This is to develop a new way of testing self-esteem by adopting DAP(Draw a Person) test and to make a platform to digitalize it for young people in the adolescent stage. This approach is to get high effectiveness of the self-esteem measurement using DAP test, including some personal inner situations which can be easily missed in the large statistical analysis. The other objective of this study is digitalize to recover limits of DAP test in the subjective rating standard. It is based on the distribution of the figure drawing expressed numerically by the anxiety index of Handler. For these two examinations, we made experiment through 4 stages with second grade middle school 73 students from July 30th to October 31th in 2009 during 4 months. Firstly, we executed 'Self Values Test' for all 73 people, and divided them into two groups; one is high self-esteem group of 36 people, the other is low self-esteem group of 37 people. Secondly, we regrouped them following D (Depression), Pd (Psychopathic Deviate), Sc (Schizophrenia) scales of MMPI; one is high self-esteem group of 7 people, the other is low self-esteem group of 13 people. Thirdly, we conducted DAP test separately for these 20 people. We intended to verify necessity and appropriateness of direction of 'Digitalizing Measurement System' by comparing and analyzing relation between DAP and Self-esteem following evaluation criteria which has similarity in 3 tests, after executing DAP to reflect peculiarity of adolescents sufficiently. We compared and analyzed result abstracted by sampling DAP test of two groups; One is high self-esteem group of 2 people, the other is low self-esteem group of 2 people; to confirm whether we can improve limitation that original psychological testing has by comparing mutual reliance of measurement test. Finally, with DAP test gained from correlations between self-esteem and melancholia following as above-mentioned steps, we discovered possibility of realization to get a concrete and individual criteria of evaluation based on Expert System as a way of enhancing accessibility in quantitative manner. 'Digitalizing Measurement Program' of DAP test suggested in this study promote results' reliability based on existing tests and measurement.
The purpose of this study is to evaluate the effect of resin cement color on the color of commercially available zirconia crown. The zirconia and resin cements used for the experiment were $NuSmile^{(R)}$ ZR Zirconia LT Shade (LT), $RelyX^{TM}$ U200 TR, A2, and A3O (TR, A2, A3O). The disks of zirconia and resin cements with diameters of 5 mm and thicknesses of 1 mm were prepared. Five disks were made for each specimen. The CIE $L^*a^*b^*$ values of zirconia, resin cements and the combinations thereof were measured on black and white backgrounds, respectively, using a spectrophotometer. The color effect of resin cement on the color of the zirconia crown was evaluated by calculating translucency parameter (TP), contrast ratio (CR), and color differences (${\Delta}E{^*}_{ab}$) based on the measured CIE $L^*a^*b^*$ values. The statistical significances were verified by one-way ANOVA and the Tukey-multiple comparisons tests. As a result, the TP and CR values were decreased (p<0.05) and increased, respectively, in the combination of zirconia and resin cement disks compared to zirconia disk per se. When using the black background, the ${\Delta}E{^*}_{ab}$ values between zirconia and the combination of the zirconia and three resin cement disks were imperceptible level. The A3O showed the lowest ${\Delta}E{^*}_{ab}$ value among three resin cements. When using the white background, the ${\Delta}E{^*}_{ab}$ values between zirconia and the combination of zirconia and TR resin cement (LT/TR) disks showed acceptable level. However, the ${\Delta}E{^*}_{ab}$ values between zirconia and the combination of zirconia and A2 resin cement (LT/A2) disks showed unacceptable level. Meanwhile, the ${\Delta}E{^*}_{ab}$ values between zirconia and the combination of zirconia and A3O resin cement (LT/A3O) disks showed perceptible but acceptable level. Within the limits of this study, the colors of resin cements did not cause unacceptable color changes of zirconia except the combination of LT/A2 on the white background. The resin cement that gave the least color changes to zirconia was A3O. This means that the resin cement A3O is recommended to use for minimizing color changes when cementing commercially available zirconia crown to tooth.
Purpose: This study was to evaluate the wear resistance of 3D printed, milled, and conventionally cured provisional resin materials. Materials and methods: Four types of resin materials made with different methods were examined: Stereolithography apparatus (SLA) 3D printed resin (S3P), digital light processing (DLP) 3D printed resin (D3P), milled resin (MIL), conventionally self-cured resin (CON). In the 3D printed resin specimens, the build orientation and layer thickness were set to $0^{\circ}$ and $100{\mu}m$, respectively. The specimens were tested in a 2-axis chewing simulator with the steatite as the antagonist under thermocycling condition (5 kg, 30,000 cycles, 0.8 Hz, $5^{\circ}C/55^{\circ}C$). Wear losses of the specimens were calculated using CAD software and scanning electron microscope (SEM) was used to investigate wear surface of the specimens. Statistical significance was determined using One-way ANOVA and Dunnett T3 analysis (${\alpha}=.05$). Results: Wear losses of the S3P, D3P, and MIL groups significantly smaller than those of the CON group (P < .05). There was no significant difference among S3P, D3P, and MIL group (P > .05). In the SEM observations, in the S3P and D3P groups, vertical cracks were observed in the sliding direction of the antagonist. In the MIL group, there was an overall uniform wear surface, whereas in the CON group, a distinct wear track and numerous bubbles were observed. Conclusion: Within the limits of this study, provisional resin materials made with 3D printing show adequate wear resistance for applications in dentistry.
Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.
Nowadays, customer satisfaction has been one of company's major objectives, and the index to measure and communicate customer satisfaction has been generally accepted among business practices. The major issues of CSI(customer satisfaction index) are three questions, as follows: (a)what level of customer satisfaction is tolerable, (b)whether customer satisfaction and company performance has positive causality, and (c)what to do to improve customer satisfaction. Among these, the second issue is recently attracting academic research in several perspectives. On this study, the second issue will be addressed. Many researchers including Anderson have regarded customer satisfaction as core competencies, such as brand equity, customer equity. They want to verify following causality "customer satisfaction → market performance(market share, sales growth rate) → financial performance(operating margin, profitability) → corporate value performance(stock price, credit ratings)" based on the process model of marketing performance. On the other hand, Insoo Jeon and Aeju Jeong(2009) verified sequential causality based on the process model by the domestic data. According to the rejection of several hypotheses, they suggested the balance model of marketing performance as an alternative. The objective of this study, based on the existing process model, is to examine the causal relationship between customer satisfaction and corporate value performance. Anderson and Mansi(2009) proved the relationship between ACSI(American Customer Satisfaction Index) and credit ratings using 2,574 samples from 1994 to 2004 on the assumption that credit rating could be an indicator of a corporate value performance. The similar study(Sangwoon Yoon, 2010) was processed in Korean data, but it didn't confirm the relationship between KCSI(Korean CSI) and credit ratings, unlike the results of Anderson and Mansi(2009). The summary of these studies is in the Table 1. Two studies analyzing the relationship between customer satisfaction and credit ratings weren't consistent results. So, in this study we are to test the conflicting results of the relationship between customer satisfaction and credit ratings based on the research model considering Korean credit ratings. To prove the hypothesis, we suggest the research model as follows. Two important features of this model are the inclusion of important variables in the existing Korean credit rating system and government support. To control their influences on credit ratings, we included three important variables of Korean credit rating system and government support, in case of financial institutions including banks. ROA, ER, TA, these three variables are chosen among various kinds of financial indicators since they are the most frequent variables in many previous studies. The results of the research model are relatively favorable : R2, F-value and p-value is .631, 233.15 and .000 respectively. Thus, the explanatory power of the research model as a whole is good and the model is statistically significant. The research model has good explanatory power, the regression coefficients of the KCSI is .096 as positive(+) and t-value and p-value is 2.220 and .0135 respectively. As a results, we can say the hypothesis is supported. Meanwhile, all other explanatory variables including ROA, ER, log(TA), GS_DV are identified as significant and each variables has a positive(+) relationship with CRS. In particular, the t-value of log(TA) is 23.557 and log(TA) as an explanatory variables of the corporate credit ratings shows very high level of statistical significance. Considering interrelationship between financial indicators such as ROA, ER which include total asset in their formula, we can expect multicollinearity problem. But indicators like VIF and tolerance limits that shows whether multicollinearity exists or not, say that there is no statistically significant multicollinearity in all the explanatory variables. KCSI, the main subject of this study, is a statistically significant level even though the standardized regression coefficients and t-value of KCSI is .055 and 2.220 respectively and a relatively low level among explanatory variables. Considering that we chose other explanatory variables based on the level of explanatory power out of many indicators in the previous studies, KCSI is validated as one of the most significant explanatory variables for credit rating score. And this result can provide new insights on the determinants of credit ratings. However, KCSI has relatively lower impact than main financial indicators like log(TA), ER. Therefore, KCSI is one of the determinants of credit ratings, but don't have an exceedingly significant influence. In addition, this study found that customer satisfaction had more meaningful impact on corporations of small asset size than those of big asset size, and on service companies than manufacturers. The findings of this study is consistent with Anderson and Mansi(2009), but different from Sangwoon Yoon(2010). Although research model of this study is a bit different from Anderson and Mansi(2009), we can conclude that customer satisfaction has a significant influence on company's credit ratings either Korea or the United State. In addition, this paper found that customer satisfaction had more meaningful impact on corporations of small asset size than those of big asset size and on service companies than manufacturers. Until now there are a few of researches about the relationship between customer satisfaction and various business performance, some of which were supported, some weren't. The contribution of this study is that credit rating is applied as a corporate value performance in addition to stock price. It is somewhat important, because credit ratings determine the cost of debt. But so far it doesn't get attention of marketing researches. Based on this study, we can say that customer satisfaction is partially related to all indicators of corporate business performances. Practical meanings for customer satisfaction department are that it needs to actively invest in the customer satisfaction, because active investment also contributes to higher credit ratings and other business performances. A suggestion for credit evaluators is that they need to design new credit rating model which reflect qualitative customer satisfaction as well as existing variables like ROA, ER, TA.
1. Introduction Today Internet is recognized as an important way for the transaction of products and services. According to the data surveyed by the National Statistical Office, the on-line transaction in 2007 for a year, 15.7656 trillion, shows a 17.1%(2.3060 trillion won) increase over last year, of these, the amount of B2C has been increased 12.0%(10.2258 trillion won). Like this, because the entry barrier of on-line market of Korea is low, many retailers could easily enter into the market. So the bigger its scale is, but on the other hand, the tougher its competition is. Particularly due to the Internet and innovation of IT, the existing market has been changed into the perfect competitive market(Srinivasan, Rolph & Kishore, 2002). In the early years of on-line business, they think that the main reason for success is a moderate price, they are awakened to its importance of on-line service quality with tough competition. If it's not sure whether customers can be provided with what they want, they can use the Web sites, perhaps they can trust their products that had been already bought or not, they have a doubt its viability(Parasuraman, Zeithaml & Malhotra, 2005). Customers can directly reserve and issue their air tickets irrespective of place and time at the Web sites of travel agencies or airlines, but its empirical studies about these Web sites for reserving and issuing air tickets are insufficient. Therefore this study goes on for following specific objects. First object is to measure service quality and service recovery of Web sites for reserving and issuing air tickets. Second is to look into whether above on-line service quality and on-line service recovery have an impact on overall service quality. Third is to seek for the relation with overall service quality and customer satisfaction, then this customer satisfaction and loyalty intention. 2. Theoretical Background 2.1 On-line Service Quality Barnes & Vidgen(2000; 2001a; 2001b; 2002) had invented the tool to measure Web sites' quality four times(called WebQual). The WebQual 1.0, Step one invented a measuring item for information quality based on QFD, and this had been verified by students of UK business school. The Web Qual 2.0, Step two invented for interaction quality, and had been judged by customers of on-line bookshop. The WebQual 3.0, Step three invented by consolidating the WebQual 1.0 for information quality and the WebQual2.0 for interactionquality. It includes 3-quality-dimension, information quality, interaction quality, site design, and had been assessed and confirmed by auction sites(e-bay, Amazon, QXL). Furtheron, through the former empirical studies, the authors changed sites quality into usability by judging that usability is a concept how customers interact with or perceive Web sites and It is used widely for accessing Web sites. By this process, WebQual 4.0 was invented, and is consist of 3-quality-dimension; information quality, interaction quality, usability, 22 items. However, because WebQual 4.0 is focusing on technical part, it's usable at the Website's design part, on the other hand, it's not usable at the Web site's pleasant experience part. Parasuraman, Zeithaml & Malhorta(2002; 2005) had invented the measure for measuring on-line service quality in 2002 and 2005. The study in 2002 divided on-line service quality into 5 dimensions. But these were not well-organized, so there needed to be studied again totally. So Parasuraman, Zeithaml & Malhorta(2005) re-worked out the study about on-line service quality measure base on 2002's study and invented E-S-QUAL. After they invented preliminary measure for on-line service quality, they made up a question for customers who had purchased at amazon.com and walmart.com and reassessed this measure. And they perfected an invention of E-S-QUAL consists of 4 dimensions, 22 items of efficiency, system availability, fulfillment, privacy. Efficiency measures assess to sites and usability and others, system availability measures accurate technical function of sites and others, fulfillment measures promptness of delivering products and sufficient goods and others and privacy measures the degree of protection of data about their customers and so on. 2.2 Service Recovery Service industries tend to minimize the losses by coping with service failure promptly. This responses of service providers to service failure mean service recovery(Kelly & Davis, 1994). Bitner(1990) went on his study from customers' view about service providers' behavior for customers to recognize their satisfaction/dissatisfaction at service point. According to them, to manage service failure successfully, exact recognition of service problem, an apology, sufficient description about service failure and some tangible compensation are important. Parasuraman, Zeithaml & Malhorta(2005) approached the service recovery from how to measure, rather than how to manage, and moved to on-line market not to off-line, then invented E-RecS-QUAL which is a measuring tool about on-line service recovery. 2.3 Customer Satisfaction The definition of customer satisfaction can be divided into two points of view. First, they approached customer satisfaction from outcome of comsumer. Howard & Sheth(1969) defined satisfaction as 'a cognitive condition feeling being rewarded properly or improperly for their sacrifice.' and Westbrook & Reilly(1983) also defined customer satisfaction/dissatisfaction as 'a psychological reaction to the behavior pattern of shopping and purchasing, the display condition of retail store, outcome of purchased goods and service as well as whole market.' Second, they approached customer satisfaction from process. Engel & Blackwell(1982) defined satisfaction as 'an assessment of a consistency in chosen alternative proposal and their belief they had with them.' Tse & Wilton(1988) defined customer satisfaction as 'a customers' reaction to discordance between advance expectation and ex post facto outcome.' That is, this point of view that customer satisfaction is process is the important factor that comparing and assessing process what they expect and outcome of consumer. Unlike outcome-oriented approach, process-oriented approach has many advantages. As process-oriented approach deals with customers' whole expenditure experience, it checks up main process by measuring one by one each factor which is essential role at each step. And this approach enables us to check perceptual/psychological process formed customer satisfaction. Because of these advantages, now many studies are adopting this process-oriented approach(Yi, 1995). 2.4 Loyalty Intention Loyalty has been studied by dividing into behavioral approaches, attitudinal approaches and complex approaches(Dekimpe et al., 1997). In the early years of study, they defined loyalty focusing on behavioral concept, behavioral approaches regard customer loyalty as "a tendency to purchase periodically within a certain period of time at specific retail store." But the loyalty of behavioral approaches focuses on only outcome of customer behavior, so there are someone to point the limits that customers' decision-making situation or process were neglected(Enis & Paul, 1970; Raj, 1982; Lee, 2002). So the attitudinal approaches were suggested. The attitudinal approaches consider loyalty contains all the cognitive, emotional, voluntary factors(Oliver, 1997), define the customer loyalty as "friendly behaviors for specific retail stores." However these attitudinal approaches can explain that how the customer loyalty form and change, but cannot say positively whether it is moved to real purchasing in the future or not. This is a kind of shortcoming(Oh, 1995). 3. Research Design 3.1 Research Model Based on the objects of this study, the research model derived is
. 3.2 Hypotheses 3.2.1 The Hypothesis of On-line Service Quality and Overall Service Quality The relation between on-line service quality and overall service quality I-1. Efficiency of on-line service quality may have a significant effect on overall service quality. I-2. System availability of on-line service quality may have a significant effect on overall service quality. I-3. Fulfillment of on-line service quality may have a significant effect on overall service quality. I-4. Privacy of on-line service quality may have a significant effect on overall service quality. 3.2.2 The Hypothesis of On-line Service Recovery and Overall Service Quality The relation between on-line service recovery and overall service quality II-1. Responsiveness of on-line service recovery may have a significant effect on overall service quality. II-2. Compensation of on-line service recovery may have a significant effect on overall service quality. II-3. Contact of on-line service recovery may have a significant effect on overall service quality. 3.2.3 The Hypothesis of Overall Service Quality and Customer Satisfaction The relation between overall service quality and customer satisfaction III-1. Overall service quality may have a significant effect on customer satisfaction. 3.2.4 The Hypothesis of Customer Satisfaction and Loyalty Intention The relation between customer satisfaction and loyalty intention IV-1. Customer satisfaction may have a significant effect on loyalty intention. 3.2.5 The Hypothesis of a Mediation Variable Wolfinbarger & Gilly(2003) and Parasuraman, Zeithaml & Malhotra(2005) had made clear that each dimension of service quality has a significant effect on overall service quality. Add to this, the authors analyzed empirically that each dimension of on-line service quality has a positive effect on customer satisfaction. With that viewpoint, this study would examine if overall service quality mediates between on-line service quality and each dimension of customer satisfaction, keeping on looking into the relation between on-line service quality and overall service quality, overall service quality and customer satisfaction. And as this study understands that each dimension of on-line service recovery also has an effect on overall service quality, this would examine if overall service quality also mediates between on-line service recovery and each dimension of customer satisfaction. Therefore these hypotheses followed are set up to examine if overall service quality plays its role as the mediation variable. The relation between on-line service quality and customer satisfaction V-1. Overall service quality may mediate the effects of efficiency of on-line service quality on customer satisfaction. V-2. Overall service quality may mediate the effects of system availability of on-line service quality on customer satisfaction. V-3. Overall service quality may mediate the effects of fulfillment of on-line service quality on customer satisfaction. V-4. Overall service quality may mediate the effects of privacy of on-line service quality on customer satisfaction. The relation between on-line service recovery and customer satisfaction VI-1. Overall service quality may mediate the effects of responsiveness of on-line service recovery on customer satisfaction. VI-2. Overall service quality may mediate the effects of compensation of on-line service recovery on customer satisfaction. VI-3. Overall service quality may mediate the effects of contact of on-line service recovery on customer satisfaction. 4. Empirical Analysis 4.1 Research design and the characters of data This empirical study aimed at customers who ever purchased air ticket at the Web sites for reservation and issue. Total 430 questionnaires were distributed, and 400 were collected. After surveying with the final questionnaire, the frequency test was performed about variables of sex, age which is demographic factors for analyzing general characters of sample data. Sex of data is consist of 146 of male(42.7%) and 196 of female(57.3%), so portion of female is a little higher. Age is composed of 11 of 10s(3.2%), 199 of 20s(58.2%), 105 of 30s(30.7%), 22 of 40s(6.4%), 5 of 50s(1.5%). The reason that portions of 20s and 30s are higher can be supposed that they use the Internet frequently and purchase air ticket directly. 4.2 Assessment of measuring scales This study used the internal consistency analysis to measure reliability, and then used the Cronbach'$\alpha$ to assess this. As a result of reliability test, Cronbach'$\alpha$ value of every component shows more than 0.6, it is found that reliance of the measured variables are ensured. After reliability test, the explorative factor analysis was performed. the factor sampling was performed by the Principal Component Analysis(PCA), the factor rotation was performed by the Varimax which is good for verifying mutual independence between factors. By the result of the initial factor analysis, items blocking construct validity were removed, and the result of the final factor analysis performed for verifying construct validity is followed above. 4.3 Hypothesis Testing 4.3.1 Hypothesis Testing by the Regression Analysis(SPSS) 4.3.2 Analysis of Mediation Effect To verify mediation effect of overall service quality of and , this study used the phased analysis method proposed by Baron & Kenny(1986) generally used. As
shows, Step 1 and Step 2 are significant, and mediation variable has a significant effect on dependent variables and so does independent variables at Step 3, too. And there needs to prove the partial mediation effect, independent variable's estimate ability at Step 3(Standardized coefficient $\beta$eta : efficiency=.164, system availability=.074, fulfillment=.108, privacy=.107) is smaller than its estimate ability at Step 2(Standardized coefficient $\beta$eta : efficiency=.409, system availability=.227, fulfillment=.386, privacy=.237), so it was proved that overall service quality played a role as the partial mediation between on-line service quality and satisfaction. As
shows, Step 1 and Step 2 are significant, and mediation variable has a significant effect on dependent variables and so does independent variables at Step 3, too. And there needs to prove the partial mediation effect, independent variable's estimate ability at Step 3(Standardized coefficient $\beta$eta : responsiveness=.164, compensation=.117, contact=.113) is smaller than its estimate ability at Step 2(Standardized coefficient $\beta$eta : responsiveness=.409, compensation=.386, contact=.237), so it was proved that overall service quality played a role as the partial mediation between on-line service recovery and satisfaction. Verified results on the basis of empirical analysis are followed. First, as the result of , it shows that all were chosen, so on-line service quality has a positive effect on overall service quality. Especially fulfillment of overall service quality has the most effect, and then efficiency, system availability, privacy in order. Second, as the result of , it shows that all were chosen, so on-line service recovery has a positive effect on overall service quality. Especially responsiveness of overall service quality has the most effect, and then contact, compensation in order. Third, as the result of and , it shows that and all were chosen, so overall service quality has a positive effect on customer satisfaction, customer satisfaction has a positive effect on loyalty intention. Fourth, as the result of and , it shows that and all were chosen, so overall service quality plays a role as the partial mediation between on-line service quality and customer satisfaction, on-line service recovery and customer satisfaction. 5. Conclusion This study measured and analyzed service quality and service recovery of the Web sites that customers made a reservation and issued their air tickets, and by improving customer satisfaction through the result, this study put its final goal to grope how to keep loyalty customers. On the basis of the result of empirical analysis, suggestion points of this study are followed. First, this study regarded E-S-QUAL that measures on-line service quality and E-RecS-QUAL that measures on-line service recovery as variables, so it overcame the limit of existing studies that used modified SERVQUAL to measure service quality of the Web sites. Second, it shows that fulfillment and efficiency of on-line service quality have the most significant effect on overall service quality. Therefore the Web sites of reserving and issuing air tickets should try harder to elevate efficiency and fulfillment. Third, privacy of on-line service quality has the least significant effect on overall service quality, but this may be caused by un-assurance of customers whether the Web sites protect safely their confidential information or not. So they need to notify customers of this fact clearly. Fourth, there are many cases that customers don't recognize the importance of on-line service recovery, but if they would think that On-line service recovery has an effect on customer satisfaction and loyalty intention, as its importance is very significant they should prepare for that. Fifth, because overall service quality has a positive effect on customer satisfaction and loyalty intention, they should try harder to elevate service quality and service recovery of the Web sites of reserving and issuing air tickets to maximize customer satisfaction and to secure loyalty customers. Sixth, it is found that overall service quality plays a role as the partial mediation, but now there are rarely existing studies about this, so there need to be more studies about this.
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