• Title/Summary/Keyword: learning organization

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Employee Performance Distributions: Analysis of Motivation, Organizational Learning, Compensation and Organizational Commitment

  • Astri Ayu PURWATI;William WILLIAM;Muhammad Luthfi HAMZAH;Rosyidi HAMZAH
    • Journal of Distribution Science
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    • v.21 no.4
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    • pp.57-67
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    • 2023
  • Purpose: This study aims to measuring the employee performance distributions of company in using relationship analysis between motivation, organization learning, compensation, and Organizational commitment. Research design and methodology: The study was conducted on 102 employees as a sample. Data were analyzed using Path Analysis in Structural Equation Modeling (SEM) with PLS. Results: the research result has shown that motivation and compensation have a positive significant effect on organizational commitment. While organizational learning has negative and insignificant effect on organizational commitment. Furthermore, motivation, organizational learning and motivation have no significant effect on employee performance distribution and organizational commitment has a positive significant effect on employee performance distribution. Results for mediating effect has obtained where organizational commitment mediates the effect of motivation and compensation on employee performance distribution, but cannot mediate the effect of organizational learning on employee performance distribution. Conclusion: Organizational commitment in this study can make employees feel comfortable and attached to the company so that employees can perform well to achieve company goals. Motivation and compensation are driving factors in improving employee performance distribution and will achieved if employees have good organizational commitment. In this study, organizational learning is not an important factor in improving employee performance distribution.

Development of Retirement Prediction Model based on Work Life Profile Using Machine Learning Method (기계 학습 방법을 이용한 직장 생활 프로파일 기반의 퇴직 예측 모델 개발)

  • Yun, You-Dong;Lee, Seol-Hwa;Ji, Hye-Sung;Lim, Heui-Seok
    • The Journal of Korean Association of Computer Education
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    • v.20 no.1
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    • pp.87-97
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    • 2017
  • Recently, much research has been done on the turnover and retirement intentions of the organization members as many companies recognize the negative impact of the human resource outflow on the organization. However, most of the studies are conducted in the form of questionnaires, and there is still a lack of studies on the turnover and retirement intentions based on the work life data. In this study, we analyzed the factors affecting the retirement of employees based on the work life profile, and created a retirement prediction model using the machine learning method. As a result, we could identify various factors that were not covered in previous researches. In addition, we have established a basis for research that can provide a solution for the problem of human resource outflow by generating a good performance retirement prediction model.

Detecting Insider Threat Based on Machine Learning: Anomaly Detection Using RNN Autoencoder (기계학습 기반 내부자위협 탐지기술: RNN Autoencoder를 이용한 비정상행위 탐지)

  • Ha, Dong-wook;Kang, Ki-tae;Ryu, Yeonseung
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.27 no.4
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    • pp.763-773
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    • 2017
  • In recent years, personal information leakage and technology leakage accidents are frequently occurring. According to the survey, the most important part of this spill is the 'insider' within the organization, and the leakage of technology by insiders is considered to be an increasingly important issue because it causes huge damage to the organization. In this paper, we try to learn the normal behavior of employees using machine learning to prevent insider threats, and to investigate how to detect abnormal behavior. Experiments on the detection of abnormal behavior by implementing an Autoencoder composed of Recurrent Neural Network suitable for learning time series data among the neural network models were conducted and the validity of this method was verified.

Machine Learning in Media Industry :Focusing on Content Value Evaluation and Production Development (기계학습의 미디어 산업 적용 :콘텐츠 평가 및 제작 자원을 중심으로)

  • Kwon, Shin-Hye;Park, Kyung-Woo;Chang, Byeng-Chul;Chang, Byeng-Hee
    • The Journal of the Korea Contents Association
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    • v.19 no.7
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    • pp.526-537
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    • 2019
  • This study researched the effect of application systems for media industry by using machine learning method focusing on industrial organization theory. First, for applying the system successfully, formation of sympathy about needs is required. The introduction of machine learning can bring change in each stage of value chain especially, decision making process of investment and production process. In investment side, objective performance prediction data can enhance efficiency, and content diversity can decrease with concentrated investment phenomenon to secured content by the system. In production side, if the system support to make creators decrease simple repeat works, production efficiency will increase.

An Empirical Study on Critical Success Factors in Implementing the Web-Based Distance Learning System : In Case of Public Organization. (사이버교육 효과의 영향요인에 관한 실증적 연구: 공공조직을 중심으로)

  • 정해용;김상훈
    • The Journal of Information Systems
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    • v.11 no.1
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    • pp.51-74
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    • 2002
  • The purpose of this study is to empirically investigate critical success factors for effective implementation of web-based distance learning system. First of all, four critical success factors are theoretically derived from reviewing previous research. They are: (1) learner-related factor including the variables such as teaming ability, learning attitude, and attending motivation, (2) environmental factor including the variables of physical and mental support for learners, (3) instructional design factor represented by one variable, the degree of appropriateness of learning contents, and (4) the factor concerning the level of self-directed learning readiness embracing the variables such as curiosity for learning, openness towards challenge of learning and affection for learning. Subsequently, the relationships between these four critical success factors and the degree of learning satisfaction are empirically investigated. The data for empirical analysis of the research are collected from 1,020 respondents who have already passed the web-based distance learning courses which have been implemented in Information and Communication Officials Training Institute. Out of 1,020 responded questionnaires, 875 data were available for statistical analyses. The main results of this study are as follows. Firstly, the most important factor for successful implementation of the web-based distance learning system is shown to be the instructional design factor, and in the next place, the self-directed learning readiness factor, the environmental factor and the learner-related one in sequence. Secondly, additional analysis of the variables included in the instructional design factor shows that availability of practical information and knowledge is the most influencing variable, and next, interesting composition of contents, reasonable learning amount, optimal level of instruction, and understandable explanation are significantly important in the descending order. Lastly, among learning motivators, strong intention of acquiring business knowledges and skills is found to be the most important satisfier in the web-based distance learning. The theoretical contribution of this study is to derive a comprehensive model of critical success factors for implementing the web-based distance learning system. And, the practical implication of this study is to propose efficient and effective guidelines for developing and operating the web-based distance learning system in the various kinds of organizations.

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The Effect of Employee's Self Leadership of Construction Company on Organization Citizenship Behaviour and Organizational Trust through Psychology Empowerment (중소 ICT건설기업 조직원의 셀프리더십이 심리적 임파워먼트 통하여 조직시민행동과 조직신뢰에 미치는 영향)

  • Choi, JaeYoung;Hwang, Changyu
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.15 no.3
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    • pp.207-223
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    • 2019
  • This study aims to explore the casual relation between construction company employees' Self-Leadership and two variables: Organization Citizenship Behaviour and Organizational Trust through Psychology Empowerment. To explain in details, this study examines how the independent variable, Self Leadership, with its behavior-focused, natural reward and constructive thought pattern strategies, affects the dependent variable, Organization Citizenship Behavior and Organizational Trust through the intervening variable, Psychology Empowerment. A survey was conducted on current employees of construction companies in metropolitan areas to empirically examine the research model. The result of study hypothesis on Self-Leadership is as follows; first, Self-Leadership showed a positive effect on Psychology Empowerment, Organization Citizenship Behaviour and Organizational Trust. Second, Psychology Empowerment showed a positive effect on Organization Citizenship Behaviour. Third, Psychology Empowerment showed a positive effect on Organizational Trust. The capacity of individuals is critical when it comes to competitiveness of construction companies. When employees willingly participate in building trust within the company, the work place will become more and more constructive; based on trust, efficiency will increase because people from different processes can work together and performance will also improve even when project managers are absent because others could help their role instead, thus driving more efficient human resource management to the company. To conclude, a company's vision can be spread wide and far when their employees engage themselves in Learning Organization with Self Leadership. They will also be satisfied with their work through improving interpersonal relationship at work.

A study on the standardization strategy for building of learning data set for machine learning applications (기계학습 활용을 위한 학습 데이터세트 구축 표준화 방안에 관한 연구)

  • Choi, JungYul
    • Journal of Digital Convergence
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    • v.16 no.10
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    • pp.205-212
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    • 2018
  • With the development of high performance CPU / GPU, artificial intelligence algorithms such as deep neural networks, and a large amount of data, machine learning has been extended to various applications. In particular, a large amount of data collected from the Internet of Things, social network services, web pages, and public data is accelerating the use of machine learning. Learning data sets for machine learning exist in various formats according to application fields and data types, and thus it is difficult to effectively process data and apply them to machine learning. Therefore, this paper studied a method for building a learning data set for machine learning in accordance with standardized procedures. This paper first analyzes the requirement of learning data set according to problem types and data types. Based on the analysis, this paper presents the reference model to build learning data set for machine learning applications. This paper presents the target standardization organization and a standard development strategy for building learning data set.

A Study on the Introduction of Professional Learning Communities for Continuing Education of Librarians (사서 계속교육을 위한 전문가학습공동체 도입에 관한 연구)

  • Ji Hei Kang;Byoung-Moon So;Youngmi Jung
    • Journal of the Korean Society for Library and Information Science
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    • v.58 no.1
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    • pp.181-198
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    • 2024
  • As the teaching and learning paradigm shifts, the demand for informal learning is increasing. In this study, we reviewed related literature and analyzed cases of operating professional learning communities in order to apply professional learning communities to librarianship education and training programs. Seven operational cases of professional learning communities, both domestic and foreign, within the field of librarianship and other fields were selected. The organizational structure, operational format and method, learning content, and support systems were analyzed. Through this analysis, the concept of a librarian learning community was defined, and implications for organizing and operating a librarian learning community were derived from the spontaneity and multi-layeredness of composition, diversity of learning community operation formats, and fieldality of learning content. As a support system for the smooth operation and activation of the librarian learning communities continuity of program operation by the operating organization, support and cooperation from affiliated organizations, education and training programs, platform establishment and operation, and dissemination and feedback of results for activation were presented.

Circuit Placement in Arbitrarily-Shaped Region Using Self-Organization (자율조직을 이용한 임의의 모양을 갖는 영역에서의 회로배치)

  • Kim, Sung-Soo;Kyung, Chong-Min
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.7
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    • pp.140-145
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    • 1989
  • In this paper, we present an effective circuit placement method called SOAP (self-organization assisted placement) for rectilinear or arbitrarily-shaped region arised form the layout of ASIC (application specific integrated circuit). Self-organization is a learning algorithm for neural networks proposed by [1] which adjusts weights of synapses connected to neurons such that topologically close neurons are sensitive to inputs that are physically similar. In SOAP, we obtain a good circuit placement result in arbitrarily-shaped region by replacing the block of circuit and the position (x, y coordinates) of the block with the neuron and the weight pair of synapses connected to the neuron, respectively. This method can also be extended to the circuit placement over the nonplanar surface.

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Knowledge Management Activity and Performance of University Hospital Employees (대학병원직원의 지식경영활동과 성과에 관한 연구)

  • Lee, Hyun-Sook
    • Health Policy and Management
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    • v.24 no.3
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    • pp.291-300
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    • 2014
  • Background: The efficient knowledge management in hospital organization is generally known as the important activities relevant to employees' knowledge sharing behavior and work performance. This research examined factors affecting employees' knowledge sharing behavior and work performance in top 4 university hospitals. This study is based on individual factors such as incentives, reciprocity, behavioral control, and subjective norms. Also, there are organizational factors such as CEO support, learning climate, IT system, rewards system, and trust. Methods: Data was collected from employees who are working at 3 hospitals university in Seoul and 1 university hospital in Gyeonggi-Do through the self-administered questionnaires. A total of 779 questionnaires were analyzed by PASW SPSS ver. 18.0. (SPSS Inc., Chicago, IL, USA). Results: The significant variables affecting knowledge sharing behavior are behavioral control (in individual factor) and CEO, IT system, and trust (in organization factor). Also the significant variables affecting work performance are incentives, reciprocity, subjective norms, and behavioral control (in individual factor) and CEO support, IT system, reward system, and trust (in organization factor). Conclusion: The personality and organization characteristics factors is important to improve knowledge sharing behavior and work performance of hospital employees. Therefore, to make more efficient knowledge management is to build and system knowledge sharing culture, system, and leadership and to develop practical strategies.