• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.79-86
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• 2021

As the usefulness of big data analysis has been drawing attention, many studies in the business research area begin to use big data to predict firm performance. Previous studies mainly rely on data outside of the firm through news articles and social media platforms. The voices within the firm in the form of employee satisfaction or evaluation of the strength and weakness of the firm can potentially affect firm value. However, there is insufficient evidence that online employee reviews are valid to predict firm value because the data is relatively difficult to obtain. To fill this gap, from 2014 to 2019, we employed 97,216 reviews collected by JobPlanet, an online firm review website in Korea, and developed a machine learning-based predictive model. Among the proposed models, the LSTM-based model showed the highest accuracy at 73.2%, and the MAE showed the lowest error at 0.359. We expect that this study can be a useful case in the field of firm value prediction on domestic companies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.726-741
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• 2022

The purpose of this study is to provide instructive theoretical models for art (music) education institutions especially when unpredictable risks, such as pandemics, occur again. Based on the customer behavior theory of the business-to-business-to-customer (B2B2C) platform, and in combination with the technology acceptance model (TAM) and expectation confirmation model (ECM), this study proposes an online education model from the perspective of art education. The framework is based on the three decision-making processes of the customer, and includes the product owner, content owner, and customer area. This paper highlights the factors that influence customers in making decisions when art education institutions are product owners. Regression analysis was introduced to study the factors influencing the expectation confirmation, and the overall fitting testing and six hypotheses testing of 385 effective samples were performed using the structural equation modeling (SEM). The results show that the course-design and after-service positively influenced the expectation confirmation, and the domain image positively influenced the continuance behavior. Negative emotions skipped the mediator (expectation confirmation) and directly exerted a significant negative impact on customers' willingness to continue system usage (continuance behavior). In addition, expectation confirmation positively influenced continuance behavior. The paths of detailed items comprising course-design, after-service, and negative emotion were also analyzed and discussed. In this path analysis, ordinary art learners did not believe that AI partners can play a very good auxiliary role. The findings contribute to the scope of information systems acting as an art education platform academically, and provide effective and theoretical support for the actual operation of art education institutions.

• Journal of Fashion Business
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• v.16 no.5
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• pp.88-105
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• 2012

The purpose of this study is to examine the influence of popular culture in fashion politics phenomenon of leader. As study methods the literature study concerning fashion phenomenon and nature of popular culture were used for theoretical background and visual data from magazine, news paper, and internet were used for exploratory study. The results of this study are as follows. First, fashion politics phenomenon of leader in fashion merchandising through the marketing strategy is characterized as commercial profit. These characteristics enable the fashion industry and popular culture affect the formation to provide opportunity. Second, the fashion politics phenomenon of leader projected through mass media are the fashion icons and strong role models that are copied by consumers, conformity the popular, set a powerful fashion trend. The conformity by the mechanism of the interaction of the public will contribute to the formation of popular culture. Third, Semotics symbolism expressed in the fashion politics phenomenon of the leader, the intended message is communicated to the public by creating a positive image. Positive image of the leader of the public support and acceptance is the power to create.

• Journal of Fashion Business
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• v.17 no.5
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• pp.57-69
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• 2013

The purpose of this study is to compare the traditional shopping model and virtual avatar fitting model with regards to credibility and favorable impression effects on shopping mall satisfaction, product preferences, and purchasing intentions of apparel e-commerce. Questionnaires are distributed to 10-30s years old consumers who live in Seoul. Data are analyzed by descriptive statistics, Cronbach's ${\alpha}$, and regression analysis. The results are that the provoked credibility and favorable impression from the traditional shopping model affects the consumers' shopping mall satisfaction and buying intention in descending order. In additional, the credibility from traditional shopping model affects the product preference. The provoked credibility from the virtual fitting model influences the consumers' product preferences, and buying intentions. The favorable impression from the virtual fitting model affects shopping mall satisfaction. In general, provoked credibility from virtual avatar fitting model and traditional shopping model play key roles which could influence the consumers' buying intention.

• International journal of advanced smart convergence
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• v.7 no.3
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• pp.73-78
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• 2018

This study focuses on presenting the IT program module provided by BKLS measure in order to solve the problem of capital cost due to information asymmetry of external investors and corporate executives. Barron at al(1998) set up a BKLS measure to guide the market by intermediate analysts. The BKLS measure was measured by using the changes in the analyst forecast dispersion and analyst mean forecast error squared. This study suggests a model of the algorithm that the BKLS measure can be provided to all investors immediately by IT program in order to deliver the meaningful value in the domestic capital market as measured. This is a method of generating and analyzing real-time or non-real-time prediction models by transferring the predicted estimates delivered to the Big Data Log Analysis System through the statistical DB to the statistical forecasting engine. Because BKLS measure is not carried out in a concrete method, it is practically very difficult to estimate the BKLS measure. It is expected that the BKLS measure of Barron at al(1998) introduced in this study and the model of IT module provided in real time will be the starting point for the follow-up study for the introduction and realization of IT technology in the future.

• Asian Journal of Innovation and Policy
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• v.12 no.1
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• pp.054-074
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• 2023

With the advent of the '4th Industrial Revolution', digitalization using AI (Artificial Intelligence), big data, IoT (Internet of Things), cloud computing and mobile is accelerating across all industries and global companies have fundamentally reorganized customer experiences, business models, and operations centering on digital transformation. Business innovation drives productivity improvement, process simplification, price, competitiveness and sustainable expansion. Whether digital transformation will be necessary for the current industrial environment is no longer important, and how quickly companies achieve digitalization has emerged as the utmost crucial element in industrial continuity. As non-face-to-face and remote technologies have begun in earnest, and accelerated in the pharmaceutical industry. They are looking for ways to provide value, generate profits, improve efficiency, and sustain the future. Compared to other industries, the pharmaceutical-related sectors have shown high interest in digital transformation especially to reduce costs and meet the challenge of delivering products during the pandemic environment.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2003.10a
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• pp.108.2-109
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• 2003

The Gyeonggi-do Agricultural Research and Extension Services has developed a web-site (www.epilove.com) in collaboration with EPINET to provide information on agricultural weather and rice disease and insect pest management in Gyeonggi-do. Weather information includes near real-time weather data monitored by automated weather stations (AWS) installed at rice paddy fields of 11 Agricultural Technology Centers (ATC) in Gyeonggi-do, and weekly weather forecast by Korea Meteorological Administration (KMA). Map images of hourly air temperature and rainfall are also generated at 309m x 309m resolution using hourly data obtained from AWS installed at 191 locations by KMA. Based on near real-time weather data from 11 ATC, hourly infection risks of rice blast, sheath blight, and bacterial grain rot for individual districts are estimated by disease forecasting models, BLAST, SHBLIGHT, and GRAINROT. Users can diagnose various diseases and insects of rice and find their information in detail by browsing thumbnail images of them. A database on agrochemicals is linked to the system for disease and insect diagnosis to help users search for appropriate agrochemicals to control diseases and insect pests.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.167-183
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• 2017

The rapid growth of information technology and mobile service platforms, i.e., internet, google, and facebook, etc. has led the abundance of data. Due to this environment, the world is now facing a revolution in the process that data is searched, collected, stored, and shared. Abundance of data gives us several opportunities to knowledge discovery and data mining techniques. In recent years, data mining methods as a solution to discovery and extraction of available knowledge in database has been more popular in e-commerce service fields such as, in particular, movie recommendation. However, most of the classification approaches for predicting the movie popularity have used only several types of information of the movie such as actor, director, rating score, language and countries etc. In this study, we propose a classification-based support vector machine (SVM) model for predicting the movie popularity based on movie's genre data and social network data. Social network analysis (SNA) is used for improving the classification accuracy. This study builds the movies' network (one mode network) based on initial data which is a two mode network as user-to-movie network. For the proposed method we computed degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality as centrality measures in movie's network. Those four centrality values and movies' genre data were used to classify the movie popularity in this study. The logistic regression, neural network, $na{\ddot{i}}ve$ Bayes classifier, and decision tree as benchmarking models for movie popularity classification were also used for comparison with the performance of our proposed model. To assess the classifier's performance accuracy this study used MovieLens data as an open database. Our empirical results indicate that our proposed model with movie's genre and centrality data has by approximately 0% higher accuracy than other classification models with only movie's genre data. The implications of our results show that our proposed model can be used for improving movie popularity classification accuracy.

• Journal of Fashion Business
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• v.19 no.5
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• pp.63-76
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• 2015

The purpose of this study was to design a training program for utilization of 3D special makeup mask program. This study was conducted with a 3D computer graphics software program, for special makeup mask using a variety of creative educational models and case study with comparative analysis. The makeup program applied to the majors and liberal arts classes for program design. Inthis study, the selected major courses included ' stage make up ', make up application', and illustrations and color '. Students were required to take a class targeted to questionnaire completion and analysis. The research method included literature search, and Internet navigation, of experimental research. The research targeted select college students attending a 4-year university located in Dae-jeon, Korea. ETRI's "3D mask special makeup simulation program" was used in support. A survey of the study conducted from September 1, 2013, to August 30, 2014, showed a total of 94 additional statistical analyses. First, grade 3 44.6% was attained by 91.7% of the first year student majoring in liberal arts classes, Second, students' in the 3D special dress up mask program Interestingly, attained high recognition in its mastering, usability, and creativity. Furthermore, the major student satisfaction was higher for the '3D special makeup mask program. Third, students '3D special dress up was one of the biggest advantages of the program', the mask ' that models 3D ' faces. In addition, the student's delicate dress called for critical technology skills. It is thought to be suitable for practical training and improving the efficiency and performance if applied to universities and beauty schools, such as the regular high school curriculum through research.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.4
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• pp.198-206
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• 2008

Internet protocol television (IPTV), one of the most emerging services, offers multimedia streaming services with security, reliability, and relevant quality of service (QoS)/quality of experience (QoE). It provides added values to all the involving players and also brings technical and business challenges to them. For IPTV services, we expect to adopt the next generation network (NGN) environment for high quality and the Web technologies for personalization to meet the customer's necessity. Web can provide an open, flexible, and agile platform. Therefore, in this paper, we propose personalized IPTV services based on Web-based open platform in NGN environment and present functional architecture for Web-based personalized IPTV services. Technical issues for deploying the proposed IPTV services using Web are also provided. The objective of this paper is to analyze the critical architectural issues for developing viable and feasible networking platform models for personalized IPTV services.