• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.3
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• pp.115-122
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• 2011

The critical role played by manufacturing performance measurement systems in achieving competitive success is increasingly recognized. Developing an integrated performance measurement model is significant for strategic management. This study consist of several principal steps. Performance criteria from the literature and an questionnaire were utilized prior to building the performance model. The AHP(Analytic Hierarchy Process) is utilized to evaluate the weight of each criterion when generating the performance measurement model for Korea automobile parts manufacturing company. AHP analysis showed clear difference in the priority between 5 criteria and 24 sub-criteria in terms of manufacturing performance of Korean automobile parts manufacturing company. The result of priority evaluation in the 5 criteria of 2nd level was ranked quality, cost, delivery, employee, flexibility. And the critical sub-criteria in the 24 sub-criteria of 3rd level was ranked claim rate, process defect rate, outsourcing parts defect rate, ability to quality management innovation, claim cost, etc.

• 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.

• Communications for Statistical Applications and Methods
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• v.22 no.5
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• pp.507-518
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• 2015

It is not easy to select a linear mixed model since the main interest for model building could be different and the number of parameters in the model could not be clearly defined. In this paper, performance of conditional Akaike Information Criteria and its bias-corrected version are compared with marginal Bayesian and Akaike Information Criteria through a simulation study. The results from the simulation study indicate that bias-corrected conditional Akaike Information Criteria shows promising performance when candidate models exclude large models containing the true model, but bias-corrected one prefers over-parametrized models more intensively when a set of candidate models increases. Marginal Bayesian and Akaike Information Criteria also have some difficulty to select the true model when the design for random effects is nested.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.4
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• pp.15-20
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• 2009

The purpose of this study was to test the applicability of the HSPEXP model performance criteria for calibrating hydrologic parameters of HSPF. Baran watershed, located at Whasung city, was selected as a study watershed in this study. Input data for the HSPF model were obtained from the digital elevation map, landuse map, soil map and others. Water flow data from 1996 to 2000 was used for calibration and from 2002 to 2007 was for validation. Using the HSPEXP decision-support software, hydrology parameters were adjusted based on total volume, then low flows, storm flows, and finally seasonal flows. Suggested criteria for each model performance variables were referenced from the previous research. For the calibration period, all the HSPEXP model performance criteria were satisfied while two criteria were slightly violated for the validation period.

• Journal of Information Technology Services
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• v.4 no.2
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• pp.125-133
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• 2005

Because of paradigm change to web service, numerous institutes have been suggested supporting solution about web service, and actively developed system using web service but it is hard to find out a systematic study for web service performance enhancement. Generally, there are SOAP message processing improvement and configuration optimization of server viewpoint for web service performance enhancement. Web service performance enhancement through SOAP message processing improvement have been studied related research but configuration optimization of server is hard to find out a systematic tuning model and performance criteria. In this paper, I suggested performance testing based tuning model and criteria of configuration optimization of server viewpoint. We executed practical analysis using tuning model about web service in internet. This paper show that the proposed tuning model and performance criteria is applicable to web service performance enhancement.

• Journal of the Korean Statistical Society
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• v.36 no.3
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• pp.435-445
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• 2007

This paper addresses for the first time the use of complete data information criteria in unsupervised learning of the Naive-Bayes model. A Monte Carlo study sets a large experimental design to assess these criteria, unusual in the Bayesian network literature. The simulation results show that complete data information criteria underperforms the Bayesian information criterion (BIC) for these Bayesian networks.

• International Journal of Quality Innovation
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• v.4 no.2
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• pp.1-15
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• 2003

This paper examines the use of the EFQM Model in H.E. Institutions in the UK and offers a case study of how one University used the Excellence Model as a means to change the way it operated. It identifies and discusses the critical success factors for a university utilizing the Model, in particular Leadership (criteria 1), People Management, particularly with regard to performance evaluation (criteria 3), having key processes in place (criteria 5) and the identification of the correct key performance results for its various stakeholders (criteria 9).

• Journal of the Korea Safety Management & Science
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• v.9 no.4
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• pp.49-56
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• 2007

It is known that human factors account for 80 percent of all railway accidents. To reduce human errors must be the most efficient shortcut to railway safety. For public transportation employees like railway, the more delicate safety management should be executed in individual level. However, there are rarely efforts to improve safety performance of workers who are the subject operating the railway system. This paper develops a hierarchy model to evaluate the human safety performance in railway industry. To evaluate the model, AHP (Analytic Hierarchy Process) methodology is adopted. The hierarchy model is composed of four levels which are objective, two criteria, specific factors of criteria, and rating scales. In addition, since employees for evaluation are over 10, the pairwise comparisons for rating scales are carried out by the absolute measurement. We explore the applicability of AHP to the performance evaluation of railway safety workers by an example and also investigate the changes of alternatives that are railway employees according to the changes of human characteristic which is one of criteria.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.395-406
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• 2009

Korean government has operated EA by the act on efficient introduction of information system and operation, etc. But the evaluation system for EA and the criteria don't prepare well. Particularly, There is no model for EA performance measurement and the way is insufficient. In this study, we derived 8 areas and 17 criteria for the performance evaluation based on the Performance Reference Model of U.S FEA and Korea. And we also derived 8 areas and 10 criteria for it based on the OMB EA Assessment Framework and the EA maturity model in Korea. We propose the performance evaluation model of the five areas that consists of the business performance, customer performance, process, human resource and the technology for EA performance evaluation. To verify the model, we applied the model to three organizations and evaluated EA performance. In addition, we compared the performance result with the performance evaluation area of EA maturity model of Korea to verify the result. We also analyzed the criteria of the proposed performance evaluation model with the current EA maturity model and Performance Reference Model of Korea. As a result of the evaluation, we verified of the proposed performance evaluation model, too.

• Journal of Korean Society of Forest Science
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• v.95 no.5
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• pp.569-579
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• 2006

This study focuses on the application of multi-criteria performance measures based on the concept of equifinality to the calibration of the rainfall-runoff model TOPMODEL in a small deciduous forest catchment. The performance of each parameter set was evaluated by six performance measures, individually, and each set was identified as a behavioral or non-behavioral parameter set by a given behavioral acceptance threshold. Many behavioral parameter sets were scattered throughout the parameter space, and the range of model behavior and the sensitivity for each parameter varied considerably between the different performance measures. Sensitivity was very high in some parameters, and varied depending on the kind of performance measure as well. Compatibilities of behavioral parameter sets between different performance measures also varied, and very few parameter sets were selected to be used in making god predictions for all performance measures. Since different behavioral parameter sets with different likelihood weights were obtained for each performance measure, the decision on which performance measure to be used may be very important to achieve the goal of study. Therefore, one or more suitable performance measures should be selected depending on the environment and the goal of a study, and this may lead to decrease model uncertainty.