• International Journal of Quality Innovation
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• v.3 no.2
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• pp.84-92
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• 2002

In this Paper, We propose new performance measure model in Logistic Industry. New model has been learned by key points of PZB model and advanced structure of MBNQA which has cause measure points and effect measure points. The Structure of new performance measure model is Cubic Model which is reflected with time. We try to verify this model apply advance logistic company.

• Korean Journal of Construction Engineering and Management
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• v.5 no.4 s.20
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• pp.79-86
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• 2004

One of the most difficult tasks in pavement management information systems is establishing the links between performance measures of a structure and the design and construction inputs. In-situ pavement performance can be considered a response variable to many project input variables, such as design, construction, and traffic loading effects. If we are to fully understand the component of pavement performance and specify the inputs through design and construction specifications to achieve that performance we must develop quantitative relationship between input and response variables through a scientific, fully integrated Pavement Performance Analysis System (PPAS). Hence, the objective of this study is to design a database model required for developing an effective database template that will allow analysis of pavement performance measures based on design and construction information linked by location. In order to select the most appropriate database model, a conceptual database model (Entity Relationship Model) and dimensional model, which is believed to be the most effective modeling technique for data warehouse project, are designed and compared. It is believed that other state highway agencies could adopt the proposed design strategy for implementing a PPAS at the discretion of the state highway agencies.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.665-677
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• 2022

Purpose: The purpose of this study is to analyze the current status and investigate relevant indicators so that R&D performance evaluation suitable for government-funded research institutes can proceed. A suitable performance evaluation model was presented based on the surveyed indicators. Based on the presented performance evaluation model, the importance was analyzed to calculate the weight for each indicator of the performance evaluation model. Methods: The method applied in this study presented a performance evaluation model based on the organizational performance evaluation cases of advanced overseas countries. By using the AHP(Analytic Hierarchy Process) technique, the weight of each indicator of the performance evaluation model was studied. Results: As a result of examining the indicators necessary for the evaluation model, focusing on overseas cases, 13 evaluation items were derived. A weight was calculated for the importance of the study results. And the scientific/technical research results showed the highest excellence. Conclusion: Key indicators of performance evaluation suitable for government-funded research institutes were derived and presented through detailed modeling in three stages. A realistic model that can objectively evaluate the performance of government-funded research institutes was proposed using the AHP technique.

• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.310-314
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• 2023

The purpose of this study is to predict the remaining capacity of lithium-ion batteries and evaluate their performance using five artificial intelligence models, including linear regression analysis, decision tree, random forest, neural network, and ensemble model. We is in the study, measured Excel data from the CS2 lithium-ion battery was used, and the prediction accuracy of the model was measured using evaluation indicators such as mean square error, mean absolute error, coefficient of determination, and root mean square error. As a result of this study, the Root Mean Square Error(RMSE) of the linear regression model was 0.045, the decision tree model was 0.038, the random forest model was 0.034, the neural network model was 0.032, and the ensemble model was 0.030. The ensemble model had the best prediction performance, with the neural network model taking second place. The decision tree model and random forest model also performed quite well, and the linear regression model showed poor prediction performance compared to other models. Therefore, through this study, ensemble models and neural network models are most suitable for predicting the remaining capacity of lithium-ion batteries, and decision tree and random forest models also showed good performance. Linear regression models showed relatively poor predictive performance. Therefore, it was concluded that it is appropriate to prioritize ensemble models and neural network models in order to improve the efficiency of battery management and energy systems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.423-428
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• 2010

In the initial design phase of superscalar microprocessors, a performance model is necessary. A theoretic performance model is very useful since performance for various architecture parameters can be obtained by simply computing equations, without repeating simulations, Previous studies established theoretic performance models using the relation between the instruction window size and the issue width, with the penalties due to branch mispredictions and cache misses. However, the study was intended for unlimited number of functional units, which is insufficient for the real case application. This paper proposes a superscalar microprocessor theoretical performance model which also works for the limited functional units. To enhance the accuracy of our limited functional unit model, instruction dependency rates are employed. By using trace-driven data of SPEC 2000 integer programs as input, this paper shows that the theoretically computed performance of superscalar microprocessor with limited number of functional units is quite similar to the measured performance.

• International Journal of Quality Innovation
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• v.6 no.3
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• pp.19-37
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• 2005

It is generally accepted that leadership is the foundation for creation of a company's business results. However, empirical evidence is lacking. This paper examines the relationship between leadership and key performance results based on a Return on Leadership Model. The model links Denison's four leadership traits to people results, customer results, and ultimately key performance results. Further specified, the model is a structural equation model with nine latent variables, each measured by a set of indicators, observed by survey questions. To validate the model, an empirical study was conducted, and 379 managers from medium-sized and large companies in Denmark participated. The estimation of the model shows that the model structure explains return on leadership very well, and the findings support the developed model. We are able to quantify the relationships from leadership to people results, customer results and key performance results and, in this way, the data presented here provide evidence that leadership is linked to key performance results. Several results and applications of the model are shown. The findings provide new knowledge about how leadership can be linked to performance, and how excellent leadership creates key performance results.

• Journal of Information Technology Applications and Management
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• v.20 no.3
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• pp.143-167
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• 2013

The main propose of this research is to examine the performances in ERP introduced enterprises by utilizing BSC model proposed by Kaplan and Norton [1992], to realize this goals, a theoretical review on ERP, BSC, and other related issues is performed in advance, accordingly, research model was generated. In conceptual model analysis, we focused on casual relationships among four performance measurement indicators after introduction of ERP proposed by Kaplan and Norton [2000]. To test the model, structural equation modeling is employed to analyze data collected from 164 enterprises which have introduced ERP for more than 1 year. Survey respondents were confined within the representatives of each enterprise's ERP. Hypotheses proposed in our research are tested by covariance structure model, results are listed as follow : First, learning and growth performance is significant factors for improving both internal process performance and customer performance; second, process performance has a positive impact on customer performance third, despite that customer performance is positively related to financial performance, no direct relationship is found between internal process performance and financial performance, an indirect relationship is built through intermediate medium of customer performance. Based upon these results, we discuss implications at the latter part of paper. Meanwhile, we also provide research limitations, and future research in the final section.

• International Journal of Quality Innovation
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• v.7 no.1
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• pp.112-127
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• 2006

How to measure Quality Performance (QP) or excellence performance in organizations is very important for improving the quality of an organization's products and services. This paper takes Quality Function Deployment (QFD) as a useful tool to identify the key characteristics of quality performance and measure the influence factors on quality performance. Most national quality awards provide a framework of the criteria to show the essential elements of an organization's quality performance and get the Quality Performance Score (QPS) by self-assessment using the criteria. By means of these criteria, especially, the criteria of China Quality Award (CQA), a measurable indicator system for quality performance is set up. A four-phase QFD model of assessment for quality performance is developed. This QFD model not only presents the most important efforts for the deployment of the measurable indicators of quality performance, but also takes great advantage of evaluating the quality performance and obtaining the quality performance score. The measurable indicator hierarchy of quality performance is formed and its implementation method for assessment quality performance is described in this paper.

• Korea Journal of Hospital Management
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• v.4 no.2
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• pp.162-191
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• 1999

This study was conducted to establish finance performance evaluation model for physicians in each clinical department, by using factors which determines financial outcome(performance) in each clinical department The ultimate aim of study is to develop effective performance-based pay system for physicians. The system, by motivating physicians, should increase their productivity. To do so, it is critical to establish finance performance evaluation model to achieve final goal of this study. 232 private hospitals were chosen from 693 hospitals which were subject to hospital survey by the Korea Institute of Health Services Management and their revenue and expense-related data during 1997 were collected. By adopting multiple regression method, the study shows that the evaluation model for each clinical department was statistically significant. The study suggest the effective performance-based pay system based on financial performance of each clinical department. The pay system includes the level of compensation, the way of how to allocate profits to each department, and criteria whether the compensation should provide or not. In conclusion, the study has following implications. First, the study suggest finance performance evaluation model for each clinical department Second, the study suggest guidelines and plans to establish qualitative measure of financial performance in each clinical department. Third, the study suggest that adopting performance-based pay for physicians could be impetus to achieve organizational goal by motivating them with fair compensation.

• Journal of the Korean GEO-environmental Society
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• v.16 no.5
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• pp.13-25
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• 2015

This paper proposes an extended model evaluation method that considers not only the model performance but also the model structure and parameter uncertainties in hydrologic modeling. A simple reservoir model (SFM) and distributed kinematic wave models (KWMSS1 and KWMSS2 using topography from 250-m, 500-m, and 1-km digital elevation models) were developed and assessed by three evaluative criteria for model performance, model structural stability, and parameter identifiability. All the models provided acceptable performance in terms of a global response, but the simpler SFM and KWMSS1 could not accurately represent the local behaviors of hydrographs. Moreover, SFM and KWMSS1 were structurally unstable; their performance was sensitive to the applied objective functions. On the other hand, the most sophisticated model, KWMSS2, performed well, satisfying both global and local behaviors. KMSS2 also showed good structural stability, reproducing hydrographs regardless of the applied objective functions; however, superior parameter identifiability was not guaranteed. A number of parameter sets could result in indistinguishable hydrographs. This result indicates that while making hydrologic models complex increases its performance accuracy and reduces its structural uncertainty, the model is likely to suffer from parameter uncertainty.