• Korean Journal of Construction Engineering and Management
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• v.14 no.3
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• pp.78-87
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• 2013

The modern society has been drastically changed from the industrial economic society to the knowledge based society, to catch up with the knowledge and the change of technology required for the modern people, the people can not live in the modern society without the continued study or education. In case of architectural design firm, it is concentrating on the productivity of enterprise by cultivating the working level through the self education focused on the improvement of inner capacity. In connection with this, the efficiency of enterprises are analyzed by carrying out the Data Envelopment Analysis(DEA) utilizing the financial ratio index in the various field of industries recently, the analysis study for the efficiency utilizing DEA is increased in the construction industries as well. However, in case of construction industries, the study focused on the efficiency of administration only has been progressed, it is the real situation that the approach for the analysis of education efficiency of each enterprise is very insufficient. Therefore, this study analyzed the education efficiency of architectural design firm after the selection of input and output variables by utilizing the DEA model and utilizing the AHP analysis technique by deducting the variables through the preceding study in relation to the education efficiency and the interview with the specialists.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5B
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• pp.364-378
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• 2008

Data Envelopment Analysis(DEA) models can be used for performance evaluation on governmental funding projects for IT small and medium-sized enterprises associated with multiple-outputs/multiple-inputs. In order to enhance the accuracy of DEA efficiency scores, DEA models with exogenously fixed variables are required where the corporate competency is taken into account. Additionally, it is necessary to use multiple DEA basic as well as extended models so as to relax the restriction on the performance evaluation to relying on a single DEA model. In this study; 1)a DEA data structure is designed including exogenously fixed variables representing corporate asset, revenue and the number of employees at the point in time that the governmental funding project concerned is initiated; 2)DEA basic as well as extended models are established according to the DEA data structure presented abovementioned; and 3)a case study is illustrated with an empirical testbed dataset. As for the DEA basic models, CCR, BCC, Super-efficiency model are adopted. The DEA extended models are developed based on the models associated with noncontrollable and nondiscretionary variables. In the case study, it is explained a comparison of DEA models and also major numerical outcomes such as efficiency scores, ranks derived from each DEA model are integrated using Analytic Hierarchy Process(AHP) weights. Performance significance with DEA efficiency scores between technical categories are tested based not only on parametric but also nonparametric single-factor analysis of variance method.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.77-86
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• 2008

Firstly, this study is to compare two types of productivity changes in Seoul's urban bus industry by public transport reforms: one with considering accident costs (ML), the other without considering accident costs (M). The directional distance function (DDF), which is a form of data envelopment analysis, and the Malmquist (Luenberger) productivity index (ML, M) are used for the analysis. The results show that productivity increased regardless of accident costs over time, and the ML index is a little higher than the M index, which means that most firms experienced more of a reduction ratio of accident costs than a reduction ratio of inputs. Secondly, this paper is to analyze how reforms affect productivity changes. The results show that operational speed improvements or passenger increases most affect productivity increases, which means that the installment of median bus lanes or introduction of free transfers among public transport modes were effective in reducing both inputs and accident costs. However, operational system reforms including mid-public management were related with productivity changes but they were not as effective.

• Journal of Distribution Science
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• v.12 no.8
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• pp.5-15
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• 2014

Purpose - The method of TV home shopping is a kind of retail method that provides the viewer with information about products and, further, sells the products to consumers through the media of television. The domestic home-shopping industry has been expanding since 1995, and there are six companies in this arena as of 2012. In this study, we evaluate the management efficiency of TV home-shopping companies and provide suggestions for improving efficiency, using the DEA (data envelopment analysis) model. Hence, we expect to contribute to the progress of the companies' efficiency and the development of the TV home-shopping industry, where deepening competition is inevitable because it is experiencing the maturing market stage in its life cycle. Research design, data, and methodology - Efficiency is the ratio of the quantity of input to the quantity of output of a product or service. It is necessary to estimate aggregate inputs and aggregate outputs, which are calculated by applying a weighting to a number of input and output factors, to measure the efficiency. The DEA model is divided into the CCR model and the BCC model. The CCR model is a basic model that assumed constant returns to scale (CRS), and the BCC model extends the CCR model to accommodate technologies exhibiting variable returns to scale (VRS), and concerns only the technical efficiency without considering the efficiency of returns to scale. In this study, we consider six companies each year from 2008 to 2012 as a DMU (Decision Making Unit) and analyze the differences in efficiency for each company in each year. Furthermore, we evaluate the operating characteristics of TV home-shopping companies, using three models, in accordance with the overall performance, profitability, and marketability of the business. Results - The result of the analysis, using DEA models, shows that Hyundai Home Shopping (2009, 2010, 2011), GS Home Shopping (2011), NS Home Shopping (2011) and CJ O Shopping (2012) possess MPSS (most productive scale size), with a score 1.0 in CCR, BCC, and scale efficiency. Particularly, Hyundai Home Shopping is shown to be the most efficient in terms of overall business performance, marketability, and profitability. The overall efficiency of the home shopping industry has displayed an increasing trend since 2008, even though it decreased marginally in 2012; further, we can observe that home shopping companies operate with increasing efficiency with the passage of time. Conclusions - Home shopping companies have focused on market expansion rather than profits, as they displayed better efficiency in marketability than increase in profitability during the period 2008-2012. In addition, the main reason for the increased efficiency in the home shopping industry is the market expansion through the revenue increase of each home shopping company. This study can be used as a reference when home shopping companies attempt to devise future strategies, as it suggests efficiency benchmarks and development levels for each home shopping company.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.6
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• pp.763-774
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• 2021

The COVID-19 virus has generated major shockwaves in all spheres of human life since its outbreak. Maritime transport (both cargo and passenger) is one of the industries most heavily affected, yet over 80% of the world cargo is transported by sea. This study analyzes maritime port operational efficiencies before and after the start of the COVID-19 pandemic to determine whether the pandemic has caused major differences in the operational efficiencies of many leading Asian maritime container ports via data envelopment analysis (DEA). The results of both the CCR and BCC models reveal that overall, efficiency during the COVID-19 pandemic has been higher than before the pandemic despite a few inefficiencies. This implies that the pandemic has so far not has major consequences for the operational efficiency of maritime ports. However, two ports (Busan and Guangzhou) should adjust the scale sizes and technical capacities of their operations to improve performance.

• Knowledge Management Research
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• v.22 no.4
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• pp.237-260
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• 2021

This study aims to make suggestions for more effective budget utilization and R&D project investment through verification of the efficiency of research results for the government's R&D projects. Efficiency was analyzed using Data Envelope Analysis(DEA) and 'Malmquist Index analysis' for the research results of convergence research projects organized by the National Science and Technology Research Association. The analysis targets were convergence research projects organized by the National Science and Technology Research Association and general entrusted research projects by government-funded research institutes, and dynamic analysis was conducted using DEA and Malmquist Index analysis. As a result of the analysis, the convergence research project showed high efficiency from the static perspective of DEA. On the other hand, from a dynamic perspective through the Malmquist Index analysis method, the efficiency of the general consignment project gradually declined, while the efficiency of the convergence research project improved every year. This suggests that convergence studies have higher results than general studies. Through the results of this study, we intend to present objective standards for performance evaluation of government R&D investment and provide objective implications for rational investment policies and research project planning of research personnel and research funds to improve efficiency for government-funded research institutes.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.177-187
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• 2002

In this paper, we consider a multi-factor, multi-cause decision making problem of supply chain. And we show how to measure the operational efficiency of the components in supply chain and also how to improve the efficiency of each component and whole supply chain. As a methodology, the data envelopment analysis (DEA) is adopted to measure the efficiency by considering weight factors such as flexibility, information sharing, logistics level, etc. The proposed algorithm allows whole supply chain to have the improved efficiency rate.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.265-280
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• 2001

Estimation of the edge of a distribution has many important applications. It is related to classification, cluster analysis, neural network, and statistical image recovering. The problem also arises in measuring production efficiency in economic systems. Three most promising nonparametric estimators in the existing literature are introduced. Their statistical properties are provided, some of which are new. Themes of future study are also discussed.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.04a
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• pp.365-373
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• 2000

Data Envelopment Analysis (DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications and merits, some features of DEA remain bothersome. DEA offers no guideline about to which direction relatively inefficient DMUs improve since a reference set of an inefficient DMU, several efficient DMUs, hardly provides a stepwise path for improving the efficiency of the inefficient DMU.In this paper, we aim to show that DEA can be used to evaluate the efficiency of life insurance companies while overcoming its limitation with the aids of machine learning methods.

• 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.