• 대한공업교육학회지
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• v.33 no.2
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• pp.97-119
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• 2008

The purpose of this research is to clarify the elements of the function of the role of industrial high schools that its experts perceived. The content of this research is verify the function element required for the performance of the role of specialized education through content validity ratio(CVR). This research adopted the method of literature research and Delphi method, which is to collect and come to an agreement of the opinions of the 26 research panels. The first round is constructed by the semi-constructed questionnaire for the analysis of the opinions of the panels by inductive method. The second round is to categorize the result of the first one into 7 domains, and asked each category by Likert's 5 scale checklists, and statistically analyzed mean, medium, standard deviation, and quartile. The third round is to statistically analyze Mean, standard deviation, medium, and validity ratio(CVR) to reassure the opinions of the panels on the basis of the result of the first one. The categorized contents of the function required for the performance of the specialized education in this research is 'in-service visit and in-service training', 'licence acquiring education', 'employment counseling and job employment information', 'custom-made education connected with industry', 'career education' and 'enhancement of basic career competency'. The panels are divided into professors, teachers, professionals, and policy administrators, and they verified the validity rate of the function role and priority of emphasis. The result showed that the tendency of the education is converting from physical function-centered education to education of emotional attitude and competence of thought.

• Management & Information Systems Review
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• v.36 no.5
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• pp.1-26
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• 2017

In the meantime, research on corporate informatization focuses on the completeness of information technology itself and its financial effects, so there is insufficient research on whether information technology can support business strategy. It is necessary to verify whether the management strategy implementation of the company can be led through the informatization of the enterprise and the relation between the main mechanism factors and the informatization performance. In this study, what a mechanism factor is applied in the process of result creation of informatization from three mechanism perspectives such as selecting mechanism, learning mechanism and coordinating mechanism with cases of representative domestic IT company and what an importance mechanism factors have been ascertained. This study results in 8 propositions. For a main agent of companies, securement of information capability of organizations has been selected to realize informatization results and investment of informatization has been selected to solve organizational decentralization problems as the most important factor. Additionally, as competition in the industry gets fierce, investment on informatization has been changed to a utility way of implementation of strategies and decision on investment has been made through the official process and information technology. Differentiated company capability has been made based on acquisition of technical knowledge and company information has been expanded to its whole employees through the information system. Also, informatization change management and outside subcontractor management have been acknowledged as an important adjustment factor of company. The first implication of this study is that since case studies on mechanism factors that preceding studies on informatization results did not empirically cover have directly been dealt with based on experiences of executives in charge of business and in charge of informatization, this study can provide practical views about factors that should be mainly managed for informatization results of IT companies. Secondly, since ser-M framework has been applied for IT companies for the first time, this study can academically contribute to companies in other fields about main mechanism factors for result creation of informatization based on deeper understanding and empirical cases.

• (The) Research of the performance art and culture
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• no.34
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• pp.111-131
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• 2017

Korean Shamanism has long been regarded as the peripheral cult or supersition by the majoriy of the society. This fact is a result by the influence of the mass media, especially the motion pictures, which intentionally reflected the negative images of the Shamanism. The documentary films, which stress the objectivity and the reality, rather disclose the neutral position toward the Shamanism. In fact, the directors of the documentary films who have more or less close relationship with the Shamanism have tried to exhibit the mental world and the traditionality of the Shamanism. In this paper, I will explore the value of Shamanism reflected in the documentary films. I focus of two films; directed by the Korean and directed by a foreigner. In this way, I can compare the attitudes of the two directors toward the Korean Shamanism. The director of confessed that he was attracted by the aspect of a musical underlied in the shaman ritual. However, the film does not show the artistic beauty of the shaman music because the director failed to understand the essential aspect of the shaman ritual, that is, the music. In this way, the director failed to show the distinct characteristics of the shamanism to the audience. The director of , a music herself, was focused on the music of the shamanism. The story flows to the adventure to seek a "master" with a long journey to enjoy diverse genres of Korean performing arts. This story resembles the epic shaman song, the Princess Bari. In this way, the audience can easily grasp the beauty of Korean culture. Music is said to be a universal language and, at the same time, a non-universal language which reflects a special trait of a cultural community. The Korean shaman ritual music is a non-universal language that is an accumulation of the Korean culture for a long time. The Korean director fails to exhibit the essential characteristics of the Shamanism since he does not have enough knowledge toward the shaman ritual music in . However, the foreign director, who is a music herself, successively disclose the underlying beauty of Korean shaman ritual music and Korean traditional culture in .

• Journal of Global Scholars of Marketing Science
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• v.19 no.3
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• pp.28-36
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• 2009

While existing literature has focused extensively on the strengths and weaknesses of the Chaebol and their ownership and governance, there have been few studies of Korean non-Chaebol firms. However, Lee, Lee and Pennings (2001) did not specifically investigate the competitive strategies that non-Chaebol firms use to survive against the Chaebol in the domestic Korean market. The motivation of this paper is to document, through four exploratory case studies, the successful competitive strategies of non-Chaebol Korean companies against the Chaebol and then offer some propositions that may be useful to other entrepreneurial firms as well as public policy makers. Competition and cooperation as conceptualized by product similarity and cooperative inter.firm relationship respectively, are major dimensions of firm.level marketing strategy. From these two dimensions, we develop the following $2{\times}2$ matrix, with 4 types of competitive strategies for non-Chaebol companies against the Chaebol (Fig. 1.). The non-Chaebol firm in Cell 1 has a "me-too" product for the low-end market while conceding the high-end market to a Chaebol. In Cell 2, the non-Chaebol firm partners with a Chaebol company, either as a supplier or complementor. In Cell 3, the non-Chaebol firm engages in direct competition with a Chaebol. In Cell 4, the non-Chaebol firm targets an unserved part of the market with an innovative product or service. The four selected cases such as E.Rae Electronics Industry Company (Co-exister), Intops (Supplier), Pantech (Competitor) and Humax (Niche Player) are analyzed to provide each strategy with richer insights. Following propositions are generated based upon our conceptual framework: Proposition 1: Non-Chaebol firms that have a cooperative relationship with a Chaebol will perform better than firms that do not. Proposition 1a; Co-existers will perform better than Competitors. Proposition 1b: Partners (suppliers or complementors) will perform better than Niche players. Proposition 2: Firms that have no product similarity with a Chaebol will perform better than firms that have product similarity. Proposition 2a: Partners (suppliers or complementors) will perform better than Co.existers. Proposition 2b: Niche players will perform better than Competitors. Proposition 3: Niche players should perform better than Co-existers. Proposition 4: Performance can be rank.ordered in descending order as Partners, Niche Players, Co.existers, Competitors. A team of experts was constituted to categorize each of these 216 non-Chaebol companies into one of the 4 cells in our typology. Simple Analysis of Variance (ANOVA) in SPSS statistical software was used to test our propositions. Overall findings are that it is better to have a cooperative relationship with a Chaebol and to offer products or services differentiated from a Chaebol. It is clear that the only profitable strategy, on average, to compete against the Chaebol is to be a partner (supplier or complementor). Competing head on with a Chaebol company is a costly strategy not likely to pay off for a non-Chaebol firm. Strategies to avoid head on competition with the Chaebol by serving niche markets with differentiated products or by serving the low-end of the market ignored by the Chaebol are better survival strategies. This paper illustrates that there are ways in which small and medium Korean non-Chaebol firms can thrive in a Chaebol environment, though not without risks. Using different combinations of competition and cooperation firms may choose particular positions along the product similarity and cooperative relationship dimensions to develop their competitive strategies-co-exister, competitor, partner, niche player. Based on our exploratory case-study analysis, partner seems to be the best strategy for non-Chaebol firms while competitor appears to be the most risky one. Niche players and co-existers have intermediate performance, though the former do better than the latter. It is often the case with managers of small and medium size companies that they tend to view market leaders, typically the Chaebol, with rather simplistic assumptions of either competition or collaboration. Consequently, many non-Chaebol firms turn out to be either passive collaborators or overwhelmed competitors of the Chaebol. In fact, competition and collaboration are not mutually exclusive, and can be pursued at the same time. As suggested in this paper, non-Chaebol firms can actively choose to compete and collaborate, depending on their environment, internal resources and capabilities.

• (The) Research of the performance art and culture
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• no.36
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• pp.505-530
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• 2018

The purpose of this study is to examine the meaning of learning methods for education to transmit the items designated as intangible cultural heritages focusing on Seoul-gut. Recently, as the Act on the Preservation and Promotion of Intangible Cultural Heritages was promulgated, 'the archetype' instead of 'the prototype' has become highlighted as a crucial axis for transmission. Although there are some controversies over the definition of the archetype among scholars, it is now possible for transmitters to make use of transformations rather freely being freed from strict orientation to the prototype to follow some fixed frame. Examining learning methods used in education to transmit mudang-gut, one of the items designated as intangible cultural heritages, however, this author has found that the prototype is still emphasized or in the center of learning instead. Presenting learning methods employed for Hwanghaedopyeongsansonoreum-gut of a national intangible cultural heritage, Namijanggunsadang-gut of Seoul Special City's intangible cultural heritage, and Bonghwasandodang-gut as examples, this researcher intends to reveal the reality. In the recent situation that education centering around academies is being widely spread to transmit mudang-gut, setting forth the designation of some of the items as intangible cultural heritages, they are publishing articles on newspaper as an advertisement to encourage learning about mudang-gut. Responding to the advertisement, there are more and more shamans intending to learn mudang-gut coming to the society for preserving items designated as intangible cultural heritages. They can, of course, perform mudang-gut on their own but come to learn it as there is no fixed or definite system for it. Even though the concept of the archetype was introduced, as now it is possible to learn the fixed frame through learning about the prototype regarding the item of mudang-gut as an intangible cultural heritage, those involved in shamanism are coming to it more and more. As transmitting the prototype rather deteriorated the liveliness of gut, those involved in shamanism are coming to it to learn about gut thinking that it is where they can learn the basic frame and also acquire more detailed knowledge about shamanism. Therefore, it is needed for the item of mudang-gut designated as an intangible cultural heritage to accept the aspects of change and develop new methods of education to transmit intangible cultural heritages.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.5
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• pp.591-610
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• 2020

Concrete with activated carbon and titanium dioxide (TiO₂) has been used to reduce the particulate matter (PM) in underground structures (e.g., tunnels) due to the high performance of nitrogen oxides (NOx) abatement. Damage (e.g. crack, spalling, or detachment) can be caused by the environmental and ageing effects on the surface of the particulate matter reduction concrete, installed on the tunnel lining. Therefore, it is important to evaluate the existence of spalling on the concrete surface for maintaining performance of NOx reduction. In this study, a basic research was performed for feasibility of spalling evaluation using electrical resistivity characteristics. Given the test results, the electrical resistivity was decreased as the ratios of activated carbon (0~15%) and TiO₂ (0~25%) were increased for specimens. Under a dry condition, electrical resistivity of cement specimens, mixed with activated carbon and TiO₂, was decreased up to 2.3 times, compared with the normal cement specimen. In addition, under saturation conditions (degree of saturation: 85~98%), electrical resistivity of cement specimens with activated carbon, was decreased up to 3.5 times, compared with the normal cement specimen. Regardless of the condition (dry or saturated), the difference of electrical resistivity values shows the range of 2.3~2.8 times between the mixing specimen (with activated carbon (15%) and TiO₂ (25%)) and the normal cement specimen. This study can help to provide basic knowledge for spalling evaluation using the electrical resistivity on the surface of the particulate matter reduction concrete in tunnels.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.91-110
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• 2011

This paper analyzes the cases where the hotels have increased their services and enhanced their work process through IT solutions to cope with computerization globalization. Also the cases have been studies where national hotels use the CRM solution internally to respond effectively to customers requests, increase customer analysis, and build marketing strategies. In particular, this study discusses the introduction of the CRM solutions and CRM sales business and marketing services using a process for utilizing the presumed, CRM by introducing effective DEA(Data Envelopment Analysis). First, the comparison has done regarding the relative efficiency of L Company with the CCR model, then compared L Company's restaurants and facilities' effectiveness through BCC model. L Company reached a conclusion that it is important to precisely create and manage sales data which are the preliminary data for CRM, and for that reason it made it possible to save sales data generated by POS system on each sales performance database. In order to do that, it newly established Oracle POS system and LORIS POS system concerned with restaurants for food and beverage as well as rooms, and made it possible to stably generate and manage sales data and manage. Moreover, it set up a composite database to control comprehensively the results of work processes during a specific period by collecting customer registration information and made it possible to systematically control the information on sales performances. By establishing a system which unifies database and managing it comprehensively, impeccability of data has been greatly enhanced and a problem which generated asymmetric data could be thoroughly solved. Using data accumulated on the comprehensive database, sales data can be analyzed, categorized, classified through data mining engine imbedded in Polaris CRM and the results can be organized on data mart to provide them in the form of CRM application data. By transforming original sales data into forms which are easy to handle and saving them on data mart separately, it enabled acquiring well-organized data with ease when engaging in various marketing operations, holding a morning meeting and working on decision-making. By using summarized data at data mart, it was possible to process marketing operations such as telemarketing, direct mailing, internet marketing service and service product developments for perceived customers; moreover, information on customer perceptions which is one of CRM's end-products could feed back into the comprehensive database. This research was undertaken to find out how effectively CRM has been employed by comparing and analyzing the management performance of each enterprise site and store after introducing CRM to Hotel enterprises using DEA technique. According to the research results, efficiency evaluation for each site was calculated through input and output factors to find out comparative CRM system usage efficiency of L's Company four sites; moreover, with regard to stores, the sizes of workforce and budget application show a huge difference and so does the each store efficiency. Furthermore, by using the DEA technique, it could assess which sites have comparatively high efficiency and which don't by comparing and evaluating hotel enterprises IT project outcomes such as CRM introduction using the CCR model for each site of the related enterprises. By using the BCC model, it could comparatively evaluate the outcome of CRM usage at each store of A site, which is representative of L Company, and as a result, it could figure out which stores maintain high efficiency in using CRM and which don't. It analyzed the cases of CRM introduction at L Company, which is a hotel enterprise, and precisely evaluated them through DEA. L Company analyzed the customer analysis system by introducing CRM and achieved to provide customers identified through client analysis data with one to one tailored services. Moreover, it could come up with a plan to differentiate the service for customers who revisit by assessing customer discernment rate. As tasks to be solved in the future, it is required to do research on the process analysis which can lead to a specific outcome such as increased sales volumes by carrying on test marketing, target marketing using CRM. Furthermore, it is also necessary to do research on efficiency evaluation in accordance with linkages between other IT solutions such as ERP and CRM system.