• Knowledge Management Research
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• v.7 no.2
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• pp.69-96
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• 2006

The purpose of this study is to find success factors of knowledge management in Korean firms, confirm them empirically, and verify their relative importance in terms of company size and industry type. The major studies on the knowledge management were deliberately selected and interpretively analyzed to find the success factors of Korean firms. As a result of the analysis, five success factors(top management's will, evaluation reward, organizational culture, knowledge management system, organizational structure) have been found. The empirical researches to make certain whether the above five factors derived are actually true or not have been separately performed by using questionnaire method. Based on the data collected, it is found that all five factors are significant. The degree of relative importance among the success factors of knowledge management in Korean firms has been found as: (i)top management's will, (ii)organizational culture, (iii)evaluation-reward, (iv)knowledge management system, (v)organizational structure. In company size, large firm's degree of relative importance among the success factors are: (i)top management's will, (ii)organizational culture, (iii)evaluation-reward, (iv)knowledge management system, (v) organizational structure. And medium-small firm's degree of relative importance among the success factors of knowledge management in Korean firms has been found as: (i)top management's will, (ii)organizational culture, (iii) evaluation-reward, (iv)knowledge management system, (v)organizational structure. Finally, in type of industry, manufactural firm's degree of relative importance among the success factors of knowledge management in Korean firms has been found as: (i)top management's will, (ii)organizational culture, (iii)evaluation-reward, (iv)knowledge management system, (v)organizational structure. And non-manufactural firm's degree of relative importance among the success factors of knowledge management in Korean firms are: (i)top management's will, (ii)organizational culture, (iii)evaluation-reward, (iv)knowledge management system, (v)organizational structure.

• Journal of the Korean Society for information Management
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• v.20 no.4 s.50
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• pp.67-90
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• 2003

When we introduce knowledge management system in our organization, first of all, we need to change the way of motivating the members so as to voluntarily activate knowledge sharing activity For this, it is very important to establish fair evaluation and adequate reward system about knowledge contribution. In this study, I hypothesized a desirable evaluation and reward model for knowledge contribution on the basis of analysis of documents and cases concerning them in domestic enterprises and R&D institutes that adopted knowledge management. Also, I took a survey to analyze the response of the members of KAERI (Korea Atomic Energy Research Institute) about the evaluation and reward for knowledge contribution. I expect that the analysis results of this study can be applied very usefully in R&B institutes that want to introduce knowledge management.

• Journal of Korean Elementary Science Education
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• v.21 no.1
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• pp.101-109
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• 2002

A cooperative teaming has been taken to consolidate the autonomous motivation of students and to develop a desirable attitude in a mutual cooperative atmosphere. Some studies on the reward effect showed that the reward after the evaluation, in the processes of cooperative learning, worked on students' learning motive directly, and the group reward was effective in learning attitude and the individual reward in academic achievement, respectively. Assuming that the group reward and the individual reward are organized and applied as a complex reward, the effects of rewards will appear, this study examined the effect of the complex reward on academic achievement and teaming attitude. For this study. 2 classes were randomly selected out of a elementary school in Gwangju and the teaming unit was based on chapter 4「The structure and function of plants」 in the 5-1 elementary Science textbook. This research has been done for 4 weeks after the students learned STAD for 8 weeks previously. The learning attitude was examined in pre and post tests, and the academic achievement was inspected twice at 2-week intervals after the pre test. The results were analysized by the SAS program In the case of academic achievement, both groups showed a significant improvement(p<.05). The experimental group showed no significant improvement in the first test, compared with the control group(p>.05), but after 4 weeks, it showed a significant improvement in the second test, compared with the control group(p<.05). From this result, it is identified that the reward should be done for a long time and the individual reward of the complex reward is successful in improving academic achievement. However, in the case of learning attitude, there was no meaningful difference in both groups(p>.05). But the control group showed a significant improvement, compared with the experimental group(p<.05). According to this result, it is indicated that the group reward only is more effective in improving learning attitude and complex reward can decrease the individual competition in experimental group.

• Knowledge Management Research
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• v.5 no.1
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• pp.83-99
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• 2004

This research aims to verify individual and organizational factors that will affect knowledge sharing, especially in research & development organizations with a premise that knowledge sharing is one of the most important factors of successful knowledge management. Many factors which are supposed to affect knowledge sharing arc empirically investigated in this research : individual factors ((1)self esteem (2)expected contribution), organizational factors ((3)top management's will, (4)accessibility of knowledge management system (5)validity of evaluation & reward knowledge sharing, (6)trust, (7)open communication). As a result, it is found that 'expected contribution' among individual factors and 'open communication' and 'validity of evaluation & reward' among organizational factors are highly correlated with knowledge sharing. These findings suggest that enhancement of perceived expected contribution among employees and building cultures of open communication and effective evaluation & reward system for knowledge sharing will contribute to activation of knowledge sharing in the research and development organizations.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.169-178
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• 2019

Due to the characteristics of an ad hoc network without a control center, self-organization, and flexible topology, the trust evaluation of the nodes in the network is extremely difficult. Based on the analysis of ad hoc networks and the blockchain technology, a blockchain-based node-level trust evaluation model is proposed. The concepts of the node trust degree of the HASH list on the blockchain and the perfect reward and punishment mechanism are adopted to construct the node trust evaluation model of the ad hoc network. According to the needs of different applications the network security level can be dynamically adjusted through changes in the trust threshold. The simulation experiments demonstrate that ad-hoc on-demand distance vector(AODV) Routing protocol based on this model of multicast-AODV(MAODV) routing protocol shows a significant improvement in security compared with the traditional AODV and on-demand multipath distance vector(AOMDV) routing protocols.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.166-169
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• 2003

Reinforcement learning if a kind of machine learning. It aims to adapt an agent to a given environment with a clue to a reward and a penalty. Q-learning [8] that is a representative reinforcement learning system treats a reward and a penalty at the same time. There is a problem how to decide an appropriate reward and penalty values. We know the Penalty Avoiding Rational Policy Making algorithm (PARP) [4] and the Penalty Avoiding Profit Sharing (PAPS) [2] as reinforcement learning systems to treat a reward and a penalty independently. though PAPS is a descendant algorithm of PARP, both PARP and PAPS tend to learn a local optimal policy. To overcome it, ion this paper, we propose the Multi Best method (MB) that is PAPS with the multi-start method[5]. MB selects the best policy in several policies that are learned by PAPS agents. By applying PS, PAPS and MB to a soccer game environment based on the SoccerBots[9], we show that MB is the best solution for the soccer game environment.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.11-19
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• 2024

Multi-agent systems can be utilized in various real-world cooperative environments such as battlefield engagements and unmanned transport vehicles. In the context of battlefield engagements, where dense reward design faces challenges due to limited domain knowledge, it is crucial to consider situations that are learned through explicit sparse rewards. This paper explores the collaborative potential among allied agents in a battlefield scenario. Utilizing the Multi-Robot Warehouse Environment(RWARE) as a sparse reward environment, we define analogous problems and establish evaluation criteria. Constructing a learning environment with the QMIX algorithm from the reinforcement learning library Ray RLlib, we enhance the Agent Network of QMIX and integrate Random Network Distillation(RND). This enables the extraction of patterns and temporal features from partial observations of agents, confirming the potential for improving the acquisition of sparse reward experiences through intrinsic rewards.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.4
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• pp.275-286
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• 2020

The study explores factors that affect the performance of responsibility accounting at public universities in Vietnam. The study conducted a survey of 130, out of 154 public universities in Vietnam and uses regression analysis methods. The results identify eight groups of factors affecting the performance of responsibility accounting at these establishments of higher education: Division of the organization into responsibility centers, Estimation and Reality, Cost and income allocation, University autonomy, Management decentralization, Estimation, Reward, and Report. Costs and income allocation for responsibility centers, university autonomy, and the division of universities into responsibility centers are shown to significantly affect the performance of public universities in Vietnam. The results show that the performance of responsibility accounting at public universities in Vietnam is influenced by decentralization of management, division of the organization into responsibility centers, reward, cost and income allocation, estimation, evaluation of the results achieved between the estimation compared with reality, release of reports and university autonomy. Among the factors, cost and income allocation, university autonomy, division of the organization into responsibility centers, reward and evaluation of results achieved between estimation and reality have strong impacts. The study findings also indicate that the school council does not affect responsibility accounting at these universities.

• International Journal of Contents
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• v.6 no.4
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• pp.30-34
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• 2010

Effective job scheduling scheme is a crucial part of complex heterogeneous distributed systems. Gang scheduling is a scheduling algorithm for grid systems that schedules related grid jobs to run simultaneously on servers in different local sites. In this paper, we address grid jobs (gangs) schedule modeling using Stochastic reward nets (SRNs), which is concerned for static and dynamic scheduling policies. SRN is an extension of Stochastic Petri Net (SPN) and provides compact modeling facilities for system analysis. Threshold queue is adopted to smooth the variations of performance measures. System throughput and response time are compared and analyzed by giving reward measures in SRNs.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.4
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• pp.1-14
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• 1995

A new stochastic Petri nets model, called Stochastic Petri Nets Reward Model(SPNRM) is used for modeling and evaluating the performance of telecommunication protocols. We have developed a SPNRM of the TDX-10 Internal protocol, which has a packet data exchange facility between DCEs, Especially a timer and retransmission handling model is presented for error control of the data transmission phase. The stochastic Petri nets package(SPNP), a software package for SPNRM used in this paper, has been used to generate numerical results by analytical-numerical method rather than simulation. From the steady state solution of the net, it is possible to calculate automatically the performance measure of the protocol medeled with both end-to-end and link-by-link method, which are the mean response times and the throughputs.