• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.947-960
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• 2023

In Korea, traditional paper promissory notes are currently undergoing a transformation, being gradually replaced by electronic notes. This transformation is being steered under the Korea Financial Telecommunications Institute, a trusted authority. However, existing electronic systems have security vulnerabilities, including the risk of hacking and internal errors within the institute. To this end, we have defined a novel anonymous electronic promissory note system based on blockchain. We have constructed a concrete protocol and conducted security analysis of our protocol. Note that, in our protocol, every note information is committed so that the note remains undisclosed until the point of payment. Once the note information becomes public on the blockchain, it enables the detection of illicit activities, such as money laundering and tax evasion. Furthermore, our protocol incorporates a feature of split endorsement, which is a crucial functionality permitted by the Korean electronic note system. Consequently, our proposed protocol is suitable for practical applications in financial transactions.

• Land and Housing Review
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• v.2 no.4
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• pp.439-452
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• 2011

The goal of this research is to suggest the desirable directions of the land policies implement system based on analysis of existing those of Korea with the paradigm shift of land policies. We classify the land policies into land ownership, land use, land development and land management ones, and then analyze their implement system characteristics. The results are follows : firstly, the land policies implement systems have been set to large scale and rapid development. Secondly, although the systems have been specialized by their areas, the comprehensive manage systems for the harmony between development and conservation are lacking. Thirdly, the parts of the central government powers related to land use has been hand covered to local governments. And the participations of residences private companies have enlarged in the land development. Fourthly, the purposes of the information management on land use have been changed from tax collection into planned land use, but the information management has not met the need of planned land use. This study shows that firstly, the implement system focusing on large development projects might be no longer effective because of high possibility of the property prices stabilization, so moderately small ones must be found. Secondly, the system cope with the climate change and to realize the efficient utility of land is needed. Thirdly, it is necessary to take the actual measures to participate a variety of subjects. Fourthly, the system modification of the land information manage system as land policies infra is also needed to establish integral land policies.

• Journal of Service Research and Studies
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• v.10 no.3
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• pp.67-80
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• 2020

The information system audit service has been recognized for its effectiveness in improving the management efficiency of informatization projects in the public sector and improving the quality of information systems. However, according to several recent studies, it is not very helpful in securing quality by indicating formal audit performance and incorrect functions or errors in a short audit period. So, if the effectiveness of audit is proved to ensure the quality of the information system from the perspective of the software life cycle and to successfully operate and maintain it, the use of audit for the successful construction of the information system will be an essential factor. Therefore, this study investigated whether the current audit service users are satisfied with the current information system audit and what they expect. If it is different from what was expected, the difference between expectations and performance was analyzed to improve user satisfaction, and a survey was conducted through interviews with experts in the information system field. Based on the empirical results through the questionnaire, in order to reduce the difference in expectations from the user's point of view in the information system audit service, a plan to improve the audit system suitable for the new audit environment was proposed.

• Management & Information Systems Review
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• v.7
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• pp.21-51
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• 2001

For increasing the competitiveness and efficiency of Korea's finance industry under the new e-finance paradigm, this paper compared the practical use of finance portal site' on service parts and stage between Korea and U.S.A.. The services which can be served from site are banking, mortgage and credit loan, stock, card, retirement tax, PFM(Personal Finance Management), EBPP(Electronic Bill Presentment and Payment) and Account Aggregation and so on. The stage of site can be divided as the information provide stage which only gives information about service parts, on-line transaction stage which real-time transaction is possibile and PFM services provide stage according to development process. As a result, the beginning of finance portal service in Korea was lated about 10years and more than it of U.S.A. So the development stage of domestic portal site is still staying in the first step and the providing services and contents or business model development parts are also in the same stage than U.S.A. Resides, Korea's sites mainly focus on their first service parts even though they recently aim internet finance portal, and provide not real time transaction but finance information. On the other hand, the U.S.A. site support substantially not only various on-line transactions but also distinctive personal services like PFM(Personal Finance Management), EBPP(Electronic Bill Presentment and Payment), Account Aggregation and Trans-account, brokerage, education center, mortgage loan, mutual fund, option, pension fund and IPOs and so on. Thus, the site of Korea need to establish real type of internet finance portal which provides one-stop services on every type of finance to customers in the real time and also require the strategic integration among finance institutions. The next turn, they need to build information system and education center to give best satisfaction to customers and acquire customer information and marker environment changes and need to provide distinctive services to quality customers throughout database from this. Also the site should provide various type of banking services which refereed above like PEM, EBPP and education center etc, and the government of Korea should support the building of IT infrastructure to Physical, legal, systematic, sociocultural, technical and human resource sections. This paper provided the future movement direction of the domestic finance portal through comparison and analysis on the practical use of it between Korea and U.S.A. and also wanted to contribute for developing and reading of Korea finance portal in the new era of the finance paradigm.

• Management & Information Systems Review
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• v.35 no.3
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• pp.81-93
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• 2016

UK "FSMA" provides a safe harbour for members of professions, which are lawyers, accountants, and actuaries in their provision of certain financial services, despite the general prohibition, the professions carry on exempt regulated activities. In particular, DPBs(designated professional bodies), which professional bodies are designated by the Treasury, must have rules and have to supervise and regulate their members those activities by rules. Also, the FSA must keep itself informed about the role of DPBs, and may make directions concerning the safe harbour in relation to particular classes of persons of different descriptions of regulated activities. On the other hand, Korea "FSCMA" explicitly except provision of financial services by professions to investment adviser without regard to mainstream financial services activities or incidental activities. Under "FSMA", if the professions conduct provision of financial services as mainstream activities, they must be authorized person and even if their activities is incidental, they have to comply with exemption sections. Therefore, there is a need of prepare the legal safeguards about provision of financial services by professions for the investor protection.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.157-176
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• 2018

The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.

• Management & Information Systems Review
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• v.28 no.3
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• pp.117-140
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• 2009

The purpose of this study is to investigate the effects of corporate mecenat activities, ultimately making more firmly established the theory of mecenat activities from the perspective of marketing. For the purpose, this researcher examined the motives of such activities and analyzed the current state and problems of those activities in Korea. In this study, the motives of corporate mecenat activities are largely classified into the improvement of corporate image, which is identified from the view of cultural investment, and direct corporate profits like tax favor, from the view of marketing. Regarding the effects of corporate mecenat activities, P. Kotler and J. Scheff suggested that in future, corporate supports to art would be the most remarkable part of marketing. In association, the Australian Foundation for Culture & Humanities and Arthur Andersen described the effects of corporate mecenat activities in form of cultural investment largely in terms of business, market and employees. In a similar vein, the Korea Business Council for the Arts classifies the effects of corporate mecenat activities largely into three, corporate legitimacy, market advantage and benefit to employees. In relation to corporate mecenat activities, now, the theory of mecenat which is established from the perspective of marketing is considered more persuasive than that which is provided from the perspective of philanthropy. For more corporate efficiency and effectiveness, in conclusion, it's needed to orient the theory of mecenat from the perspective of marketing.

• Information Systems Review
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• v.20 no.2
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• pp.1-19
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• 2018

In many countries, governments invest a substantial amount of budget in open government data (OGD) for governmental performance and transparency. To understand the actual performance of such policies, the governments should measure the realized value. Many organizations and researchers have attempted to assess the value of OGD. However, they have neglected a perspective of consumers who benefit from OGD. Moreover, little research has quantified the economic value. This research examines extant methods of intangible asset valuation to quantify the economic value of OGD in a citizen perspective. In consideration of the extant research methods and the characteristics of OGD, the contingent valuation method is the most appropriate because it effectively reflects various users and their purpose of use. We then conduct a survey of citizens living in Seoul, Korea and assess the economic value of OGD provided by the Seoul government. Findings show that citizens' willingness to pay (WTP) differs across respondents' prior experience, tax resistance, perceived benefit and perceived reality of virtual scenario, but it does not differ across their demographics. WTP also significantly varies across the question formats. We discuss the reliability of the results and implications for future research.

• The Journal of Society for e-Business Studies
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• v.23 no.1
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• pp.1-22
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• 2018

The value chain has been utilized as a strategic tool to improve competitive advantage, mainly at the enterprise level and at the industrial level. However, in order to conduct value chain analysis at the enterprise level, the client companies of the parent company should be classified according to whether they belong to it's value chain. The establishment of a value chain for a single company can be performed smoothly by experts, but it takes a lot of cost and time to build one which consists of multiple companies. Thus, this study proposes a model that automatically classifies the companies that form a value chain based on actual transaction data. A total of 19 transaction attribute variables were extracted from the transaction data and processed into the form of input data for machine learning method. The proposed model was constructed using the Random Forest algorithm. The experiment was conducted on a automobile parts company. The experimental results demonstrate that the proposed model can classify the client companies of the parent company automatically with 92% of accuracy, 76% of F1-score and 94% of AUC. Also, the empirical study confirm that a few transaction attributes such as transaction concentration, transaction amount and total sales per customer are the main characteristics representing the companies that form a value chain.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.3
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• pp.71-80
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• 2021

The selection of an appropriate neural network algorithm is an important step for accurate data prediction in machine learning. Many algorithms based on basic artificial neural networks have been devised to efficiently predict future data. These networks include deep neural networks (DNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and gated recurrent unit (GRU) neural networks. Developers face difficulties when choosing among these networks because sufficient information on their performance is unavailable. To alleviate this difficulty, we evaluated the performance of each algorithm by comparing their errors and processing times. Each neural network model was trained using a tax dataset, and the trained model was used for data prediction to compare accuracies among the various algorithms. Furthermore, the effects of activation functions and various optimizers on the performance of the models were analyzed The experimental results show that the GRU and LSTM algorithms yields the lowest prediction error with an average RMSE of 0.12 and an average R2 score of 0.78 and 0.75 respectively, and the basic DNN model achieves the lowest processing time but highest average RMSE of 0.163. Furthermore, the Adam optimizer yields the best performance (with DNN, GRU, and LSTM) in terms of error and the worst performance in terms of processing time. The findings of this study are thus expected to be useful for scientists and developers.