• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.165-172
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• 2020

In this paper we propose an uses on-device-based edge computing technology and big data analysis methods through the use of on-device-based edge computing technology and analysis of big data, which are distributed computing paradigms that introduce computations and storage devices where necessary to solve problems such as transmission delays that occur when data is transmitted to central centers and processed in current general smart factories. However, even if edge computing-based technology is applied in practice, the increase in devices on the network edge will result in large amounts of data being transferred to the data center, resulting in the network band reaching its limits, which, despite the improvement of network technology, does not guarantee acceptable transfer speeds and response times, which are critical requirements for many applications. It provides the basis for developing into an AI-based facility prediction conservation analysis tool that can apply deep learning suitable for big data in the future by supporting intelligent facility management that can support productivity growth through research that can be applied to the field of facility preservation and smart factory industry with integrated hardware technology that can accommodate these requirements and factory management and control technology.

• Management & Information Systems Review
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• v.38 no.3
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• pp.113-125
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• 2019

This study empirically analyzes the effect of SNS informativeness, playfulness and reliability on purchase intention and the effect of consumer's purchase intention on business performance through structural equation model, In doing so, this study aims to suggest ways to enhance consumers' purchase intention and consequently increase the business performance through various SNS marketing strategies that can efficiently manage consumers. The questionnaires were distributed to adult men and women who are in their 20s through 60s, actively use SNS, and primarily reside in Daegu and Gyeongbukdo. The 400 copies of questionnaire were distributed from September 15 to October 1, 2018, of which 364 (91%) were used for the empirical analysis, except for 36 of the questionnaires that were unfaithful or unresponsive. Basic statistical analysis including frequency analysis was performed using SPSS 22.0 and AMOS 24.0, reliability and validity analysis were also performed, and finally hypotheses were tested by performing confirmatory factor analysis and path analysis of structural equation model. All of the SNS informativeness, playfulness and reliability were shown to have positive effects on the purchase intention. In addition, the effect of purchase intention on business performance was found to be significant. Companies should come up with a strategic SNS marketing plan to encourage consumers to enhance the willingness to purchase their products and services through SNS, and to make actual purchases, thereby improving business performance.

• Management & Information Systems Review
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• v.38 no.3
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• pp.187-210
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• 2019

Companies shall hold social responsibility as a member of the social community. Corporate social responsibility uses corporate resources, yet it plays important roles in reducing social imbalance. Their responsibilities are highly associated with the corporate sustainability. Many earlier studies on the association between corporate social responsibility and corporate sustainability have been attempted. Yet it should be mentioned that they do not show a variety of realities as linearity between dependent variables and independent variables were assumed. Thus, this study aims to analyze Markov blanket, a node of minimum descriptive variables that relieve a rigid assumption among variables and affect corporate sustainability by using Bayesian network. Sensitivity analysis was used to elicit how other variables affect by reflecting the complex reality when real factors are changed. As an important result of this study, the firm's future earnings sustainability is naturally related to operating earnings, and as the corporate governance structure is sound, the firm is able to steadily fulfill its social responsibility. However, the fact that the size of a company is large does not mean that it is in good compliance with corporate laws. This would not be unrelated to the fact that many of today's companies are not complying with the law and are suffering social condemnation. Results from this study will serve as a useful analytic tool when investors and creditors showing interests in corporate sustainability for assessing the value of companies and making investment decisions. Moreover, they can be used as references for relevant agency supervising capital markets to establish or improve appropriate institutions aimed at improving corporate sustainability.

• Management & Information Systems Review
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• v.38 no.1
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• pp.181-199
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• 2019

The purpose of this study is to examine whether or not the volatility of the 1997~1998 Asian crisis still affects the monthly stock returns of Korea, Japan, Singapore, Hong Kong and China from 1980 to 2018. This study investigated whether the volatility has already fallen to pre-crisis levels. To illustrate the possible structural changes in the unconditioned variance due to the Asian financial crisis, we use the MRS-GARCH model, which is a regime switching model. The main results of this study were as follows: First, the stock return of each country was weak in the high volatility regime except Japan resulted by the Asian financial crisis from 1997 to 1998 until March 2018, and the Asian stock market has not yet calmed down except for the global financial crisis period of 2007 and 2008. Second, the conditional volatility has been significantly and persistently decreased and eliminated after the Asian financial crisis. Thus, we could be judged that the Asian stock market was not fully recovered(stable) due to the Asian crisis including the capital liberalization high inflation, worsening current account deficit, overseas low interest rates and expansion of credit growth in 1997 and 1998, but the Asian stock market was largely settled down, except for the 2007 and 2008 in Global financial crises. Considering the similarity between the Asian stock markets and the similar correlation of the regime switching, it may be worthwhile to analyze the MRS-GARCH model.

• Knowledge Management Research
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• v.22 no.2
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• pp.247-268
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• 2021

Investors mainly use PER and PBR among financial ratios for valuation and investment decision-making. I conduct an analysis of two basic financial ratios from a statistical perspective. Financial ratios contain key accounting numbers which reflect firm fundamentals and are useful for valuation or risk analysis such as enterprise credit evaluation and default prediction. The distribution of financial data tends to be extremely heavy-tailed, and PER and PBR show exceedingly high level of kurtosis and their extreme cases often contain significant information on financial risk. In this respect, Extreme Value Theory is required to fit its right tail more precisely. I introduce not only GPD but exGPD. GPD is conventionally preferred model in Extreme Value Theory and exGPD is log-transformed distribution of GPD. exGPD has recently proposed as an alternative of GPD(Lee and Kim, 2019). First, I conduct a simulation for comparing performances of the two distributions using the goodness of fit measures and the estimation of 90-99% percentiles. I also conduct an empirical analysis of Information Technology firms in Korea. Finally, exGPD shows better performance especially for PBR, suggesting that exGPD could be an alternative for GPD for the analysis of financial ratios.

• Informatization Policy
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• v.28 no.2
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• pp.57-80
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• 2021

This study aimed to identify the causes of adult cyberbullying, an issue which arouses little academic interest despite its seriousness and its harmful consequences, in order to provide basic data for the formulation of reasonable measures for preventing and reducing adult cyberbullying. To that end, the author of the study analyzed the results of the government-led Cyber Violence Survey conducted in 2019. First, the online survey panel owned by the research company selected a sample of 1,500 adult men and women in their 20s to 50s in proportion to reflect the composition of the local population. The survey was conducted online, with male subjects and female subjects accounting for 51.5% and 48.7% of the respondents, respectively. The result of the analysis shows that the respondents' attitude towards cyberbullying was fully mediaed according to such factors as gender, age, family relations, relationship with colleagues, Internet usage time, and contact with illegal content. In addition, partial mediation was observed with regard to online delinquency colleague numbers and cyberbullying victimization. As a result, the respondents' attitude towards cyberbullying was found to be the most important factor affecting adult cyberbullying. Based on these results, this study suggests that the formation of a non-conservative attitude towards cyberbullying should be considered to be more important than any other factors when preparing programs aimed at preventing cyberbullying.

• Journal of the Society of Disaster Information
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• v.18 no.3
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• pp.532-541
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• 2022

Purpose: The purpose of this study is to suggest that the existing power demand prediction method including power demand according to fine dust is included in the existing power consumption by using an air purifier to improve the air quality due to fine dust. Method: The method of the study was compared and analyzed using data on the concentration of fine dust in Seoul for three years, household power consumption, and climate observation, and the effect of fine dust on power consumption in Seoul was identified in April and October. Result: The power consumption of home air purifiers in Seoul due to fine dust differences between April and October was calculated to be 2,141 MWh, accounting for 3.4% of the total difference in the use of home appliances in April and October. Conclusion: The effect of fine dust on household power consumption was verified, and power demand prediction is essential for economic system operation and stable power supply, so power consumption due to fine dust should be considered as well as focusing on power consumption of existing air conditioners and heaters.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.431-453
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• 2022

Hate is a collective expression of exclusivity toward others and it is fostered and reproduced through false public perception. This study aims to explore the objects and issues of hate discussed in our society using text mining techniques. To this end, we collected 17,867 news data published from 1990 to 2020 and constructed a co-word network and cluster analysis. In order to derive an explicit co-word network highly related to hate, we carried out sentence split and extracted a total of 52,520 sentences containing the words 'hate', 'prejudice' and 'discrimination' in the preprocessing phase. As a result of analyzing the frequency of words in the collected news data, the subjects that appeared most frequently in relation to hate in our society were women, race, and sexual minorities, and the related issues were related laws and crimes. As a result of cluster analysis based on the co-word network, we found a total of six hate-related clusters. The largest cluster was 'genderphobic', accounting for 41.4% of the total, followed by 'sexual minority hatred' at 28.7%, 'racial hatred' at 15.1%, 'selective hatred' at 8.5%, 'political hatred' accounted for 5.7% and 'environmental hatred' accounted for 0.3%. In the discussion, we comprehensively extracted all specific hate target names from the collected news data, which were not specifically revealed as a result of the cluster analysis.

• Journal of Korean Library and Information Science Society
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• v.53 no.2
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• pp.189-214
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• 2022

The purpose of this study is to provide an understanding of the current status of picture book-related research in Korea. For this purpose, 1,660 picture book-related research papers produced in Korea by 2021 were analyzed. The results revealed through the analysis are summarized as follows. First, research papers began to appear in the mid-1990s and began to increase significantly around 2010. Second, the journal with the most research papers was 『Journal of Children's Literature and Education』, accounting for 17.7% of the total. Third, the representative researchers who led the production of the papers are Eun-Ja Hyun and Hea-Sook Jo. Fourth, by research type, individual research papers accounted for 39% and joint research 61%. Fifth, as a result of the analysis of the research topic, the study of the contents (analysis) of picture books (33.4%), the study of the effect of picture books (29.6%), and the study of perception, reaction, and experience of picture books (18.0%) were in order. Sixth, as a result of the research method analysis, experimental studies (35.7%), content analysis (33.7%), literature studies (13.3%), and qualitative studies (9.3%) were in order. Based on the results of the analysis, the researcher suggested diversifying the research production route, expanding the trend of collaboration between universities and the field, diversifying research topics, and enhancing the validity and diversity of research methods.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.129-136
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• 2023

The government of the Republic of Korea is conducting quality management of public open data by conducting a public data quality management level evaluation. Public open data is provided in various open formats such as XML, JSON, and CSV, with CSV format accounting for the majority. When diagnosing the quality of public open data in CSV format, the quality diagnosis manager determines and diagnoses the domain for each field based on the field name and data within the field of the public open data file. However, it takes a lot of time because quality diagnosis is performed on large amounts of open data files. Additionally, in the case of fields whose meaning is difficult to understand, the accuracy of quality diagnosis is affected by the quality diagnosis person's ability to understand the data. This paper proposes a domain discrimination model for public open data in CSV format using field names and data distribution statistics to ensure consistency and accuracy so that quality diagnosis results are not influenced by the capabilities of the quality diagnosis person in charge, and to support shortening of diagnosis time. As a result of applying the model in this paper, the correct answer rate was about 77%, which is 2.8% higher than the file format open data diagnostic tool provided by the Ministry of Public Administration and Security. Through this, we expect to be able to improve accuracy when applying the proposed model to diagnosing and evaluating the quality management level of public data.