• Korea Trade Review
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• v.43 no.6
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• pp.215-238
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• 2018

Tariff reduction from FTAs are applied to imported goods, but not to traveler's goods. There are difficulties in meeting the FTA's conditions for free tariff application, such as origin of goods and direct transportation. This study suggests the optimal cut-off level of a simple tax rate applied to traveler's goods with respect to traveler' welfare and government tax revenue. Among three different scenarios of simple tax reductions by ordering its weighted magnitude of effects, the optimal tariff was found to be 2% applied to all goods. The effects of a 2% reduction of simple tax rate would increase traveler' welfare by 16.8 billion won and reduce tax revenue by only 0.34 billion won.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.

• Proceedings of the Korea Database Society Conference
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• 2001.11a
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• pp.473-505
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• 2001

예측 기관에 따라서 B2B의 시장 규모 및 성장률에 대한 차이는 있지만 B2B 시장이 빠른 속도로 성장하고 있으며, 이 같은 추세는 계속될 것이라는 점에 대한 이견은 없는 편이다. B2B는 기업에게 비용 절감과 시간 절약, 업무 효율성 증대 등의 다양한 효과를 제공해 줄 수 있기 때문에 앞으로도 그 중요성은 더 커질 것으로 예상된다. 그러나 B2B의 중요성 및 성장세와는 별도로 아직까지 B2B에 참여하는 기업들이 큰 효과를 거두지 못하고 있는 것이 사실이다. 이에 따라 많은 학자들과 컨설팅 회사들이 B2B의 모형, 추진 전략, 성공 요인들을 다양한 각도에서 제시하고 있다. 하지만 B2B에 대한 실증적 연구가 부족하여, 기업의 실무자들이 실질적인 도움을 얻기에는 부족한 점이 있기 때문에 B2B의 성공 요인과 추진 전략에 대한 실증적 연구가 절실히 필요하다. 본 연구의 목적은 B2B 유형 중 가장 널리 활용되고 있는 MRO e-marketplace의 성공에 영향을 주는 요인들을 실증적으로 분석하는 것이다. MRO e-marketplace의 성공 요인을 환경적 특성, 제품 특성, B2B 사이트 특성 등 3 그룹으로 분류한 후, 38개 기업에서 수집된 설문지를 분석하여 MRO e-marketplace의 성공 요인을 실증적으로 분석하였다. MRO e-marketplace의 성공 요인들을 요인 분석한 결과, 기업 내부 환경 요인, 기업 외부 환경 요인, 제품 정보 요인, 제품 공급 능력 요인, 사이트 기본 기능 요인, 사이트 편의성 요인, 사이트 보안성 요인 등 총 8개 요인으로 분류되었다. 한편 MRO e-marketplace의 도입 효과를 측정한 비용 절감, 시간 절약, 업무 효율성 증대, 거래 투명성 증대 등의 4개의 문항은 하나의 요인으로 묶여, 이를 MRO e-marketplace 성공으로 정의하였다. MRO e-marketplace의 성공에 영향을 미치는 요인을 찾기 위해, 추출된 8개 요인과 MRO e-marketplace 성공 간의 상관 관계를 분석하였다. 8개 요인 중에서 기업 내부 환경 요인, 제품 공급 능력 요인, 사이트 기본 기능 요인이 MRO e-marketplace의 성공에 영향을 미치는 것으로 나타났다. 마지막으로 MRO e-marketplace 성공 요인들의 상대적 중요도를 파악하기 위해 회귀 분석을 실시하였는데, 참여 기업의 내부 환경 요인이 가장 큰 중요한 것으로 나타났고, 그 다음은 제품 공급 능력 요인과 사이트 기본 기능 요인으로 나타났다. 이 같은 실증적 결과는 MRO e-marketplace나 B2B의 성공을 위해서는 참여 기업의 내부 환경 조성이 매우 중요함을 시사해 준다. 또한 참여 기업의 제품 공급 능력 요인 역시 MRO e-marketplace의 성공에 직접적인 영향을 주기 때문에 공급기업들의 제품 공급 능력을 높이는데 노력해야 한다. 또한 MRO e-marketplace를 운영하는 기업들은 사이트의 기능을 높이는데 많은 노력을 기울여야 한다는 것을 시사하고 있다. MRO e-marketplace의 성공 요인을 실증적으로 분석한 본 연구의 결과는 MRO e-marketplace와 B2B의 추진 전략의 이론적 모형 개발에 유용하게 활용될 수 있을 것이다. 또한 본 연구의 결과는 MRO e-marketplace와 B2B의 성공을 높이기 위한 추진 전략을 수립하는데 유용하게 활용될 수 있을 것으로 기대된다.

• Journal of Korea Port Economic Association
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• v.36 no.1
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• pp.59-76
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• 2020

The purpose of this study is to analyze the factors of the main selection criteria of the contract form used to conclude the sales contracts of used ships and to assist parties in selecting the most suitable contract form for trading situations. The methods of the study are based on identifying the factors from the questionnaires using analytic hierarchy process analysis, following the selection of typical details through interviews with the S&P Broker Group and finding the solutions that match each detail. The analysis shows that ship traders prefer the Norwegian Sales Form (NSF) to NIPPONSALE for various reasons. Considering the sellers' situations, NFS is the more reasonable option for major countries, except Japan. NIPPONSALE is relatively more focused on the advantages of the buyer's conditions, including for Japan. It is important to select the appropriate clauses from these types of contract, according to the trading conditions, including the main and additional terms, in order to create a mutual agreement between the shipper and the consignee that leads to more cooperation and balances the purposes of both parties in adjusting the time for securing and disposing of the vessels.

• Korean Journal of Poultry Science
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• v.32 no.3
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• pp.179-186
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• 2005

This study was conducted to establish a comprehensive guideline for grading system of poultry meat cuts. Slaughter and further processed houses were divided into large(>70,000 heads/day), middle($50,000\~25,000$ heads/day), and small scale(<25,000 heads/day), and the production managers were asked by the Questionnaire. Most poultry meat cuts produced by larger- and middle-slaughter house were consumed by dealers, franchisee and department store in increasing order, whereas further processed poultry meat cuts(small scale) provided meals for the students in the high amount. The packaging step was best f3r the determination of grading in the large slaughter house. This survey indicated that two or more grades were proper to determine the grading in the middle slaughter house, however only two grades were proper for the others. Freshness, bruise, wound, trimming and the inclusion of foreign materials affected to the grading. Poultry meat cuts were accepted for the grading in large-slaughter house, but whole poultry carcass was accepted for the grading in the others. Most managers agreed with that the grading system was only applied for the amounts requested. They also suggested that the grading system of poultry meat cuts were necessary in near future, even though it was not urgent to apply.

• Knowledge Management Research
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• v.22 no.3
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• pp.253-271
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• 2021

Due to the spread of COVID-19, the use of O2O order·delivery applications are becoming very common. Unlike the past, where customers could choose the desired transaction method and channel, these days, where customers' choices are very limited, it is urgent to consider the concept of shadow labor which has been hindered by the convenience and the benefits of order·delivery app. To this end, in this study, the service quality factors perceived by users of O2O order·delivery app and their shadow work attributes were identified, and priorities according to their relative importance and satisfaction level were suggested. In order to fulfill research objectives, first, after collecting user reviews for an O2O order·delivery app, the subject words were derived using topic modeling. Research variables were selected by linking 11 keywords with the concepts of previous studies on service quality of mobile apps and those about shadow labor. Eight variables of usefulness, ease of use, stability, design quality, personalization, responsiveness, update, and presence were selected. Based on 32 measurement items from the variables, a revised IPA was conducted, and finally, 'keep', 'concentrate', 'low priority', or 'overkill' service quality factors are revealed.

• Information Systems Review
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• v.19 no.3
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• pp.201-228
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• 2017

Vulnerability information, which can cause serious damage to information assets, has become a valuable commodity, thereby leading to the creation of a vulnerability market. Vulnerability information is traded on the vulnerability market from several hundred dollars to hundreds of thousands of dollars depending on its severity and importance, and the types and scope of the vulnerability markets are varying. Based on previous studies on vulnerability markets and hackers, this study empirically analyzed the effects of the security researcher's vulnerability research motivation on his/her vulnerability market use intention. The results are discussed as follows. First, vulnerability research self-efficacy had a significant effect on flow and on white and black market use intention but not on perceived benefit. Second, flow had a significant effect on perceived benefit and on black market use intention but had no effect on white market use intention. Third, perceived profit had a significant effect on white and black market use intention. Fourth, vulnerability research self-efficacy had a significant effect on perceived benefit through flow. Fifth, flow had a significant effect on white and black market use intention through perceived profit. These findings can be used to predict the behavior of security researchers who have experience in exploiting vulnerabilities.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.69-93
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• 2012

Various influence-related relationships in Social Network Services (SNS) among users, posts, and user-and-post, can be expressed using links. The current research evaluates the influence of specific users or posts by analyzing the link structure of relevant social network graphs to identify influential users. We applied the concept of mutual interactions proposed for ranking semantic web resources, rather than the voting notion of Page Rank or HITS, to blogosphere, one of the early SNS. Through many experiments with network models, where the performance and validity of each alternative approach can be analyzed, we showed the applicability and strengths of our approach. The weight tuning processes for the links of these network models enabled us to control the experiment errors form the link weight differences and compare the implementation easiness of alternatives. An additional example of how to enter the content scores of commercial or spam posts into the graph-based method is suggested on a small network model as well. This research, as a starting point of the study on identifying influential users in SNS, is distinctive from the previous researches in the following points. First, various influence-related properties that are deemed important but are disregarded, such as scraping, commenting, subscribing to RSS feeds, and trusting friends, can be considered simultaneously. Second, the framework reflects the general phenomenon where objects interacting with more influential objects increase their influence. Third, regarding the extent to which a bloggers causes other bloggers to act after him or her as the most important factor of influence, we treated sequential referencing relationships with a viewpoint from that of PageRank or HITS (Hypertext Induced Topic Selection).

• Korea Science and Art Forum
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• v.20
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• pp.147-158
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• 2015

This study made an approach to the industrial exhibition space, which is a medium of marketing communication, from the position of an enterprise and consumers through the output of Space Design, and conducted it with focus on B2B transactions among specialized exhibitions. In addition, this study inquired into what factors should be considered along with space design by interpreting the purpose of participating in the exhibition and space design of the enterprise which supply capital goods, elements, related technologies and materials, etc. This study aimed at drawing the direct/indirect effect, produced by space design, on the marketing by analyzing correlation between space design and participating enterprises' marketing. Despite the marketing effect of the exhibition, which was proved by preceding research results, the reality is that exhibition-participating expenses work as considerable burden on enterprises. Particularly, booth design, which is forming the most proportion among the participating expenses, was found to have insufficient influence on visitors due to the decline in its importance among diverse factors influencing visitor's decision to visit a booth. Regardless of the business category of participating enterprises in the exhibition, the standard of exhibits was ranked as the most important consideration factor in visiting a booth. Even by business category, the standard of booth design rarely had an influence on booth visit. Booth design had an affirmative influence on participating enterprise's preference, but its influence on product purchase or business talk & contact with a participating enterprise or price was found to be extremely low. It's difficult to judge marketing success or failure of an exhibition by the form and standard of booth design. Preferably, this study infers that it's necessary to put much weight on qualitative excellence of an exhibition, which consists of participation of an enterprise in possession of excellent technologies, exhibits with higher standards and high-quality visitors with purchasing power. This study suggests that it's more effective to set up the plan for expansion of participation in exhibition by optimally regulating the proportion of space design in participating expense to increase marketing effectiveness of an exhibition. The limitations of this study, analysis of which based on the visitors to an exhibition only, requires supplementation through the follow-up research work on participating enterprises in the exhibition.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.