• Asia pacific journal of information systems
• /
• v.19 no.2
• /
• pp.157-178
• /
• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Asia pacific journal of information systems
• /
• v.18 no.1
• /
• pp.97-115
• /
• 2008

Introduction The e-government is concerned with using Internet and Web technologies to exchange information and services with citizens, businesses and other related organizations, and it centers on three functions, namely informational, interactive, and transactional [UN, 2001]. Many developed countries like the U.S. have been actively involved in e-government projects, since they enable both more effective public services for citizens and more efficient internal operations. Korea is among these leading countries that are planning to leverage computer and communication technologies to provide for integration of work processes and information as well as convenient access to information and services. For this reason, evaluating e-government projects is becoming a crucial issue for both researchers and policy-makers. However, most research to date has primarily focused on a model of success of an e-government system designed for citizens, overlooking internal systems specifically created for employees working in a public organization. This paper is intended to propose a model to measure the success of a Web-based information system designed for use by internal users at Chungwadae, the executive branch of Korea's central government. The paper is also aimed at applying the model to the assessment of the present system being used at Chungwadae in comparison with the preceding system. Evaluating an e-Government System The most widely cited model of information systems success today is that of DeLone and McLean[1992, 2003, 2004]. The original model states that the success of an information system can be measured using six dimensions, including system quality, information quality, use, user satisfaction, individual impact, and organizational impact. Although the ultimate success of an information system may be reflected in the impact that the system has upon individuals as well as an organization, aspects of using the system such as system use and user satisfaction can play an important role in determining the system success, because the system would be a sheer failure if users don't like and use the system. As a response to criticisms given by numerous researchers, the authors adapted their model to fit the emerging Web-based environment. The revised model[DeLone and McLean, 2003] they offered included an additional quality dimension, namely service quality, and combined individual and organizational impacts into net benefits which can also influence user satisfaction. The e-government system success model can be built around this updated model. Our model incorporates information quality, system quality, and service quality as in the DeLone and McLean model. However, the 'system use' dimension has been replaced by perceived usefulness, as suggested by Seddon[1998]. In addition, because the e-government systems that this paper focuses on are internal public systems used in government agencies, the 'net benefits' dimension has been replaced by perceived work efficiency. Based on the proposed model, a total of nine hypotheses have been formulated which we tested using an empirical analysis. Methods A questionnaire form has been created with items that are designed to examine the relationships among the variables in the model. The questionnaire has been handed over, in person, to 65 members of Chungwadae staff who are now actively using the E-Support System, the present information system created to support internal work at Chungwadae. We made arrangements to meet with each individual who agreed to participate in our survey, and helped to fill out the survey form with explanations. Of the 65 copies that were delivered, only 33 were returned, and 30 responses of these have been adopted for our analysis, since three were not valid. The extremely small sample size was due to the limited number of staff members who had adequate experience required of this study. Results We gathered data from the questionnaire survey and analyzed them using a regression analysis to test the hypotheses. As shown in the table below, the results indicated that all three dimensions of an information system’s quality are positively related to user satisfaction. However, information quality and system quality were found to be positively related to perceived usefulness, while service quality was not. In addition, perceived usefulness is not positively related to user satisfaction, implying that a user may find a system useful, but may not be satisfied with it. Finally, user satisfaction and perceived usefulness both are positively related to perceived work efficiency. This suggests that workers' positive experience with the system is important to guarantee favorable work efficiency. Conclusions We conclude that the proposed model proved useful in measuring the success of an internal information system used by a government agency. To demonstrate the applicability and usefulness of the model in the paper, we applied the model to the assessment of the present internal system used at Chungwadae in comparison with the preceding system. The results showed that the present system outperforms the preceding one in a statistically significant way. Future research will have to focus on applying the model to Korea's governmental agencies other than Chungwadae and examine whether it proves applicable in different types of governmental organizations.

• The Journal of Korean Academy of Prosthodontics
• /
• v.47 no.3
• /
• pp.328-334
• /
• 2009

Statement of problem: Pier abutments act as a Class I fulcrum lever system when the teeth are incorporated in a fixed partial denture with rigid connectors. Therefore non-rigid connector incorporated into the fixed partial denture might reduce the stresses created by the leverage. Purpose: The purpose of this study was to evaluate, by means of finite element method, the effects of non-rigid connectors and supporting alveolar bone level on stress distribution for fixed partial dentures with pier abutments. Material and methods: A 2-dimensional finite element model simulating a 5-unit metal ceramic fixed partial denture with a pier abutment with rigid or non-rigid designs, the connector was located at the distal region of the second premolar, was developed. In the model, the lower canine, second premolar, and second molar served as abutments. Four types of alveolar bone condition were employed. One was normal bone condition and others were supporting bone reduced 20% height at one abutment. Two different loading conditions, each 150 N on 1st premolar and 1st molar and 300N on 1st molar, were used. Results: Two types of FPD were displaced apically. The amount of displacement decreased in an almost linear slope away from the loaded point. Non-rigid design tended to cause the higher stresses in supporting bone of premolar and molar abutments and the lower stresses in that of canine than rigid design. Alveolar bone loss increased the stresses in supporting bone of corresponding abutment. Conclusion: Careful evaluation of the retentive capacity of retainers and the periodontal condition of abutments may be required for the prosthetic design of fixed partial denture with a pier abutment.

• The Korean Journal of Air & Space Law and Policy
• /
• v.28 no.2
• /
• pp.349-384
• /
• 2013

The Sputnik 1 launching in 1957 made the world recognize the necessity of international regulations on space development and activities in outer space. The United Nations established COPUOS the very next year, and adopted the mandate to examine legal issues concerning the peaceful uses of outer space. At the time, the military sector of the U.S.A. and the Soviet Union were in charge of the space development and they were not welcomed to discuss the prohibition of the military uses of outer space at the legal section in the COPUOS. Although both countries had common interests in securing the freedom of military uses in outer space. As the social and economic benefits derived from space activities have become more apparent, civil expenditures on space activities have continued to increase in several countries. Virtually all new spacefaring states explicitly place a priority on space-based applications to support social and economic development. Such space applications as satellite navigation and Earth imaging are core elements of almost every existing civil space program. Likewise, Moon exploration continues to be a priority for such established spacefaring states as China, Russia, India, and Japan. Recently, Companies that manufacture satellites and ground equipment have also seen significant growth. On 25 February 2012 China successfully launched the eleventh satellite for its indigenous global navigation and positioning satellite system, Beidou. Civil space activities began to grow in China when they were allocated to the China Great Wall Industry Corporation in 1986. China Aerospace Corporation was established in 1993, followed by the development of the China National Space Administration. In Japan civil space was initially coordinated by the National Space Activities Council formed in 1960. Most of the work was performed by the Institute of Space and Aeronautical Science of the University of Tokyo, the National Aerospace Laboratory, and, most importantly, the National Space Development Agency. In 2003 all this work was assumed by the Japanese Aerospace Exploration Agency(JAXA). Japan eases restrictions on military space development. On 20 June 2012 Japan passed the Partial Revision of the Cabinet Establishment Act, which restructured the authority to regulate Japanese space policy and budget, including the governance of the JAXA. Under this legislation, the Space Activities Commission of the Ministry of Education, Culture, Sports, Science, and Technology, which was responsible for the development of Japanese space program, will be abolished. Regulation of space policy and budget will be handed over to the Space Strategy Headquarter formed under the Prime Minister's Cabinet. Space Strategy will be supported by a Consultative Policy Commission as an academics and independent observers. By revoking Article 4 (Objectives of the Agency) of a law that previously governed JAXA and mandated the development of space programs for "peaceful purposes only," the new legislation demonstrates consistency with Article 2 of the 2008 Basic Space Law. In conformity with the principles laid down in the 1967 Outer Space Treaty JAXA is now free to pursue the non-aggressive military use of space. New legislation is the culmination of a decade-long process that sought ways to "leverage Japan's space development programs and technologies for security purposes, to bolster the nation's defenses in the face of increased tensions in East Asia." In this connection it would also be very important and necessary to create an Asian Space Agency(ASA) for strengthening cooperation within the Asian space community towards joint undertakings.

• Management & Information Systems Review
• /
• v.39 no.1
• /
• pp.93-114
• /
• 2020

Platform is considered as an alternative strategy to the traditional linear pipeline based business. Moreover, in the 4th industrial revolution period, efficiency driven pipeline business model needs to be changed to platform business. We have such success stories about platform as Apple, Google, Amazon, Uber, and so on. However, for those smaller corporations, it is not easy to find out the transformation strategy. The essence of platform business is to leverage network effect in management. Thus platform based management can be rephrased as network management across the business functions. Research on platform business is popular and related to diverse facets. But few scholars cover what the research trend of the domain is. The main purpose of this paper is to identify the research trend on platform business in Korea. To do that we first propose the analytical model for platform architecture whose components are consumers, suppliers, artifacts, and IT platform system. We conjecture that mapping of the research work on platform to the components of the model will make us understand the hidden domain of platform research. We propose three hypotheses regarding the characteristics of research and one proposition for the transitional path from pipeline to platform business model. The mapping is based on the research articles filtered from the Korea Citation Index, using keyword search. Research papers are searched through the keywords provided by authors using the word of "platform". The filtered articles are summarized in terms of the attributes such as major component of platform considered, platform type, main purpose of the research, and research method. Using the filtered data, we test the hypotheses in exploratory ways. The contribution of our research is as follows: First, based on the findings, scholars can find the areas of research on the domain: areas where research has been matured and territory where future research is actively sought. Second, the proposition provided can give business practitioners the guideline for changing their strategy from pipeline to platform oriented. This research needs to be considered as exploratory not inferential since subjective judgments are involved in data collection, classification, and interpretation of research articles.

• The Korean Journal of Financial Management
• /
• v.21 no.2
• /
• pp.99-123
• /
• 2004

We focus in this study on incremental financing decisions and estimate a logit model for the probability a firm will choose a private placement over a public bond issue. We hypothesize that information asymmetry, financial risk, agent cost, and proprietary information may affect a firm's choice between public debt and private placements. We find that as the size of firm increases, the probability of choosing a private placement declines significantly. The age of the firm, however, is not a significant factor affecting the firm's choice between public and privately-placed bond. The coefficients on the firm's leverage and non-investment grade dummy are significantly positive, meaning firms with high financial risk and credit risk select private placements. The findings regarding agency-related variables, PER and Tobin's Q, are somewhat complex. We find significant evidence that firms with high PER prefer private placements to public bonds, suggesting that borrowers with options to engage in asset substitution or underinvestment are more likely to choose private placements. The coefficient of Tobin's Q is negative, but not significant, which weakly support the hold-up hypothesis. When we construct an interaction term on the Tobin's Q with a non-investment rating dummy, however, the Tobin's Q interaction term becomes positive and significant. Thus, high Tobin's Q firms with a speculative rating are significantly more likely to choose a private placement, regardless of the potential hold-up problems. The ratio of R&D to sales, proxy for proprietary information, is positively significant. This result can be interpreted as evidence in favor of a role for proprietary information in the debt sourcing decision process for these firms.

• Journal of Intelligence and Information Systems
• /
• v.25 no.4
• /
• pp.53-65
• /
• 2019

Object tracking is one of important steps to achieve video-based surveillance systems. Object tracking is considered as an essential task similar to object detection and recognition. In order to perform object tracking, various machine learning methods (e.g., least-squares, perceptron and support vector machine) can be applied for different designs of tracking systems. In general, generative methods (e.g., principal component analysis) were utilized due to its simplicity and effectiveness. However, the generative methods were only focused on modeling the target object. Due to this limitation, discriminative methods (e.g., binary classification) were adopted to distinguish the target object and the background. Among the machine learning methods for binary classification, total error rate minimization can be used as one of successful machine learning methods for binary classification. The total error rate minimization can achieve a global minimum due to a quadratic approximation to a step function while other methods (e.g., support vector machine) seek local minima using nonlinear functions (e.g., hinge loss function). Due to this quadratic approximation, the total error rate minimization could obtain appropriate properties in solving optimization problems for binary classification. However, this total error rate minimization was based on a batch mode setting. The batch mode setting can be limited to several applications under offline learning. Due to limited computing resources, offline learning could not handle large scale data sets. Compared to offline learning, online learning can update its solution without storing all training samples in learning process. Due to increment of large scale data sets, online learning becomes one of essential properties for various applications. Since object tracking needs to handle data samples in real time, online learning based total error rate minimization methods are necessary to efficiently address object tracking problems. Due to the need of the online learning, an online learning based total error rate minimization method was developed. However, an approximately reweighted technique was developed. Although the approximation technique is utilized, this online version of the total error rate minimization could achieve good performances in biometric applications. However, this method is assumed that the total error rate minimization can be asymptotically achieved when only the number of training samples is infinite. Although there is the assumption to achieve the total error rate minimization, the approximation issue can continuously accumulate learning errors according to increment of training samples. Due to this reason, the approximated online learning solution can then lead a wrong solution. The wrong solution can make significant errors when it is applied to surveillance systems. In this paper, we propose an exactly reweighted technique to recursively update the solution of the total error rate minimization in online learning manner. Compared to the approximately reweighted online total error rate minimization, an exactly reweighted online total error rate minimization is achieved. The proposed exact online learning method based on the total error rate minimization is then applied to object tracking problems. In our object tracking system, particle filtering is adopted. In particle filtering, our observation model is consisted of both generative and discriminative methods to leverage the advantages between generative and discriminative properties. In our experiments, our proposed object tracking system achieves promising performances on 8 public video sequences over competing object tracking systems. The paired t-test is also reported to evaluate its quality of the results. Our proposed online learning method can be extended under the deep learning architecture which can cover the shallow and deep networks. Moreover, online learning methods, that need the exact reweighting process, can use our proposed reweighting technique. In addition to object tracking, the proposed online learning method can be easily applied to object detection and recognition. Therefore, our proposed methods can contribute to online learning community and object tracking, detection and recognition communities.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.14 no.5
• /
• pp.187-200
• /
• 2019

The main purpose of this study is to investigate the effects of motivation of the employment in Korea with gender, nationality, motivation of studying in Korea, major satisfaction and Korean proficiency level of foreign students who are studying in Korea. The second purpose is to analyze the current factors, to leverage educational management and to make and support some policy of Minister of Education for international students in order to promote utilization of employment of the students in Korea during 4 years of studying. This paper is used by IBM SPSS Statistics 24 Version for data analysis. As a result of the analysis, the average of students in Southeast Asia, Central Asia and South and North America Africa was higher than Japan and China in terms of motivation of employment in Korea. First, the external motivation to study in Korea has affected TOPIK with positive influence. Second, in the relationship between motivation to study in Korea and the majors satisfaction, the higher the internal motivation of study, the higher the majors' satisfaction level. Third, in the relationship between motivation to study in Korea and motivation of the employment in Korea, internal motivation to study has a positive effect on motivation of the employment. As internal motivation increases, grade of the motivation of the employment increases. Fourth, the relationship between major satisfaction and employment showed positive (+) effect. In other words, the higher the major satisfaction, the higher the motivation of the employment. Fifth, TOPIK has a negative effect on motivation of the employment. It means that external motivation was the main factor that positively influenced TOPIK and internal motivation was also main factors that positively influenced both major satisfaction and motivation of the employment in Korea. Sixth, when the internal motivation has an effect on motivation of Korea employment, the higher the major satisfaction as the parameter, the higher the motivation of Korea employment. Therefore, it will be helpful to understand the meaning of studying motivation and major satisfaction of international students, and to be used as basic data on education policies of universities and governments supporting the career and employment for international students.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.151-176
• /
• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.17 no.2
• /
• pp.115-128
• /
• 2022

This research aims to analyze of the Effect of Army Start-up Support Program (hereinafter, ASSP) on the level of discharged or scheduled to be discharged soldier's satisfaction of their military service. In addition, this paper also seeks to elaborate on how those Army-supported programs, such as Start-up competitions, mentoring, camp, and school, can increase the level of military service satisfaction. By participating in those programs, service members can leverage their time in the military to make opportunity for their future career rather than consider it as a career break, increasing their military service satisfaction. Finally, on the basis of findings, this paper advocates for expanding Service Members startup Support Program of government agencies and municipalities and enhancing younger population's individual capabilities through ASSP. This research used ASSPs, such as Army Start-up competitions, mentoring, camp, and school, as independent variables. For controlled variables, this paper takes demographic elements such as status and career path of the participants. Our empirical analysis reveals that ASSP has a direct impact on the military service satisfaction, supported by the statistics from the hierarchical regression analysis. However, the research also suggests that individual' military service satisfaction from ASSP may differ from one another in accordance with the controlled variables such as status and career of the participants. This paper proves that ASSP can play a substantial role in enhancing service members' capabilities during their time in military and that Army fosters talent and connects itself to the nation and society. In addition, this research could contribute to increasing employment rate of and expanding Start-up support program of government agencies and municipalities for younger population by providing empirical results which advocates the latter's necessity.