• Title/Summary/Keyword: Asset Quality Classification

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Exploring Corporate Knowledge Management Cases Based on Business Function Oriented Knowledge Asset Classification Schema (비즈니스 기능 중심 지식자산 분류체계에 따른 기업 지식관리 사례 탐색)

  • Kim, In-Sook;Choi, Byoung-Gu;Lee, Hee-Seok
    • Information Systems Review
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    • v.3 no.2
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    • pp.245-260
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    • 2001
  • While past knowledge management researches have focused on conceptualization and strategic implications, knowledge asset researches attempt to provide practical guidelines for companies. However, each research classifies knowledge asset from its own perspective, and thus it is not a trivial task to leverage consistent and inclusive criteria in managing corporate knowledge asset. The objective of this paper is to develop a knowledge asset classification schema on the basis of the three business functions: customer relationship management, product innovation, and infrastructure management. To demonstrate the feasibility of our schema, it has been applied to 9 Korean corporations. Knowledge assets are evaluated according to core capabilities, which are main drivers of sustainable competitive advantages. The results of case study show that the leveraged classification schema reflects current knowledge asset management and characteristics of corporations. Our finding is that most top-quality knowledge management corporations are likely to develop well-balanced knowledge asset.

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Comparison of Machine Learning Analysis on Predictive Factors of Children's Planning-Organizing Executive Function by Income Level: Through Home Environment Quality and Wealth Factors

  • Lim, Hye-Kyung;Kim, Hyun-Ok;Park, Hae-Seon
    • Journal of People, Plants, and Environment
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    • v.24 no.6
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    • pp.651-662
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    • 2021
  • Background and objective: This study identifies whether children's planning-organizing executive function can be significantly classified and predicted by home environment quality and wealth factors. Methods: For empirical analysis, we used the data collected from the 10th Panel Study on Korean Children in 2017. Using machine learning tools such as support vector machine (SVM) and random forest (RF), we evaluated the accuracy of the model in which home environment factors classify and predict children's planning-organizing executive functions, and extract the relative importance of variables that determine these executive functions by income group. Results: First, SVM analysis shows that home environment quality and wealth factors show high accuracy in classification and prediction in all three groups. Second, RF analysis shows that estate had the highest predictive power in the high-income group, followed by income, asset, learning, reinforcement, and emotional environment. In the middle-income group, emotional environment showed the highest score, followed by estate, asset, reinforcement, and income. In the low-income group, estate showed the highest score, followed by income, asset, learning, reinforcement, and emotional environment. Conclusion: This study confirmed that home environment quality and wealth factors are significant factors in predicting children's planning-organizing executive functions.

An Empirical Analysis about the usefulness of Internal Control Information on Corporate Soundness Assessment (기업건전성평가에 미치는 내부통제정보의 유용성에 관한 실증분석 연구)

  • Yoo, Kil-Hyun;Kim, Dae-Lyong
    • Journal of Digital Convergence
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    • v.14 no.8
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    • pp.163-175
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    • 2016
  • The purpose of this study is to provide an efficient internal control system formation incentives for company and to confirm empirically usefulness of the internal accounting control system for financial institutions by analyzing whether the internal control vulnerabilities of companies related significantly to the classification and assessment of soundness of financial institutions. Empirical analysis covered KOSPI, KOSDAQ listed companies and unlisted companies with more than 100 billion won of assets which have trading performance with "K" financial institution from 2008 until 2013. Whereas non-internal control vulnerability reporting companies by the internal control of financial reporting received average credit rating of BBB on average, reporting companies received CCC rating. And statistically significantly, non-reporting companies are classified as "normal" and reporting companies are classified as "precautionary loan" when it comes to asset quality classification rating. Therefore, reported information of internal control vulnerability reduced the credibility of the financial data, which causes low credit ratings for companies and suggests financial institutions save additional allowance for asset insolvency prevention and require high interest rates. It is a major contribution of this study that vulnerability reporting of internal control in accordance with the internal control of financial reporting can be used as information significant for the evaluation of financial institutions on corporate soundness.

The Application of Reconfigurable Software Systems (재구성 가능한 소프트웨어 시스템의 적용)

  • Choi, Hanyong
    • Journal of Digital Convergence
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    • v.19 no.8
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    • pp.219-224
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    • 2021
  • The convergence of various industries has removed the boundaries of software application fields and reduced the restrictions on convergence fields. Software requirements are diversified and they want to reconfigure software requirements in a fast cycle. Since various changes in requirements have to be accepted technically, research on methodologies and standards to increase the efficiency of software productivity and methods for standardizing and producing software are needed. In this study, we studied how the reusability and complexity of the software asset reconfiguration system appeared according to the developer's characteristics and environment to utilize the assets optimized in previous studies. At this time, we measured how the change in complexity according to the usability and asset composition method that appears according to the developer's characteristics appears, but there is a limit to the collected data, so it is necessary to secure the quality of the measured value through continuous data collection. In addition, an intelligent system application plan is needed to supplement the problem of context classification in the use stage of complex assets.

A Study on the Analysis of Current Issues and the Operation Plan of News Media Asset Management System in Korean Broadcasting Companies: the Case Study of KBS Digital Newsroom (방송사 보도영상관리시스템 운영 현황분석과 개선안 연구 - KBS 디지털뉴스룸 사례를 중심으로 -)

  • Choi, Hyo-jin;Park, Choonwon;Kim, Sooyoung;Song, Jeonga;Park, Yeajin;Shin, Bongseung;Ji, Sunho;Sun, Sangwon
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.33 no.3
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    • pp.123-155
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    • 2022
  • This study focuses on the management of the news production system in broadcasting companies. This paper concentrates on the process of data registration and metadata management in order to examine whether the currently produced news can have value as a 'public record' in the long term, and whether reliable and accurate information is preserved. In addition, the user experience in the current system is analyzed through in-depth interviews with Ingest Managers, Editors, and Archive Managers, who are closely related to metadata creation compared to other members of the its News Department. Finally, a sustainable metadata quality management method is sought to increase the value of news footage as a 'public record'. In this study, these points can be found out: the metadata of the news agency footage is input manually according to the user's will or working style, that is, the user-friendly metadata input system is insufficient. Accordingly, it can be seen that the quality of the metadata of the news video continues to deteriorate. As an alternative to overcome this, it is found that work flow improvement, system improvement, classification system and metadata improvement plan, etc. are definitely necessary in the short and long term.

Morpho-GAN: Unsupervised Learning of Data with High Morphology using Generative Adversarial Networks (Morpho-GAN: Generative Adversarial Networks를 사용하여 높은 형태론 데이터에 대한 비지도학습)

  • Abduazimov, Azamat;Jo, GeunSik
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2020.01a
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    • pp.11-14
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    • 2020
  • The importance of data in the development of deep learning is very high. Data with high morphological features are usually utilized in the domains where careful lens calibrations are needed by a human to capture those data. Synthesis of high morphological data for that domain can be a great asset to improve the classification accuracy of systems in the field. Unsupervised learning can be employed for this task. Generating photo-realistic objects of interest has been massively studied after Generative Adversarial Network (GAN) was introduced. In this paper, we propose Morpho-GAN, a method that unifies several GAN techniques to generate quality data of high morphology. Our method introduces a new suitable training objective in the discriminator of GAN to synthesize images that follow the distribution of the original dataset. The results demonstrate that the proposed method can generate plausible data as good as other modern baseline models while taking a less complex during training.

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The Linkage Strategies Between Productivity Metrics and Financial Accounting Metrics in TPM and PAC Activities (TPM, PAC 활동에서 생산성지표와 재무회계 지표의 연계방안 전략)

  • Choi, Sungwoon
    • Journal of the Korea Safety Management & Science
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    • v.15 no.3
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    • pp.151-161
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    • 2013
  • This paper proposes a strategic model of linkage between productivity metrics and financial accounting metrics to properly evaluate the financial effect of TPM activities and the business performance. This linkage strategy provides a connection tool for clear communication between factory-level and headquarters that the metrics proposed by this paper ultimately improves a quality of support from the management by receiving the factors required for productivity activities in the practical field. This factor includes such as equipment, raw materials and labors. Here, we propose that chain reaction models using break down structure of productivity metrics and financial metrics enhance the knowledge sharing of KPI (Key Performance Indicator) which generally tend to create oversimplified communication between management in headquarters and employees in the practical fields. The productivity metrics include OEE(Overall Equipment Effectiveness) of TPM (Total Productive Maintenance), OLE (Overall Labor Effectiveness) of PAC(Performance and Analysis and Control) activities, and OYE (Overall Yield Effectiveness) of TMM(Total Material Management) activities. The financial accounting metrics include ROE(Return on Equity), ROA(Return on Asset), and AVR(Added-Value Rate). The suggested chain reaction model selects the financial metrics as initial stage and branch down until final stage of productivity metrics. When demand exceeds supply, an ideal speed rate, the lean OEE strategy can be initially applied to reduce the gap between the demand and supply, then apply variable costing to estimate correct amount of operating profit. In addition, the paper presents a new type of model for linkage between financial accounting metrics including CAPEX(Capital Expenditure), OPEX(Operating Expenditure), EVA(Economic Added Value), DCL(Degree of Combined Leverage), and TPM productivity activities including AM(Autonomous Maintenance), PM(Preventive Maintenance), MP(Maintenance Prevention) and QM(Quality Maintenance). In order to support the evidence of proposed linkage strategy, a case analysis on 52 projects from national TPM contest from 2011 to 2012 is analyzed. The case presents the classification of CAPEX and OPEX activities from TPM, and proposes the correct implementation of financial effect for TPM projects.