Changes in consumer needs and behaviors according to lifestyle changes lead to consumption culture, affecting the automobile market. However, research and research to provide options tailored to the lifestyle of consumers in related markets are still insufficient. Focusing on pickup truck accessories applied to pickup trucks that reflect lifestyle the most among vehicle types, this study first examined the theoretical background of the aftermarket market and lifestyle of pickup trucks. Second, through image mapping, the market possibilities and opportunity factors of pickup trucks were discovered through market size analysis and possibilities, and through this, user types could be classified. Third, interviews were conducted with those representing user types, the contents were organized, and interviews were conducted centering on related groups to create a persona of a user group, and what needs each group's persona wanted. Finally, a design concept suitable for the issue keywords and insights derived for each user lifestyle type was presented. In this study, the user type was divided into ① outdoor activity type, ② hobby activity type, and ③ small-scale work type, and a design case study was conducted by applying the concept suitable for the keyword for each group. For the outdoor activity type, a variable storage structure and a living space-type accessory design were presented, and for the hobby type, a modular decktop design and a sports coupe-type hardtop design were presented. For the small business type, a partition that is easy to fix the load and a stepper design that is easy to board the cargo box were presented. It is expected that the size of the pickup truck aftermarket will be expanded by diversifying the option designs that users want by lifestyle by applying them to the development of pickup truck accessories that fit the lifestyle of pickup truck users in the automobile market, which is currently mass customized.
Korea has developed as an influential country over Asia and all over the world based on remarkable economic development. And the background of this development was possible due to the existence of those who sacrificed precious lives and contributed to the nation's existence in the past crisis. Every year, Korea holds an annual commemorative event with people of national merit, Korean War veterans, and their families, expressing gratitude for sacrifices and contributions at home and abroad, and providing economic support. The tragedy of the Korean War and the pro-democracy movement in Korea over the past half century will one day become a history of the distant past over time. As generations change and the purpose and method of exchange by region change, the tragic situation that occurred earlier and the way people sacrificed for the country are expected to be different from before. In particular, it is true that the number of Korean War veterans and their families is gradually decreasing as they are now old. In addition, due to the outbreak of global infectious diseases such as COVID-19, it is difficult to plan and conduct face to face events as well as before. Currently, Korea's digital technology is introducing various methods. 5G communication networks, smart-phones, tablet PCs, and smart devices that can experience virtual reality are already used in our real lives. Business meetings are held in a metaverse environment, and concerts by famous singers are held in an online environment. Artificial intelligence technology has also been introduced in the field of human resource recruitment and customer response services, improving the work efficiency of companies. And it seems that this technology can be used in the field of veterans. In particular, there is a metaverse technology that can vividly show the situation during the Korean War, and a way to digitalize the voices and facial expressions of currently surviving veterans to convey their memories and lessons to future generations in the long run. If this digital technology method is realized on an online platform to hold a veterans' celebration event, veterans and their families on the other side of the world will be able to participate in the event more conveniently.
Can money buy happiness? If not, what are the factors that influence happiness? What makes people happy? What are the factors that influence happiness among Korean adults? How can we better explain factors that influence happiness? These are the research questions that led to the analyses of psychological, relational, financial resources that influence happiness. To examine differences in socio-economic status, adults and elderly from three different districts that vary wealth and income were interviewed in their own home. A total of 313 respondents (male=133, female=180) between the ages of 20 through 80 completed a questionnaire that contained background information, emotional support scale and happiness scale developed by the present researcher and resiliency of efficacy developed by Bandura(1995). The results are as follows. First, monthly income influence happiness to some extent, but when the variable was excluded from the path analysis, the goodness-of-fit did not change significantly. Although those who have more money can be happier, those without much money can also be happy. These results indicate that financial resource has limited influence on happiness. In addition, monthly income did influence self-efficacy of respondents indicating that those with more money were not necessarily more confident about themselves. Second, an important factor influencing happiness is the relational resource. Emotional support was the most powerful predictor of happiness, four to five times more important than monthly income. Third, self-efficacy influenced happiness. Those respondents with higher resiliency of efficacy had higher happiness scores and the influence was two times greater than monthly income. Moreover, self-efficacy played a mediating role between emotional support and happiness. Fourth, those respondents with higher occupational achievement reported higher happiness score and the influence was two times greater than monthly income. Fifth, success of children influenced happiness score and the influence was 1.5 times greater than monthly income. Sixth, education did not directly influence happiness, but had an indirect influence through self-efficacy and occupational achievement. Seventh, age was not related to self-efficacy and happiness.
Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.
Service failure is one of the major reasons for customer defection. As the business environment gets tougher and more competitive, a single service failure might bring about fatal consequences to a service provider or a firm. Sometimes a failure won't end up with an unsatisfied customer's simple complaining but with a wide-spread animosity against the service provider or the firm, leading to a threat to the firm's survival itself in the society. Therefore, we are in need of comprehensive understandings of complainants' attitudes and behaviors toward service failures and firm's recovery efforts. Even though a failure itself couldn't be fixed completely, marketers should repair the mind and heart of unsatisfied customers, which can be regarded as an successful recovery strategy in the end. As the outcome of recovery efforts exerted by service providers or firms, recovery of the relationship between customer and service provider need to put on the top in the recovery goal list. With these motivations, the study investigates how service failure and recovery makes the changes in dynamics of fundamental elements of customer-firm relationship, such as customer affection, customer trust and loyalty intention by comparing two time points, before the service failure and after the recovery, focusing on the effects of recovery satisfaction and the failure severity. We adopted La & Choi (2012)'s framework for development of the research model that was based on the previous research stream like Yim et al. (2008) and Thomson et al. (2005). The pivotal background theories of the model are mainly from relationship marketing and social relationships of social psychology. For example, Love, Emotional attachment, Intimacy, and Equity theories regarding human relationships were reviewed. As the results, when recovery satisfaction is high, customer affection and customer trust that were established before the service failure are carried over to the future after the recovery. However, when recovery satisfaction is low, customer-firm relationship that had already established in the past are not carried over but broken up. Regardless of the degree of recovery satisfaction, once a failure occurs loyalty intention is not carried over to the future and the impact of customer trust on loyalty intention becomes stronger. Such changes imply that customers become more prudent and more risk-aversive than the time prior to service failure. The impact of severity of failure on customer affection and customer trust matters only when recovery satisfaction is low. When recovery satisfaction is high, customer affection and customer trust become severity-proof. Interestingly, regardless of the degree of recovery satisfaction, failure severity has a significant negative influence on loyalty intention. Loyalty intention is the most fragile target when a service failure occurs no matter how severe the failure criticality is. Consequently, the ultimate goal of service recovery should be the restoration of customer-firm relationship and recovery of customer trust should be the primary objective to accomplish for a successful recovery performance. Especially when failure severity is high, service recovery should be perceived highly satisfied by the complainants because failure severity matters more when recovery satisfaction is low. Marketers can implement recovery strategies to enhance emotional appeals as well as fair treatments since the both impacts of affection and trust on loyalty intention are significant. In the case of high severity of failure, recovery efforts should be exerted to overreach customer expectation, designed to directly repair customer trust and elaborately designed in the focus of customer-firm communications during the interactional recovery process to affect customer trust rebuilding indirectly. Because it is a longer and harder way to rebuild customer-firm relationship for high severity cases, low recovery satisfaction cannot guarantee customer retention. To prevent customer defection due to service failure of high severity, unexpected rewards as a recovery will be likely to be useful since those will lead to customer delight or customer gratitude toward the service firm. Based on the results of analyses, theoretical and managerial implications are presented. Limitations and future research ideas are also discussed.
Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.
Background : The p53 gene codes for a DNA-binding nuclear phosphoprotein that appears to inhibit the progression of cells from the G1 to the S phase of the cell cycle. Mutations of the p53 gene are common in a wide variety of human cancers, including lung cancer. In lung cancers, point mutations of the p53 gene have been found in all histological types including approximately 45% of resected NSCLC and even more frequently in SCLC specimens. Mutant forms of the p53 protein have transforming activity and interfere with the cell-cycle regulatory function of the wild-type protein. The majority of p53 gene mutations produce proteins with altered conformation and prolonged half life; these mutant proteins accumulate in the cell nucleus and can be detected by immunohistochemical staining. But protein overexpression has been reported in the absence of mutation. p53 protein overexpression or gene mutation is reported poor prognostic factor in breast cancer, but in lung cancer, its prognostic significance is controversial. Method : We investigated the p53 abnormalities by nucleotide sequencing, polymerase chain reaction-single strand conformation polymorphism(PCR-SSCP), and immunohistochemical staining. We correlated these results with each other and survival in 75 patients with NSCLC resected with curative intent. Overexpression of the p53 protein was studied immunohistochemically in archival paraffin- embedded tumor samples using the D07(Novocastra, U.K.) antibody. Overexpression of p53 protein was defined by the nuclear staining of greater than 25% immunopositive cells in tumors. Detection of p53 gene mutation was done by PCR-SSCP and nucleotide sequencing from the exon 5-9 of p53 gene. Result: 1) Of the 75 patients, 36%(27/75) showed p53 overexpression by immunohistochemical stain. There was no survival difference between positive and negative p53 immunostaining(overall median survival of 26 months, disease free median survival of 13 months in both groups). 2) By PCR-SSCP, 27.6%(16/58) of the patients showed mobility shift. There was no significant difference in survival according to mobility shift(overall median survival of 27 in patients without mobility shift vs 20 months in patients with mobility shift, disease free median survival of 8 months vs 10 months respectively). 3) Nucleotide sequence was analysed from 29 patients, and 34.5%(10/29) had mutant p53 sequence. Patients with the presence of gene mutations showed tendency to shortened survival compared with the patients with no mutation(overall median survival of 22 vs 27 months, disease free median survival of 10 vs 20 months), but there was no statistical significance. 4) The sensitivity and specificity of immunostain based on PCR-SSCP was 67.0%, 74.0%, and that of the PCR-SSCP based on the nucleotide sequencing was 91.8%, 96.2% respectively. The concordance rate between the immunostain and PCR-SSCP was 62.5%, and the rate between the PCR-SSCP and nucleotide sequencing was 95.3%. Conclusion : In terms of detection of p53 gene mutation, PCR-SSCP was superior to immunostaining. p53 gene abnormalities either overexpression or mutation were not a significant prognostic factor in NSCLC patients resected with curative intent. However, patients with the mutated p53 gene showed the trends of early relapse.
To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.
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.
본 웹사이트에 게시된 이메일 주소가 전자우편 수집 프로그램이나
그 밖의 기술적 장치를 이용하여 무단으로 수집되는 것을 거부하며,
이를 위반시 정보통신망법에 의해 형사 처벌됨을 유념하시기 바랍니다.
[게시일 2004년 10월 1일]
이용약관
제 1 장 총칙
제 1 조 (목적)
이 이용약관은 KoreaScience 홈페이지(이하 “당 사이트”)에서 제공하는 인터넷 서비스(이하 '서비스')의 가입조건 및 이용에 관한 제반 사항과 기타 필요한 사항을 구체적으로 규정함을 목적으로 합니다.
제 2 조 (용어의 정의)
① "이용자"라 함은 당 사이트에 접속하여 이 약관에 따라 당 사이트가 제공하는 서비스를 받는 회원 및 비회원을
말합니다.
② "회원"이라 함은 서비스를 이용하기 위하여 당 사이트에 개인정보를 제공하여 아이디(ID)와 비밀번호를 부여
받은 자를 말합니다.
③ "회원 아이디(ID)"라 함은 회원의 식별 및 서비스 이용을 위하여 자신이 선정한 문자 및 숫자의 조합을
말합니다.
④ "비밀번호(패스워드)"라 함은 회원이 자신의 비밀보호를 위하여 선정한 문자 및 숫자의 조합을 말합니다.
제 3 조 (이용약관의 효력 및 변경)
① 이 약관은 당 사이트에 게시하거나 기타의 방법으로 회원에게 공지함으로써 효력이 발생합니다.
② 당 사이트는 이 약관을 개정할 경우에 적용일자 및 개정사유를 명시하여 현행 약관과 함께 당 사이트의
초기화면에 그 적용일자 7일 이전부터 적용일자 전일까지 공지합니다. 다만, 회원에게 불리하게 약관내용을
변경하는 경우에는 최소한 30일 이상의 사전 유예기간을 두고 공지합니다. 이 경우 당 사이트는 개정 전
내용과 개정 후 내용을 명확하게 비교하여 이용자가 알기 쉽도록 표시합니다.
제 4 조(약관 외 준칙)
① 이 약관은 당 사이트가 제공하는 서비스에 관한 이용안내와 함께 적용됩니다.
② 이 약관에 명시되지 아니한 사항은 관계법령의 규정이 적용됩니다.
제 2 장 이용계약의 체결
제 5 조 (이용계약의 성립 등)
① 이용계약은 이용고객이 당 사이트가 정한 약관에 「동의합니다」를 선택하고, 당 사이트가 정한
온라인신청양식을 작성하여 서비스 이용을 신청한 후, 당 사이트가 이를 승낙함으로써 성립합니다.
② 제1항의 승낙은 당 사이트가 제공하는 과학기술정보검색, 맞춤정보, 서지정보 등 다른 서비스의 이용승낙을
포함합니다.
제 6 조 (회원가입)
서비스를 이용하고자 하는 고객은 당 사이트에서 정한 회원가입양식에 개인정보를 기재하여 가입을 하여야 합니다.
제 7 조 (개인정보의 보호 및 사용)
당 사이트는 관계법령이 정하는 바에 따라 회원 등록정보를 포함한 회원의 개인정보를 보호하기 위해 노력합니다. 회원 개인정보의 보호 및 사용에 대해서는 관련법령 및 당 사이트의 개인정보 보호정책이 적용됩니다.
제 8 조 (이용 신청의 승낙과 제한)
① 당 사이트는 제6조의 규정에 의한 이용신청고객에 대하여 서비스 이용을 승낙합니다.
② 당 사이트는 아래사항에 해당하는 경우에 대해서 승낙하지 아니 합니다.
- 이용계약 신청서의 내용을 허위로 기재한 경우
- 기타 규정한 제반사항을 위반하며 신청하는 경우
제 9 조 (회원 ID 부여 및 변경 등)
① 당 사이트는 이용고객에 대하여 약관에 정하는 바에 따라 자신이 선정한 회원 ID를 부여합니다.
② 회원 ID는 원칙적으로 변경이 불가하며 부득이한 사유로 인하여 변경 하고자 하는 경우에는 해당 ID를
해지하고 재가입해야 합니다.
③ 기타 회원 개인정보 관리 및 변경 등에 관한 사항은 서비스별 안내에 정하는 바에 의합니다.
제 3 장 계약 당사자의 의무
제 10 조 (KISTI의 의무)
① 당 사이트는 이용고객이 희망한 서비스 제공 개시일에 특별한 사정이 없는 한 서비스를 이용할 수 있도록
하여야 합니다.
② 당 사이트는 개인정보 보호를 위해 보안시스템을 구축하며 개인정보 보호정책을 공시하고 준수합니다.
③ 당 사이트는 회원으로부터 제기되는 의견이나 불만이 정당하다고 객관적으로 인정될 경우에는 적절한 절차를
거쳐 즉시 처리하여야 합니다. 다만, 즉시 처리가 곤란한 경우는 회원에게 그 사유와 처리일정을 통보하여야
합니다.
제 11 조 (회원의 의무)
① 이용자는 회원가입 신청 또는 회원정보 변경 시 실명으로 모든 사항을 사실에 근거하여 작성하여야 하며,
허위 또는 타인의 정보를 등록할 경우 일체의 권리를 주장할 수 없습니다.
② 당 사이트가 관계법령 및 개인정보 보호정책에 의거하여 그 책임을 지는 경우를 제외하고 회원에게 부여된
ID의 비밀번호 관리소홀, 부정사용에 의하여 발생하는 모든 결과에 대한 책임은 회원에게 있습니다.
③ 회원은 당 사이트 및 제 3자의 지적 재산권을 침해해서는 안 됩니다.
제 4 장 서비스의 이용
제 12 조 (서비스 이용 시간)
① 서비스 이용은 당 사이트의 업무상 또는 기술상 특별한 지장이 없는 한 연중무휴, 1일 24시간 운영을
원칙으로 합니다. 단, 당 사이트는 시스템 정기점검, 증설 및 교체를 위해 당 사이트가 정한 날이나 시간에
서비스를 일시 중단할 수 있으며, 예정되어 있는 작업으로 인한 서비스 일시중단은 당 사이트 홈페이지를
통해 사전에 공지합니다.
② 당 사이트는 서비스를 특정범위로 분할하여 각 범위별로 이용가능시간을 별도로 지정할 수 있습니다. 다만
이 경우 그 내용을 공지합니다.
제 13 조 (홈페이지 저작권)
① NDSL에서 제공하는 모든 저작물의 저작권은 원저작자에게 있으며, KISTI는 복제/배포/전송권을 확보하고
있습니다.
② NDSL에서 제공하는 콘텐츠를 상업적 및 기타 영리목적으로 복제/배포/전송할 경우 사전에 KISTI의 허락을
받아야 합니다.
③ NDSL에서 제공하는 콘텐츠를 보도, 비평, 교육, 연구 등을 위하여 정당한 범위 안에서 공정한 관행에
합치되게 인용할 수 있습니다.
④ NDSL에서 제공하는 콘텐츠를 무단 복제, 전송, 배포 기타 저작권법에 위반되는 방법으로 이용할 경우
저작권법 제136조에 따라 5년 이하의 징역 또는 5천만 원 이하의 벌금에 처해질 수 있습니다.
제 14 조 (유료서비스)
① 당 사이트 및 협력기관이 정한 유료서비스(원문복사 등)는 별도로 정해진 바에 따르며, 변경사항은 시행 전에
당 사이트 홈페이지를 통하여 회원에게 공지합니다.
② 유료서비스를 이용하려는 회원은 정해진 요금체계에 따라 요금을 납부해야 합니다.
제 5 장 계약 해지 및 이용 제한
제 15 조 (계약 해지)
회원이 이용계약을 해지하고자 하는 때에는 [가입해지] 메뉴를 이용해 직접 해지해야 합니다.
제 16 조 (서비스 이용제한)
① 당 사이트는 회원이 서비스 이용내용에 있어서 본 약관 제 11조 내용을 위반하거나, 다음 각 호에 해당하는
경우 서비스 이용을 제한할 수 있습니다.
- 2년 이상 서비스를 이용한 적이 없는 경우
- 기타 정상적인 서비스 운영에 방해가 될 경우
② 상기 이용제한 규정에 따라 서비스를 이용하는 회원에게 서비스 이용에 대하여 별도 공지 없이 서비스 이용의
일시정지, 이용계약 해지 할 수 있습니다.
제 17 조 (전자우편주소 수집 금지)
회원은 전자우편주소 추출기 등을 이용하여 전자우편주소를 수집 또는 제3자에게 제공할 수 없습니다.
제 6 장 손해배상 및 기타사항
제 18 조 (손해배상)
당 사이트는 무료로 제공되는 서비스와 관련하여 회원에게 어떠한 손해가 발생하더라도 당 사이트가 고의 또는 과실로 인한 손해발생을 제외하고는 이에 대하여 책임을 부담하지 아니합니다.
제 19 조 (관할 법원)
서비스 이용으로 발생한 분쟁에 대해 소송이 제기되는 경우 민사 소송법상의 관할 법원에 제기합니다.
[부 칙]
1. (시행일) 이 약관은 2016년 9월 5일부터 적용되며, 종전 약관은 본 약관으로 대체되며, 개정된 약관의 적용일 이전 가입자도 개정된 약관의 적용을 받습니다.