• Journal of Korea Technology Innovation Society
• /
• v.19 no.4
• /
• pp.711-735
• /
• 2016

Drug Development is very important for promoting public health and pharmaceutical industry. There has been many studies on the efficiency of drug development, but there are few studies on the drug development R&D performed by government. Since CCR model assumes unidirectional influence of input and output, it is not appropriate to analyze the efficiency of R&D due to the time-lag and spill-over effect. Also, BBC model which assumes variable returns to scale has difficulty in deriving priorities between decision making units. Recently, Range Adjusted Measure (RAM) model has been suggested in R&D efficiency analysis. RAM model measures the efficincy by eliminating inefficiencies under variable returns to scale assumption, and its strong monotonicity enables to provide clear priorities between decision making units. In this study, we analyzed the efficiency of national R&D programs for drug development using the two-step approach, including RAM model and Tobit regression analysis, and discussed major policy implications.

• Journal of Information Technology Services
• /
• v.16 no.4
• /
• pp.15-31
• /
• 2017

This study analyzes 45 Korea IT service companies from 2012 to 2016 using DEA analysis. Large enterprises, medium enterprises and small and medium enterprises (SMEs). CCR model and BCC model were used for efficiency analysis. Among the various analytical objects, the decision objects which yield the maximum output with minimum input are compared with other analysis objects. The relative inefficiency was measured through this, and Technical Efficiency (TE), Pure Technology Efficiency (PTE), Scale Efficiency (SE), scale profit, reference frequency were analyzed. Also, we analyzed the Technology Gap Ratio (TGR), which is the distance between production function and Meta-Frontier for each firm, using Meta-Frontier analysis. Finally, the Tobit model is used to analyze the sources of efficiency and inefficiency. The inputs are assets, capital, and employees, and the output factor is sales. The analysis shows that large firms are achieving technological achievements more efficiently than small and medium enterprises. As a result, medium-sized enterprises and SMEs can improve efficiency overall through efficient operation of workforce and appropriate combination of inputs such as assets and capital. Also, as a result of the influence factor analysis, it was found that the ratio of the managed asset ratio and the management cost ratio were significant factors influencing the efficiency of the IT service companies. This study suggests the efficiency analysis using DEA for many Korea IT service companies. Inefficient parts of each company are classified according to size and technology. Also, we identify the most efficient companies and analyze the causes of those companies whose profits are lower than their size.

• Journal of Korea Port Economic Association
• /
• v.18 no.1
• /
• pp.3-26
• /
• 2002

The purpose of this paper is to Investigate the productive efficiency and competitive strength of world container ports using the DEA, Super-efficiency, and FDH methods with the raw data from previous research by Jun et al.(1993). The super-efficiency measure examines the maximal radial change In input, outputs for an observation to remain efficient. Therefore, it provides a means of distinguishing between efficient observations, which would otherwise seem identical. FDH provides a good test mechanism for examining the practical implications of the choice available among alternative efficiency measures and orientations, because of the lack of convexity of its production possibility set. Both methods are complementary to DEA. This paper follows the traditional productivity analysis method overcoming the limitation of previous studies by using the DEA, FDH and Super-efficiency methods, and proposing in measure the relative competitive strength of worldwide container ports. The main empirical results of this paper are as follows: Firstly the ports of Singapore, Hongkong, Kilrung, Busan, Tokyo. and Longbeach were found to be efficient In the CCR model. The ports of Felixstowe, Bangkok, Singapore, Hongkong, Kilung, Busan, Tokyo, and Longbeach were found to be efficient in the BCC model. Secondly, super. efficiency rankings under CRS and input-oriented model are as follows: Longbeach, Keelung, Singapore, Busan, Tokyo, and Honkong. However, it was difficult In differenciate the rankings under the VRS and input-oriented model. due to major difficulties posed by the ports of Singapore, Hongkong, and Longbeach. Thirdly, the FDH method shows that the inefficient ports are Bremerhaven, Antwerp, Le Havre, Kobe, Seattle, New York The policy Implications of this study are as follows: Firstly, when port authorities want to measure the international competitive strength of container ports and enhance their productive efficiency, they should consider the traditional method as well as introducing the Super-efficiency and FDH methods. Secondly, according to the analysis results of the super-efficiency and FDH methods, poll authorities should recommend benchmarks ports and dominated ports as reference ports in order to enhance the productive efficiency of their container ports that have an efficiency rating of less than 1. Efficient ports whose efficiency ratings are over 1 in the Input-oriented Super-efficiency model should also consider the usage of input and output elements used by more efficient ports.

• Proceedings of the Korea Port Economic Association Conference
• /
• 2007.07a
• /
• pp.391-405
• /
• 2007

The purpose of this paper is to verify the two problems(normalization for the different inputs and outputs data, and translation invariant for the negative data) which will be occurred in measuring the seaport DEA(data envelopment analysis) efficiency. The main result is as follow: Normalization and translation invariant in the BCC model for measuring the seaport efficiency by using 26 Korean seaport data in 1995 with two inputs(berthing capacity, cargo handling capacity) and three outputs(import cargo throughput, export cargo throughput, number of ship calls) was verified. The main policy implication of this paper is that the port management authority should collect the more specific data and publish these data on the inputs and outputs in the seaports with consideration of negative(ex. accident numbers in each seaport) and positive value for analyzing the efficiency by the scholars, because normalization and translation invariant in the data was verified.

• Korea Journal of Hospital Management
• /
• v.16 no.4
• /
• pp.35-66
• /
• 2011

This study analyzed efficiency by utilizing DEA analytical technique centering on materials for 2009 of 20 major university hospitals in capital area. Input variables were utilized professor & full-time doctor, resident, nurse & number of bed hospitals. Output variables were analyzed by dividing number of annual outpatients & number of annual inpatients, and annually total outpatient profit & inpatient profit into a model of the standard for number of patients and the standard for medical profit. DEA analysis was elicited efficiency score by applying CCR, BCC, BFG, scale profit, and SE model. Through t-test after eliciting efficiency score, the implications were suggested by comparing efficiency between DMU in Seoul and DMU in capital area, by comparing between high-class general hospitals and general hospitals, and by comparing between high-class general hospitals in Seoul and 5 big hospitals. As a result of analysis, the major university hospitals in capital area showed high efficiency as a whole close to "1," but indicated low efficiency relatively in CCR field. Thus, the expansion in scale within capital area was indicated to reach the limit. Second, in a model of analyzing the standard for number of patients, the medical institutions, which are being operated efficiently, were indicated to be 10 DMUs. In the standard for medical profit, 12 DMUs were analyzed to be operated efficiently. Third, the efficiency in general hospital was higher than high-class general hospital. Thus, the efficiency of operation was indicated to be more important than scale. Also, large high-class hospitals(big 5) where are located in downtown Seoul showed the higher efficiency than other general high-class general hospitals, but were indicating very low efficiency in some DMUs. Fourth, as a result of generalizing and evaluating the number of patients and the medical profit, the efficient DMU was indicated to be more when analyzing on the basis of medical profit than the standard for number of patients. Thus, major university hospitals in capital area were indicated to make more effort for section in medical profit. Based on the analytical results of efficiency, a strategy for reinforcing efficiency in inefficient DMU was indicated to be needed a strategy of creating customers for promoting number of patients and a strategy for making operation efficient for increasing profitability.

• The Journal of the Korea Contents Association
• /
• v.19 no.5
• /
• pp.64-73
• /
• 2019

This study analyzed the efficiency by using the DEA model to evaluate the competitiveness of specialty construction firms. The target of the analysis is 300 firms with continuous data from 2010 to 2017 as listed and externally listed firms. Significant analysis results are as follows. First, the efficiency of specialty construction firms is lower than that of general construction industry. Second, efficiency by type was highest in facilities construction and dismantling work. This shows that the relevant industries such as reinforced concrete works and scaffolding and demolition work are relatively efficient in specialty construction industry. Third, the efficiency of specialty construction industry is affected by economic fluctuations. When the construction industry is in the expansion phase, the efficiency value is high and the efficiency value is low in the down phase. Finally, in the scale profitability analysis, specialty construction industry was most analyzed by DRS. This means that it is effective to scale down for the efficiency of the firm.

• Korean Journal of Organic Agriculture
• /
• v.30 no.3
• /
• pp.351-374
• /
• 2022

In recent years, the development of rice industry has been highly valued by the state. In hubei area, due to the development of the modernization and the shortage of labor, traditional way of rice cultivation methods is facing serious challenges, and economic benefits have become the decisive factor for the effective promotion and application of rice cultivation methods. According to the research results, first, in the input-side analysis, in the CCR model, D5, D12, D26, D28, D32, D36 farmers with high efficiency appear. The analysis result shows that among the 60 farmers, the average efficiency is 89%, and there is an inefficiency of 11%. In the BCC model, 14 farmers were identified as high-efficiency farmers, with an average efficiency of 0.9453. Second, in direct seeding cultivation of rice, the average scale efficiency is 0.9227, while the average pure technical efficiency is 0.9644. This shows that the effect of scale efficiency is greater than that of purely technical factors, ignoring the reasons for the low operational efficiency of direct seeding cultivation farmers. It can be predicted that with the further deepening of farmers' understanding of this planting mode, the proportion of rice direct seeding may be further expanded in the future. Relevant agricultural departments should further promote this technology to farmers, study the direct seeding technology using scientific methods, and evaluate the changes of this cultivation mode. The agricultural departments of government should concern about the climate risk assessment of direct seeding rice, the environmental impact assessment caused by the extensive use of herbicides, the application of mechanical technology in the process of direct seeding, the lodging of direct seeding rice, and other related issues.

• Journal of Distribution Science
• /
• v.11 no.8
• /
• pp.5-14
• /
• 2013

Purpose - We live in a world of constant change and competition. Many airports have specific competitiveness goals and strategies for achieving and maintaining them. The global economic recession, financial crises, and rising oil prices have resulted in an increasingly important role for facility investment and renewal and the implementation of appropriate policies in ensuring the competitive advantage for airports. It is thus important to analyze the factors that enhance efficiency and productivity for an airport. This study aims to determine the efficiency levels of 20 major airports in East Asia, Europe, and North America. Further, this study also suggests suitable policies and strategies for their development. Research design, data, and methodology - This paper employs the DEA-CCR, DEA-BCC, and DEA-Malmquist production index analysis models to determine airport efficiency. The study uses data on the efficiency and productivity of the world's leading airports between 2006 and 2010. The input variables include the airport size, the number of runways, the size of passenger terminals, and the size of cargo terminals. The output variables include the annual number of passengers and the annual cargo volume. The study uses basic data from the 2010 World Airport Traffic Report (ACI). The world's top 20 airports (as rated by the ACI report) are investigated. The study uses the expanded DEA Model and the Super Efficiency Model to identify the most effective airports among the top 20. The Malmquist productivity index analysis is used to measure airport effectiveness. Results - This study analyzes longitudinal and cross-sectional data on the world's top 20 airports covering 2006 to 2010. A CCR analysis shows that the most efficient airports in 2010 were Gatwick Airport (LGW), Zurich Airport (ZRH), Vienna Airport (VIE), Leonardo da Vinci Fiumicino Airport (FCO), Los Angeles International Airport (LAX), Seattle-Tacoma Airport (SEA), San Francisco Airport (SFO), HongKong Airport (HKG), Beijing Capital International Airport (PEK), and Shanghai Pudong Airport (PVG). We find that changes in airport productivity are affected more by technical factors than by airport efficiency. Conclusions - Based on the study results, we offer four airport development proposals. First, a benchmark airport needs to be identified. Second, inefficiency must be reduced and high-cost factors need to be managed. Third, airport operations should be enhanced through technical innovation. Finally, scientific demand forecasting and facility preparation must become the focus of attention. This paper has some limitations. Because the Malmquist productivity index is based on the hypothesis of the, the identified production change could be over- or under-estimated. Further, as DEA estimates the relative efficiency. It also cannot generalize to include all airport conditions because the variables are limited. To measure airport productivity more accurately, other input variables and environmental variables such as financial and policy factors should be included.

• Korean Journal of Agricultural Science
• /
• v.39 no.2
• /
• pp.279-289
• /
• 2012

This study was conducted to survey and diagnose operation status of the agricultural machinery rental service, analyse and compare operational efficiency among 82 city and county ATDEC (agricultural technology development and extension center) using the DEA (Data Envelopment Analysis) method, and recommend future direction, for improvement of the business. Input variables were invested budget and labor, and output variable was rental return. Percentages of return to investment on the rental service were calculated as 68.3% and 63.9% when analyzed with CCR (Charnes, Cooper and Rhodes) and BCC (Banker, Charnes and Cooper) models, respectively, indicating inefficiency of the service operation. Increase of rental charge would increase efficiency by 63.9~68.3% depending on models, and decrease of financial and labor investment would improve the efficiency by about 11.3%. Technical efficiency would be more important than scale efficiency, therefore adjustment of over-invested budget and labor needed to be made together with increase of rental charge to improve the operation. Among the ATDECs providing the rental service, 6 (7.3%), 43 (52.4%), and 33 (40.2%) were in state of CRS (constant return to scale), IRS (increasing return to scale), and DRS (decreasing return to scale), respectively. These indicated public aspects of the rental system, over-investment, lack of output component for input component, meaning that scale income would be increased by qualitative expand of rental charge. Efficiency analysis of the rental system by region showed that efficient ATDECs to be benchmarked by others were in the order of DMU-70, DMU-54, DMU-29, DMU-5, DMU-22, DMU-2, and DMU-61. More comprehensive and extensive survey and analyses would be necessary in the future.

• International Area Studies Review
• /
• v.14 no.3
• /
• pp.205-219
• /
• 2010

In general, industrial production involves large amounts of harmful by-product, causing serious pollution and ecological risk. Eco-efficiency, which indicates how efficient the economic activity is by considering both the environmental risks and economic performance, is a new concept for economic sustainability analysis and quantitative ecological risk analysis. Data envelopment analysis (DEA) has been widely used to examine eco-efficiency in recent years. Whereas traditional DEA models such as CCR and BCC model neglect undesirable outputs, this paper adopts a stochastic undesirable-output DEA model to measure the eco-efficiency of each province of China and Korea. The results indicate that whereas the eco-efficiency of the eastern region was the highest, that of the western region was the lowest. The reason may come from the negative external dis-economies of environment. And thus the governmental efforts for outreach on the underdeveloped regions should be promoted.