• International Journal of Automotive Technology
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• v.6 no.5
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• pp.537-544
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• 2005

This paper presents the efficiency measurement and energy analysis for a parallel HEY. Using the HEV test rig, the efficiency of each powertrain component is measured for a given driving cycle including the regenerative braking system. Accompanied by the efficiency measurements, a detailed energy analysis is performed. Based on the efficiency measurement and energy analysis, a HEV performance simulator is developed. Using the simulator, the HEV performance is evaluated for a mild hybrid system. It is expected that the HEV simulator developed can be used to obtain further optimization potentials.

• Journal of ILASS-Korea
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• v.29 no.1
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• pp.1-6
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• 2024

This paper is a numerical analysis study for evaluating the energy efficiency of electric vehicles. Currently, the methods for testing and evaluating the energy consumption efficiency of electric vehicles have limitations such as resources and time. Therefore, there is a need for research on developing models to predict the energy consumption efficiency of electric vehicles. In this study, a numerical analysis research is conducted to predict the energy efficiency of electric vehicles using a vehicle dynamics numerical analysis model. To validate the accuracy of the simulation model, it is compared the results of dynamometer tests with the simulation results and used the Unified Diagnostic Services (UDS) protocol to acquire internal data from the electric vehicle. It is ensured the reliability of the simulation model by comparing data such as motor speed, battery voltage, current, state of charge (SOC), regenerative braking power generation, and total driving distance of the test vehicle with dynamometer test data and simulation model results.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.159-164
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• 2012

Although the display industry plays an important role in the entire Korean economy, few empirical research has analyzed the efficiency of display companies. The purpose of this paper is to measure and analyze efficiency of korean listed display firms using DEA(Data Envelopment Analysis) models. We evaluate the CCR and BCC efficiency in DEA models and the return to scale of the Korean listed display companies. The benchmarking companies and efficiency value for the display companies with inefficiency are also provided to improve their efficiency. We analyzed the 44 listed companies consisted of 7 listed on KOSPI and 37 listed on KOSDAQ at the end of 2010. The analysis results show six companies whose values of CCR are 1, and fourteen firms whose values of BCC efficiency are 1. In additions, the six companies have the scalability efficiency. Eventually the efficiency analysis can provide the valuable information for inefficient companies to find benchmarking companies and to improve their efficiency.

• Korea Journal of Hospital Management
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• v.13 no.3
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• pp.69-93
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• 2008

Rising healthcare cost is a global phenomenon that justifies governments' introduction of 'incentive regulation' plan for the improvement of hospital efficiency. A number of previous studies tried to evaluate the efficiency of healthcare organization by using Data Envelopment Analysis(DEA), a common efficiency benchmarking method. However, there is a concern that this kind of efficiency evaluation could induce "quantity-quality trade-off". Moreover, as quality aspect is especially important in terms of 'effectiveness' of health care, it should be considered in efficiency evaluation of healthcare organization. A number of different models were tried so far to incorporate quality aspect into DEA, however, none is universally recognized as a standard. Thus, in this study, previous quality-incorporating DEA models were categorized into 6 types according to the way of incorporating quality aspect, and strengths and limitations of each type were reviewed with a set of artificial data as an example. Based on this review, a new quality-incorporating efficiency evaluation model, named Quality-adjusted output DEA(QAO-DEA), was suggested. As an exploratory empirical analysis, technical efficiency of human resource were measured with different quality-incorporating DEA models, using 2004 data from National University Hospitals. In conclusion, Quality-adjusted output DEA(QAO-DEA) model seems to be one of the most desirable alternatives to incorporate quality aspect in efficiency evaluation of hospital, and deserves the consideration as a policy tool to induce simultaneous improvement of both efficiency and quality.

• Korea Journal of Hospital Management
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• v.5 no.1
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• pp.84-104
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• 2000

This paper analyzes the technical efficiency of thirty two hospitals in Korea using DEA(Data Envelopment Analysis). DEA provides an efficiency measure for each hospital compared to the most efficient one. The amount and sources of inefficiency that are identified by the DEA are useful for benchmarking to improve efficiency. The results from multiple regression analysis and Wilcoxon Rank Sum test show that bed turnover, hospital size, and average length of stay are related to hospital efficiency.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.1
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• pp.99-111
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• 2016

This paper presents a framework to analyze the change in the research and development (R&D) efficiency of government-funded research institutes (GRIs) in Korea. Cumulative data envelopment analysis/Malmquist index method is utilized to analyze the changes in R&D efficiency of GRIs. Data analysis of the R&D activities of 10 GRIs in Korea Research Council of Fundamental Science & Technology showed that the average R&D efficiency of the 10 GRIs improved from 2009 to 2013. However, the efficiency of a few GRIs decreased in terms of the catch-up index. The proposed framework can help management teams diagnose the current state of R&D activities and determine the efficacy of strategic actions by comparing efficiencies in the past.

• Journal of Distribution Science
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• v.16 no.5
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• pp.91-101
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• 2018

Purpose - This study compares the management efficiency of retailers in China, Korea and other global countries. China's retail industry is experiencing a recession. In order to strengthen the competitiveness of retailers, it is necessary to manage the efficiency. Therefore, we analyzed the management efficiency of Chinese retailers as well as Korea and global retailers who are competing with Chinese retailers. Research design, data, and methodology - The DEA(Data Envelopment Analysis) carried out for evaluating the relative efficiency of multiple DMUs (decision making units) with homogeneity. Data were collected from the American Retail Trade Association (2017). In those distributors' data, 5 of China and 5 of Korea and 10 of other global countries' analyzed. CCR and BCC analysis were performed to determine the cause of the inefficiency of DMUs by measuring the technical efficiency, pure technology efficiency and scale efficiency. Result - Among the 20 retail distributors, Costco, Kroger (Global), Eland World, BGF(Korea) are operating efficiently. Chinese retailers are operating inefficiently. Retailers' CRS status means the growth rate of input is equal to the growth rate of output. In the case of DRS status, the ratio of output to input variable is much smaller. In order to improve inefficiency, reducing input variables can be a solution. For the firms in IRS status, the rate of increase in output is relative greater than the input. That means efficiency is good condition. The analysis result shows that most retailers are showing DRS status especially Chinese retailers. Scale efficiency is a major cause of inefficiency rather than pure technology efficiency. It is recommended for ineffective retailers to reduce inputs to become efficient retailers. Otherwise, retrain existing employees or introducing advanced technologies to increase the output. Conclusions - Most of Chinese retailers are operating inefficiently which caused by the excessive investment in the inputs. On the other hand, Other global retailers are analyzed to be efficient by DEA. In this study, benchmarking targets of some retailers' suggested to improve the management efficiency especially in inputs.

• Health Policy and Management
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• v.33 no.3
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• pp.355-362
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• 2023

Background: Financial efficiency in monetary units and operational efficiency in non-monetary units are separately classified and evaluated. This is done to prevent the duplication of monetary units and non-monetary units in inputs and outputs. In addition, analyses are conducted to determine the factors that affect each aspect of efficiency. To prevent duplication of monetary and non-monetary units in inputs and outputs, financial efficiency, consisting of monetary units, and operational efficiency, comprising non-monetary units, are separately classified and evaluated. Furthermore, an analysis is conducted to identify the factors that affect each aspect of efficiency. Methods: This study conducted a panel analysis of 34 regional public hospitals and influencing factors on efficiency for 5 years from 2015 to 2019. Financial efficiency and operational efficiency were calculated through data envelopment analysis. Moreover, multiple regression analysis was conducted to identify the factors that influence both financial efficiency and operational efficiency. Results: The factors that affect financial efficiency include the number of medical institutions within the treatment area and the ratio of patients receiving medical care. Additionally, operational efficiency is influenced by the type of medical institution, the number of medical institutions within the treatment area, and the number of nursing positions per 100 beds. Conclusion: In order for regional public hospitals to faithfully fulfill their functions and roles as regional base public hospitals, several measures are necessary. Firstly, continuous monitoring and reasonable support are required to ensure efficient operation and performance. Secondly, a financial support plan tailored to the characteristics of local medical centers is needed. Additionally, local medical centers should strive to enhance their own efficiency.

• Journal of Korea Port Economic Association
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• v.32 no.2
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• pp.123-135
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• 2016

This study uses Data Envelopment Analysis(DEA) to investigate the management efficiency of Korean shipping companies based on business administration costs such as corporate entertainment, advertisement, and labor costs. We analyze shipping enterprises listed on the Korean stock market of the period of 2010-2014. Corporate entertainment, advertisement and labor costs are used as input variables and sales and net income are used as output variables. We use technical efficiency, pure technical efficiency, scale efficiency and returns to scale to propose a plan to improve the efficiency of inefficiency decision-making units (DMUs). The results of the efficiency analysis show that six of the DMUs in the technical efficiency of CCR model and eight of the DMUs in the pure technical efficiency of BCC model are in efficient state. In terms of return to scale, six of the DMUs(24% of all DMUs) show increasing returns to scale, while 13 DMUs(52% of all DMUs) showdecreasing returns to scale. Because multiple efficient state for DMUs exist in the technical efficiency analysis, we conduct a super efficiency analysis. The results show that the efficient state of the twomost efficient DMUs are 1.314 and 1.243, respectively. This implies that these DMUs could maintain their current levels of the efficiency if they increase the amount spent on advertisements, corporate entertainment and labor costs by 31.4% and 24.3%. respectively. We conclude this study by providing the efficiency states of each DMU and target for improving the inefficiencies in each case.

• The Journal of Fisheries Business Administration
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• v.34 no.2
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• pp.109-129
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• 2003

The purpose of this study is to evaluate the managerial efficiency of fisheries cooperatives in Korea by using data envelopment Analysis(DEA). The DEA method is a relative evaluation method on the basis of linear programming. Also, it is known as a useful method for the evaluation of not-for-profit organizations which cannnot be measured by mere monetray units for their performances. The 50 units have been taken for the purpose of analysis. All of the units are homogeneous groups, and the produce multiple services with multiple inputs. Input variables are a number of employee, fixed assets, and business managerial costs. Output variables include a number of deposits, a number of loans, a total deposits, a total loans, and operational income for one year. The empirical results of this study are as follows. First, the average technical efficiency showed 82.35% which revealed about 17.65% of non-efficiency in 2001. Second, in 15 DMUs, the overall inefficiency is mainly attributed to their efficient operations or management. To be opposed, in 18 DMUs, the overall inefficiency is mainly attributed to their scale efficiency. Third, efficiency ranking results by DEA do not agree with the ratio analysis by fisheries cooperatives. Fourth, average efficiency level by year was improving gradually by 0.7408 in 1999, 0.8023 in 2000, and 0.8235 in 2001 at significant 10% level.