• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8791-8799
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• 2015

In this paper, One-way car-sharing System represents the verification system consider events in revenue effects. Revenue which the time and distance represented the graph, compare one-way vehicle relocate car-sharing system which proven in existing international papers with one-way vehicle relocate car-sharing system consider the event currently in the Korea. Especially, The maximum profit according to the distance and time were assessed through multiple linear regression analysis, and there are probable maximum loss allow for the maximum loss. The company suggested using the event as a discount coupon to customers through various marketing strategies, and then focused on increasing customer demand. So, Correlation analysis to determine the maximum revenue of the actual travel distance and time were carried out through Non-linear Regression.

• Journal of Korea Multimedia Society
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• v.12 no.7
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• pp.953-961
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• 2009

The usage of DRM-applied digital contents reduces user's convenience, thus it leads the many users to avoid using DRM-applied digital contents. In this paper, therefore, we propose the new distribution model in which the users, who purchase the DRM-applied digital contents, can resale freely those contents to the other users. As a result, the proposed model induces the users to distribute contents soundly by including them in one of distribution objects. For the purpose of this, in this paper, we propose that a packaged content and usage rights are transferred to another user by using a method which based on some existing digital ticket or coupon. In addition, the security of the proposed system is discussed for the double transfer, the forgery and the modification of usage rights, and the reproduction of contents and usage rights.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.22-29
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• 2021

COVID-19, which has spread around the world, is also affecting local economic industries such as the domestic tourism industry and the service industry. In particular, the quality of life is threatened as safety prevention rules related to infectious diseases such as social distancing have been regularized. The purpose of this study is to analyze the impact on safety quarantine on users of the summer festival at Songho Beach in Haenam, a summer resort. In addition, it protrudes through big data surveys, demographic analysis, and technology analysis on the management of users who have changed in the COVID-19 era. It is expected to be a reference material by utilizing practical data on users in the future. In addition, this study is significant that it has been reviewed for safety and satisfaction for tourists using the summer beach festival through quarantine management using ICT technology in the COVID-19 situation, and needs to be used as good guidelines and examples for this study in the future.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.374-377
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• 2009

기업 경영이 점차 글로벌화 되어가는 환경 하에서 중소기업의 경쟁력강화대책의 일환으로 경영컨설팅 지원사업이 시작된 지 10년이 되었다. 그동안 실증적인 사후자료에 의한 평가는 전무한 실정으로 본 연구에서는 중소기업 쿠폰제 경영컨설팅 사업을 통한 사업참여 중소기업의 재무적 상황을 중심으로 사업참여 전 후를 비교 분석함으로써 본 사업의 시행성과를 분석하는 데 그 목적이 있다. 이를 위해 2005년도 중소기업 쿠폰제 경영컨설팅 지원사업 참여기업 중 지원사업 중 지원예산의 규모가 가장 크고, 업체에 지원금액이 많은 사업 혁신과제컨설팅(II)부문의 컨설팅을 수행한 기업들을 대상으로 수집한 재무비율분석 자료를 활용하여 사업참여 이전 및 이후의 재무상황 변화를 분석하였으며, 2005년을 기준으로 이전 1년 및 이후 2년간을 비교하였으며, 2005년 중소기업 쿠폰제 경영컨설팅 지원사업 혁신과제컨설팅(II) 70업체 중 사업참여 이전 및 이후 2년간의 자료를 구할 수 있는 34개 업체를 대상으로 하였다. 각 년도별 표본의 재무비율 산출은 EXCEL 2007을 사용하였으며, 쿠폰제 경영컨설팅 전 후 두표본 집단간의 차이 검증은 SPSS win 15.0K의 Wilcoxon 부호순위검정을 실시하여 검증하였다. 검증결과 경영컨설팅 전 후 전반적으로 가설은 기각되고, 성장성지표의 매출액증가율 및 활동성지표의 경영컨설팅 후 2년 총자산회전율은 기각되지 않으나 역의 영향력(설명력)을 가진 것으로 나타나, 쿠폰제 경영컨설팅사업의 실질적인 효율성 제고가 필요하다.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.4
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• pp.509-518
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• 2006

Although final water of domestic water treatment plants almost contains highly corrosive characteristics, the countermeasures for eliminating internal corrosion of pipeline system have not been conducted yet by controlling water quality in plants. The technologies of internal corrosion control are to control water quality parameters(pH, Alkalinity, and Calcium Hardness etc.) and to use corrosion inhibitor. Under the conditions of domestic water treatment, first of all, the technologies of adjusting water quality parameters has to be considered. Otherwise, The technology of using corrosion inhibitor is favorably thought to be applied with the technology of adjusting water quality parameters in accordance with the result of availability for water treatment process. Since the technology of adjusting water quality parameter influences on other water treatment processes, the guideline of water quality management to be apt for water quality characteristic is required to be estabilished. While the selection of proper chemicals and technologies is dependent upon the raw water characteristics and water treatment process, typically, the technology of $Ca(OH)_2$ & $CO_2$ additions is considered more effective than other technologies in order to adjust pH and Alkalinity, increase $Ca^{2+}$ and form $CaCO_3$ film

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.23-38
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• 2012

There is a large difference between purchasing patterns in an online shopping mall and in an offline market. This difference may be caused mainly by the difference in accessibility of online and offline markets. It means that an interval between the initial purchasing decision and its realization appears to be relatively short in an online shopping mall, because a customer can make an order immediately. Because of the short interval between a purchasing decision and its realization, an online shopping mall transaction usually contains fewer items than that of an offline market. In an offline market, customers usually keep some items in mind and buy them all at once a few days after deciding to buy them, instead of buying each item individually and immediately. On the contrary, more than 70% of online shopping mall transactions contain only one item. This statistic implies that traditional data mining techniques cannot be directly applied to online market analysis, because hardly any association rules can survive with an acceptable level of Support because of too many Null Transactions. Most market basket analyses on online shopping mall transactions, therefore, have been performed by expanding the co-occurrence criteria of traditional association rule mining. While the traditional co-occurrence criteria defines items purchased in one transaction as concurrently purchased items, the expanded co-occurrence criteria regards items purchased by a customer during some predefined period (e.g., a day) as concurrently purchased items. In studies using expanded co-occurrence criteria, however, the criteria has been defined arbitrarily by researchers without any theoretical grounds or agreement. The lack of clear grounds of adopting a certain co-occurrence criteria degrades the reliability of the analytical results. Moreover, it is hard to derive new meaningful findings by combining the outcomes of previous individual studies. In this paper, we attempt to compare expanded co-occurrence criteria and propose a guideline for selecting an appropriate one. First of all, we compare the accuracy of association rules discovered according to various co-occurrence criteria. By doing this experiment we expect that we can provide a guideline for selecting appropriate co-occurrence criteria that corresponds to the purpose of the analysis. Additionally, we will perform similar experiments with several groups of customers that are segmented by each customer's average duration between orders. By this experiment, we attempt to discover the relationship between the optimal co-occurrence criteria and the customer's average duration between orders. Finally, by a series of experiments, we expect that we can provide basic guidelines for developing customized recommendation systems. Our experiments use a real dataset acquired from one of the largest internet shopping malls in Korea. We use 66,278 transactions of 3,847 customers conducted during the last two years. Overall results show that the accuracy of association rules of frequent shoppers (whose average duration between orders is relatively short) is higher than that of causal shoppers. In addition we discover that with frequent shoppers, the accuracy of association rules appears very high when the co-occurrence criteria of the training set corresponds to the validation set (i.e., target set). It implies that the co-occurrence criteria of frequent shoppers should be set according to the application purpose period. For example, an analyzer should use a day as a co-occurrence criterion if he/she wants to offer a coupon valid only for a day to potential customers who will use the coupon. On the contrary, an analyzer should use a month as a co-occurrence criterion if he/she wants to publish a coupon book that can be used for a month. In the case of causal shoppers, the accuracy of association rules appears to not be affected by the period of the application purposes. The accuracy of the causal shoppers' association rules becomes higher when the longer co-occurrence criterion has been adopted. It implies that an analyzer has to set the co-occurrence criterion for as long as possible, regardless of the application purpose period.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.1-20
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• 2018

Car Sharing Service is provided with sharing the vehicleas you can use it anywhere and anytime. The paper verified the factors impact between providing infrastructure characteristics such as scarcity, system quality and service quality and user evaluation factors based on DeLone & McLean IS Success Model. User evaluation factors have an influence on net benefit. D&M IS model mainly proved inner organization impact. The research collected experienced car sharing service, we analyzed the 224 respondents. The result of the hypothesis follows. The scarcity of time is negatively related to perceived social support and app trust. Provisional coupon is positively related to perceived social support and app trust. But, scarcity of quantity is not related to user evaluation factors. Most of the system qualities are related to app trust, however, privacy concern isn't related to app trust. the paper's demographic characteristic is lack of experience frequency. User evaluation factors that are perceived social support and app trust are positively related to user satisfaction and WoM intention. User satisfaction is individual impact and WoM intention is organization impact. Two factors are the net benefit in car sharing service. The area of sharing economy should more study about correlation among experimental various factors. Thus, the paper has different significant from antecedent research. because of trying to experimental analysis.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.171-183
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• 2012

In the development of technologies, the exhibition industry has received much attention from governments and companies as an important way of marketing activities. Also, the exhibitors have considered the exhibition as new channels of marketing activities. However, the growing size of exhibitions for net square feet and the number of visitors naturally creates the competitive environment for them. Therefore, to make use of the effective marketing tools in these environments, they have planned and implemented many promotion technics. Especially, through smart environment which makes them provide real-time information for visitors, they can implement various kinds of promotion. However, promotions ignoring visitors' various needs and preferences can lose the original purposes and functions of them. That is, as indiscriminate promotions make visitors feel like spam, they can't achieve their purposes. Therefore, they need an approach using STP strategy which segments visitors through right evidences (Segmentation), selects the target visitors (Targeting), and give proper services to them (Positioning). For using STP Strategy in the smart exhibition environment, we consider these characteristics of it. First, an exhibition is defined as market events of a specific duration, which are held at intervals. According to this, exhibitors who plan some promotions should different events and promotions in each exhibition. Therefore, when they adopt traditional STP strategies, a system can provide services using insufficient information and of existing visitors, and should guarantee the performance of it. Second, to segment automatically, cluster analysis which is generally used as data mining technology can be adopted. In the smart exhibition environment, information of visitors can be acquired in real-time. At the same time, services using this information should be also provided in real-time. However, many clustering algorithms have scalability problem which they hardly work on a large database and require for domain knowledge to determine input parameters. Therefore, through selecting a suitable methodology and fitting, it should provide real-time services. Finally, it is needed to make use of data in the smart exhibition environment. As there are useful data such as booth visit records and participation records for events, the STP strategy for the smart exhibition is based on not only demographical segmentation but also behavioral segmentation. Therefore, in this study, we analyze a case of the promotion methodology which exhibitors can provide a differentiated service to segmented visitors in the smart exhibition environment. First, considering characteristics of the smart exhibition environment, we draw evidences of segmentation and fit the clustering methodology for providing real-time services. There are many studies for classify visitors, but we adopt a segmentation methodology based on visitors' behavioral traits. Through the direct observation, Veron and Levasseur classify visitors into four groups to liken visitors' traits to animals (Butterfly, fish, grasshopper, and ant). Especially, because variables of their classification like the number of visits and the average time of a visit can estimate in the smart exhibition environment, it can provide theoretical and practical background for our system. Next, we construct a pilot system which automatically selects suitable visitors along the objectives of promotions and instantly provide promotion messages to them. That is, based on the segmentation of our methodology, our system automatically selects suitable visitors along the characteristics of promotions. We adopt this system to real exhibition environment, and analyze data from results of adaptation. As a result, as we classify visitors into four types through their behavioral pattern in the exhibition, we provide some insights for researchers who build the smart exhibition environment and can gain promotion strategies fitting each cluster. First, visitors of ANT type show high response rate for promotion messages except experience promotion. So they are fascinated by actual profits in exhibition area, and dislike promotions requiring a long time. Contrastively, visitors of GRASSHOPPER type show high response rate only for experience promotion. Second, visitors of FISH type appear favors to coupon and contents promotions. That is, although they don't look in detail, they prefer to obtain further information such as brochure. Especially, exhibitors that want to give much information for limited time should give attention to visitors of this type. Consequently, these promotion strategies are expected to give exhibitors some insights when they plan and organize their activities, and grow the performance of them.