• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.851-858
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• 2021

Due to the increase in renewable energy and distributed resources, not only traditional data but also various energy-related data are being generated in the new energy industry. In other words, there are various renewable energy facilities and power generation data, system operation data, metering and rate-related data, as well as weather and energy efficiency data necessary for new services and analysis. Energy big data processing technology can systematically analyze and diagnose data generated in the first half of the power production and consumption infrastructure, including distributed resources, systems, and AMI. Through this, it will be a technology that supports the creation of new businesses in convergence between the ICT industry and the energy industry. To this end, research on the data analysis system, such as itemized characteristic analysis of the collected data, correlation sampling, categorization of each feature, and element definition, is needed. In addition, research on data purification technology for data loss and abnormal state processing should be conducted. In addition, it is necessary to develop and structure NIFI, Spark, and HDFS systems so that energy data can be stored and managed in real time. In this study, the overall energy data processing technology and system for various power transactions as described above were proposed.

• The Korean Journal of Financial Management
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• v.26 no.3
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• pp.103-138
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• 2009

In this article we examine a unique data set of intraday fair disclosure(FD) releases to shed light on market efficiency within the trading day. Specifically, this paper analyze the response of stock prices on fair disclosure disseminated in real-time through KIND(Korea Investor's Network for Disclosure) on Korea stock exchange during the period from January 2003 to September 2004. We find that the prices of stock experiences a statistically and economically significant increase beginning seconds after the fair disclosure is initially announced and lasting approximately two minutes. The stock price responds more strongly to fair disclosure on smaller firm but the response to fair disclosure on the largest firm stock is more gradual, lasting five minutes. We also examine the profitability of a short-term trading strategy based on dissemination of fair disclosure. After controlling for trading costs we find that trader who execute a trade following initial disclosure generate negative profits, but trader buying stock before initial disclosure realize statistically significant positive profit after two minute of disclosure. Summarizing overall results, our evidence supports that security prices on Korea stock exchange reflects all available information within two minutes and the Korea stock market is semi-strongly efficient enough that a trader cannot generate profits based on widely disseminated news unless he acts almost immediately.

• The Journal of Society for e-Business Studies
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• v.11 no.2
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• pp.49-69
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• 2006

The virtual community has been recognized as an effective marketing tool and has been an important motive of using internet to Internet users, but very few attempts have been done for the development of virtual community success. Although many studies have been made on influencing factors of virtual community success, the comprehensive studies have never been done so far. Therefore, this study focused on developing the comprehensive model and verifying empirically. This study proposed five influencing factors(Virtual Community Operational factor, Characteristics of Users, Usefulness, Trust, Commitment) that affect virtual community success and three success factors(Sense of Virtual Community, Loyalty, Purchasing Intention) by carrying out literature review extensively and suggesting the relationship among factors. The relationship among factors were empirically validated by structural equation modeling. The data used in this study were collected from 292 users of the existing virtual communities. As the result of statistical analysis. It was found that Virtual Community Operational Factor and Characteristics of Users statistically significantly influenced Virtual Community Success. Also, it was shown that the intervening effects of Usefulness, Trust and Commitment were statistically significant, but that the relationship between commitment and Loyalty was not statistically significant. Finally, it turned out that the causality among success variables of Virtual Community was supported, but that sense of Virtual Community was required to be measured by new measurements.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.83-96
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• 2018

Extracting keywords representing documents is very important because it can be used for automated services such as document search, classification, recommendation system as well as quickly transmitting document information. However, when extracting keywords based on the frequency of words appearing in a web site documents and graph algorithms based on the co-occurrence of words, the problem of containing various words that are not related to the topic potentially in the web page structure, There is a difficulty in extracting the semantic keyword due to the limit of the performance of the Korean tokenizer. In this paper, we propose a method to select candidate keywords based on semantic similarity, and solve the problem that semantic keyword can not be extracted and the accuracy of Korean tokenizer analysis is poor. Finally, we use the technique of extracting final semantic keywords through filtering process to remove inconsistent keywords. Experimental results through real web pages of small business show that the performance of the proposed method is improved by 34.52% over the statistical similarity based keyword selection technique. Therefore, it is confirmed that the performance of extracting keywords from documents is improved by considering semantic similarity between words and removing inconsistent keywords.

• The Journal of Society for e-Business Studies
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• v.22 no.4
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• pp.159-173
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• 2017

In order to provide technical financial support to small and medium-sized venture companies based on technology, the government implemented the TCB evaluation, which is a kind of technology rating evaluation, from the Kibo and a qualified private TCB. In this paper, we briefly review the current state of TCB evaluation and available indicators related to technology evaluation accumulated in the Korea Credit Information Services (TDB), and then use indicators that have a significant effect on the technology rating score. Multiple regression techniques will be explored. And the relative importance and classification accuracy of the indicators were calculated by applying the key indicators as independent features applied to the generalized boosting model, which is a representative machine learning classifier, as the class influence and the fitness of each model. As a result of the analysis, it was analyzed that the relative importance between the two models was not significantly different. However, GBM model had more weight on the InnoBiz certification, R&D department, patent registration and venture confirmation indicators than regression model.

• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.197-220
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• 2011

The smartphone is simply beyond the means of communication equipment, to line up the turning point of mobile convergence, is recognized as a service tool of new concept the camera, game, multimedia function, digital multimedia broadcasting, mobile internet etc, that use of smartphone is working toward developed a variety and new business models. The study is empirically studied casualties that self-determination influences flow and satisfaction which is intrinsic motivation of smartphone. There are many studies on flow, is intrinsic motivation, influencing satisfaction and Loyalty, but there are little studies which variables influences flow. this study is explore causality of autonomy, competence, relatedness which are major variables of self-determination theory that studied factors effecting intrinsic motivation influencing flow and satisfaction. This study developed a research model to explain the use of smartphone, and collected 670 survey responses from the office workers of seoul S company who had experiences with such smartphone. To prove the validity of the proposed research model, SEM analysis is applied with valid 670 questionnaires. The results, firstly, autonomy positively influences flow. secondly, competence significantly influences flow. thirdly, relatedness significantly influenced flow. also, upper above results shows that flow influences satisfaction.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.19-38
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• 2017

The core of the smartphone business environment is changing from H/W to S/W and with it the paradigm of an enterprise's base of competition is changing from H/W to service. In accordance with this paradigm, in this study we have determined H/W, S/W and telecommunication service as smartphone business factors. The purpose of this study is to first analyze the influence business factors has on consumer satisfaction and customer loyalty. Secondly, to analyze the influence switching cost has on customer loyalty. As a result, the factor that has a notable influence on customer satisfaction turned out to be the H/W factor. On the other hand S/W factor and communication service turned out to have very little influence. In addition, the factors influencing customer loyalty turned out to be H/W factor and S/W factor. Telecommunication service did not have much of an influence. Customer satisfaction turned out to act as mediation effect between H/W factor and customer loyalty. Like the result of other preceding researches, switching cost turned out to have a significant influence on customer loyalty. This study differs from other studies in that while other existing studies analyzed H/W, S/W and communication service separately, this study analyzed the influence H/W, S/W and communication service as a whole has on customer satisfaction and customer loyalty. We speculate that the results of this study would provide some insight both in an academic and practical level for stagnant smartphone industry.

• The Journal of Society for e-Business Studies
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• v.18 no.1
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• pp.33-55
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• 2013

Information sharing behavior in the Internet has raised much interest. Recently, social network sites provide a new information sharing channel for the users who want to connect with others based on common social background or tastes. Especially, we focus that a social network site becomes one of major routes for information sharing about socially influential issues. Therefore, studying how information is diffused via a social network site may give theoretically, practically significant implication. Based on the assertion, we investigated user's behavior to mediate other user's information messages. We define information mediating behavior as concurrent actions of filtering and distributing behavior of the digital content that is originated from one of the connected users. In this study, we intended to understand the effects of information mediating behavior, and tried to understand characteristics of re-mediating of previously mediated information. Using an agent-based simulation model, we found that information mediating behavior increased the extent of information diffusion significantly. In addition, even a small degree of mediating probability could boost up the level of information diffusion in the case of a re-mediating condition. We believe that those findings provide remarkable insight of research and business application on both of information sharing and diffusion in a social network site.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.71-89
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• 2019

In order to come up with satisfying product and improvement, firms use traditional marketing research methods to obtain consumers' opinions and further try to reflect them. Recently, gathering data from consumer communication platforms like internet and SNS has become popular methods. Meanwhile, with the development of information technology, mobile companies are launching new digital products for children to protect them from harmful content and provide them with necessary functions and information. Among these digital products, Kids Phone, which is a wearable device with safe functions that enable parents to learn childern's location. Kids phone is relatively cheaper and simpler than smartphone but it is noted that there are several problems such as some useless functions and frequent breakdowns. This study analyzes the reviews of Kids phones from domestic mobile companies, identifies the characteristics, strengths and weaknesses of the products, proposes improvement methods strategies for devices and services through SNS consumer analysis. In order to do that customer review data from online shopping malls was gathered and was further analyzed through text mining methods such as TF/IDF, Sentiment Analysis, and network analysis. Customer review data was gathered through crawling Online shopping Mall and Naver Blog/$Caf\acute{e}$. Data analysis and visualization was done using 'R', 'Textom', and 'Python'. Such analysis allowed us to figure out main issues and recent trends regarding kids phones and to suggest possible service improvement strategies based on sentiment analysis.

• The Journal of Society for e-Business Studies
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• v.25 no.4
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• pp.33-60
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• 2020

Along with the rapid advance in internet technologies, ubiquitous mobile device usage has enabled consumers to access real-time information and increased interaction with others through various social media. Consumers can now get information more easily when making purchase decisions, and these changes are affecting the brand landscape. In a digitally connected world, brand image is not communicated to the consumers one-sidedly. Rather, with consumers' growing influence, it is a result of co-creation where consumers have an active role in building brand image. This explains a reality where people no longer purchase products just because they know the brand or because it is a famous brand. However, there has been little discussion on the matter, and many practitioners still rely on the traditional measures of brand indicators. The goal of this research is to present the limitations of traditional definition and measurement of brand and brand image, and propose a more direct and adequate measure that reflects the nature of a connected world. Inspired by the proverb, "A man is known by the company he keeps," the proposed measurement offers insight to the position of brand (or brand image) through co-purchased product networks. This paper suggests a framework of network analysis that clusters brands of cosmetics by the frequency of other products purchased together. This is done by analyzing product networks of a brand extracted from actual purchase data on Amazon.com. This is a more direct approach, compared to past measures where consumers' intention or cognitive aspects are examined through survey. The practical implication is that our research attempts to close the gap between brand indicators and actual purchase behavior. From a theoretical standpoint, this paper extends the traditional conceptualization of brand image to a network perspective that reflects the nature of a digitally connected society.