• Journal of the Korean Society for information Management
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• v.25 no.1
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• pp.99-127
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• 2008

National competence is based on the quality of university education, which is determined by the competitiveness of academia, research and information, IMD reported that Singapore, #2 country in national competence index, topped in quality of university education. Meanwhile Korea's current national knowledge infrastructure project lacks comprehensive coordination at a governmental level and has been conducted in a rather sporadic manner, without any consideration on the overall analysis of knowledge information resources. Consequently, a disproportionate amount of attention was devoted to collecting general information resources, while neglecting rare, hard-to-collect sources with historic, academic, and/or cultural values. This study proposes to build an academic resource management system to fully supervise academic resources at least, among national knowledge information resources which is a national asset, and also to allocate budget and cultivate new information building projects based on overall analysis on academic resources. In other words, there is a need for a management system to implement efficient linkage, distribution and utilization of academic resources and, to that end, we need to build an academic resource management system at a national level, maximizing the benefits from the knowledge society that we live in.

• The Journal of Information Systems
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• v.12 no.2
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• pp.57-72
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• 2003

The purpose of this paper is to propose the modeling of multiagent based SCM and implement the prototype in the Internet environment. SCM process follows the supply chain operations reference (SCOR) model which has been suggested by Supply Chain Counsil. SCOR model has been positioned to become the industry standard for describing and improving operational process in SCM. Five basic processes, plan, source, matte, deliver and return are defined in the SCOR model, through which a company establishes its supply chain competitive objectives. A supply chain is a world wide network of suppliers, factories, warehouses, distribution centers and retailers through which raw materials are acquired, transformed or manufactured and delivered to customers by autonomous or semiautonomous process. With the pressure from the higher standard of customer compliance, a frequent model change, product complexity and globalization, the combination of supply chain process with an advanced infrastructure in terms of multiagent systems have been highly required. Since SCM is fundamentally concerned with coherence among multiple decision makers, a multiagent framework based on explicit communication between constituent agents such as suppliers, manufacturers, and distributors is a natural choice. Multiagent framework is defined to perform different activities within a supply chain. Dynamic and changing functions of supply chain can be dealt with multi-agent by cooperating with other agents. In the areas of inventory management, remote diagnostics, communications with field workers, order fulfillment including tracking and monitoring, stock visibility, real-time shop floor data collection, asset tracking and warehousing, customer-centric supply chain can be applied and implemented utilizing multiagent. In this paper, for the order processing event between the buyer and seller relationship, multiagent were defined corresponding to the SCOR process. A prototype system was developed and implemented on the actual TCP/IP environment for the purchase order processing event. The implementation result assures that multiagent based SCM enhances the speed, visibility, proactiveness and responsiveness of activities in the supply chain.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.3
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• pp.5-17
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• 2017

This study extends research into whether disclosure of corporate and financial information is associated with firms' costs of equity capital. This study sets out to examine empirically the determinants of corporate disclosure in the annual reports of 37 largest and most liquid firms listed on Kazakhstan Stock Exchange (KASE) in Kazakhstan. It also reports the results of the association between company-specific characteristics and disclosure of the sample companies. Based on the analysis of existing empirical research, the disclosure index has been constructed and regression analysis of the influence of the disclosure index on the cost of equity capital has been conducted. The obtained results show that the received findings correlate with foreign empirical studies, and the disclosure index in this sample has a negative impact on the cost of equity capital. Using cost of equity capital estimates derived from capital asset pricing model, we find that firms with higher levels of financial transparency are associated with significantly lower costs of equity capital. Economic theory assumes that by increasing the level of corporate reporting, firms not only increase their stock market liquidity, but also decrease the investors' estimation risk, arising from uncertainty about future returns and payout distributions. The results show that firms on the Kazakhstan market can reduce their cost of equity capital by increasing the level of their voluntary corporate disclosures.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.349-360
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• 2020

The study aims to empirically examine the determinants of bank margins from Pakistan, an emerging South Asian economy. To elucidate the importance of the Pakistani banking sector, secondary data has been used, which was extracted from the annual accounts of twenty-four Pakistani scheduled commercial banks (20 conventional, four full-fledged Islamic) over a sample period of 2006 to 2017. The factors identified in the dealership model and the subsequent empirical developments in the dealership model categorized as bank-specific, diversification, regulatory, and industry concentration are analyzed by applying the most-common linear dynamic panel-data estimator, the Generalized Method of Moments (GMM) estimator, developed by Arellano and Bond (1991). The findings reveal that, among the bank-specific variables, funding cost, credit risk, managerial efficiency, market share, and operating cost are significant predictors of bank margins. For diversification variables employed in the study, both variables including net non-interest income and asset diversity are as well significant predictors of bank margins. It is also found that the market concentration variable proxied by the Herfindahl-Hirschman Index (HHI) is significantly predicting bank margins. Subsequently, one of the regulatory variables, the opportunity cost of holding reserves, and one bank-specific variable, the degree of risk aversion, are insignificant in the model.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.99-112
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• 2016

Asymmetric jump-diffusion models are effectively used to model the dynamic behavior of asset prices with abrupt asymmetric upward and downward changes. However, the estimation of their extension to the multivariate asymmetric jump-diffusion model has been hampered by the analytically intractable likelihood function. This article confronts the problem using a data augmentation method and proposes a new Bayesian method for a multivariate asymmetric Laplace jump-diffusion model. Unlike the previous models, the proposed model is rich enough to incorporate all possible correlated jumps as well as mention individual and common jumps. The proposed model and methodology are illustrated with a simulation study and applied to daily returns for the KOSPI, S&P500, and Nikkei225 indices data from January 2005 to September 2015.

• Journal of the Korean Data and Information Science Society
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• v.22 no.2
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• pp.137-148
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• 2011

In this paper, we systematically investigate regional differences of the dead due to injuries in cities, towns and counties about transportation accidents, suicides and fall accidents, which have recently been an important issue of health problems in Korea, The data are from the Annual Report on the Cause of Death Statistics in Korea in 2008. They include the deaths over the age 19 from transportation accidents, suicides and fall accidents with the criterion of the International Statistical Classification of Diseases. Poisson HGLM is applied to estimate the mortality rate under the assumption that the number of deaths follow a Poisson distribution, by considering regions as random effects and by adjusting age, sex and standardized residence tax as fixed effects. Using the results of random effects prediction, the regional differences in cities, counties and towns are marked in disease mapping. The results showed that there were significant regional differences of mortality rates for transportation accidents and suicides, but no significant differences for fall accidents.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.9-17
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• 2021

With the advancement of big data analysis, artificial intelligence, machine learning, etc., data analytics technology has developed to help with optimal decision-making. However, in certain areas, the lack of data restricts the use of these techniques. For example, real estate related data often have a long release cycle because of its recent release or being a non-liquid asset. In order to overcome these limitations, we studied the scalability of the existing time series through the TimeGAN model. A total of 45 time series related to weekly real estate data were collected within the period of 2012 to 2021, and a total of 15 final time series were selected by considering the correlation between the time series. As a result of data expansion through the TimeGAN model for the 15 time series, it was found that the statistical distribution between the real data and the extended data was similar through the PCA and t-SNE visualization algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1384-1389
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• 2020

Although the fintech industry is developing rapidly around the world, the domestic development situation is rather slow compared to the speed. Therefore, the future development direction can be set by analyzing the current status of the fintech industry in order to suggest the direction of development in the domestic fintech industry. The main services provided by companies belonging to the domestic fintech industry are in the areas of remittance settlement, financial investment, asset management, crowdfunding, P2P finance, overseas remittance, fintech SI, insurtech, virtual currency, security, and authentication. It is divided into. This study identifies the main technologies used in the service and grasps the current domestic status. In addition, it analyzes the distribution of workers by each service. This study is expected to play an important role in the development of the financial industry through technical analysis of fintech companies.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.307-318
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• 2021

The objective of this study is to analyze the performance of Islamic banks with the Maqashid Shariah approach. The analysis technique used is the Simple Additive Weighting Method (SAW) to solve multi-attribute decision problems. The sampling technique used was purposive sampling while the data came from the annual report of each bank. The results showed that the BTPN Shariah (BTPNS) and Bank Muamalat Indonesia (BMI) are ranked first and second respectively on the Maqashid Shariah Index (MSI) with values of 0.265429 and 0.237110 respectively. Panin Dubai Shariah Bank (PDSB) ranked third with an MSI value of 0.180733, followed by BCA Shariah which ranked fourth with an MSI value of 0.151299. BRI Shariah ranked fifth with an MSI value of 0.128606, followed by BNI Shariah which ranked sixth with an MSI value of 0.124661. Bank Mega Shariah ranked last with an MSI value of 0.087068. Furthermore, there is a relationship (correlation) between ROE, ROA, and OEOI and MSI since each data has a value of 0.000, 0.000, 0.050, and 0.001 respectively, which is smaller than the significance value of 0.05. On the other hand, NPF, TPF, and Asset Growth Rates do not correlate with the MSI since each data has a value of 0.051, 0.252, and 0.215 respectively which is greater than the significance value of 0.05.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.38.2-38.2
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• 2020

Horizon Run 5 (HR5) is a cosmological hydrodynamical simulation which captures the properties of the Universe on a Gpc scale while achieving a resolution of 1 kpc. This enormous dynamic range allows us to simultaneously capture the physics of the cosmic web on very large scales and account for the formation and evolution of dwarf galaxies on much smaller scales. Inside the simulation box. we zoom-in on a high-resolution cuboid region with a volume of 1049 × 114 × 114 Mpc3. The subgrid physics chosen to model galaxy formation includes radiative heating/cooling, reionization, star formation, supernova feedback, chemical evolution tracking the enrichment of oxygen and iron, the growth of supermassive black holes and feedback from active galactic nuclei (AGN) in the form of a dual jet-heating mode. For this simulation we implemented a hybrid MPI-OpenMP version of the RAMSES code, specifically targeted for modern many-core many thread parallel architectures. For the post-processing, we extended the Friends-of-Friend (FoF) algorithm and developed a new galaxy finder to analyse the large outputs of HR5. The simulation successfully reproduces many observations, such as the cosmic star formation history, connectivity of galaxy distribution and stellar mass functions. The simulation also indicates that hydrodynamical effects on small scales impact galaxy clustering up to very large scales near and beyond the baryonic acoustic oscillation (BAO) scale. Hence, caution should be taken when using that scale as a cosmic standard ruler: one needs to carefully understand the corresponding biases. The simulation is expected to be an invaluable asset for the interpretation of upcoming deep surveys of the Universe.