Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.
Journal of the Korean Society of Clothing and Textiles
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v.32
no.4
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pp.573-585
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2008
Flow has attracted more interests in consumer behaviors, with pleasure and fantasy getting more important in shopping. "Flow" means the experience with which consumers feel as pleased and satisfied as in playing pleasantly, and the optimal experience they feel when they are indulged in an activity. The purpose of this study is to investigate the relationships among challenges, skills, flow experience, and future behavioral intention in online shopping malls. In addition, a 3D shopping mall and a 2D shopping mall were selected as the stimuli in order to examine the differences in flow experience in accordance with web site types. A survey questionnaire was developed and 700 data(2D group: n=380, 3D group: n=320) were used for analysis. Data were analyzed through structural equation model to explore effects of challenges and skills on flow. The results of this study are summarized as follows. First, the perception of higher challenges and skills led to positive flow experience and higher time distortion. Second, the higher the level of time distortion was, the higher the flow experience was. This means that a shopping mall will increase flow experience, if it is interesting enough to be unaware of time passing. Third, flow experience had a positive influence on future behavioral intention. Finally, in all variables except skills, the impact of 3D shopping mall is greater than that of 2D shopping mall, which means that web site types affect flow experience.
The general public is a key stakeholder in the science and technology domain. However, traditional approaches require substantial efforts and resources to analyze how does the general public understand science and technology issues. We applied the topic modeling, a form of text clustering, to the texts about the nuclear power which were posted on an online space in order to explore the general public's thoughts on the issue. This study investigates the extent to which macro-level events influence understandings of the general public on the science and technology issues and weather these changes in understandings are sustained over time. It examines the possibility of applying topic modeling in narrowing a perception gap between the general public and the experts through a near-real-time monitoring of the public interests and perceptions about the science and technology issues.
As social networking service (SNS) users' needs and wants have become more diverse, SNS is designed to provide various services and functions. As a result, an image based SNS with the purpose of sharing various interests has emerged. More and more fashion companies are using image based SNS to use it as a medium to better communicate with their customers. This study investigates the effect of usage motivation of image based SNS with the emotion of pleasure as the mediator and its impact towards flow and brand attitude. In order to verify the research model and to test the proposed hypotheses, we conducted a pilot test on 8 image based SNS heavy users, and followed through with 215 questionnaires which were collected via online survey. The results of this study are as follows. Each usage motivation of image based SNS had significant effect on each pleasure. The visual impact had a positive effect on sensory pleasure and the common interest significantly influenced on user's affective preference. Curating, simplicity and interconnecting had a positive effect on cognitive pleasure. Affective and cognitive pleasures except sensory pleasure positively impacted the user on flow. The cognitive pleasure had a positive effect on the brand attitude. Lastly, flow had a positive effect on the brand attitude. This study is the foundation of the image based SNS academically in the new media research. Furthermore, it suggests managerial implications of a company to provide effective marketing strategy to make the best use of image based SNS.
Exposure factors based on the Korean population are required for making appropriate risk assessment. It is expected that handbooks for exposure factors will be applied in many fields, as well as by health department risk assessors. The present article describes the development of an exposure factors handbook that specifically focuses on human activities in situations involving the possible risk of exposure to environmental contaminants. We define majour exposure factors that represent behavioral patterns for risk assessment, including time spent on routine activities, in different places, on using transportation, and engaged in activities related to water contact including swimming, bathing and washing. Duration of residence and employment are also defined. National survey data were used to identify recommended levels of exposure factors in terms of time spent on routine activities and period of residence and employment. An online survey was conducted with 2073 subjects who were selected using a stratified random sampling method in order to develop a list of exposure factors for the time spent in different places and in performing water-related activities. We provide the statistical distribution of the variables, and report reference levels of average exposure based on the reliable data in our exposure factors handbook.
Purpose: Online and social media and mobile shopping are increasing and companies are required to provide personal information in order to supplement the non-invasive characteristics of the channels. With the increased provision of personal information, consumers' personal and social concerns about the prevention of personal information infringement are also increasing, and in response, personal or opt-in marketing has emerged to compensate for reckless information abuse. Despite the background of this emergence, the existing prior studies are limited to ignoring the negative feelings of consumers in the real world, including only the net function and positive effect of the opt-in mail. Research design, data and methodology: The research framework was intended to utilize the impact of human marketing activities on consumer attitudes combined with positive and negative factors. Factors that positively affect attitudes toward permation marketing were presented, such as informality, and perceived risks were presented as negative impact factors. Also, based on previous prior research, the prior factors of opt-in marketing were to present the effect on purchase intent through the medium of attitude toward opt-in marketing. Results: In this study, we used the framework of a two factor theory to address positive and negative factors as a leading factor in the customer attitude toward opt-in mail advertising, and as a result, functionality and personalization have a positive effect on customer attitude and perceived risk have a negative impact on customer attitude. In addition, it was confirmed that the customer attitude formed this way affects the intention to purchase again. Conclusions: This study suggests that we have demonstrated that marketing, an opt-in marketing that has been recognized as part of marketing that is deployed after obtaining customer consent, has been applied without any other marketing methodology. E-mail advertising at this point also provides practical implications that the system safeguards are in place under an opt-in protocol or system, and that even if an e-mail advertisement is carried out, customers will need to look at the level of awareness about the risks, and suggests that they need to consider the customer's journey that could lead to purchase at the content level.
Journal of The Korean Association of Information Education
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v.12
no.3
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pp.253-265
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2008
Recently the cyber home learning system is executed throughout the country as a part of educational policies to reduce expenditure on private education and to promote educational welfare for alienated classes. Thus, in order to examine the effectiveness of the cyber home learning system, we conducted an online questionnaire survey with elementary and secondary students, cyber teachers under the OO Office of Education. According to the results, overall satisfaction with the cyber home learning system and its effectiveness were found high. In addition, what were required for more effective the cyber home learning system were expanding the execution of unit school learning, strengthening teacher training, increasing incentives for cyber teachers, intensifying campaigns for the cyber home learning system, providing various types of information and contents of education, and activating learning activities such as community, message and chatting. This study is expected to be a steppingstone to the settlement of more effective the cyber home learning system.
Kim, Hyun-Wook;Kim, Sung-Soo;Park, Se-Woon;Kim, Eon-Kuk;Lee, Geon-Hui;Lee, Geon-Mok
Journal of Acupuncture Research
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v.27
no.4
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pp.67-84
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2010
Objectives : To review RCTs on acupuncture treatment for shoulder pain in order to establish a standard acupuncture treatment model in treating shoulder pain. Methods : RCT articles on traditional acupuncture treatment for shoulder pain were searched through online database. Quality of studies were assessed using the FEAS and the modified Jadad score. Results : Eighteen trials of acupuncture for shoulder pain were analyzed. Based on the results of these reviews the following factors might contribute to optimal results from acupuncture treatment. 1) Usage of LI, SI, TE meridians, usage of $LI_{15}$, $TE_{14}$, $GB_{21}$, $LI_{11}$, $LI_4$, $SI_{14}$, $LI_{14}$, $TE_{15}$ acupuncture points. 2) More than four acupuncture points should be used. 3) More than 15 minutes of needle retention time. 4) Needle length-40mm and diameter-0.30mm. 5) More than 9 times treatment 6) More than 5 weeks treatment duration. Conclusions : There was no relation between quality of article and effectiveness of acupuncture. To improve the remedial value, it is necessary to mention De-qi, stimulation of acupuncture and correct variation in diagnosis with the above-mentioned. It is better that clinical trials of acupuncture treatment is designed that type of RCT and double blind. Also when it is set that sham nonpenetrating acupuncture, no treatment group as a control group, and participants don't distinguish wheather acupuncture treatment or not, it will be more meaningful.
Journal of the Institute of Electronics Engineers of Korea SC
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v.39
no.2
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pp.157-165
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2002
This paper presents the implementation of the speed control system for 3 phase induction motor using PD controller and neural networks. The PD controller is used to control the motor and to train neural networks at the first time. And neural networks are widely used as controllers because of a nonlinear mapping capability, we used feedforward neural networks(FNN) in order to simply design the speed control system of the 3 phase induction motor. Neural networks are tuned online using the speed reference, actual speed measured from an encoder and control input current to motor. PD controller and neural networks are applied to the speed control system for 3 phase induction motor, are compared with PI controller through computer simulation and experiment respectively. The results are illustrated that the output of the PD controller is decreased and feedforward neural networks act main controller, and the proposed hybrid controllers show better performance than the PI controller in abrupt load variation and the precise control is possible because the steady state error can be minimized by training neural networks.
Journal of the Institute of Electronics and Information Engineers
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v.49
no.9
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pp.18-26
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2012
As the performance of the next-generation broadband wireless networks is dramatically enhanced, various services (i.e., education, video conferencing, online games, etc.) have been provided to users through a smart mobile platform. Since those services are usually provided by using the centralized architecture, it is difficult for a lot of users to provide the scalable communication service with regard to traffic management. To solve these problems, we have proposed an architecture of P2P-based group communication management scheme using smart mobile device. More specifically, we design the group management protocol and algorithm for the group member management and the traffic management. By using these methods, the mobile multimedia streaming service can be provided with scalability. In order to verify the performance of the proposed scheme, we have mathematically analyzed the performance in terms of the average transmission delay and bandwidth utilization.
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