• Title/Summary/Keyword: Key Performance Indicators

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A New Traffic Congestion Detection and Quantification Method Based on Comprehensive Fuzzy Assessment in VANET

  • Rui, Lanlan;Zhang, Yao;Huang, Haoqiu;Qiu, Xuesong
    • 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.

Mathematical Modelling and Simulation of CO2 Removal from Natural Gas Using Hollow Fibre Membrane Modules

  • Gu, Boram
    • 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.

Assessing the Performance of CMIP5 GCMs for Various Climatic Elements and Indicators over the Southeast US (다양한 기후요소와 지표에 대한 CMIP5 GCMs 모델 성능 평가 -미국 남동부 지역을 대상으로-)

  • Hwang, Syewoon
    • 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.

Factor Analysis on the Performance of Hospital Customer Relationship Management (HCRM) System (병원고객관계관리시스템의 성과요인 분석)

  • Chun, Je-Ran
    • 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.

Application of the Balanced Scorecard for the Performance Measurement in Health-care Organization (의료기관에서의 Balanced Scorecard를 이용한 성과측정)

  • Chun, Je-Ran
    • 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.

Development and Application of a Performance Prediction Model for Home Care Nursing Based on a Balanced Scorecard using the Bayesian Belief Network (Bayesian Belief Network 활용한 균형성과표 기반 가정간호사업 성과예측모델 구축 및 적용)

  • Noh, Wonjung;Seomun, GyeongAe
    • 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.

A DEA-Based Portfolio Model for Performance Management of Online Games (DEA 기반 온라인 게임 성과 관리 포트폴리오 모형)

  • Chun, Hoon;Lee, Hakyeon
    • 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.

Development of a system dynamics computer model to simulate the operational effects of the new environmental technology certification system (환경신기술인증제도의 운영효과를 모의하기 위한 시스템다이내믹스 컴퓨터 모델의 개발)

  • Kim, Taeyoung;Park, Suwan
    • 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.

A Study on Current Energy Consumption and Recycling at Public Wastewater Treatment Plants in Korea (국내 공공하수도 시설의 에너지 사용 및 자원화실태 조사연구)

  • Park, Seungho;Kim, Byongjoo;Bae, Jae-Ho;Lee, Cheol Mo;Kim, Eung-Ho
    • Journal of Korean Society of Water and Wastewater
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    • v.21 no.5
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    • pp.539-549
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    • 2007
  • To establish effective and prompt measures for energy conservation in public wastewater treatment plants in Korea, energy consumption rates in 233 utilities in 9 provinces and 7 metropolitan cities are investigated and compared to the rest of the world. Mean load factor for wastewater treatment utilities is 74.9% and those for influent pumps and aeration blowers are 56.2% and 61.0%, respectively. Mean electrical energy usages as the key performance indicators are $0.243kWh/m^3$ for overall sewage treatments and 2.07 kWh per unit kg BOD removal. Digester gas as one of major byproducts in the process amounts to $382,000m^3/day$ nationwide. While major part of the digester gas is used for sludge heating, only 7.3% of the gas is utilized for electricity generation. Both efficiencies for BOD removal and digestion gas generation are considerably lower than those in USA and EU utilities due to low concentration of organic material in influent wastewater. Such low energy regeneration, in turn, results in significantly higher energy consumption in Korean plants, compared to that in USA and EU ones.

The Impact of TPM Activities on the Business Performance of Small and Medium Sized Enterprises (TPM활동이 중소기업의 경영성과에 미치는 영향)

  • Lee, Jae-Sik
    • Management & Information Systems Review
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    • v.30 no.4
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    • pp.415-440
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    • 2011
  • Purposes of this paper are to find out the implementation strategy of TPM activities for SMEs through the analysis which examine the relationship between key activity factors and business performance. TPM activity has been playing a important role to strengthen the competitive power of the enterprises through the optimization of equipment management and maintenance. This study has been conducted using the data collected from 124 SMEs propelling TPM activity. By analyses of the questionnaires, empirical results shows that TPM activities has positive effect on business performance. The contribution of this study is that it provides a conceptual framework and empirical evidence of the causal relationship between key activity factors and business performance. The result of this study can be used for selection of the performance measurement indicators for target achievement in TPM activity. And it will contribute for objectivity of activity performance in case of displaying measurement indicator showing the performance of TPM activity.

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