The purpose of this study is to measure the relative importance of the factors that affect school to work transition that food service-related majors and workers recognize. To this end, this study composed such factors into a second hierarchy level of individual background, educational background, and preparation effort to enter labor market. The study made us of the analytic hierarchy process(AHP), which calculates the importance of each factor through the relative evaluation of each factor in the hierarchy. The results of analysis are as follows. First, in the second hierarchy level, effort to enter the labor market exhibited the highest relative importance. In the case of four-year college students, educational background had the highest relative importance. Second, in case of third hierarchy level factors relating to personal background, gender had the highest relative importance. As for educational background, the type of college had the highest relative importance. As to the effort to enter labor market, overseas working experience while in college and job searching channels had high relative importance, while vocational training experience had the lowest relative importance. Third, the analysis result of complex weighted value showed that the type of college had the highest complex weighted value. In future studies, the type of businesses and business conditions in the food service industry should be subdivided for an analysis of influential factors, and, based on this, customized career guidance should be made for specific career paths of each student.
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 Korean Institute of Information Technology
/
v.16
no.12
/
pp.1-11
/
2018
Recently, the volume of online shopping market continues to be fast-growing, that is important to provide customized service based on customer behavior evaluation analysis. The existing systems only provide analysis data on the profiles and behaviors of the consumers, and there is a limit to the processing in real time due to disk based mining. There are problems of accuracy and system performance problems to apply existing systems to web services that require real-time processing and analysis. Therefore, The system proposed in this paper analyzes the web click log streams generated in real time to calculate the concentration level of specific products and finds interested customers which are likely to purchase the products, and provides and intensive promotions to interested customers. And we verify the efficiency and accuracy of the proposed system.
Journal of Korea Entertainment Industry Association
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v.14
no.2
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pp.165-176
/
2020
Customized medical care and services timely providing effective prevention and treatment by collecting and using individuals' biomedical data are recently possible and utilized for users' health care. They are developed as the real-time health care services and information is provided to individuals by using smart phones, PC, tablet, etc. Interactive communication is supported by informing managers of analysis data and results, through collected data. It is therefore the time for constructing health care. This study attempts to prepare for patent applications of technical development at this time, by analyzing the tendency of smart wearable health care technologies, including biological signal-based health care devices and real-time health care system. Patents regarding smart wearable health care technologies were reported to have the relatively higher concentration of research development. Korea focuses on patent activities for real-time health care systems across the intervals of analysis, while U.S and European countries actively make efforts for patent activities regarding health care devices Japan conduct patent activities across health care devices and systems, based on bio-technologies. Korea has recently dominated the market of patents for bio-technologies-based health care devices and real-time health care devices and also appears to secure patents for the technologies and the market, so entry barriers to the market of smart wearable health care technologies are determined to be higher in Korea. It is important to establish the portfolios of patents, by securing patent rights for the figures of products, manufacturing methods and other related technical systems, if technologies are planned to be commercialized.
With the launch of Artificial Intelligence(AI)-based intelligent products on the market, innovative changes are taking place not only in business but also in consumers' daily lives. Intelligent products have the potential to realize technology differentiation and increase market competitiveness through advanced functions of artificial intelligence. However, there is no new product development methodology that can sufficiently reflect the characteristics of artificial intelligence for the purpose of developing intelligent products with high market acceptance. This study proposes a KANO-QFD integrated model as a methodology for intelligent product development. As a specific example of the empirical analysis, the types of consumer requirements for hair loss prediction and treatment device were classified, and the relative importance and priority of engineering characteristics were derived to suggest the direction of intelligent medical product development. As a result of a survey of 130 consumers, accurate prediction of future hair loss progress, future hair loss and improved future after treatment realized and viewed on a smartphone, sophisticated design, and treatment using laser and LED combined light energy were realized as attractive quality factors among the KANO categories. As a result of the analysis based on House of Quality of QFD, learning data for hair loss diagnosis and prediction, micro camera resolution for scalp scan, hair loss type classification model, customized personal account management, and hair loss progress diagnosis model were derived. This study is significant in that it presented directions for the development of artificial intelligence-based intelligent medical product that were not previously preceded.
The Journal of Korean Association of Computer Education
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v.16
no.1
/
pp.97-110
/
2013
The purpose of this study is to analyze the needs of teachers as main users to make suggestions for active use of educational information sharing system. The study sets three research tasks about the problems of the current system, improvements, and desired content from the perspective of teachers. To collect specific opinions, we conducted an open questionnaire survey and made a qualitative analysis using the NVivo 10 program. The present system has such problems as functional issues, lack of data reliability, systemic problems for sharing and use. We suggest that in order to enhance Web site services, authoring tools for editing contents and new search engines with customized search function need to be provided. In addition, the open market service system has to be established, so that teachers can actively create, share, and distribute to meet the various needs of teachers. Finally, to promote free access to the system, copyright issues need to be resolved to prevent the potential digital piracy.
Recently, interest in home training and changes in lifestyle are expanding the market in the healthcare field, and high value-added fashion products reflecting the dumbbell economy phenomenon are being released. This study had the following objectives: to investigate the possibility of developing a fashion item that can be applied to the dumbbell economy phenomenon; to develop the UI/UX of a smartphone application for beginners who wish to work out their upper and lower bodies regardless of time and space; and to create a wearable customized smart athleisure fashion device. First, the study identified factors related to exercise methods, breathing techniques, and range of exercises for beginners by investigating the postures of workouts of the upper and lower bodies by angles. Based on the results, the study collected empirical data through a user needs analysis from muscle strengthening exercise experts to verify the significance of the study and use as fundamental data. Second, the study developed the UI/UX of a smartphone application with three different contents: counting, suggesting exercise postures, and providing exercise calendars. Further, the study analyzed necessary user-centered concepts and characteristics in terms of design and technology and developed a wearable customized smart athleisure fashion device based on the results.
A smart TV is able to show terrestrial broadcasting and also can be used as a computer -VOD, games, image communications, application utilities and so on. In order to carry out Smart TV business, it has to contains contents, platforms, network terminal unit. If ill-equipped with any of these aboves, it must cooperate with other licensee. Therefore, Smart TV business is necessary to cooperate with each business agent. In this paper, we will look into domestic/foreign country Smart TV market, policy, vitalization strategy, and suggest the application of big data analysis methodology for Smart TV vitalization method - 1) hardware infrastructure building based on cloud computing 2) Network upgradability acceptable traffic increase 3) Technical development cooperation between each licensee 4) Variable Smart TV contents supply 5) Cooperation with party interested individuals in using UX/UI for N-Screen, network traffic estimation may increase, customized supply smart contents for consumer in real time.
In the textile industry located in Gyeonggi-do, 85% of small-sized firms have less than 10 employees; in addition, the most of them are characterized by a vendor relying specialization system that conducts foundry from the vendor that managed marketing, textile design development, and quality checks according to unit stream. The breakaway of these vendors accelerated over the last 7 years; however, industry survival is at stake because the specialization system and orders have collapsed. The following four main policies must be implemented to overcome industry hardship. Policies have been derived from survey and analysis (present condition and trends) from industrial statistics and related policies in advanced and developing countries. First, a policy to promote cooperation between small-sized foundry unit-streams. Second, unification of the marketing support function with a textile design and development support system. Third, the introduction of policy support-management system customized according to developmental stages (tall process${\rightarrow}$fabric production${\rightarrow}$sales${\rightarrow}$clothing production sales). Fourth, foundation of a control tower that puts these tasks in a vehicle and runs them and the division of roles with the central government. We must propel main tasks to manifest the developmental potential (develop eco-friend dyeing and processing technologies, change to the young next CEO in business environment, and grow the of knit market) of the Gyeonggi Textile Industry in a short period to present a condition where these four main policies are running.
In recent years, speedy development of Taiwan's hotel industry intensifies market competition, customers' demands on hotel services quality also increase with the increase of their consumption consciousness, and their demands on hotel types diversify, therefore hotel industry should concern on their unique management services quality brought by their different hotel types. The current designed service system or service transmission process may fail to meet customers' demands owing to emphasizing degree gap in service quality. What is worse, it is difficult for hotel industry to actualize complete customer segregation and to provide customized services, therefore comprehensive understanding of customers' demands on the service quality of different types hotels would contribute to operating management improvement of Taiwan hotel industry. This paper divides Taiwan hotels into three types: international tourism commercial type, holiday type and motel, the general hotels. It studies the emphasize degree gap in service quality between the industry and the customers. Data analysis shows that service quality gap (perceived gap) of hotels of different types exists in several quality aspects; what's more, the perceived gaps, service quality aspects, and its items of different types of hotel are also different. After an integrated analysis, this paper puts forward a general and customer-oriented quality item suitable for hotel industry to shorten the perceived gap of service quality, so that the hotel industry could design a service system and service transfer system, which could meet most lodging customers' demands in the context of pluralized customer sources.
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