in Indonesia. Table 3 The Results of Exploratory Factor Analysis Quality Indicators Factor Loading Eigen Value Variance Explained (%) Dimension SQ22 0.545 10.738 42.952 The quality of healthcare delivery (qs1) SQ23 0.709 SQ24 0.761 SQ25 0.687 SQ26 0.735 SQ27 0.751 SQ28 0.728 SQ29 0.694 SQ08 0.709 2.230 8.921 The quality of healthcare personnel (qs2) SQ09 0.758 SQ10 0.807 SQ11 0.780 SQ12 0.747 SQ13 0.613 SQ14 0.580 SQ15 0.583 SQ3 0.768 1.703 6.811 The adequacy of healthcare resources (qs3) SQ4 0.826 SQ5 0.796 SQ6 0.780 SQ18 0.747 1.824 7.296 The quality of administration process (qs4) SQ19 0.807 SQ20 0.820 SQ21 0.821 Note: see Table 3 for explanations on the indicators Table 4 CFA Results of Goodness of Fit Measurement Criteria Cut off Value Test Value Conclusion References RMSEA < 0.08 0.07 Good Hair et al., 2010 NFI 0.90 0.96 Good Hair et al., 2010 NNFI 0.90 0.97 Good Hair et al., 2010 CFI 0.90 0.97 Good Hair et al., 2010 IFI 0.90 0.97 Good Hair et al., 2010 RFI 0.90 0.96 Good Hair et al., 2010 GFI 0.90 0.72 Good Hair et al., 2010 8 Copyright Canadian Research & Development Center of Sciences and Cultures Developing a Service Quality Measurement Model of Public Health Center in Indonesia Confirmatory Factor Analysis also shows that the model met the criteria of discriminant and convergent validity Table 5 and 6). Convergent validity is fulfilled since (1) the value of Standardized Factor Loading for each indicators are higher than 0.5 with signifcance level below 5% (Hair et al., 2006); (2) the value of Composite Reliability of each dimensions are greater than 0.6 (Hair et al., 2006) and (3) the value of AVE for all dimensions are higher than 0.5 (Fornell and Larcker, 1981). Discriminant validity is also fulflled because the value of AVE for each dimension fell within the range of 0.55 and 0.6 (greater than squared correlation between constructs) (Fornell and Larcker, 1981). Dimensions reliability was proven by the value of Cronbach Alpha (CA) of each dimension. They exceeds the cut-off value of 0.6 (Lai and Chen, 2011; Tari et al., 2007; Hair et al., 2006) (see Table 5). With the fulfllment of reliability criteria, we concluded that the four dimensions are reliable to be used in PHC service quality measurement model. 3. 4 The Result of Model Stability Analysis To test the stability of the service quality measurement model, stability analysis was conducted. In accordance with Hair et al. (2006) opinion, this analysis utilized confirmatory factor analysis based on differences in criteria suspected to have influence on respondents perception. In addition, Cronbach Alpha analysis based on different criteria of respondents was also done. In this stage, the model was tested for its stability across three demographic profiles category (sex, age, and income). The three were selected because those are the ones that often being mentioned in consumer behavior literature as having influence on attitude and purchasing behavior (see Abreu and Lins, 2010; Choi et al., 2005; Alrubaiee and Alkaaida, 2011; Akman and Rehan, 2010; Farah et al., 2011; Al-Khayri and Hassan, 2012) and the number of sample allowed us to run statistical inference analysis after the samples were divided and regrouped (Hair et al, 2006). 3.4.1 Sex-Based Stability Analysis Table 7, 8, 9, and 10 show the results of stability test based on sex. Referring to those tables, this PHC Service Quality Model was stable for both sexes. Stability analysis shows that the model has adequate goodness of ft for the group of male respondents and female respondents (see Table 7). In both groups we found RMSEA values were well below the cut-off value of 0.08. The value of NFI, NNFI, CFI, IFI, and RFI for each group also met the cut- off value criteria (above 0.9). Table 5 Results of Reliability and Validity Test Service Quality Dimensions and Indicators Standardized Factor Loading (SFL)* Error Variance CA CR AVE QS 1 0.91 0.91 0.55 SQ22 0.64 0.60 SQ23 0.75 0.44 SQ24 0.77 0.41 SQ25 0.72 0.48 SQ26 0.74 0.46 SQ27 0.78 0.39 SQ28 0.78 0.39 SQ29 0.75 0.44 QS 2 0.91 0.91 0.55 SQ08 0.72 0.48 SQ09 0.77 0.41 SQ10 0.81 0.34 SQ11 0.79 0.38 SQ12 0.74 0.46 SQ13 0.72 0.48 SQ14 0.67 0.55 SQ15 0.71 0.50 QS 3 0.86 0.86 0.60 SQ03 0.76 0.42 SQ04 0.78 0.38 SQ05 0.77 0.41 SQ06 0.79 0.37 QS 4 0.86 0.86 0.60 SQ18 0.76 0.43 SQ19 0.79 0.38 SQ20 0.80 0.36 SQ21 0.76 0.42 9 Copyright Canadian Research & Development Center of Sciences and Cultures Tri Rakhmawati; Sik Sumaedi; I Gede Mahatma Yuda Bakti; Nidya J Astrini; Medi Yarmen; Tri Widianti; Dini Chandra Sekar; Dewi Indah Vebriyanti (2013). Management Science and Engineering, 7(2), 1-15 Table 6 The Val ue of AVE and Correl at i on Bet ween Constructs/ Dimensions of Service Quality AVE QS 1 QS 2 QS 3 QS 4 QS1 0.55 1 QS2 0.55 0.53 1 QS3 0.6 0.29 0.30 1 QS 4 0.6 0.28 0.29 0.16 1 Table 7 Goodness of Fit of Sex-Based Stability Analysis Indicator Measurement Result Male Female RMSEA 0.057 0.058 NFI 0.96 0.95 NNFI 0.98 0.98 CFI 0.99 0.98 IFI 0.99 0.98 RFI 0.95 0.94 Table 8 Results of Reliability and Validity Test on Sex-Based Stability Analysis LV / OV Male Female SFL CA / CR /AVE SFL CA / CR /AVE SQ 1 0.91/0.91/0.57 0.90/0.90/0.54 SQ22 0.68 0.59 SQ23 0.77 0.73 SQ24 0.76 0.79 SQ25 0.73 0.72 SQ26 0.73 0.75 SQ27 0.80 0.77 SQ28 0.79 0.77 SQ29 0.76 0.74 SQ 2 0.83/0.91/0.56 0.90/0.90/0.54 SQ08 0.71 0.73 SQ09 0.76 0.78 SQ10 0.81 0.82 SQ11 0.81 0.77 SQ12 0.74 0.72 SQ13 0.73 0.71 SQ14 0.71 0.63 SQ15 0.72 0.69 SQ 3 0.85/0.85/0.58 0.87/0.87/0.63 SQ03 0.80 0.72 SQ04 0.76 0.81 SQ05 0.73 0.81 SQ06 0.76 0.82 SQ 4 0.85/0.86/0.60 0.86/0.86/0.61 SQ18 0.76 0.74 SQ19 0.78 0.80 SQ20 0.80 0.80 SQ21 0.74 0.79 Table 9 AVE Value and Correlation Value between Constructs/ Dimensions on Sex-Based Stability Analysis: Male AVE SQ1 SQ2 SQ3 SQ4 SQ1 0.57 1 SQ2 0.56 0.58 1 SQ3 0.58 0.40 0.45 1 SQ4 0.6 0.40 0.31 0.20 1 Table 10 AVE Value and Correlation Value between Constructs/ Dimensions on Sex-Based Stability Analysis: Female AVE SQ1 SQ2 SQ3 SQ4 SQ1 0.54 1 SQ2 0.54 0.48 1 SQ3 0.63 0.19 0.20 1 SQ4 0.61 0.20 0.26 0.07 1 The result of stability analysis also shows that the model met the criteria of validity and reliability. The value of Standardized Factor Loading (SFL) for all indicators that are above 0.5 and signifcant on 5% alpha (Hair et al., 2006), the value of Composite Reliability for each dimension that is bigger than 0.6 (Hair et al., 2006), and the values of AVE that are above 0.5 (Fornell and Larcker, 1981) indicate that the model met the criteria of convergent validity in both groups (see Table 8). The model also fulfilled the requirement of discriminant validity where the value of AVE of each construct/ dimension is bigger than the value of squared correlation between constructs except for the dimension of the quality of healthcare delivery and the quality of personnel in male group. The values of their AVE fell slightly below their squared correlation (see Table 9 and 10). The value of Cronbach Alpha above 0.6 indicates that the model was reliable (Lai and Chen, 2011; Tari et al., 2007, Hair et al., 2006). 3.4.2 Age-Based Stability Analysis Table 11, 12, 13, 14, 15, and 16 show the results of age- based stability analysis. Referring to those tables, in general, PHC service quality measurement model was stable across all age groups. In Table 11 we can see that generally, PHC Service Quality Model still had decent goodness of ft since some of the criteria (NFI, NNFI, CFI, IFI, and RFI) were met. Furthermore, PHC Service Quality Model also satisfied the criteria of validity and reliability in for all age groups. Table 12 shows that the values of Standardized Factor Loading (SFL) for all indicators are greater than 0.5 and significant on 5% alpha (Hair et al., 2006). All the dimensions have Composite Reliability values of more that 0.6 (Hair et al., 2006) and most of them have AVE values above 0.5 (Fornell and Larcker, 1981). These results indicate that PHC Service Quality Model satisfed the criteria of convergent validity. The fulfillment of discriminant validity criteria was shown by the majority of values of AVE that exceed the value of squared correlation 10 Copyright Canadian Research & Development Center of Sciences and Cultures Developing a Service Quality Measurement Model of Public Health Center in Indonesia between constructs (see Table 13-16). Cronbach Alpha for each dimension in all age groups are bigger than 0.6, indicating a reliable model (Lai and Chen, 2011; Tari et al, 2007; Hair et al, 2006). Table 11 Goodness of Fit of Age-Based Stability Analysis Indicator Measurement Results 20 yo 20 30 yo 30 40 yo 40 yo RMSEA 0.092 0.090 0.089 0.10 NFI 0.88 0.95 0.94 0.90 NNFI 0.92 0.97 0.96 0.92 CFI 0.93 0.97 0.96 0.93 IFI 0.93 0.97 0.96 0.93 RFI 0.87 0.97 0.94 0.89 Table 12 Results of Reliability and Validity Tests of Age-Based Stability Analysis LV / OV 20 yo 20 30 yo 30 40 yo 40 yo SFL CA / CR /AVE SFL CA / CR /AVE SFL CA / CR /AVE SFL CA / CR /AVE SQ 1 0.87/0.87/0.46 0.92/0.92/0.60 0.94/0.94/0.65 0.88/0.88/0.49 SQ22 0.61 0.59 0.79 0.54 SQ23 0.76 0.77 0.80 0.65 SQ24 0.71 0.84 0.81 0.66 SQ25 0.69 0.75 0.80 0.65 SQ26 0.63 0.80 0.79 0.73 SQ27 0.67 0.82 0.83 0.83 SQ28 0.73 0.82 0.82 0.72 SQ29 0.64 0.79 0.81 0.77 SQ 2 0.85/0.85/0.42 0.93/0.93/0.61 0.92/0.92/0.59 0.91/0.91/0.56 SQ08 0.53 0.79 0.79 0.73 SQ09 0.61 0.86 0.78 0.77 SQ10 0.70 0.87 0.83 0.79 SQ11 0.67 0.87 0.77 0.83 SQ12 0.69 0.74 0.77 0.78 SQ13 0.72 0.70 0.75 0.74 SQ14 0.58 0.68 0.72 0.68 SQ15 0.65 0.74 0.72 0.64 SQ 3 0.85/0.85/0.60 0.87/0.87/0.64 0.85/0.85/0.60 0.82/0.82/0.54 SQ03 0.64 0.80 0.82 0.77 SQ04 0.78 0.82 0.73 0.78 SQ05 0.82 0.78 0.73 0.70 SQ06 0.84 0.79 0.80 0.68 SQ 4 0.75/0.76/0.44 0.90/0.90/0.69 0.81/0.87/0.62 0.90/0.90/0.70 SQ18 0.60 0.83 0.82 0.80 SQ19 0.65 0.83 0.77 0.88 SQ20 0.73 0.83 0.82 0.84 SQ21 0.66 0.84 0.75 0.82 Table 13 AVE Value and Correlation Value between Constructs/ Dimensions on Age-Based Stability Analysis: 20 yo AVE SQ1 SQ2 SQ3 SQ4 SQ1 0.46 1 SQ2 0.42 0.61 1 SQ3 0.6 0.10 0.10 1 SQ4 0.44 0.24 0.31 0.04 1 Table 14 AVE Value and Correlation Value between Constructs/ Dimensions on Age-Based Stability Analysis: 20-30 yo AVE SQ1 SQ2 SQ3 SQ4 SQ1 0.42 1 SQ2 0.61 0.58 1 SQ3 0.64 0.44 0.34 1 SQ4 0.69 0.27 0.27 0.13 1 11 Copyright Canadian Research & Development Center of Sciences and Cultures Tri Rakhmawati; Sik Sumaedi; I Gede Mahatma Yuda Bakti; Nidya J Astrini; Medi Yarmen; Tri Widianti; Dini Chandra Sekar; Dewi Indah Vebriyanti (2013). Management Science and Engineering, 7(2), 1-15 Table 15 AVE Value and Correlation Value between Constructs/ Dimensions on Age-Based Stability Analysis: 31-40 yo AVE SQ1 SQ2 SQ3 SQ4 SQ1 0.6 1 SQ2 0.59 0.56 1 SQ3 0.6 0.40 0.55 1 SQ4 0.62 0.53 0.45 0.37 1 Table 16 AVE Value and Correlation Value between Constructs/ Dimensions on Age-Based Stability Analysis: 40 yo AVE SQ1 SQ2 SQ3 SQ4 SQ1 0.44 1 SQ2 0.56 0.29 1 SQ3 0.54 0.19 0.35 1 SQ4 0.7 0.18 0.18 0.12 1 3.4.3 Income-Based Stability Test Tables 17 to 21 show the results of income-based stability test. According those tables, overall, PHC Service Quality Model was stable across all income groups. Table 17 shows that some criteria of goodness of fit (NFI, NNFI, CFI, IFI, and RFI) were met. Table 18 shows that the values of Standardized Factor Loading (SFL) for all indicators are greater than 0.5 and significant on 5% alpha (Hair et al., 2006), the values of Composite Reliability (CR) for all dimensions are greater than 0.6 (Hair et al., 2006), and all dimensions have AVE values above 0.5 (Fornell and Larcker, 1981). The results indicate the model met convergent validity. The model also met the criteria of discriminant validity that is indicated by the majority of the value of AVE for each construct/dimension in each income group greater than the squared correlation between constructs (see Table 19-21). The reliability of PHC Service Quality Model was illustrated by the values of Cronbach Alpha. The test yielded Cronbach Alpha values above 0.6 for all dimensions of each income group (Lai and Chen, 2011; Tari et al, 2007; Hair et al, 2006). Table 17 Goodness of Fit of Income-Based Stability Analysis Indicator Measurement Result No Income Income Rp1,800,000.00 Income > Rp 1,800,000.00 RMSEA 0.069 0.96 0.12 NFI 0.95 0.93 0.93 NNFI 0.97 0.95 0.94 CFI 0.97 0.95 0.95 IFI 0.97 0.95 0.95 RFI 0.97 0.92 0.92 Table 18 Results of Reliability and Validity Tests of Income-Based Stability Analysis LV / OV No Income Income Rp1,800,000.00 Income > Rp 1,800,000.00 SFL CA / CR /AVE SFL CA / CR /AVE SFL CA / CR /AVE SQ 1 0.89/0.89/0.52 0.91/0.92/0.58 0.91/0.92/0.58 SQ22 0.69 0.55 0.71 SQ23 0.77 0.75 0.73 SQ24 0.75 0.78 0.80 SQ25 0.70 0.74 0.74 SQ26 0.68 0.77 0.77 SQ27 0.72 0.84 0.79 SQ28 0.75 0.81 0.78 SQ29 0.68 0.81 0.76 SQ 2 0.89/0.89/0.51 0.90/0.91/0.55 0.92/0.92/0.60 SQ08 0.70 0.69 0.80 SQ09 0.75 0.76 0.81 SQ10 0.75 0.83 0.85 SQ11 0.74 079 0.86 SQ12 0.76 0.69 0.75 SQ13 0.70 0.74 0.71 SQ14 0.64 0.68 0.71 SQ15 0.69 0.73 0.67 SQ 3 0.84/0.84/0.57 0.89/0.89/0.67 0.84/0.84/0.56 SQ03 0.68 0.87 0.72 SQ04 0.75 0.83 0.76 SQ05 0.78 0.81 0.70 SQ06 0.80 0.78 0.80 To be continued 12 Copyright Canadian Research & Development Center of Sciences and Cultures Developing a Service Quality Measurement Model of Public Health Center in Indonesia LV / OV No Income Income Rp1,800,000.00 Income > Rp 1,800,000.00 SFL CA / CR /AVE SFL CA / CR /AVE SFL CA / CR /AVE SQ 4 0.83/0.83/0.55 0.87/0.87/0.62 0.89/0.90/0.68 SQ18 0.75 0.77 0.74 SQ19 0.75 0.80 0.84 SQ20 0.74 0.82 0.86 SQ21 0.72 0.75 0.86 Continued Table 19 AVE Value and Correlation Value between Constructs/ Dimensions on Income-Based Stability Analysis: No Income AVE SQ1 SQ2 SQ3 SQ4 SQ1 0.52 1 SQ2 0.51 0.55 1 SQ3 0.57 0.19 0.23 1 SQ4 0.55 0.31 0.29 0.10 1 Table 20 AVE Value and Correlation Value between Constructs/ Dimensions on Income-Based Stability Analysis: Income Lower Than or Equal With Rp1,800,000.00 AVE SQ1 SQ2 SQ3 SQ4 SQ1 0.58 1 SQ2 0.55 0.55 1 SQ3 0.67 0.31 0.29 1 SQ4 0.62 0.21 0.28 0.14 1 Table 21 AVE Value and Correlation Value between Constructs/ Dimensions on Income-Based Stability Analysis: Income above Rp1,800,000.00 AVE SQ1 SQ2 SQ3 SQ4 SQ1 0.58 1 SQ2 0.6 0.46 1 SQ3 0.56 0.42 0.55 1 SQ4 0.68 0.45 0.30 0.20 1 3.5 Research Implications Thi s st udy gave bot h t heor et i cal and pr act i cal implications. In the context of theoretical contributions, there are many researches that had developed service quality measurement models. However, the studies were rarely conducted in developing country. Furthermore, it is also diffcult to fnd the studies that are carried out in public health center context. It is widely-known that in management research, different contexts could lead to different results (Nair, 2006; Bhaskaran and Sukumaran, 2007). This research provided theoretical contribution in the form of service quality measurement model that is appropriate for public health center in Indonesia, a developing country. Next researchers can use this model when they study service quality in similar context. This PHC Service Quality Measurement Model has four dimensions with 24 indicators (see Table 3 to distinguish the dimensions). Those four dimensions are the quality of healthcare delivery, the quality of healthcare personnel, the adequacy of healthcare resources, and the quality of administration process. The first dimension illustrates the extent of healthcare service effectiveness in satisfying users expectations related to their illness. In other words, this dimension is related to the outcome of healthcare service. Second dimension, the quality of healthcare personnel describes personnels (doctors, nurses, and administrative staff) professionalism and their willingness to genuinely care about the users. Third dimension, the adequacy of healthcare resources, describes the sufficiency of resources owned by PHC. It includes human resource, equipment, rooms, and medicines. The last dimension, the quality of administration process, shows the performance of administrative process from the aspects of easiness and speed. Besides theoretical contribution, this research also gave contribution on the development methodology of service quality measurement model. Unlike previous researches, this study involved stability analysis based on respondents socio-demographic profiles. This became important since statistical techniques; factor analysis in this case, is only valuable if researchers can guarantee that differences in respondents characteristics will not generate different results (Hair et al., 2006). On the other side, consumer behavior literatures indicate that the difference in socio-demographic profles will potentially influence consumer attitude and purchasing behavior (Batchelor et al.,1994; Pascoe and Attkisson, 1983; Williams and Calnan, 1991; Alrubaiee and Alkaaida, 2011; Tucker, 2002). Therefore, future researchers can follow the same method to ensure that service quality measurement models generated from their studies are not affected by the differences of respondents characteristics. In the context of practical contribution, this study showed that there are four dimensions of service quality that needed to be closely monitored and improved by the management of public health center. Furthermore, the management of PHC can utilize PHC Service Quality Measurement Model as part of their quality measurement systems. Thus, they can assess their performance in each dimension and identify improvements needed to increase favorable and users-oriented service quality. In the context of Public Health Center in Indonesia, this was needed due to the agenda of bureaucratic reform that required all government-owned organizations to measure user perception. Another practical contribution of this study was that the service quality dimensions can be utilized as PHC 13 Copyright Canadian Research & Development Center of Sciences and Cultures Tri Rakhmawati; Sik Sumaedi; I Gede Mahatma Yuda Bakti; Nidya J Astrini; Medi Yarmen; Tri Widianti; Dini Chandra Sekar; Dewi Indah Vebriyanti (2013). Management Science and Engineering, 7(2), 1-15 user segmentation. Using cluster analysis, the groupings based on evaluations towards service quality dimensions can be identifed. Thus, management of PHC can identify the most accurate and efficient service strategy for each segment. For more details on how to use service quality dimension as segmentation base can be seen in the work of Lagrosen et al. (2004). CONCLUSI ON, LI MI TATI ONS, AND FUTURE RESEARCH DIRECTIONS This research aimed to develop Public Health Center Service Quality Measurement Model in Indonesia. Using survey data of 800 users of public health center, research results showed that PHC Service Quality Measurement Model consists of 24 indicators with four dimensions. Those four dimensions are the quality of healthcare delivery, the quality of healthcare personnel, the adequacy of healthcare resources, and the quality of administration process. In accordance with the research limitations, authors realized that frst, this research was designed as a cross- sectional study so the changes of respondent evaluation towards service quality could not be recognized and second, the survey was carried out in five public health centers in Indonesia using convenience sampling. This could limit the generalizability of the results. Given those limitations, authors recommend some improvements on future research. First, longitudinal researches need to be conducted in order to see the changes in PHC service quality dimensions. 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Assessment of Service Quality Dimensions in Healthcare Industry "A Comparative Study On Patient's Satisfaction With Mayiladuthurai Taluk Government vs. Private Hospitals