• East Asian Journal of Business Economics (EAJBE)
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• v.11 no.4
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• pp.41-50
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• 2023

Purpose - This study aims to examine the role of contract law in mergers and acquisitions (M&A) and to examine whether or not contract law is necessary in M&A. The study also discusses how contract law can be utilized in M&A, as well as some of the problems that arise from the use of contracts in this area. Research design, data, and methodology - To minimize bias and errors, this study used only peer-reviewed articles and book excluding internet news articles, conference papers, and dissertations. For a well-organized screen and selection process, the author conducted the extraction procedure thoroughly to eliminate some duplicated resources. Result: This study indicates that complex deals carry a high risk but also have the potential to yield substantial revenue for stakeholders. Thus, contract law is essential to the success of M&A because it helps to define the (1) terms of the transaction, (2) reduces risk, (3) offers legal safeguards, and ensures that the (4) agreement is enforced. Conclusion - This study concludes that an understanding of contract law is essential to the profitable merging of two businesses. The application of contract law provides a mechanism for enforcing the agreement, which can increase the likelihood that the stipulations of the M&A will be satisfied.

• 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.

• Journal of Korean Library and Information Science Society
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• v.24
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• pp.413-448
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• 1996

Nowadays, the World Wide Web (WWW) has become an important resource of timely information for the information-related people such as information scientists, librarians, and students in Library and Information Sciences area. They are information professionals who navigate the information on the internet. Also, they need to be information providers who build a WWW homepage. This paper is a study of the necessity, preparation, and building WWW Homepage files for school of Library and Information Sciences in the age of competition among disciplines. It is particularly focused on the colleges and universities in Republic of Korea (ROK) and North America area. The purpose of this study is to provide various kinds of reference information to prepare a homepage in the future as utilizing information on the internet effectively. Even though a Web page was necessary for a school of Library and Information Sciences to show news, and introduce the purpose of the disciplines and the curriculum of the school, and the professors of a class etc., it was not well-prepared yet in ROK. However, a web page was used well enough and prosperous in North America area (Canada, the United States, and Puerto Rico) comparatively. Those web pages were analyzed and studied to prepare for a good designing of homepages for school of Library and Information Sciences in Korea and for the age of competition among disciplines in this paper. Suggestions for designing a good homepage and guidelines for preparing a best one were studied after both reviewing literature and utilizing experiences by the author who currently serves in the School of Library and Information Sciences in Keimyung University and builds homepage for the school. As a result, the major suggestions are ; premiered, and they are as follows: (1) English version of a homepage is necessary, (2) Provide a multimedia presentation about the nature of a school (3) Incorporate a place to let people make suggestions on the contents (of a homepage), (4) Bear in mind that potential users must be familiar with abbreviations you used, (5) Absolutely do not use abbreviations that may make the content more difficult to understand, (6) Add a feature on the every single page that will take the user back to the main page, (7) Use clear, short and well-structured sentences and remember to divide text into paragraphs, (8) Date with a creation or modification date in the homepage to indicate the updated date, (9) Being a multimedia environment, use colors effectively (the guidelines were also suggested), and (10) Put colleges' name into the title of bookmarks to find out them easily.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.28-37
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• 2020

This study was conducted to propose measures to improve crisis response to environmental issues by analyzing the news big data on the 'tap water larvae' situation and identifying related major keywords and topics. To accomplish this, 1,975 cases of 'tap water larvae' reported between July 13 to August 31, 2020 were divided into three periods and analyzed using topical modeling techniques. The analysis output 15 topics for each period. According to the result, the 'tap water larvae' incident, as reported in the media, is divided into the occurrence, diffusion, and rectification stages. The government's response and civilian risk consciousness and reaction could also be seen. Based on the result, the following measures to respond to environment risk is proposed. First, it is necessary to explore the various intertwined context with the 'tap water larvae' incident at its core and develop responsiveness to environmental problems through education which forms integrated views. Second, a role to monitor the environment must be implemented and civilian-participated environmental information must be shared through the application of internet communities. Third, the cultivation and deployment of environmental communicators who provide and communicate fast and accurate environment information is required. This study, as the first in Korea to use the topic modeling analysis method based on big data related to 'tap water larvae', has academic significance in that it has empirically and systematically analyzed environmental issues which appear as unstructured data. It also political significance as it suggests ways to improve environmental education and communication.

• Journal of the Korean Society for information Management
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• v.29 no.1
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• pp.375-393
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• 2012

The population aging occurs rapidly due to the advancement of the medical technology and living conditions and this led increased interests in how the elderly manages their lives. This study attempted to understand the information needs and behavior of the elderly users as well as to find about their information access and online communications. Based on the analysis of the interviews with thirty-two elderly users, they mainly looked for information on the topics such as health, news, leisure, and hobby. In addition, they primarily used television, radio, Internet, family members, relatives, and newspaper to obtain information. Their current use of social computing services including online communities, blogs, social network sites were low. However, the elderly users were aware of the social computing services' effectiveness in increasing the satisfaction and happiness of their lives by expanding the opportunities for them to communicate with family members and other social members.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.585-592
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• 2017

As development of personal devices have made everyday use of internet much easier than before, it is getting generalized to find information and share it through the social media. In particular, communities specialized in each field have become so powerful that they can significantly influence our society. Finally, businesses and governments pay attentions to reflecting their opinions in their strategies. The stock market fluctuates with various factors of society. In order to consider social trends, many studies have tried making use of bigdata analysis on stock market researches as well as traditional approaches using buzz amount. In the example at the top, the studies using text data such as newspaper articles are being published. In this paper, we analyzed the post of 'Paxnet', a securities specialists' site, to supplement the limitation of the news. Based on this, we help researchers analyze the sentiment of investors by generating a domain-specific sentiment lexicon for the stock market.

• Journal of Preventive Medicine and Public Health
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• v.54 no.1
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• pp.22-30
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• 2021

Objectives: The coronavirus disease 2019 (COVID-19) pandemic is a public health emergency posing unprecedented challenges for health authorities. Social media may serve as an effective platform to disseminate health-related information. This study aimed to assess the extent of social media use, its impact on preventive behavior, and negative health effects such as cyberchondria and information overload. Methods: A cross-sectional observational study was conducted between June 10, 2020 and August 9, 2020 among people visiting the outpatient department of the authors' institution, and participants were also recruited during field visits for an awareness drive. Questions were developed on preventive behavior, and the Short Cyberchondria Scale and instruments dealing with information overload and perceived vulnerability were used. Results: The study recruited 767 participants with a mean age of about 45 years. Most of the participants (>90%) engaged in preventive behaviors, which were influenced by the extent of information received through social media platforms (β=3.297; p<0.001) and awareness of infection when a family member tested positive (β=29.082; p<0.001) or a neighbor tested positive (β=27.964; p<0.001). The majority (63.0%) of individuals often searched for COVID-19 related news on social media platforms. The mean±standard deviation scores for cyberchondria and information overload were 9.09±4.05 and 8.69±2.56, respectively. Significant and moderately strong correlations were found between cyberchondria, information overload, and perceived vulnerability to COVID-19. Conclusions: This study provides evidence that the use of social media as an information- seeking platform altered preventive behavior. However, excessive and misleading information resulted in cyberchondria and information overload.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.193-215
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• 2016

In recent years, the proliferation of diverse social networking services has led users to use many mediums simultaneously depending on their individual purpose and taste. Besides, while collecting information about particular themes, they usually employ various mediums such as social networking services, Internet news, and blogs. However, in terms of management, each document circulated through diverse mediums is placed in different categories on the basis of each source's policy and standards, hindering any attempt to conduct research on a specific category across different kinds of sources. For example, documents containing content on "Application for a foreign travel" can be classified into "Information Technology," "Travel," or "Life and Culture" according to the peculiar standard of each source. Likewise, with different viewpoints of definition and levels of specification for each source, similar categories can be named and structured differently in accordance with each source. To overcome these limitations, this study proposes a plan for conducting category mapping between different sources with various mediums while maintaining the existing category system of the medium as it is. Specifically, by re-classifying individual documents from the viewpoint of diverse sources and storing the result of such a classification as extra attributes, this study proposes a logical layer by which users can search for a specific document from multiple heterogeneous sources with different category names as if they belong to the same source. Besides, by collecting 6,000 articles of news from two Internet news portals, experiments were conducted to compare accuracy among sources, supervised learning and semi-supervised learning, and homogeneous and heterogeneous learning data. It is particularly interesting that in some categories, classifying accuracy of semi-supervised learning using heterogeneous learning data proved to be higher than that of supervised learning and semi-supervised learning, which used homogeneous learning data. This study has the following significances. First, it proposes a logical plan for establishing a system to integrate and manage all the heterogeneous mediums in different classifying systems while maintaining the existing physical classifying system as it is. This study's results particularly exhibit very different classifying accuracies in accordance with the heterogeneity of learning data; this is expected to spur further studies for enhancing the performance of the proposed methodology through the analysis of characteristics by category. In addition, with an increasing demand for search, collection, and analysis of documents from diverse mediums, the scope of the Internet search is not restricted to one medium. However, since each medium has a different categorical structure and name, it is actually very difficult to search for a specific category insofar as encompassing heterogeneous mediums. The proposed methodology is also significant for presenting a plan that enquires into all the documents regarding the standards of the relevant sites' categorical classification when the users select the desired site, while maintaining the existing site's characteristics and structure as it is. This study's proposed methodology needs to be further complemented in the following aspects. First, though only an indirect comparison and evaluation was made on the performance of this proposed methodology, future studies would need to conduct more direct tests on its accuracy. That is, after re-classifying documents of the object source on the basis of the categorical system of the existing source, the extent to which the classification was accurate needs to be verified through evaluation by actual users. In addition, the accuracy in classification needs to be increased by making the methodology more sophisticated. Furthermore, an understanding is required that the characteristics of some categories that showed a rather higher classifying accuracy of heterogeneous semi-supervised learning than that of supervised learning might assist in obtaining heterogeneous documents from diverse mediums and seeking plans that enhance the accuracy of document classification through its usage.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.139-148
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• 2020

Infectious diseases have long plagued mankind, and predicting and preventing them has been a big challenge for mankind. For this reasen, various studies have been conducted so far to predict infectious diseases. Most of the early studies relied on epidemiological data from the Centers for Disease Control and Prevention (CDC), and the problem was that the data provided by the CDC was updated only once a week, making it difficult to predict the number of real-time disease outbreaks. However, with the emergence of various Internet media due to the recent development of IT technology, studies have been conducted to predict the occurrence of infectious diseases through web data, and most of the studies we have researched have been using single Web data to predict diseases. However, disease forecasting through a single Web data has the disadvantage of having difficulty collecting large amounts of learning data and making accurate predictions through models for recent outbreaks such as "COVID-19". Thus, we would like to demonstrate through experiments that models that use multiple Web data to predict the occurrence of infectious diseases through LSTM models are more accurate than those that use single Web data and suggest models suitable for predicting infectious diseases. In this experiment, we predicted the occurrence of "Malaria" and "Epidemic-parotitis" using a single web data model and the model we propose. A total of 104 weeks of NEWS, SNS, and search query data were collected, of which 75 weeks were used as learning data and 29 weeks were used as verification data. In the experiment we predicted verification data using our proposed model and single web data, Pearson correlation coefficient for the predicted results of our proposed model showed the highest similarity at 0.94, 0.86, and RMSE was also the lowest at 0.19, 0.07.

• Information Systems Review
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• v.20 no.1
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• pp.41-59
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• 2018

This study analyzed the factors that affect acceptance of online direct marketing in agricultural companies. Empirical analysis was conducted using the research model based on the individual's technology acceptance model (TAM) and the information technology adoption models in organizations. These models have four dimensions: 1) technology characteristics, which include perceived usefulness and perceived ease of use of TAM 2) CEO characteristics, which including the innovativeness and IT capability of CEOs; 3) organizational readiness, which include financial, technological, and human resources capabilities and 4) environment and external pressure, which include government support and changes to the Internet environment. These concepts were empirically tested. A total of 209 valid data were collected through questionnaires and analyzed using confirmatory factor analysis and path analysis through the application of structural equation modeling. Results show that perceived usefulness, IT capability of CEOs, and changes to the Internet environment have significant effects on the adoption intention of online direct marketing. However, perceived ease of use, CEO innovativeness, government support, and the variables of organizational readiness dimension did not have significant effects on adoption intention. This study suggests practical implications for adoption of online direct marketing in agricultural companies.