Developing a Service Quality Measurement Model of Public Health Center in Indone
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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 profiles 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：///10.3968/j.mse.1913035X20130702.1718
1. INTRODUCTION
1.1 Background
In service sectors， quality is already identified 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.
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 define 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） defined it as “the consumer’s 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 influence 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.
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 confirmatory 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 profiles （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 scientific 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 profile 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”.
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 significance 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 fulfilled 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 fulfillment 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 Alkaa’ida， 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 fit 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 cutoff value criteria （above 0.9）.
CONCLUSION， LIMITATIONS， 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 first， this research was designed as a crosssectional 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. Second， to improve the generalizability， future researches should involve bigger numbers of PHC and use better sampling method， such as stratified random sampling.
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