• Electronics and Telecommunications Trends
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• v.13 no.6 s.54
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• pp.182-190
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• 1998

진보와 함께 기업들이 지식의 가치를 인식하면서 지식을 창출, 공유 그리고 활용하는 "지식경영"이라는 새로운 패러다임이 다음 세기 초를 주도할 새로운 경영 방식으로 각광받고 있다. 지식경영이란 조직과 그 구성원들 속에 내재해 있는 지식의 가치를 인식하고, 이를 기업 전체 차원의 자산으로 구체화시켜 관리, 공유, 활용하려는 의도에서 비롯된 폭 넓은 의미의 경영 방식이다. 본 고에서는 "지식경영"의 중요성을 인식하고, 선진 기업들이 "지식경영"을 성공적으로 수행하는데 있어 그 요인들은 무엇이며 그 중에서도 "정보관리 전문가"에 대해 논하고자 한다. 그리고 정보 관리자가 정보화, 지식화 라고 하는 시대의 절대적인 흐름에 어떻게 대처해야 하는가를 모색해 보고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.347-350
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• 2011

본 논문에서는 시스템 사고를 이용한 이러닝 운영 관리를 제안하였다. 효과적이고 체계적인 이러닝 운영관리는 사용자 만족과 밀접한 관계를 가진다. 사용자 만족을 통한 학습 성과의 극대화, 유지보수 노력의 절감, 생산성 향상 및 품질수준의 향상을 위해서는 시스템 사고의 도입이 필요하다. 일반적인 학습 전 단계, 학습 중 단계, 학습 후 단계로 관리되는 운영 프로세스 관리를 확장하여 자산관리, 보안관리, 백업관리, 장애관리, 업무 연속성 관리, 변경관리, 교직원 및 학습자를 포함한 이해관계자 관리 등을 포함하여 동태적인 운영관리가 필요하다. 특히 이러닝 운영관리가 교육성과에 미치는 영향이 크므로 운영관리에 대한 다각적인 접근이 필요하며 운영상의 활발한 정보 공유로 지속적인 서비스 품질 향상이 이루어져야 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.163-164
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• 2009

오늘날 기업들은 비즈니스의 가치체인(Value Chain)의 변화로 회사의 해체와 재통합 기업의 글로벌화, 비즈니스의 아웃소싱, 산업영역의 붕괴가 빈번하게 이루어지고 있는 것이 현재기업의 현실이다. 따라서 기업은 비용을 절감하고 매출을 높이며 운영자본 및 고정자산의 지출을 최소화하기 위하여 전세계 자기업의 시스템을 통합관리하려 하고 있다. 이를 충족하기 위하여 델 사는 웹 시스템을 구축하여 정보기술측면의 유연성을 확보하게 되었다. 본 논문에서는 프리웨어 프레임워크인 알바티스, 스프링프레임웍, EJB를 UML툴로 프로그램을 설계하고, JSTL, X-INTERNET로 표현함으로써 네트워크사용량, 컴포넌트개발, 프로그램배포, 오프라인작업의 가능성, 대량데이터의 처리, 웹서비스 이용, 프로그램의 설치, 유저인터페이스, 유연성, 확장성, 보안성을 측정하여 프로젝트 특성상의 적합성을 검증하려 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.683-686
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• 2008

기업이 ERP시스템을 도입 후 영업, 구매, 자산, 생산 등에서 통합 전표가 발생되어 기업의 흐름이 매우 빨라졌다. 그러나 기업이 e-Business 환경하에 있으나 회계 프로세스의 중요한 부분을 차지하는 회계증빙과 회계업무 관련 부분이 여전히 수작업 처리하는 부분이 상당히 많이 존재하고 있다. 본 연구 과제는 회계 증빙 처리와, 업무프로세스를 디지털화하는데 성공한 D 사의 사례를 소개하고 이를 이론적으로 분석하였다. D 사는 법인카드 프로세스, 스캔증빙 프로세스, 업무처리프로세스를 디지털화하였고 Paperless, 업무처리 간소화, 시간 절약, 경비 절감, 시공간의 제약 등 비용과 불필요한 업무를 없애는 데 성공하였다. 본 연구 과제를 통해 타 기업들에게도 혁신의 동인과 반향을 제시하고자 한다.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.17-34
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• 2022

With rapid advancements taking place in the Fourth Industrial Revolution, human-robot interactions have been garnering increasing attention. Robots are being actively adopted in building systems and facilities. In this study, we developed robot-friendly building certification indicators. Because these indicators were being developed for the first time, we focused only on commercial buildings. We conducted exploratory research using methodologies such as focus group interviews and the analytic hierarchy process. First, the concept of the robot-friendly building was defined through focus group interviews, and the requirements were categorized by the appropriateness of operating facilities and systems and the appropriateness of architectural and robot operating systems and networks. Next, the relative importance of the evaluation items (23 items in total) was calculated using the analytic hierarchy process. Their average score of the marks was 4.4, and the minimum and maximum were 2.0 and 11.3, respectively. This study is significant because we collected the basic data necessary to develop a one-of-its-kind evaluation system for certifying the robot-friendliness of buildings using scientific methods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1639-1650
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• 2013

Road pavement management is an important activity that affects to national economy, movement and safety of people, and also demands huge amount of budget. Therefore, its management strategy must be established under objective information. In addition, decision support system that produces the management strategy needs to consider practical benefits from various aspects. Considering these aspects, this paper aimed to develop a customized Korean life cycle cost analysis model estimating various effects on road users and socio-environmental costs based on pavement condition. The suggested LCCA model focused on Korean national highway, and tried to adopt a national guideline recommended by Korean government for securing credibility of estimation results. In the development processes, some of the suggestions that do not fit well in the situations of pavement management field were added, altered, or partially modified. These attempts to develop customized asset management system would be an important step to break away from passive attitudes relying on ready-made software, but also to improve awareness about the social benefits from the better maintenance strategy.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.352-361
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• 2013

The purpose of this study is to analyse the impact of macroeconomic and non-macroeconomic forces on the management performance of the air transport firms and offer the useful information to the managers. To conduct the regression analysis, eight macroeconomic and non-macroeconomic variables were selected individually as an independent variable. Macroeconomic variables were the return of corporate bond, West Texas Intermediate, the unemployment rate, the money supply, the trade balance, the won to USD exchange rate, the consumer price index and the index of industrial production. And non-macroeconomic variables were Taiwan earthquake, the Asian economic crisis, the 911 terrorist attacks in the US, the Iraq war, Beijing Olympic, the outbreak of a swine flu epidemic, the 1st presidential election and the 2nd presidential election. And ROA was selected as a dependent variable. As the result of analysis, it was found that the changing rates of won to USD exchange rate and consumer price index affected the changing rate of ROA significantly. And also as the result of analysing the impact of two significant macroeconomic variables and eight non-macroeconomic variables on the changing rate of ROA, it was found that the Asian economic crisis and the outbreak of a swine flu epidemic had a negative impact on it. Therefore managers should take note of a change in macroeconomic and non-macroeconomic variables carefully to improve the management performance.

• Management & Information Systems Review
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• v.28 no.3
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• pp.161-189
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• 2009

The sub-prime crisis led to the collapse of US investment banks which were considered highly competitive during the Asian Financial Crisis. The event gave us a lesson on importance of the financial supervision. Additionally concerns rise over the fact that the role model of the Capital Market Law, created for the purpose of developing the capital market, is the US investment banks. This paper investigates if the prudential regulations, among them especially the capital regulation, are able to prevent the risk the arises from Korean financial firms operating investment bank business. The current capital requirement regulation, Net Capital Ratio(NCR), is not sufficient, because it's nature of being a ratio makes the NCR ineffective when assets and liabilities are concurrently rising. We also verified the internal model which measured the market risk, by comparing the US investment and Korean banks' diversification effect. The result of the test is that it is difficult to conclude the internal model has a critical defect. This paper's contribution is that it is not sufficient use only the capital regulation in supervising financial markets.

• Management & Information Systems Review
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• v.28 no.1
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• pp.71-97
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• 2009

In this study, I compare the ability of alternative accounting method for employee stock option to reflect firm value using the Ohlson's(1995) valuation model for 200 firms. The each methods, I compare are employee stock option expense recognition based on the K-GAAP disclosures, and asset recognition at the grant date based on the SFAS No. 123 Exposure Draft: Accounting for stock-based compensation. The model include: (1) a model that uses reported earnings, equity book value, and compensation expense based on the K-GAAP disclosures; (2) a model that uses pro-forma earnings, equity book value and adds a measure of the unrecognized asset arising form granting of employee stock options. Finding form estimating equations that the K-GAAP method for calculating compensation has no explanatory power, and the SFAS No.123 Draft Exposure method for arising asset and fair value compensation better captures than market's perception of the economic impact of stock options on firm values. However, the correlation of employee stock option compensation expense is positive. These results suggest that incentive benefits derived from employee stock option plans outweigh the cost associated with plan. In addition, I couldn't find evidence that company in KOSDAQ that have high growth potential benefit more from employee stock option plan compared to lager, more mature firm in SEC.