• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.195-196
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• 2019

It It is not easy to reduce the operation costs at a time when it is hard to expect increase sales due to growing economic uncertainties. For logistics centers, which need to keeps their competitive advantage in the market by raising service levels at low cost, it is essential to drastically improve service levels at low cost. This study suggests that KPI (Key Performance Indicator) analysis should determine whether efficient logistics operation is being performed for the entire process of the logistics operation system. And also we suggests that each item should be set up, measured, and improved so that customer satisfaction can be increased based on performance indicators.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.288-299
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• 2020

The gender mainstreaming strategy was formulated at the 4th UN World Conference on Women in Beijing in 1995 and quickly spread globally. In the Korean film industry, the gender ratio of the key creative roles - directors, writers, and producers is very unbalanced. The staffs are divided into woman and man departments and there is a gap in wages between woman and man workers. Gender equality in the Korean film industry require the adoption of a gender mainstreaming strategy that involves independent agenda setting and key performance indicators.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.41-60
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• 2018

Recently, road traffic congestion is becoming a serious urban phenomenon, leading to massive adverse impacts on the ecology and economy. Therefore, solving this problem has drawn public attention throughout the world. One new promising solution is to take full advantage of vehicular ad hoc networks (VANETs). In this study, we propose a new traffic congestion detection and quantification method based on vehicle clustering and fuzzy assessment in VANET environment. To enhance real-time performance, this method collects traffic information by vehicle clustering. The average speed, road density, and average stop delay are selected as the characteristic parameters for traffic state identification. We use a comprehensive fuzzy assessment based on the three indicators to determine the road congestion condition. Simulation results show that the proposed method can precisely reflect the road condition and is more accurate and stable compared to existing algorithms.

• Korean Chemical Engineering Research
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• v.60 no.1
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• pp.51-61
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• 2022

Gas separation via hollow fibre membrane modules (HFMM) is deemed to be a promising technology for natural gas sweetening, particularly for lowering the level of carbon dioxide (CO₂) in natural gas, which can cause various problems during transportation and process operation. Separation performance via HFMM is affected by membrane properties, module specifications and operating conditions. In this study, a mathematical model for HFMM is developed, which can be used to assess the effects of the aforementioned variables on separation performance. Appropriate boundary conditions are imposed to resolve steady-state values of permeate variables and incorporated in the model equations via an iterative numerical procedure. The developed model is proven to be reliable via model validation against experimental data in the literature. Also, the model is capable of capturing axial variations of process variables as well as predicting key performance indicators. It can be extended to simulate a large-scale plant and identify an optimal process design and operating conditions for improved separation efficiency and reduced cost.

• Journal of Korea Water Resources Association
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• v.47 no.11
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• pp.1039-1050
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• 2014

The goal of this study is to demonstrate the diversity of model performance for various climatic elements and indicators. We evaluated the skills of the most advanced 17 General Circulation Models (GCMs) i.e., CMIP5 (Climate Model Inter-comparison project, phase 5) climate models in reproducing retrospective climatology from 1950 to 2000 over the Southeast US for the key climatic elements important in the hydrological and agricultural perspectives (i.e., precipitation, maximum and minimum temperature, and wind speed). The biases of raw CMIP5 GCMs were estimated for 16 different climatic indicators that imply mean climatology, temporal variability, extreme frequency, etc. using a grid-based observational dataset as reference. Based on the error (RMSE) and correlation (R) of GCM outputs, the error-based GCM ranks were assigned on average over the indicators. Overall, the GCMs showed much better accuracy in representing mean climatology of temperature comparing to other elements whereas few GCM showed acceptable skills for precipitation. It was also found that the model skills and ranks would be substantially different by the climatic elements, error statistics applied for evaluation, and indicators as well. This study presents significance of GCM uncertainty and the needs of considering rational strategies for climate model evaluation and selection.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.79-84
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• 2021

The objective of this paper is to find out the factors for the performance of the Hospital Customer Relationship Management (HCRM) system. Furthermore, the relationships between these factors have been analyzed. In order to analyze the performance of the HCRM system, factor analysis with several Key Performance Indicators (KPIs) was conducted. And also multiple regression analysis and Chi-square test were executed. In this study, several hypotheses were derived to analyze the relationships between factors of performance of HCRM system. These hypotheses were tested by using the Structural Equation Model (SEM). As the result of this study, we discovered the HCRM-Infrastructure has positive effects on the HCRM-Performance. And the HCRM-Performance has also positive influences on the hospital management performance. On the basis of the research result, we proposed some suggestions and guidelines for the successful implementation and improvement of HCRM system.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.254-264
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• 2009

The purpose of this study was to develop a performance measurement factor of Balanced Scorecard(BSC) for health-care organization. We did also the research to evaluate the validity and reliability of these indicators. Fifty six health-care organizations are participated in a survey questionnaires. This questionnaires consists of 53-questions, which are the performance evaluation indicators designed by researcher, which are based on the Norton and Kaplan's BSC-Framework. Exploratory and confirmatory factor analysis was carried out and Analytical Hierarchy Process (AHP) was applied to analyze the weight and significances of each factor. Factor analysis of the BSC resulted in 11 major measurement factors (Eigenvalue >1.0). The AHP analysis showed the list of the hospital BSC measurement factors and its KPI(Key Performance Indicator) weighted by its significance priorities. The recommendable degree of reliability and validity of these BSC factors suggests that these factors are adequate for performance measurements of the health-care organizations in Korea.

• Journal of Korean Academy of Nursing
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• v.45 no.3
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• pp.429-438
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• 2015

Purpose: This study was conducted to develop key performance indicators (KPIs) for home care nursing (HCN) based on a balanced scorecard, and to construct a performance prediction model of strategic objectives using the Bayesian Belief Network (BBN). Methods: This methodological study included four steps: establishment of KPIs, performance prediction modeling, development of a performance prediction model using BBN, and simulation of a suggested nursing management strategy. An HCN expert group and a staff group participated. The content validity index was analyzed using STATA 13.0, and BBN was analyzed using HUGIN 8.0. Results: We generated a list of KPIs composed of 4 perspectives, 10 strategic objectives, and 31 KPIs. In the validity test of the performance prediction model, the factor with the greatest variance for increasing profit was maximum cost reduction of HCN services. The factor with the smallest variance for increasing profit was a minimum image improvement for HCN. During sensitivity analysis, the probability of the expert group did not affect the sensitivity. Furthermore, simulation of a 10% image improvement predicted the most effective way to increase profit. Conclusion: KPIs of HCN can estimate financial and non-financial performance. The performance prediction model for HCN will be useful to improve performance.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.260-270
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• 2013

This paper proposes a strategic portfolio model for managing performance of online games. The portfolio matrix is composed of two dimensions: financial performance and non-financial performance. Financial performance is measured by the conventional measure, average revenue per user (ARPU). In terms of non-financial performance, five non-financial key performance indicators (KPIs) that have been widely used in the online game industry are utilized: RU (Register User), VU (Visiting User), TS (Time Spent), ACU (Average Current User), MCU (Maximum Current User). Data envelopment analysis (DEA) is then employed to produce a single performance measure aggregating the five KPIs. DEA is a linear programming model for measuring the relative efficiency of decision making unit (DMUs) with multiple inputs and outputs. This study employs DEA as a tool for multiple criteria decision making (MCDM), in particular, the pure output model without inputs. Combining the two types of performance produces the online game portfolio matrix with four quadrants: Dark Horse, Stop Loss, Jack Pot, Luxury Goods. A case study of 39 online games provided by company 'N' is provided. The proposed portfolio model is expected to be fruitfully used for strategic decision making of online game companies.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.2
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• pp.105-114
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• 2020

In this study, based on the System Dynamics (SD) methodology, the interrelationship between the factors inherent in the operation of the New Technology Certification System (NTCS) in Korea was identified by a causal map containing a feedback loop mechanism in connection with 'new technology development investment', 'commercialization of new technology', and 'sales by new technology'. This conceptualized causal map was applied to the simulation of the operations of the New Excellent Technology and Environmental Technology Verification System (NET&ETV) run by the Ministry of Environment among various NTCSs in Korea. A SD computer simulation model was developed to analyze and predict the operational performance of the NET&ETV in terms of key performance indices such as 'sales by new technology'. Using this model, we predicted the future operational status the NET&ETV and found a policy leverage that greatly influences the operation of the NET&ETV. Also the sensitivity of the key indicators to changes in the external variables in the model was analyzed to find policy leverage.