Confusing Statistical Term #4: Hierarchical Regression vs. Hierarchical Model
by KAREN
This one is relatively simple. Very similar names for two totally different concepts.
Hierarchical Models (aka Hierarchical Linear Models or HLM) are a type of linear regression models in which the observations fall into hierarchical, or completely nested levels.
Hierarchical Models are a type of Multilevel Models.
So what is a hierarchical data structure, which requires a hierarchical model?
The classic example is data from children nested within schools. The dependent variable could be something like match scores, and the predictors a whole host of things measured about the child as well as the school. Child-level predictors could be things like GPA, grade, gender and school-level predictors could be things like: total enrollment, private vs. public, mean SES.
Because multiple children are measured from the same school, their measurements are not independent. Hierarchical modeling takes that into account.
Hierarchical regression is the practice of building successive linear regression models, each adding more predictors.
For example, one common practice is to start by adding only demographic control variables to the model in one step. In the next model, you can add predictors of interest, to see if they predict the DV above and beyond the effect of the controls.
You’re actually building separate but related models in each step. But SPSS has a nice function where it will compare the models, and actually test if successive models fit better than previous ones.
So hierarchical regression is really a series of regular old OLS regression models–nothing fancy, really.
Tagged as: hierarchical linear models, hierarchical regression, HLM
South East Asian Journal of Contemporary Business, Economics and Law, Vol. 1 ISSN 2289-1560 2012 101 A STUDY OF SERVICE QUALITY: AN EMPIRICAL INVESTIGATION OF INDONESIAN AIRLINES SERVICES Hendrikus Kadang Faculty of Management and Human Resource Development (FPPSM) Universiti Teknologi Malaysia, 81300 Skudai, Johor Bahru, Malaysia Email: hkadang@yahoo.com, Tel: +6011 1503 2191 Inda Sukati Faculty of Management and Human Resource Development (FPPSM) Universiti Teknologi Malaysia, 81300 Skuadi, Johor Bahru, Malaysia Email: indasukatiutmjb@gmail.com Tel: +6017 6605 148 ABSTRACT The purpose of this study is to analyze the effect of service quality, consumer satisfaction and price reference to repurchase intention. This causal relationship amongs the variables was measured by using both the passengers’ perception of Garuda Indonesia and Lion Air airline services. The passenger’s response of both airlines received by distributes questionnaires and interviews. Purposive sampling is applied as a sampling technique in order to determine the samples. Data collection is used by distribute the questionaires and interviews the passenger of both airlines. There are 400 respondents whom filed the questionnaires and five of respondents are interviewed. We conducted validity and reliability test of the items of construct by Statistical Package for the Social Science (SPSS). Hierarchical Regression Analysis included the regression to test the mediating variable and Moderated Regression Analysis (MRA) for testing the moderating variable was applied. The results of this study indicate that service quality influence the repurchase intention of both airlines. However, price reference does not significance to influence the repurchase intention of both airlines services. The customer satisfaction significantly effect the repurchase intention and the role of consumer satisfaction as a moderating variable between the service quality and the repurchase intention can not testing in this study due to multicollinearity among the independent variables. Summarily, this study posits that consumer satisfaction perfectly as a mediating variable between service quality and the repurchase intention. This study has limitations because it is unmanageable to overcome the multicollinearity among the independent variables by using the research method above. Therefore, next researcher can used another analysis method such as structural equation modelling. On the other hands, the study also did not escape the presence of common method variance due to the collection of the response’s reaction at the same time. Keywords: Service quality, consumer satisfaction, price reference, repurchase intention, airline. INTRODUCTION In today’s dynamic business world, tastes and preferences of consumers become the basis of emerging new business establishments. Most businesses are into business ventures where there is a potential surge of consumers; others shift to more consumer-oriented businesses. The increasing consumer demand and shifting consumer behaviour towards various consumer goods and services, create new standards and innovations to producers and manufacturers, which also “drive the role of service industries is increasing” (Cronin and Taylor, 1992). The growing role of today's service industry in meeting consumer needs remains to be a challenge for the business service providers. However, the intense competition among firms offering “service” as their core products, service quality are at times disregarded which boils down to impact on consumer satisfaction. According to Taylor and Baker (1994) customer satisfaction moderate the relationship between service quality and intention to repurchase. While Bou-Llusar et al. (2001) argued that consumer satisfaction a mediating variable between perceived quality and intentions to buy. Urbany et al. (1988) stated that the price reference given by the company or the manufacturer affects the perception of the consumers which further enhances its repurchase perception. A seminal investigation of Park et al, (2005) proved that consumer satisfaction on airline's service quality affects airplane's image and passenger behaviour on their future intention. In the same vein, Taylor and Baker (1994) states that previous studies has shown that there is a moderating effect of customer satisfaction between quality of service and the intention to buy, while Bou - Llusar (2001) argued that consumer satisfaction is a mediating variable between perceived quality and intentions to purchase. Consumer’s intention to repurchase intention is not only influenced by the quality of services but also other factors such as the reference price. Moreover, several studies suppose that the price reference of the goods or services is also able to form consumer intentions to repurchase intention (Urbany et al., 1988 and Rao, 2005). LITERATUR REVIEW AND HYPOTHESES Service Quality and Customer Satisfaction Quality of services provided by the company will always be tested at every service encounter (Kotler and Keller, 2006). Furthermore, Kotler and Keller (2006) states that researches have been done relating to the service quality (SERVQUAL) and companies that manage the services well will provide a draft strategy, top management commitment to quality, highquality standard, automated technology, systems to monitor service performance and customer complaints and attention to employee satisfaction. The contribution of service quality is very important because it will impact on the increasing demand South East Asian Journal of Contemporary Business, Economics and Law, Vol. 1 ISSN 2289-1560 2012 102 (Cheney, 1993). Parasuraman et al. (1988) defines SERVQUAL as a summary of multiple item scale that has proven the truth and reliability to be able to understand the expectations and consumer perceptions of service quality. While Houser, (1993) makes The House of Quality, which implements the fifth dimension to observe the quality of services. Meanwhile, Park et al. (2005) stated that the quality of airline service and airline image determine passenger's behavioral intentions in the future. While Oliva et al. (1992) defines customer satisfaction as a true experience or the overall impression which includes the consumers consumed services and processes that reflect the stages of emotional and cognitive elements. Price Reference Reference prices established by the price listed at the time, the previous price or when the purchase price (Kotler, 2003). While Urbany et al. (1988) quoted the Federal Trade Commission that there are three basic types of retail pricing practice of reference, namely: 1. Comparing a price promotion on retail prices have been imprinted on the goods. 2. Comparing a price promotion on the price that it may be provided by the other retailers in similar goods. 3. Comparing a price promotion on retail prices, which have been recommended by the manufacturer or producer. While Compeau et al. (2004) argue that the price reference is regular price comparisons (suggested list price of the manufacture) with the price offered. Repurchase Intention Taylor and Baker (1994) stated that the repurchase intention of the customer is influenced by the level of customer satisfaction and service quality. Services provided by the company at the time of the first consumer purchase intention to buy will rise again if the goods or services satisfy them. Cronin and Taylor, (1992) also found that after getting satisfaction, then the consumer will do repurchase the goods or services. The repurchase intention would come after the consumer satisfaction (Bou-Llusar et al., 2001). While Urbany et al. (1988) indicated that the consumer intention to buy will showed up and decided to buy if the price is perceived as expected for a need. The Effect of Service Quality to the Repurchase Intention Parasuraman et al. (1985) stated that consumers will buy an item or service if it's good quality. This means that the quality of goods or services really influence the consumer intentions to buy again. There is an influence of service quality on intention to buy but more dominant if the customer satisfaction (Cronin and Taylor, 1992). Future studies about service quality performed by Taylor and Baker (1994), found that service quality affects the willingness of consumers to buy. Meanwhile, Park et al. (2005) found that service quality of an airplane affects the passenger behavior intention in the future which in this case, the intention to buy back or the desire of passengers using the airline's services again. Based on the findings of the researcher above, then the writer can formulate the following hypothesis: H1: The service quality has positively related to repurchase intention. The Effect of Price Reference to Repurchase Intention Jacobson and Obermiller (1998) stated that one important factor in increasing the purchasing power of consumers is the reference price. Reference price provided by the company would be material information that may influence consumers to purchase (Mazumdar et al., 2005). Furthermore, Mazumdar et al. (2005) indicated that the consumer's decision about when to buy goods, and services affected by the price reference. Price reference whick was received by consumer it will become an important point to decide, whether to buy or not to buy. Meanwhile, Biswas et al. (1999) suggested that information on the prices received by consumers is very important in shaping the consumer's decision to buy. While Urbany et al. (1988) argued that the price reference influences consumer perception and purchase decisions. Hence, the following hypothesis can be drawn. H2: There is an effect of price reference to the repurchase intention. The Role of Customer Satisfaction Taylor and Baker (1994) suggested that customer satisfaction is the best moderating variables the relationship between service quality and repurchase intention. Furthermore, (Bou-Llusar 2001) argued that consumer satisfaction mediated the relationship between service quality and repurchase intention. Armstrong and Seng (2000) argued that the provision of services that will provide high customer satisfaction and further strengthen lead to buy again. In other words, consumer satisfaction mediates the relationship between service quality and intention to buy. To understand the role of moderating variables and mediating variables the authors cite journal Baron and Kenny (1986) explain that the moderating variable is a member variable direct effect and strengthen the influence of predictor variables (independent variables) to the criterion variable (dependent variable). Meanwhile, the mediating variable is a variable that triggers or stimulates the relationship of predictor variables to the criterion variable. Further it is said that the function of moderating variables gives a direct effect and strengthens the relationship between independent variables and the dependent variable. Mediating variable function is to mediate the relationship between independent variables and the dependent variable. H3: Consumer satisfaction has positively related to the repurchase intention. H4: Consumer satisfaction moderates the relationship between quality services and repurchases intention. H5: Consumer satisfaction mediates the relationship between quality services and repurchases intention. South East Asian Journal of Contemporary Business, Economics and Law, Vol. 1 ISSN 2289-1560 2012 103 Based on the above literature review, research framework can be drawn as follow: Figure 1: Research Model Figure 1 describes the influence of service quality to repurchase intention (Taylor and Baker, 1994); Consumer satisfaction mediates the effect of service quality on repurchases intention (Bou-Llusar et al, 2001). In the other side, the customer satisfaction moderates the influence of service quality to repurchase intention (Taylor and Baker, 1994). While the price reference effect the intention to buy again (Urbany et al, 1988). RESEARCH METHODS Research Design Cooper and Schindler (2003) stated that the research design and planning are an activity based on time, based on the research question, directing the selection of sources and types of information, a framework for determining relationships between variables from the research and outline the procedures for each research activity. Meanwhile, Sekaran (2003) stated that the design to the study is an effort that involves a sequence of rational choice decision making. The study was conducted to achieve the research objectives. Independent variables which used were the service quality, customer satisfaction and the price reference. Meanwhile, as a dependent variable is the repurchase intention. So the research design was formulated to test the effect of service quality on repurchase intention, to test whether the customer satisfaction moderates the effect of service quality to the repurchase intention. The study also examined the effect of price reference on the repurchase intention. Population and Sample The respondent of this study are passengers who have used the services of Lion Air and Garuda Indonesia from the airport of Yogyakarta Adi Soetjipto to other airports in Indonesia and vice versa from the other airports in Indonesia to the airport of Yogyakarta Adi Soetjipto. Sample was taken from populations as representation of the population with a sample of 400 respondents (200 respondents to Garuda Indonesiaa and 200 respondents for Lion Air). Although Roscoe (1975) cited have now (1992) extended that rule of thumb the total study sample between 30-500 are sufficient for the most social research is conducted. Based on the rules, 400 respondents were selected from the number of population in this study to observe the behaviour of consumers. Techniques Sampling and Data Collection Sampling techniques that researchers practised is non-probability sampling by using purposive sampling. The reason researchers use this technique because the data is unknown number of whole populations. While the tool that researchers use is purposive sampling the data collection based on certain criteria (Sekaran, 2003). In this study, sample was taken from passengers whom used the services of Garuda Indonesia and Lion Air airline at Adi Soetjipto Yogyakarta airport, Indonesia. As a way of collecting data that researchers use the survey method, in which the questionnaires used to collect primary data. Respondents who filled out questionnaires were passengers whom actually have used the services both of airlines at Adi Soetjipto Yogyakarta airport. These passengers have to flight to another airport in Indonesia and the other way around. Validity and Reliability Testing Validity test was conducted to measure whether the use of research instruments really able to explain the construct under investigation. The methods used were Confirmatory Factor Analysis with SPSS for Windows Release 16. This is confirmatory factor analysis because the question in the questionnaire items adapted from previous research that has been done regarding the quality of aviation services (Park et al., 2005). If the value of factor loading greater than or equal to 0.4, then the instrument is considered valid (Hair et al., 1998). Meanwhile, Sekaran (2003) further explained that if factor loading ≥ 0.3, it would be considered as the minimum limit and more importantly when factor loading ≥ 0.4. Whereas if factor loading ≥ 0.5 it will be accepted significantly. Reliability of a measuring instrument is an indication of whether the measure is to remain stable and consistent when the instrument measures the concept and help to access whether or not the measuring instrument to test the level of reliability used Cronbach's Alpha with the aid of SPSS. It considered sufficiently reliable if the alpha valued greater than or equal to 0.6 (Hair et al., 1998). Sekaran (1992) categorizes the level of reliability of a measuring instrument of research as follows: Cronbach Alpha 0.8 to 10 = good reliability Cronbach Alpha 0.6 to 0.79 = acceptable reliability Cronbach Alpha ≤ 0.6 = poor reliability Repurchase Intention Customer Satisfaction Service Quality Price Reference South East Asian Journal of Contemporary Business, Economics and Law, Vol. 1 ISSN 2289-1560 2012 104 Analysis Method This study uses Moderated Regression Analysis (MRA) to test the hypothesis. MRA is a special application of multiple linear reggression containing elements or multiplicative interaction of two or more independent variables. This test will see the impact of service quality on intention to buy back; customer satisfaction moderates the influence of service quality on intention to buy again, and the influence of reference prices on the repurchase intention. Before testing the hypothesis, the researcher analyzes the hierarchical regression to see the effect of each independent variable on the dependent variable. Technical implementation of the regression analysis was conducted with the help of SPSS. Research Procedure and Result Procedures for conducting field research was started from the distribution of questionnaires, data collection, interviews, tabulation of data, descriptive analysis, validity and reliability testing, regression analysis and interpretation. Number of questionnaires distributed as many as 450 sheets with the following details: 225 questionnaires to Garuda Indonesia passenger and 225 questionnaires for Lion Air passenger. The number of returned questionnaires there were 439 (218 questionnaires to Garuda Indonesia and Lion Air to 221 questionnaires). However, after sorting the questionnaires are worthy of the sample was 200 questionnaires to Garuda Indonesia with its response rate of 96% and 200 questionnaires to Lion Air to the response rate were 98.22%. While the results of interviews indicate that in general the factors that influence purchase intention re-ticketing or use the services of a return flight is the flight schedule conformance with the desired time of passengers. Passengers often choose flight service because ticket prices are relatively cheap it is disclosed by Lion Air passengers. Another respondent said that the issues of aviation safety services are the most important factor. Validity and Reliability Testing The results of validity testing have been conducted and found that there was the item of each constructs, which was not significant. According to Hair et al., (1998) that an item which has a significantly factor loading it means that the item is a single unit of instrument, which is capable of measure and predict the constructs. After performing the validation test, it appears that the items measured the construct of service quality, where only 14 items of 22 items, measured by reference to the price of 3 items 4 item and customer satisfaction is measured by 4 items from the 5 items. Further the validity test was followed by reliability test. Reliability test results in it appears that all the items that have been tested its validity seem reliable and the value of Cronbach's alpha was > 0.6 as suggested by Hair et al. (1998). Descriptive Analysis Table 1 shows the response of passengers on each flight service (Garuda Indonesia and Lion Air) on the service quality, the price reference and customer satisfaction. It appears that consumer’s perception of service quality, provided by Garuda Indonesia airline is better than Lion Air service quality. Table 1: Descriptive Analysis on Airline Services Variables N Garuda Indonesia Lion Air Mean SD Mean SD Service Quality 400 3.6986 .42102 2.9782 .42783 Price Reference 400 3.0400 .86618 2.9813 .75934 Customer Satisfaction 400 3.8290 .61974 3.5230 .58134 Repurchase Intention 400 3.9650 .51488 3.8350 .37211 Source: primary data Passengers do not agree to a price reference provided by the two companies despite the slight difference of ticket prices by both Garuda Indonesia and Lion Air. Passenger satisfaction preferences on the services of Garuda Indonesia have higher levels of satisfaction than Lion Air passengers. Finally, it shows that most airline passengers appear to continuously use the services of theses airlines through repurchase mode. Simultaneously descriptive analysis done on the data on Table 1, describes that passengers’ perception to airline services offered by both airlines remain low. Table 2: Correlation between variables Variable N Mean DS SQ PR CS SQ*CS RI SQ 400 3.2084 .76045 PR 400 2.8983 .89443 .072** .150 CS 400 3.7850 .61342 .169** .001 .303** .000 SQ*CS 400 12.2224 3.82030 .860** .000 .214** .000 .637** .000 RI 400 3.9000 .45334 .214** .000 .220 .000 .767** .000 .546** .000 ** Correlation is significant at the 0.01 level (2-tailed); SQ = service quality; PR = price reference; CS = customer satisfaction; SQ*CS = interaction of SQ and CS; RI = repurchase intention. Source: primary data South East Asian Journal of Contemporary Business, Economics and Law, Vol. 1 ISSN 2289-1560 2012 105 If the descriptive analysis of the results observed simultaneously both the aviation services, it appeared in Table 3 that the response of passengers to the services quality is still not good or a passenger in doubt concerning the quality of services provided by the services of this airline. This can happen because of the quality of services to poor Lion Air as the results of descriptive analysis of each flight service. Passengers do not agree to a reference price of the services provided by airlines. While the relatively high level of passenger satisfaction for an average passenger satisfaction leads to a score of 4 or agrees, which means passengers are satisfied using the services of the flight. The average value of intent to purchase or reuse of these flight services also lead to a score of 4 or passengers agree to use the two services of this airline. The correlation between the variable service quality and the price reference is not significant because the research model does not have a relationship. Service quality correlates to customer satisfaction and repurchase intention as the research model. Further price reference has a correlation with customer satisfaction and intention to buy because it has significant value. So is consumer satisfaction correlates with quality of service and intention to buy back as the research model. Data Analysis and Testing of Hypothesis Table 4 shows the stages of the hierarchical regression from stage I to stage IV. In the first stage shows the effect of service quality on intention to buy again. R2 values of 0.046 means that only 4.6% of the variance of repurchase intention can be explained by the variation of the service quality variable. While the significance of test results showed that the service quality significantly affects the repurchase intention with a significance level of 0.000. Later in the second stage the influence of service quality and price reference to the repurchase intention the R2 value of 0.088 gives the sense that only 8.8% of the variance of repurchase’s intention that can be explained by the quality of services and reference prices. While the coefficient value for the quality of service parameters for the calculated t value of 0.199 and 4.140 with a significance level of 0.000, then the value of the parameter coefficient for the reference price of 0.206 and the calculated t value of 4.280 with a significance level of 0.000 indicates that the service quality and price reference significantly affect the repurchase intention. Table 3: Hierarchical Regression Analysis Variables Step of Hierarchical Regression Step 1 Step 2 Step 3 Step 4 β t p β t p β t p β t p SQ .214 4.366 000 .199 4.140 000 .087 2.685 .008 .623 2.660 .008 PR .206 4.280 .000 -.016 .481 .631 -.013 -.378 .706 CS .758 22.342 .000 1.107 .7150 .000 SQ*CS .692 -2.311 .021 Rsquare F P .046 19.062 .000 .088 19.105 .000 .596 195.113 .000 .602 149.274 .000 Source: primary data In the third stage of the regression results seem to influence the quality of service, the price reference and customer satisfaction on repurchase intention. On the other hand, price reference has a negative effect on repurchase intention by β value = -0.016 and insignificant p value = 0.005. This is caused by the variance of customer satisfaction because prior to the consumer's satisfaction of included in the regression model, the parameter value of the price reference is still positive and significant. Meanwhile, service quality and customer satisfaction has a positive and significant influence on repurchase intention. Finally, the fourth stage shows the moderation regression, which examines the influence of the service quality, the price reference, customer satisfaction and interaction of service quality and customer satisfaction. The results of this regression analysis showed that both the price reference, and the interaction between service quality and customer satisfaction has a negative parameter asset value. This fact needs to be identified whether the parameter value gives an indication of multicollinearity negative. These results are also incompatible with the classical regression assumption that does not justify the existence of multicollinearity or high correlations among the independent variables or independent variables (Gujarati, 2003). Hair et al. (2006) says that in order to identify the presence of multicollinearity among the independent variable takes the value of tolerance and the Variance Inflation Factor (VIF). If a high tolerance value means the value of VIF is low, then it indicates that its multicollinearity is small. Furthermore, Gujarati (2003) in his book provides a solution to overcome the multicollinearity among the independent variables in five ways: 1. priori information, a priori assumes that beta () of variable which was identified lead to multicollinearity equated with a particular value of the beta () variables that have no multicollinearity then insert in the new regression equation. 2. Connect the cross-sectional data and time-series data. 3. Removed of the variables was identified cause multicollinearity. 4. transformed the variables in terms of time-series data. 5. Increase some more a new data. The fifth solution is raised by Gujarati (2003) above, there are only two that can be done is get rid of the variables that lead to high multicollinearity and add new data for the three other solutions cannot be used in data such as data cross-sectional study. South East Asian Journal of Contemporary Business, Economics and Law, Vol. 1 ISSN 2289-1560 2012 106 The best solution is to remove the variables that give rise to multicollinearity (interaction quality service and customer satisfaction) as shown in Table 4. Table 4: Regression Analysis for moderating investigation by Multicollinearity Testing Independent Variables β t p Tolerance VIF Dependent Variable SQ .087 2.685 .008 .971 1.030 RI PR -.016 -.481 .631 .907 1.102 RI CS .758 22.342 .000 .886 1.128 RI Rsquare F p .596 195.113 .000 Source: primary data Table 5 shows that there is no multicollinearity. Based on this regression can be concluded that the first hypothesis says that the service quality influences the repurchase intention supported because the results showed a significant effect. This means that the quality of service provided by the services of Garuda Indonesia and Lion Air influencing intention to purchase the airline reticketing services. These results are consistent with findings obtained in the study Taylor and Baker (1994) that service quality has an influence on the intention to buy. The results of this study did not support the second hypothesis which argues that price reference effect the repurchase intention. This can happen because of the influence of reference prices only as a source of information that is not the dominant determining intent to purchase or use services on the flight time of the study was conducted. This finding is consistent with research conducted by Urbany et al. (2001). Further study could not confirm the results of research conducted by Taylor and Baker (1994), which found that consumer satisfaction moderated the relationship between service quality and consumer intentions to behave in the future. This is caused by the interaction of service quality and customer satisfaction lead to multicollinearity and should be discarded. Thus, the third hypothesis cannot be tested in this study. This study supports the hypothesis that consumer satisfaction mediates the effect of service quality on intention to buy back (Bou-Llusar et al., 2001). The results of regression analysis to examine the mediating role of customer satisfaction (Table 6) shows that consumer satisfaction mediates the effect of service quality on intention to buy again and significant. However, the role of mediation that was found was a partial mediation (partial mediating) because the value of the second linear regression parameters of service quality on intention to buy back (Regression II) is greater than the value of the third parameter linear regression on the effect of service quality on intention to buy back ( Baron and Kenny, 1986). Table 5: Reggression Analysis for Testing the Mediating Variable Independent Variables Reggression of Baron & Kenny (1986) Dependent Variables Reggression 1 Reggression 2 Reggression 3 β t p β t p β t p SQ .169 3.419 .001 CS SQ .214 4.366 .000 RI SQ .087 2.677 .008 RI CS .753 23.266 .000 Rsquare F P .029 11.690 .001 .046 19.062 .000 .596 293.121 .000 Source: primary data Mediating role of customer satisfaction shows that the airlines' service quality provided by Garuda Indonesia and Lion Air maintance the passenger satisfying. Therefore, they will choose both airlines in the future. CONCLUSSION The results of this study demonstrate the influence of significant quality aviation services to passengers on intentions to buy or reuse services Garuda Indonesia and Lion Air. These results mean that the quality of services has a significant influence on intention to buy again. Reference price is not affected significantly in the repurchase intention. It means that there is no price reference effect to the passenger's intention to use the services Garuda Indonesia and Lion Air. Then the study could not test the third hypothesis which says that the customer satisfaction moderates the effect of service quality to the repurchase intention because there is a force of multicollinearity among the independent variables. Indeed, there is an interaction which made the reduced of independent variable's effect, so it must be discarded (Gujarati, 2003). Finally, this study finds that customer satisfaction would mediate the effect of service quality on intention to buy back tickets Garuda Indonesia and Lion Air. Mediating role that was found was a partial mediation. South East Asian Journal of Contemporary Business, Economics and Law, Vol. 1 ISSN 2289-1560 2012 107 IMPLICATION AND LIMITATION These results indicate that the better performance of services can stimulate the higher intentions of the consumer to use the services again. While it appears there was an inconsistency given the influence of reference prices on the intention to use the airline's services. On the other hand, it shows the consistency of customer satisfaction and its role as a mediator cannot be tested as a moderator. This study has limitations because it is difficult to overcome the multicollinearity among the independent variables. As a result, researchers must get rid of the interaction between service quality and customer satisfaction affects intention to buy again. Researchers use only Moderated Regression Analysis (MRA) to test moderating role of customer satisfaction and by using the structural equation modeling will be the best solution for testing the moderating effect. In addition, this study also did not escape the presence of common method variance due to the collection of the response's reaction at the same time so there is a variance of consumer responses to variables, which should be collected in the different time. REFERENCES Armstrong, Robert W and Seng, Tan Boon. (2000). Corporate-Customer Satisfaction in the Banking Industry of Singapore. International Journal of Bank Marketing. Pp 97 – 111. Baron, Reuben M. and Kenny, David A. (1986). The Moderator- Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations. Journal of Personality and Social Psychology Vol. 51 No. 6, 1173-1182 Biswas, Abhijit., Pullig, Chris., Krishnan, Balaji C., Burton, Scot. (1999). Consumer Evaluation of Reference Price advertisements: Effects of Other Brands’ Prices and Semantic Cues. Journal of Public Policy and Merketing. Vol. 18 No. 1, spring 52 – 65. Bou-Llusar, Juan Carlos, Camison-Zornoza, Cesar and Escrig-Tena, Belen.(2001). Measuring the Relationship between Firm Perceived Quality and Customer Satisfaction and Its Influence on Purchase Intentions. Total Quality Management, Vol. 12 No. 6, 719 – 734 Cheney, w. David. (1993). International Competitiveness and Sustainable Development. Journal Economic Development Review. Vol.11 pp. 68-70 Cooper, Donald R. and Schindler, Pamela S. (2003). Business Research Methods, 8th ed, New York: McGraw-Hill Book Co. Compeau, Larry D., Mullikin, Joan Lindsey, Grewal, Dhruv and Petty, Ross D. (2004). Consumers’ Interpretation of the Semantic Phrases Found in Reference Price Advertisements. The Journal of Consumer Affairs. Vol.38 No. 1 Cronin, J. Joseph and Taylor, Steven. (1992). SERVPERF Versus SERVQUAL: Reconciling Performance Based and Perception-Minus-Expectations Measurement of Service Quality. Journal of Marketing, Vol. 58 (January) pp 125-131. Gujarati, Damodar N. (2003). Basic Econometrics, 2nd Ed McGraw-Hill, Inc. Hair, J.R., R.E. Anderson, R.L. Tatham, and W.C. Black. (1998). Multivariate Data Analysis, 5th ed. Upper Saddle River, New Jersey. Prentice Hall International, Inc. Houser, J.R. (1993). How Puritten Burnet Used the House of Quality. Sloan Management Review, (Spring: 61 – 69). Jacobson, Robert and Obermiller, Carl. (1989). The Formation of Reference Price. Advance in Consumer Research, Vol. 16. Mazumdar, Tridib, Raj, S.P., and Sinha, Indrajit. (2005). Reference Price Research: Review and Proposistions. Journal of Marketing, Vol. 69 pp.84 – 102. Kotler, Philip .(2003). Marketing Management, 11th ed. New Jersey: Pearson Education, Inc. Kotler, Philip and Keller, Kevin Lane. (2006). Marketing Management, 12th ed. New Jersey: Pearson Education, Inc. Oliva, Terence A., Oliver, Richard L., and MacMillan Ian C. (1992). A Catastrophe Model for Developing Service Satisfaction Strategies. Journal of Marketing Vol. 56 (July) pp.83 – 95 Parasuraman, A., Zeithaml, Valarie A., and Berry, Leonard L. (1985). Problems and Strategies in Services Marketing. Journal of Marketing, Vol. 49 pp.33 – 46. -----------(1985). A Conceptual Model of Service Quality and Its Implications for Future Research. Journal of Marketing, Vol. 49 pp 41 – 50. -----------(1988). SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality. Journal of Retailing, Vol. 64. No. 1 pp. 12 – 40. Park, Jii-Woo, Robertson, R. and Wu, Cheng-Lung. (2005). Investigating the Effects of Airline Service Quality on Airline Image and Passengers’ Future Behavioural Intenstions. Journal of Retailing, Vol. 64. No. 1 pp. 12 –40 Rao, Akshay R. (2005). The Quality of Price as a Quality Cue. Journal of Marketing Research, Vol. XLII pp. 401 – 405 Sekaran, Uma. (1992). Research Methods for Business. 4th ed John Wiley & Sons, Inc. New York. ………………(2003). Research Methods for Business. 4th ed John Wiley & Sons, Inc. New York. Taylor Steven A. and Baker, Thomas L. (1994). An Assessment of the Relationship Between Service Quality and Customer Satisfaction in the Formation of Consumers’ Purchase Intentions. Journal of Retailing, Vol. 70 No. 2 pp163 – 178 Urbany, Joel E., Bearden, William O., and Weilbaker, C. (2001). The Effect of Plausible and Exaggerated Reference Prices on Consumer Perceptions and Price Search. Journal of Consumer Research, Vol. 15. pp. 95 – 110
South East Asian Journal of Contemporary Business, Economics and Law, Vol. 1 ISSN 2289-1560 2012 101 A STUDY OF SERVICE QUALITY: AN EMPIRICAL INVESTIGATION OF INDONESIAN AIRLINES SERVICES Hendrikus Kadang Faculty of Management and Human Resource Development (FPPSM) Universiti Teknologi Malaysia, 81300 Skudai, Johor Bahru, Malaysia Email: hkadang@yahoo.com, Tel: +6011 1503 2191 Inda Sukati Faculty of Management and Human Resource Development (FPPSM) Universiti Teknologi Malaysia, 81300 Skuadi, Johor Bahru, Malaysia Email: indasukatiutmjb@gmail.com Tel: +6017 6605 148 ABSTRACT The purpose of this study is to analyze the effect of service quality, consumer satisfaction and price reference to repurchase intention. This causal relationship amongs the variables was measured by using both the passengers’ perception of Garuda Indonesia and Lion Air airline services. The passenger’s response of both airlines received by distributes questionnaires and interviews. Purposive sampling is applied as a sampling technique in order to determine the samples. Data collection is used by distribute the questionaires and interviews the passenger of both airlines. There are 400 respondents whom filed the questionnaires and five of respondents are interviewed. We conducted validity and reliability test of the items of construct by Statistical Package for the Social Science (SPSS). Hierarchical Regression Analysis included the regression to test the mediating variable and Moderated Regression Analysis (MRA) for testing the moderating variable was applied. The results of this study indicate that service quality influence the repurchase intention of both airlines. However, price reference does not significance to influence the repurchase intention of both airlines services. The customer satisfaction significantly effect the repurchase intention and the role of consumer satisfaction as a moderating variable between the service quality and the repurchase intention can not testing in this study due to multicollinearity among the independent variables. Summarily, this study posits that consumer satisfaction perfectly as a mediating variable between service quality and the repurchase intention. This study has limitations because it is unmanageable to overcome the multicollinearity among the independent variables by using the research method above. Therefore, next researcher can used another analysis method such as structural equation modelling. On the other hands, the study also did not escape the presence of common method variance due to the collection of the response’s reaction at the same time. Keywords: Service quality, consumer satisfaction, price reference, repurchase intention, airline. INTRODUCTION In today’s dynamic business world, tastes and preferences of consumers become the basis of emerging new business establishments. Most businesses are into business ventures where there is a potential surge of consumers; others shift to more consumer-oriented businesses. The increasing consumer demand and shifting consumer behaviour towards various consumer goods and services, create new standards and innovations to producers and manufacturers, which also “drive the role of service industries is increasing” (Cronin and Taylor, 1992). The growing role of today's service industry in meeting consumer needs remains to be a challenge for the business service providers. However, the intense competition among firms offering “service” as their core products, service quality are at times disregarded which boils down to impact on consumer satisfaction. According to Taylor and Baker (1994) customer satisfaction moderate the relationship between service quality and intention to repurchase. While Bou-Llusar et al. (2001) argued that consumer satisfaction a mediating variable between perceived quality and intentions to buy. Urbany et al. (1988) stated that the price reference given by the company or the manufacturer affects the perception of the consumers which further enhances its repurchase perception. A seminal investigation of Park et al, (2005) proved that consumer satisfaction on airline's service quality affects airplane's image and passenger behaviour on their future intention. In the same vein, Taylor and Baker (1994) states that previous studies has shown that there is a moderating effect of customer satisfaction between quality of service and the intention to buy, while Bou - Llusar (2001) argued that consumer satisfaction is a mediating variable between perceived quality and intentions to purchase. Consumer’s intention to repurchase intention is not only influenced by the quality of services but also other factors such as the reference price. Moreover, several studies suppose that the price reference of the goods or services is also able to form consumer intentions to repurchase intention (Urbany et al., 1988 and Rao, 2005). LITERATUR REVIEW AND HYPOTHESES Service Quality and Customer Satisfaction Quality of services provided by the company will always be tested at every service encounter (Kotler and Keller, 2006). Furthermore, Kotler and Keller (2006) states that researches have been done relating to the service quality (SERVQUAL) and companies that manage the services well will provide a draft strategy, top management commitment to quality, highquality standard, automated technology, systems to monitor service performance and customer complaints and attention to employee satisfaction. The contribution of service quality is very important because it will impact on the increasing demand South East Asian Journal of Contemporary Business, Economics and Law, Vol. 1 ISSN 2289-1560 2012 102 (Cheney, 1993). Parasuraman et al. (1988) defines SERVQUAL as a summary of multiple item scale that has proven the truth and reliability to be able to understand the expectations and consumer perceptions of service quality. While Houser, (1993) makes The House of Quality, which implements the fifth dimension to observe the quality of services. Meanwhile, Park et al. (2005) stated that the quality of airline service and airline image determine passenger's behavioral intentions in the future. While Oliva et al. (1992) defines customer satisfaction as a true experience or the overall impression which includes the consumers consumed services and processes that reflect the stages of emotional and cognitive elements. Price Reference Reference prices established by the price listed at the time, the previous price or when the purchase price (Kotler, 2003). While Urbany et al. (1988) quoted the Federal Trade Commission that there are three basic types of retail pricing practice of reference, namely: 1. Comparing a price promotion on retail prices have been imprinted on the goods. 2. Comparing a price promotion on the price that it may be provided by the other retailers in similar goods. 3. Comparing a price promotion on retail prices, which have been recommended by the manufacturer or producer. While Compeau et al. (2004) argue that the price reference is regular price comparisons (suggested list price of the manufacture) with the price offered. Repurchase Intention Taylor and Baker (1994) stated that the repurchase intention of the customer is influenced by the level of customer satisfaction and service quality. Services provided by the company at the time of the first consumer purchase intention to buy will rise again if the goods or services satisfy them. Cronin and Taylor, (1992) also found that after getting satisfaction, then the consumer will do repurchase the goods or services. The repurchase intention would come after the consumer satisfaction (Bou-Llusar et al., 2001). While Urbany et al. (1988) indicated that the consumer intention to buy will showed up and decided to buy if the price is perceived as expected for a need. The Effect of Service Quality to the Repurchase Intention Parasuraman et al. (1985) stated that consumers will buy an item or service if it's good quality. This means that the quality of goods or services really influence the consumer intentions to buy again. There is an influence of service quality on intention to buy but more dominant if the customer satisfaction (Cronin and Taylor, 1992). Future studies about service quality performed by Taylor and Baker (1994), found that service quality affects the willingness of consumers to buy. Meanwhile, Park et al. (2005) found that service quality of an airplane affects the passenger behavior intention in the future which in this case, the intention to buy back or the desire of passengers using the airline's services again. Based on the findings of the researcher above, then the writer can formulate the following hypothesis: H1: The service quality has positively related to repurchase intention. The Effect of Price Reference to Repurchase Intention Jacobson and Obermiller (1998) stated that one important factor in increasing the purchasing power of consumers is the reference price. Reference price provided by the company would be material information that may influence consumers to purchase (Mazumdar et al., 2005). Furthermore, Mazumdar et al. (2005) indicated that the consumer's decision about when to buy goods, and services affected by the price reference. Price reference whick was received by consumer it will become an important point to decide, whether to buy or not to buy. Meanwhile, Biswas et al. (1999) suggested that information on the prices received by consumers is very important in shaping the consumer's decision to buy. While Urbany et al. (1988) argued that the price reference influences consumer perception and purchase decisions. Hence, the following hypothesis can be drawn. H2: There is an effect of price reference to the repurchase intention. The Role of Customer Satisfaction Taylor and Baker (1994) suggested that customer satisfaction is the best moderating variables the relationship between service quality and repurchase intention. Furthermore, (Bou-Llusar 2001) argued that consumer satisfaction mediated the relationship between service quality and repurchase intention. Armstrong and Seng (2000) argued that the provision of services that will provide high customer satisfaction and further strengthen lead to buy again. In other words, consumer satisfaction mediates the relationship between service quality and intention to buy. To understand the role of moderating variables and mediating variables the authors cite journal Baron and Kenny (1986) explain that the moderating variable is a member variable direct effect and strengthen the influence of predictor variables (independent variables) to the criterion variable (dependent variable). Meanwhile, the mediating variable is a variable that triggers or stimulates the relationship of predictor variables to the criterion variable. Further it is said that the function of moderating variables gives a direct effect and strengthens the relationship between independent variables and the dependent variable. Mediating variable function is to mediate the relationship between independent variables and the dependent variable. H3: Consumer satisfaction has positively related to the repurchase intention. H4: Consumer satisfaction moderates the relationship between quality services and repurchases intention. H5: Consumer satisfaction mediates the relationship between quality services and repurchases intention. South East Asian Journal of Contemporary Business, Economics and Law, Vol. 1 ISSN 2289-1560 2012 103 Based on the above literature review, research framework can be drawn as follow: Figure 1: Research Model Figure 1 describes the influence of service quality to repurchase intention (Taylor and Baker, 1994); Consumer satisfaction mediates the effect of service quality on repurchases intention (Bou-Llusar et al, 2001). In the other side, the customer satisfaction moderates the influence of service quality to repurchase intention (Taylor and Baker, 1994). While the price reference effect the intention to buy again (Urbany et al, 1988). RESEARCH METHODS Research Design Cooper and Schindler (2003) stated that the research design and planning are an activity based on time, based on the research question, directing the selection of sources and types of information, a framework for determining relationships between variables from the research and outline the procedures for each research activity. Meanwhile, Sekaran (2003) stated that the design to the study is an effort that involves a sequence of rational choice decision making. The study was conducted to achieve the research objectives. Independent variables which used were the service quality, customer satisfaction and the price reference. Meanwhile, as a dependent variable is the repurchase intention. So the research design was formulated to test the effect of service quality on repurchase intention, to test whether the customer satisfaction moderates the effect of service quality to the repurchase intention. The study also examined the effect of price reference on the repurchase intention. Population and Sample The respondent of this study are passengers who have used the services of Lion Air and Garuda Indonesia from the airport of Yogyakarta Adi Soetjipto to other airports in Indonesia and vice versa from the other airports in Indonesia to the airport of Yogyakarta Adi Soetjipto. Sample was taken from populations as representation of the population with a sample of 400 respondents (200 respondents to Garuda Indonesiaa and 200 respondents for Lion Air). Although Roscoe (1975) cited have now (1992) extended that rule of thumb the total study sample between 30-500 are sufficient for the most social research is conducted. Based on the rules, 400 respondents were selected from the number of population in this study to observe the behaviour of consumers. Techniques Sampling and Data Collection Sampling techniques that researchers practised is non-probability sampling by using purposive sampling. The reason researchers use this technique because the data is unknown number of whole populations. While the tool that researchers use is purposive sampling the data collection based on certain criteria (Sekaran, 2003). In this study, sample was taken from passengers whom used the services of Garuda Indonesia and Lion Air airline at Adi Soetjipto Yogyakarta airport, Indonesia. As a way of collecting data that researchers use the survey method, in which the questionnaires used to collect primary data. Respondents who filled out questionnaires were passengers whom actually have used the services both of airlines at Adi Soetjipto Yogyakarta airport. These passengers have to flight to another airport in Indonesia and the other way around. Validity and Reliability Testing Validity test was conducted to measure whether the use of research instruments really able to explain the construct under investigation. The methods used were Confirmatory Factor Analysis with SPSS for Windows Release 16. This is confirmatory factor analysis because the question in the questionnaire items adapted from previous research that has been done regarding the quality of aviation services (Park et al., 2005). If the value of factor loading greater than or equal to 0.4, then the instrument is considered valid (Hair et al., 1998). Meanwhile, Sekaran (2003) further explained that if factor loading ≥ 0.3, it would be considered as the minimum limit and more importantly when factor loading ≥ 0.4. Whereas if factor loading ≥ 0.5 it will be accepted significantly. Reliability of a measuring instrument is an indication of whether the measure is to remain stable and consistent when the instrument measures the concept and help to access whether or not the measuring instrument to test the level of reliability used Cronbach's Alpha with the aid of SPSS. It considered sufficiently reliable if the alpha valued greater than or equal to 0.6 (Hair et al., 1998). Sekaran (1992) categorizes the level of reliability of a measuring instrument of research as follows: Cronbach Alpha 0.8 to 10 = good reliability Cronbach Alpha 0.6 to 0.79 = acceptable reliability Cronbach Alpha ≤ 0.6 = poor reliability Repurchase Intention Customer Satisfaction Service Quality Price Reference South East Asian Journal of Contemporary Business, Economics and Law, Vol. 1 ISSN 2289-1560 2012 104 Analysis Method This study uses Moderated Regression Analysis (MRA) to test the hypothesis. MRA is a special application of multiple linear reggression containing elements or multiplicative interaction of two or more independent variables. This test will see the impact of service quality on intention to buy back; customer satisfaction moderates the influence of service quality on intention to buy again, and the influence of reference prices on the repurchase intention. Before testing the hypothesis, the researcher analyzes the hierarchical regression to see the effect of each independent variable on the dependent variable. Technical implementation of the regression analysis was conducted with the help of SPSS. Research Procedure and Result Procedures for conducting field research was started from the distribution of questionnaires, data collection, interviews, tabulation of data, descriptive analysis, validity and reliability testing, regression analysis and interpretation. Number of questionnaires distributed as many as 450 sheets with the following details: 225 questionnaires to Garuda Indonesia passenger and 225 questionnaires for Lion Air passenger. The number of returned questionnaires there were 439 (218 questionnaires to Garuda Indonesia and Lion Air to 221 questionnaires). However, after sorting the questionnaires are worthy of the sample was 200 questionnaires to Garuda Indonesia with its response rate of 96% and 200 questionnaires to Lion Air to the response rate were 98.22%. While the results of interviews indicate that in general the factors that influence purchase intention re-ticketing or use the services of a return flight is the flight schedule conformance with the desired time of passengers. Passengers often choose flight service because ticket prices are relatively cheap it is disclosed by Lion Air passengers. Another respondent said that the issues of aviation safety services are the most important factor. Validity and Reliability Testing The results of validity testing have been conducted and found that there was the item of each constructs, which was not significant. According to Hair et al., (1998) that an item which has a significantly factor loading it means that the item is a single unit of instrument, which is capable of measure and predict the constructs. After performing the validation test, it appears that the items measured the construct of service quality, where only 14 items of 22 items, measured by reference to the price of 3 items 4 item and customer satisfaction is measured by 4 items from the 5 items. Further the validity test was followed by reliability test. Reliability test results in it appears that all the items that have been tested its validity seem reliable and the value of Cronbach's alpha was > 0.6 as suggested by Hair et al. (1998). Descriptive Analysis Table 1 shows the response of passengers on each flight service (Garuda Indonesia and Lion Air) on the service quality, the price reference and customer satisfaction. It appears that consumer’s perception of service quality, provided by Garuda Indonesia airline is better than Lion Air service quality. Table 1: Descriptive Analysis on Airline Services Variables N Garuda Indonesia Lion Air Mean SD Mean SD Service Quality 400 3.6986 .42102 2.9782 .42783 Price Reference 400 3.0400 .86618 2.9813 .75934 Customer Satisfaction 400 3.8290 .61974 3.5230 .58134 Repurchase Intention 400 3.9650 .51488 3.8350 .37211 Source: primary data Passengers do not agree to a price reference provided by the two companies despite the slight difference of ticket prices by both Garuda Indonesia and Lion Air. Passenger satisfaction preferences on the services of Garuda Indonesia have higher levels of satisfaction than Lion Air passengers. Finally, it shows that most airline passengers appear to continuously use the services of theses airlines through repurchase mode. Simultaneously descriptive analysis done on the data on Table 1, describes that passengers’ perception to airline services offered by both airlines remain low. Table 2: Correlation between variables Variable N Mean DS SQ PR CS SQ*CS RI SQ 400 3.2084 .76045 PR 400 2.8983 .89443 .072** .150 CS 400 3.7850 .61342 .169** .001 .303** .000 SQ*CS 400 12.2224 3.82030 .860** .000 .214** .000 .637** .000 RI 400 3.9000 .45334 .214** .000 .220 .000 .767** .000 .546** .000 ** Correlation is significant at the 0.01 level (2-tailed); SQ = service quality; PR = price reference; CS = customer satisfaction; SQ*CS = interaction of SQ and CS; RI = repurchase intention. Source: primary data South East Asian Journal of Contemporary Business, Economics and Law, Vol. 1 ISSN 2289-1560 2012 105 If the descriptive analysis of the results observed simultaneously both the aviation services, it appeared in Table 3 that the response of passengers to the services quality is still not good or a passenger in doubt concerning the quality of services provided by the services of this airline. This can happen because of the quality of services to poor Lion Air as the results of descriptive analysis of each flight service. Passengers do not agree to a reference price of the services provided by airlines. While the relatively high level of passenger satisfaction for an average passenger satisfaction leads to a score of 4 or agrees, which means passengers are satisfied using the services of the flight. The average value of intent to purchase or reuse of these flight services also lead to a score of 4 or passengers agree to use the two services of this airline. The correlation between the variable service quality and the price reference is not significant because the research model does not have a relationship. Service quality correlates to customer satisfaction and repurchase intention as the research model. Further price reference has a correlation with customer satisfaction and intention to buy because it has significant value. So is consumer satisfaction correlates with quality of service and intention to buy back as the research model. Data Analysis and Testing of Hypothesis Table 4 shows the stages of the hierarchical regression from stage I to stage IV. In the first stage shows the effect of service quality on intention to buy again. R2 values of 0.046 means that only 4.6% of the variance of repurchase intention can be explained by the variation of the service quality variable. While the significance of test results showed that the service quality significantly affects the repurchase intention with a significance level of 0.000. Later in the second stage the influence of service quality and price reference to the repurchase intention the R2 value of 0.088 gives the sense that only 8.8% of the variance of repurchase’s intention that can be explained by the quality of services and reference prices. While the coefficient value for the quality of service parameters for the calculated t value of 0.199 and 4.140 with a significance level of 0.000, then the value of the parameter coefficient for the reference price of 0.206 and the calculated t value of 4.280 with a significance level of 0.000 indicates that the service quality and price reference significantly affect the repurchase intention. Table 3: Hierarchical Regression Analysis Variables Step of Hierarchical Regression Step 1 Step 2 Step 3 Step 4 β t p β t p β t p β t p SQ .214 4.366 000 .199 4.140 000 .087 2.685 .008 .623 2.660 .008 PR .206 4.280 .000 -.016 .481 .631 -.013 -.378 .706 CS .758 22.342 .000 1.107 .7150 .000 SQ*CS .692 -2.311 .021 Rsquare F P .046 19.062 .000 .088 19.105 .000 .596 195.113 .000 .602 149.274 .000 Source: primary data In the third stage of the regression results seem to influence the quality of service, the price reference and customer satisfaction on repurchase intention. On the other hand, price reference has a negative effect on repurchase intention by β value = -0.016 and insignificant p value = 0.005. This is caused by the variance of customer satisfaction because prior to the consumer's satisfaction of included in the regression model, the parameter value of the price reference is still positive and significant. Meanwhile, service quality and customer satisfaction has a positive and significant influence on repurchase intention. Finally, the fourth stage shows the moderation regression, which examines the influence of the service quality, the price reference, customer satisfaction and interaction of service quality and customer satisfaction. The results of this regression analysis showed that both the price reference, and the interaction between service quality and customer satisfaction has a negative parameter asset value. This fact needs to be identified whether the parameter value gives an indication of multicollinearity negative. These results are also incompatible with the classical regression assumption that does not justify the existence of multicollinearity or high correlations among the independent variables or independent variables (Gujarati, 2003). Hair et al. (2006) says that in order to identify the presence of multicollinearity among the independent variable takes the value of tolerance and the Variance Inflation Factor (VIF). If a high tolerance value means the value of VIF is low, then it indicates that its multicollinearity is small. Furthermore, Gujarati (2003) in his book provides a solution to overcome the multicollinearity among the independent variables in five ways: 1. priori information, a priori assumes that beta () of variable which was identified lead to multicollinearity equated with a particular value of the beta () variables that have no multicollinearity then insert in the new regression equation. 2. Connect the cross-sectional data and time-series data. 3. Removed of the variables was identified cause multicollinearity. 4. transformed the variables in terms of time-series data. 5. Increase some more a new data. The fifth solution is raised by Gujarati (2003) above, there are only two that can be done is get rid of the variables that lead to high multicollinearity and add new data for the three other solutions cannot be used in data such as data cross-sectional study. South East Asian Journal of Contemporary Business, Economics and Law, Vol. 1 ISSN 2289-1560 2012 106 The best solution is to remove the variables that give rise to multicollinearity (interaction quality service and customer satisfaction) as shown in Table 4. Table 4: Regression Analysis for moderating investigation by Multicollinearity Testing Independent Variables β t p Tolerance VIF Dependent Variable SQ .087 2.685 .008 .971 1.030 RI PR -.016 -.481 .631 .907 1.102 RI CS .758 22.342 .000 .886 1.128 RI Rsquare F p .596 195.113 .000 Source: primary data Table 5 shows that there is no multicollinearity. Based on this regression can be concluded that the first hypothesis says that the service quality influences the repurchase intention supported because the results showed a significant effect. This means that the quality of service provided by the services of Garuda Indonesia and Lion Air influencing intention to purchase the airline reticketing services. These results are consistent with findings obtained in the study Taylor and Baker (1994) that service quality has an influence on the intention to buy. The results of this study did not support the second hypothesis which argues that price reference effect the repurchase intention. This can happen because of the influence of reference prices only as a source of information that is not the dominant determining intent to purchase or use services on the flight time of the study was conducted. This finding is consistent with research conducted by Urbany et al. (2001). Further study could not confirm the results of research conducted by Taylor and Baker (1994), which found that consumer satisfaction moderated the relationship between service quality and consumer intentions to behave in the future. This is caused by the interaction of service quality and customer satisfaction lead to multicollinearity and should be discarded. Thus, the third hypothesis cannot be tested in this study. This study supports the hypothesis that consumer satisfaction mediates the effect of service quality on intention to buy back (Bou-Llusar et al., 2001). The results of regression analysis to examine the mediating role of customer satisfaction (Table 6) shows that consumer satisfaction mediates the effect of service quality on intention to buy again and significant. However, the role of mediation that was found was a partial mediation (partial mediating) because the value of the second linear regression parameters of service quality on intention to buy back (Regression II) is greater than the value of the third parameter linear regression on the effect of service quality on intention to buy back ( Baron and Kenny, 1986). Table 5: Reggression Analysis for Testing the Mediating Variable Independent Variables Reggression of Baron & Kenny (1986) Dependent Variables Reggression 1 Reggression 2 Reggression 3 β t p β t p β t p SQ .169 3.419 .001 CS SQ .214 4.366 .000 RI SQ .087 2.677 .008 RI CS .753 23.266 .000 Rsquare F P .029 11.690 .001 .046 19.062 .000 .596 293.121 .000 Source: primary data Mediating role of customer satisfaction shows that the airlines' service quality provided by Garuda Indonesia and Lion Air maintance the passenger satisfying. Therefore, they will choose both airlines in the future. CONCLUSSION The results of this study demonstrate the influence of significant quality aviation services to passengers on intentions to buy or reuse services Garuda Indonesia and Lion Air. These results mean that the quality of services has a significant influence on intention to buy again. Reference price is not affected significantly in the repurchase intention. It means that there is no price reference effect to the passenger's intention to use the services Garuda Indonesia and Lion Air. Then the study could not test the third hypothesis which says that the customer satisfaction moderates the effect of service quality to the repurchase intention because there is a force of multicollinearity among the independent variables. Indeed, there is an interaction which made the reduced of independent variable's effect, so it must be discarded (Gujarati, 2003). Finally, this study finds that customer satisfaction would mediate the effect of service quality on intention to buy back tickets Garuda Indonesia and Lion Air. Mediating role that was found was a partial mediation. South East Asian Journal of Contemporary Business, Economics and Law, Vol. 1 ISSN 2289-1560 2012 107 IMPLICATION AND LIMITATION These results indicate that the better performance of services can stimulate the higher intentions of the consumer to use the services again. While it appears there was an inconsistency given the influence of reference prices on the intention to use the airline's services. On the other hand, it shows the consistency of customer satisfaction and its role as a mediator cannot be tested as a moderator. This study has limitations because it is difficult to overcome the multicollinearity among the independent variables. As a result, researchers must get rid of the interaction between service quality and customer satisfaction affects intention to buy again. Researchers use only Moderated Regression Analysis (MRA) to test moderating role of customer satisfaction and by using the structural equation modeling will be the best solution for testing the moderating effect. In addition, this study also did not escape the presence of common method variance due to the collection of the response's reaction at the same time so there is a variance of consumer responses to variables, which should be collected in the different time. REFERENCES Armstrong, Robert W and Seng, Tan Boon. (2000). Corporate-Customer Satisfaction in the Banking Industry of Singapore. International Journal of Bank Marketing. Pp 97 – 111. Baron, Reuben M. and Kenny, David A. (1986). The Moderator- Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations. Journal of Personality and Social Psychology Vol. 51 No. 6, 1173-1182 Biswas, Abhijit., Pullig, Chris., Krishnan, Balaji C., Burton, Scot. (1999). Consumer Evaluation of Reference Price advertisements: Effects of Other Brands’ Prices and Semantic Cues. Journal of Public Policy and Merketing. Vol. 18 No. 1, spring 52 – 65. Bou-Llusar, Juan Carlos, Camison-Zornoza, Cesar and Escrig-Tena, Belen.(2001). Measuring the Relationship between Firm Perceived Quality and Customer Satisfaction and Its Influence on Purchase Intentions. Total Quality Management, Vol. 12 No. 6, 719 – 734 Cheney, w. David. (1993). International Competitiveness and Sustainable Development. Journal Economic Development Review. Vol.11 pp. 68-70 Cooper, Donald R. and Schindler, Pamela S. (2003). Business Research Methods, 8th ed, New York: McGraw-Hill Book Co. Compeau, Larry D., Mullikin, Joan Lindsey, Grewal, Dhruv and Petty, Ross D. (2004). Consumers’ Interpretation of the Semantic Phrases Found in Reference Price Advertisements. The Journal of Consumer Affairs. Vol.38 No. 1 Cronin, J. Joseph and Taylor, Steven. (1992). SERVPERF Versus SERVQUAL: Reconciling Performance Based and Perception-Minus-Expectations Measurement of Service Quality. Journal of Marketing, Vol. 58 (January) pp 125-131. Gujarati, Damodar N. (2003). Basic Econometrics, 2nd Ed McGraw-Hill, Inc. Hair, J.R., R.E. Anderson, R.L. Tatham, and W.C. Black. (1998). Multivariate Data Analysis, 5th ed. Upper Saddle River, New Jersey. Prentice Hall International, Inc. Houser, J.R. (1993). How Puritten Burnet Used the House of Quality. Sloan Management Review, (Spring: 61 – 69). Jacobson, Robert and Obermiller, Carl. (1989). The Formation of Reference Price. Advance in Consumer Research, Vol. 16. Mazumdar, Tridib, Raj, S.P., and Sinha, Indrajit. (2005). Reference Price Research: Review and Proposistions. Journal of Marketing, Vol. 69 pp.84 – 102. Kotler, Philip .(2003). Marketing Management, 11th ed. New Jersey: Pearson Education, Inc. Kotler, Philip and Keller, Kevin Lane. (2006). Marketing Management, 12th ed. New Jersey: Pearson Education, Inc. Oliva, Terence A., Oliver, Richard L., and MacMillan Ian C. (1992). A Catastrophe Model for Developing Service Satisfaction Strategies. Journal of Marketing Vol. 56 (July) pp.83 – 95 Parasuraman, A., Zeithaml, Valarie A., and Berry, Leonard L. (1985). Problems and Strategies in Services Marketing. Journal of Marketing, Vol. 49 pp.33 – 46. -----------(1985). A Conceptual Model of Service Quality and Its Implications for Future Research. Journal of Marketing, Vol. 49 pp 41 – 50. -----------(1988). SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality. Journal of Retailing, Vol. 64. No. 1 pp. 12 – 40. Park, Jii-Woo, Robertson, R. and Wu, Cheng-Lung. (2005). Investigating the Effects of Airline Service Quality on Airline Image and Passengers’ Future Behavioural Intenstions. Journal of Retailing, Vol. 64. No. 1 pp. 12 –40 Rao, Akshay R. (2005). The Quality of Price as a Quality Cue. Journal of Marketing Research, Vol. XLII pp. 401 – 405 Sekaran, Uma. (1992). Research Methods for Business. 4th ed John Wiley & Sons, Inc. New York. ………………(2003). Research Methods for Business. 4th ed John Wiley & Sons, Inc. New York. Taylor Steven A. and Baker, Thomas L. (1994). An Assessment of the Relationship Between Service Quality and Customer Satisfaction in the Formation of Consumers’ Purchase Intentions. Journal of Retailing, Vol. 70 No. 2 pp163 – 178 Urbany, Joel E., Bearden, William O., and Weilbaker, C. (2001). The Effect of Plausible and Exaggerated Reference Prices on Consumer Perceptions and Price Search. Journal of Consumer Research, Vol. 15. pp. 95 – 110
What are type I and type II errors?
When you do a hypothesis test, two types of errors are possible: type I and type II. The risks of these two errors are inversely related and determined by the level of significance and the power for the test. Therefore, you should determine which error has more severe consequences for your situation before you define their risks.
No hypothesis test is 100% certain. Because the test is based on probabilities, there is always a chance of drawing an incorrect conclusion.
- Type I error
- When the null hypothesis is true and you reject it, you make a type I error. The probability of making a type I error is α, which is the level of significance you set for your hypothesis test. An α of 0.05 indicates that you are willing to accept a 5% chance that you are wrong when you reject the null hypothesis. To lower this risk, you must use a lower value for α. However, using a lower value for alpha means that you will be less likely to detect a true difference if one really exists.
- Type II error
- When the null hypothesis is false and you fail to reject it, you make a type II error. The probability of making a type II error is β, which depends on the power of the test. You can decrease your risk of committing a type II error by ensuring your test has enough power. You can do this by ensuring your sample size is large enough to detect a practical difference when one truly exists.
The probability of rejecting the null hypothesis when it is false is equal to 1–β. This value is the power of the test.
| Null Hypothesis | ||
| Decision | True | False |
| Fail to reject | Correct Decision (probability = 1 - α) | Type II Error - fail to reject the null when it is false (probability = β) |
| Reject | Type I Error - rejecting the null when it is true (probability = α) | Correct Decision (probability = 1 - β) |
Example of type I and type II error
To understand the interrelationship between type I and type II error, and to determine which error has more severe consequences for your situation, consider the following example.
A medical researcher wants to compare the effectiveness of two medications. The null and alternative hypotheses are:
- Null hypothesis (H0): μ1= μ2The two medications are equally effective.
- Alternative hypothesis (H1): μ1≠ μ2The two medications are not equally effective.
A type I error occurs if the researcher rejects the null hypothesis and concludes that the two medications are different when, in fact, they are not. If the medications have the same effectiveness, the researcher may not consider this error too severe because the patients still benefit from the same level of effectiveness regardless of which medicine they take. However, if a type II error occurs, the researcher fails to reject the null hypothesis when it should be rejected. That is, the researcher concludes that the medications are the same when, in fact, they are different. This error is potentially life-threatening if the less-effective medication is sold to the public instead of the more effective one.
As you conduct your hypothesis tests, consider the risks of making type I and type II errors. If the consequences of making one type of error are more severe or costly than making the other type of error, then choose a level of significance and a power for the test that will reflect the relative severity of those consequences.
No comments:
Post a Comment