• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.143-152
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• 2019

In this study, the author seeks to identify the status of the online job information service market and present strategic guidelines to maintain the market ecosystem based on it. The research method was carried out as a descriptive study to identify the online job information service market by utilizing various secondary data. Specifically, the market analysis identified the high potential growth rate of the job information service market and key issues. Industry trend analysis analyzed key service features, job seeker types and features, service use trends, promotion and marketing methods. Finally, through SWOT analysis of the market, strategic guidelines were proposed to lead the market ecosystem into a virtuous circle. In the first place, these findings will help us gain a comprehensive view of the market by identifying the status of the job information service market with a focus on the main issues. It may also provide companies in the industry with the necessary clues to their continued survival within the industry. Furthermore, the government and public organizations are expected to contribute to boosting the job information service market with the aim of creating and improving jobs.

• Journal of the Korean Applied Science and Technology
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• v.40 no.1
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• pp.24-34
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• 2023

This study sought to explore the online consumption propensity of sports goods by generation of the productive population and to provide basic data to predict the future consumption market by segmenting online consumers in the sports 4.0 market. Therefore, this survey was conducted on those who consumed sports goods among the generation-specific groups (Generation Y and above, Z) of the productive population, and a total of 478 people's data were applied to the final analysis. Data processing was conducted with SPSS statistics (ver.21.0), frequency analysis, exploratory factor analysis, correlation analysis of re-examination reliability, reliability analysis, and decision tree analysis. According to the online consumption propensity of sports goods by generation of the productive population, there is a high probability of being classified as Generation Z group if the factors of leisure, joy, and environment are high. In addition, the classification accuracy of such a model was 69.7%.

• Journal of Korean Society for Quality Management
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• v.31 no.1
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• pp.21-41
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• 2003

The purpose of this research is to identify if psychological temptation, site quality and sense of community influence user's flow and addiction and if causalities among flow, addiction, customer satisfaction and customer loyalty are different between Korean and Japanese online games. To perform our research, we use MCSF(Multi-group Confirmatory Factor Analysis) and MSEM(Multi-group Structural Equation Model). The empirical results of SEM(Structural Equation Model) including high-order factor analysis indicate that all of paths in our model are the same for both countries. Therefore, site quality and sense of community have impacts on the flow, while on the other hand, psychological temptation has impacts on the addiction. Customer satisfaction and loyalty are positively related not with the addiction but with the flow. In addition, customer loyalty is significantly influenced by the flow and the customer satisfaction. In Conclusion, the empirical results of MSEM(Multi-group Structural Equation Model) indicate sense of community to flow, flow to loyalty and customer satisfaction to loyalty are different between Korea and Japan. This indicates that companies to penetrate into Japa online game industry should have a concern with Japanese Social and Cultural features and to develop strategies which correspond with Japanese culture.

• The Journal of the Korea Contents Association
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• v.7 no.11
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• pp.215-222
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• 2007

As Korean online game market is saturated, Korean online game companies are trying to push into North American market. In order to succeed in foreign markets, understanding of user characteristics in that country is most important. In this study, investigation on user characteristics has been performed using user DB from A online game and B online game. They are currently in service by M company in America. Connection time, payment, and royalty are analyzed as a results. Based on the analysis, several advance strategies into North America are suggested. This results could be very useful for Korean MMORPG company to try to push into North America.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.559-575
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• 2014

Individual investors are increasingly flocking to message boards to seek, clarify, and exchange information. Businesses like Seekingalpha.com and business magazines like Fortune are evaluating, synthesizing, and reporting the comments made on message boards or blogs. In March of 2012, Yahoo! Finance Message Boards recorded 45 million unique visitors per month followed by AOL Money and Finance (19.8 million), and Google Finance (1.6 million) [McIntyre, 2012]. Previous studies in the finance literature suggest that online communities often provide more accurate information than analyst forecasts [Bagnoli et al., 1999; Clarkson et al., 2006]. Some studies empirically show that the volume of posts in online communities have a positive relationship with market activities (e.g., trading volumes) [Antweiler and Frank, 2004; Bagnoli et al., 1999; Das and Chen, 2007; Tumarkin and Whitelaw, 2001]. The findings indicate that information in online communities does impact investors' investment decisions and trading behaviors. However, research explicating the correlation between information on online communities and stock market activities (e.g., trading volume) is still evolving. Thus, it is important to ask whether a volume of posts on online communities influences trading volumes and whether trading volumes also influence these communities. Online stock message boards offer two different types of information, which can be explained using an economic and a psychological perspective. From a purely economic perspective, one would expect that stock message boards would have a beneficial effect, since they provide timely information at a much lower cost [Bagnoli et al., 1999; Clarkson et al., 2006; Birchler and Butler, 2007]. This indicates that information in stock message boards may provide valuable information investors can use to predict stock market activities and thus may use to make better investment decisions. On the other hand, psychological studies have shown that stock message boards may not necessarily make investors more informed. The related literature argues that confirmation bias causes investors to seek other investors with the same opinions on these stock message boards [Chen and Gu, 2009; Park et al., 2013]. For example, investors may want to share their painful investment experiences with others on stock message boards and are relieved to find they are not alone. In this case, the information on these stock message boards mainly reflects past experience or past information and not valuable and predictable information for market activities. This study thus investigates the two roles of stock message boards-providing valuable information to make future investment decisions or sharing past experiences that reflect mainly investors' painful or boastful stories. If stock message boards do provide valuable information for stock investment decisions, then investors will use this information and thereby influence stock market activities (e.g., trading volume). On the contrary, if investors made investment decisions and visit stock message boards later, they will mainly share their past experiences with others. In this case, past activities in the stock market will influence the stock message boards. These arguments indicate that there is a correlation between information posted on stock message boards and stock market activities. The previous literature has examined the impact of stock sentiments or the number of posts on stock market activities (e.g., trading volume, volatility, stock prices). However, the studies related to stock sentiments found it difficult to obtain significant results. It is not easy to identify useful information among the millions of posts, many of which can be just noise. As a result, the overall sentiments of stock message boards often carry little information for future stock movements [Das and Chen, 2001; Antweiler and Frank, 2004]. This study notes that as a dependent variable, trading volume is more reliable for capturing the effect of stock message board activities. The finance literature argues that trading volume is an indicator of stock price movements [Das et al., 2005; Das and Chen, 2007]. In this regard, this study investigates the correlation between a number of posts (information on stock message boards) and trading volume (stock market activity). We collected about 100,000 messages of 40 companies at KOSPI (Korea Composite Stock Price Index) from Paxnet, the most popular Korean online stock message board. The messages we collected were divided into in-trading and after-trading hours to examine the correlation between the numbers of posts and trading volumes in detail. Also we collected the volume of the stock of the 40 companies. The vector regression analysis and the granger causality test, 3SLS analysis were performed on our panel data sets. We found that the number of posts on online stock message boards is positively related to prior stock trade volume. Also, we found that the impact of the number of posts on stock trading volumes is not statistically significant. Also, we empirically showed the correlation between stock trading volumes and the number of posts on stock message boards. The results of this study contribute to the IS and finance literature in that we identified online stock message board's two roles. Also, this study suggests that stock trading managers should carefully monitor information on stock message boards to understand stock market activities in advance.

• The Journal of Society for e-Business Studies
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• v.23 no.1
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• pp.65-88
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• 2018

This case is an analysis of how a late comer to the market of online dating in Korea, Dorsia, successfully develops its services called Amanda. Since 2010, the online dating market in Korea has been fast growing. Despite its short history, many corporations have attempted to make success in the market. But most of them were unable to gain foothold in a market where the first comer had a huge advantage. Amanda, however, has provided differentiated services to great success in a short period. This paper conducted a semi-structured interview with major executives of Dorsia to acquire data which were then used to interpret based on the theories of business management and psychology. This study presents a strategic insight into how competitiveness can be gained in internet-based businesses in the online dating market, as well as those in markets that have similar traits. Moreover, by identifying issues that need to be addressed in order for Amanda to continue its growth, the study seeks to simultaneously review the issues that need resolution related to online commerce, as well as the great potential of online commerce.

• Asia pacific journal of information systems
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• v.30 no.4
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• pp.719-740
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• 2020

The stock market changes continuously as new information emerges, affecting the judgments of investors. Online news articles are valued as a traditional window to inform investors about various information that affects the stock market. This paper proposed new ways to utilize online news articles with technical indicators. The suggested hybrid model consists of three models. First, a self-attention-based convolutional neural network (CNN) model, considered to be better in interpreting the semantics of long texts, uses news content as inputs. Second, a self-attention-based, bi-long short-term memory (bi-LSTM) neural network model for short texts utilizes news titles as inputs. Third, a bi-LSTM model, considered to be better in analyzing context information and time-series models, uses 19 technical indicators as inputs. We used news articles from the previous day and technical indicators from the past seven days to predict the share price of the next day. An experiment was performed with Korean stock market data and news articles from 33 top companies over three years. Through this experiment, our proposed model showed better performance than previous approaches, which have mainly focused on news titles. This paper demonstrated that news titles and content should be treated in different ways for superior stock price prediction.

• Journal of Digital Convergence
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• v.17 no.4
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• pp.115-122
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• 2019

In the online marketplace, consumers are exposed to various products and freely express opinions. As consumer product reviews have a important effect on the success of online markets and other consumers, online market needs to accurately analyze the consumers' emotions about their products. Text mining, which is one of the data analysis techniques, can analyze the consumer's reviews on the products and efficiently manage the products. Previous studies have analyzed specific domains and less than 20,000 data, despite the different accuracy of the analysis results depending on the data domain and size. Further, there are few studies on additional factors that can improve the accuracy of analysis. This study analyzed 72,530 review data of food product domain that was not mainly covered in previous studies by using ensemble technique. We also examined the influence of summary review on improving accuracy of analysis. As a result of the study, this study found that Boosting ensemble technique has the highest accuracy of analysis. In addition, the summary review contributed to improving accuracy of the analysis.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.145-151
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• 2011

This study assumed the competitive structure based on genre classification for Korean online game contents market, and carried out the analysis on the degree and characteristics of the competition that appear differently in each sub market classified according to the genre. First, to analyze the market power of the rank 1 and 2 game contents in each genre, using the play time share ratio and standard deviation statistics values in the genre, ANOVA analysis and Cluster analysis were carried out for each genre. According to ANOVA analysis result, in the rank 1 game share ratio in each genre, there was a relationship of 'FPS/Racing > RST/Sports > Poker > Go-stop > RPG > Arcade > Board', and in the play time total share ratio of rank 1 and 2 games, the relationship of 'RTS > FPS/Racing > Sports > RPG > Go-stop > Poker > Arcade > Board' was verified. And in Cluster analysis, the groups of the genres with the degree of market power tendency and the variability at similar level were classified and stated.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.273-287
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• 2024

Purpose - This study conducts the co-occurrence analysis, one of the social network analysis using global OTA's online reviews and grades in order to understand the experience structure of foreign tourists visiting cutural tourism resources in Jeju, Korea. Design/methodology/approach - For this purpose, this study selects 6 cultural tourism resources in Jeju as the study sites, and collects qualitative review data (noun, adjectives, and verb) and quantitative grade data. Findings - The co-occurrence network analysis between words and grade of market and street shows that the grade of 5 appears the most simultaneous with pork, buy, lot, try, fresh, black, food, price, seafood, local, market, good, street, etc. and the grade of 1 connects with small, dish, better, taste, etc. And the co-occurrence network analysis between words and grade of tradition and folklore shows that the grade of 5 appears the most simultaneous with village, place, museum, visit, time, life, culture, women, diver, use, lot, etc. and the grade of 1 connects with minute, spend, room, recommend, honey, etc. Research implications or originality - The above research results are relevant in order to find out the core experience of foreign tourists using online review and grade generated by foreign tourists and use as the important information to develop the strategies related to the planning and management of cultural tourism resources.