• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.173-190
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• 2015

The purpose of this study is to improve bankruptcy prediction models by using a novel hybrid under-sampling approach. Most prior studies have tried to enhance the accuracy of bankruptcy prediction models by improving the classification methods involved. In contrast, we focus on appropriate data preprocessing as a means of enhancing accuracy. In particular, we aim to develop an effective sampling approach for bankruptcy prediction, since most prediction models suffer from class imbalance problems. The approach proposed in this study is a hybrid under-sampling method that combines the k-Reverse Nearest Neighbor (k-RNN) and one-class support vector machine (OCSVM) approaches. k-RNN can effectively eliminate outliers, while OCSVM contributes to the selection of informative training samples from majority class data. To validate our proposed approach, we have applied it to data from H Bank's non-external auditing companies in Korea, and compared the performances of the classifiers with the proposed under-sampling and random sampling data. The empirical results show that the proposed under-sampling approach generally improves the accuracy of classifiers, such as logistic regression, discriminant analysis, decision tree, and support vector machines. They also show that the proposed under-sampling approach reduces the risk of false negative errors, which lead to higher misclassification costs.

• Journal of the Korea Convergence Society
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• v.9 no.5
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• pp.33-41
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• 2018

The purpose of this study is to develop more accurate and robust emotion prediction neural network (EPNN) model by combining heart rate variability (HRV) and neural network. For the sake of improving the prediction performance more reliably, the proposed EPNN model is based on various types of activation functions like hyperbolic tangent, linear, and Gaussian functions, all of which are embedded in hidden nodes to improve its performance. In order to verify the validity of the proposed EPNN model, a number of HRV metrics were calculated from 20 valid and qualified participants whose emotions were induced by using money game. To add more rigor to the experiment, the participants' valence and arousal were checked and used as output node of the EPNN. The experiment results reveal that the F-Measure for Valence and Arousal is 80% and 95%, respectively, proving that the EPNN yields very robust and well-balanced performance. The EPNN performance was compared with competing models like neural network, logistic regression, support vector machine, and random forest. The EPNN was more accurate and reliable than those of the competing models. The results of this study can be effectively applied to many types of wearable computing devices when ubiquitous digital health environment becomes feasible and permeating into our everyday lives.

• Journal of Arbitration Studies
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• v.18 no.1
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• pp.121-145
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• 2008

Northeast Asia is increasingly making a transition to distinctive and crucial region in the 21st Century and growing into one of world's top three economic spheres along with the EU and NAFTA. In 2003, Korean government announced the Northeast Asian economic hub country plan as an important agenda. As a means of coping with the changing global environment, Korean government designated Incheon in 2003 as the country's first Free Economic Zone ahead of Busan and Gwangyang Bay in the south of the country because Incheon has a geographical advantage linking North America and Europe with Incheon International Airport and Incheon Seaport. The purpose of this paper is to make research on establishment and operation of an arbitral body entitled ${\ulcorner}International Arbitration Center{\lrcorner}$ (IAC) within Incheon Free Economic Zone(IFEZ). For the purpose of this, the writer in this paper, reviewed the necessity of the IAC's establishment and its legal basis as well as the role and function of the Center. Also, the writer presented plans for how to operate the IAC and how to cooperate with the key arbitral organizations of foreign countries for the settlement promotion of commercial disputes including trade and investment. With development of the IFEZ, world-renowned enterprises will invest in the Incheon economic bloc and conduct economic activities, business operation, marketing, logistics, financing, etc. In this connection, diverse types of commercial disputes are expected to occur between foreign companies entering the IFEZ and Korean firms. In this connection, the Korean Commercial Arbitration Board(KCAB) has been operating its liaison office in the IFEZ since 2004. However, in view of the increasing arbitration demand, the IAC should be set up in the IFEZ in the near future by the positive support of the government in the respect of both administration and finance because the free economic zone-related law provides for the installation of arbitration organization. For the success of the IAC, the Center will have to provide not only good quality of arbitral services that can satisfy arbitration parties but also need to conduct researches and make efforts so that arbitration can be utilized well in the IFEZ. If the IFEZ can provide advantageous business environments to those multinational enterprises intending to the Incheon economic bloc, the IAC will also contribute to the settlement of commercial disputes arising from the Gaeseong Industrial Complex in North Korea in view of the geographical advantage and logistic benefit of the IFEZ. Finally, this paper also suggests a new model for a joint dispute resolution system by the initiative of Korean government and Korean arbitral organizations for the settlement of commercial disputes within Northeast Asia, for which the CAMCA(Commercial Arbitration and Mediation Center for the Americas) of NAFTA can be a good example.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.441-456
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• 2021

Enterprise is focused on R&D innovative activities in order to achieve sustainable growth & secure competitive advantage. There are many factors that influence enterprise innovation performance, but enterprise innovation activities do not always have a positive effect. Therefore, this study analyzed the effects of on innovation performance, focusing on innovation acceleration factors and innovation hindrance factors. The research model analyzed 2,081 national manufacturing enterprises that responded to the 2016 Korean Innovation Survey (STEPI). SPSS 25.0 was used to perform reliability, feasibility, and logistic regression analysis. The results are as follows. First, innovation activities have positive effects on enterprise product and process innovation performance. On the other hand, government support had the opposite results. Second, the collaboration of technology showed a positive effect on product innovation performance, independent of innovation acceleration and hindrance factors. Third, innovation activities showed a positive effect on process innovation performance, regardless of the innovation acceleration and hindrance factors. Unlike prior studies limited to technological innovation, this study analyzed the attitudes of enterprises toward innovation acceleration and hindrance factors. This study is expected to contribute to establishing a strategy for reducing the failure and risk of innovation due to its findings on how innovation performance varies by groups.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.122-132
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• 2019

This study investigated the effects of preference reversal according to product characteristics and situation. To investigate the relationship between consumer preference reversal and selection change, three research problems were set up and multiple logistic regression analysis was performed considering categorical dependent variables. The results showed that the decrease in preference for the medical service products and general manufacturing products had a significant effect on selection change and selection delay. In addition, we found that selection change according to the importance of attributes in the medical service product was more sensitive than the general product, while selection change according to the preference reversal was higher in general products. This study examined the causal relationship between choices by illuminating the preference concept as the central value of consumers from a different viewpoint than the existing preference and preference inversion research. In addition, the results of this study suggest that it can include not only selective change according to preference reversal, but also alternatives such as selective delay.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.107-117
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• 2019

In the era of SNS, many people relies on it to express their emotions about various kinds of products and services. Therefore, for the companies eagerly seeking to investigate how their products and services are perceived in the market, emotion mining tasks using dataset from SNSs become important much more than ever. Basically, emotion mining is a branch of sentiment analysis which is based on BOW (bag-of-words) and TF-IDF. However, there are few studies on the emotion mining which adopt feature selection (FS) methods to look for optimal set of features ensuring better results. In this sense, this study aims to propose FS methods to conduct emotion mining tasks more effectively with better outcomes. This study uses Twitter and SemEval2007 dataset for the sake of emotion mining experiments. We applied three FS methods such as CFS (Correlation based FS), IG (Information Gain), and ReliefF. Emotion mining results were obtained from applying the selected features to nine classifiers. When applying DT (decision tree) to Tweet dataset, accuracy increases with CFS, IG, and ReliefF methods. When applying LR (logistic regression) to SemEval2007 dataset, accuracy increases with ReliefF method.

• Journal of Digital Convergence
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• v.17 no.5
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• pp.137-143
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• 2019

Fake news is a form of misinformation that has the advantage of rapid spreading of information on media platforms that users interact with, such as social media. There has been a lot of social problems due to the recent increase in fake news. In this paper, we propose a method to detect such false news. Previous research on fake news detection mainly focused on text analysis. This research focuses on a network where social media news spreads, generates qualities with DeepWalk, a network embedding method, and classifies fake news using logistic regression analysis. We conducted an experiment on fake news detection using 211 news on the Internet and 1.2 million news diffusion network data. The results show that the accuracy of false network detection using network embedding is 10.6% higher than that of text analysis. In addition, fake news detection, which combines text analysis and network embedding, does not show an increase in accuracy over network embedding. The results of this study can be effectively applied to the detection of fake news that organizations spread online.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.2
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• pp.165-180
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• 2019

Recently, the Korean government announced that it would focus on fostering intrapreneurship and corporate spin-off. The government encourages intrapreneurship because it ultimately seeks to develop industries and markets, grow innovative companies, and job creation. In particular, the government believes that enhancing intrapreneurship will reduce the personal fear of failures, expand open innovation by utilizing resources within existing companies related to innovation creation, and lead to new start-ups. Accordingly, this research reviewed the previous studies on corporate entrepreneurship activities and entrepreneurial self-efficacy and briefly looked at the status of global intrapreneurship activities. Based on the Global Entrepreneurship Monitor Adult Population Survey data in 2015, this study conducted a logistic regression analysis with the data of 27 OECD member countries' and Korean respondents. The finding confirms that the personal experience of intrapreneurship could be positively associated with entrepreneurial self-efficacy of the person. Therefore, it seems to be worth for the Korean government considering policies that support intrapreneurship as part of the start-up policy.

• Korean small business review
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• v.42 no.2
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• pp.23-42
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• 2020

In this paper, it is analyzed that the financial factors of successful/unsuccessful companies in restructuring among Korean SMEs. For this purpose, the cases of 494 SMEs that had been subjected to workout programs due to financial distress between 2008-2014 were collected from A bank which is a SME financing bank, and had been subjected to logistic regression and t-test. And the sample cases are categorized into two groups, companies subject to external audit and the others, to provide more reliability. The result suggests; First, in all sample cases of SMEs, those are success factors for workout in connection with smaller total assets, lager sales amount, lower ratio of intangible assets, higher ratio of operating profit, lower ratio of short-term debt, higher ratio of long-term debt, and longer corporation history. Secondly, several factors have different influence on companies subject to external audit and the others. Lastly, the success factors for workout in Korean SMEs turned out to be different from those suggested in previous studies that are focused on large company. Some of the financial factors that led financially distressed firm to a successful restructuring showed the same results as large companies, but some of them were not related to them or even had the inverse influence on SMEs. This implies that SMEs have their distinctive success factors.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.75-91
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• 2023

As the business-to-customer (B2C) online market expands after the COVID-19 pandemic, the logistics industry has been constructing automated warehouses to handle multi-product, low-volume logistics. When constructing a logistics automation warehouse, it is crucial to validate that the facility's performance and operational logic are designed to meet the required throughput of the automated warehouse from the system design phase. This study proposes simulation-based validation and optimal alternatives for an H logistics automation warehouse in Iksan, Jeollabuk-do. Firstly, we focused on the box supply and packing processes, which are related to the release process, among the entire logistic processes. Then, we analyzed the potential bottlenecks in the target process and designed and implemented a discrete-event simulation model based on the analysis results. The simulation experiments showed that the facility parameters and operational logic identified in the system design phase did not satisfy the performance requirements of the entire automated warehouse. Additional experiments were conducted to suggest alternatives to meet the system performance requirements by changing the facility parameters and operational logic. We expect that the proposed study will be utilized in the future, not only in the system design phase but also in the system construction phase, for verification purposes to ensure that the construction proceeds according to the design.