• Korean Journal of Occupational Health Nursing
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• v.11 no.2
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• pp.108-120
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• 2002

This study analyzed the managerial efficiency of 11 organizations, the branch centers of a occupational health service organization in Korea, using the Data Envelopment Analysis (DEA) method. The DEA is a good method for evaluating health services since it can handle multiple inputs and outputs simultaneously, and also identify the sources and amount of inefficiency. The author approached this study using two efficient models: the monetary value model and the real value model. The DEA method based on the monetary value model included cost factors, while the real value model excluded cost factors. The input variables used were manpower of physicians, medical technicians, nurses, industrial hygienists and administrators; labor, maintenance, and material expenses. The output variables used were the number of medical examinations, workplace evaluations, group health management services and income from each service. The major results were as follows: First, in the monetary value model, 6 out of 11 organizations (54.6%) showed an efficiency score of 1.0, which means that they have been operating in very efficient ways. However, 5 organizations (46.4%) showed themselves to be relatively inefficient. Second, in the real value model, 7 out of 11 organizations (63.4%) showed an efficiency score of 1.0, which means they have been operating efficiently, while 4 organizations (46.4%) showed themselves to be relatively inefficient. Third, the reliability of DEA method were analyzed by comparing the results of the monetary value model and real value model. The results of 8 out of 11 organizations were same in terms of being efficient or not. Thus, the DEA could be a valid application method for occupational health service organizations. Fourth, the organizations that displayed common inefficiency in both the monetary value model and in the real value model 3, 9, and 10, were also considered to be managed inefficiency from expertise opinion. In summary, this study evaluated the efficiency of occupational health service organizations applying the DEA method with different variables, and found that the results of analysis could be valid in terms of both modeling and expert sense. In the future, the DEA method will be used as a useful tool to identify and evaluate the efficiency of occupational health service organizations through more applications and refinements.

• Journal of Digital Convergence
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• v.9 no.6
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• pp.1-11
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• 2011

It is time to review the direction of R&D investment which is the source of change in knowledge information ages. The DEA(Data Envelopment Analysis) is a efficient method by using the ratio of input and output elements. In this paper, we analyzed industry relationship and efficiency by DEA in order to analyze ripple effect of the regional industry technology development project. According to these results, we found the primary affected factor in performance of this project was human resource, and the turnover of participated company was not on the rise yet. On types of the project, we could find the efficiency quotient of critical technique development project was higher than of common technique development project because project period or budget scale infected to project performance. We expect the enhancement of technique developer, tenn and budget, and it is necessary the project results should lead performance such as sales force and employee growth.

• Journal of Information Technology Services
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• v.16 no.4
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• pp.1-13
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• 2017

This study examines how specific technology from Information and Communications Technology (ICT)-which plays a critical role in increasing productivity by promoting a spread of technology across the society though the use of big data, mobile or wearable devices-impacts of the productivity of society and productivity of added values, respectively. The impact of technology was studied from the perspective of efficiency levels of input. In order to provide an analysis, we have categorized ICT into 16 specific technologies and have set the number of companies and number of employees each as an input factor while setting the respective output and the output of added values as an output factor. Afterwards, we have applied data envelopment analysis (DEA) which is a form of nonparametric frontier analysis and measured the productivity and efficiency of added values for each technology. According to the analysis results, there were 2 technologies by the CRS standards, and 3 technologies by the VRS standards that showed relative efficiency levels. We have also presented some efficiency improvement strategies for specific technologies that revealed relative inefficiency and offered a reference set and projection point. In addition, we provide an analysis on scale efficiencies (SE), diminishing returns to scale (DRS), and increasing returns to scale (IRS) of each ICT.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.297-304
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• 2020

This paper applies the Data Envelopment Analysis (DEA) to compute the managerial efficiency of 30 insurance companies listed on the Saudi stock exchange for the duration of four years from 2015 to 2018. The companies taken as a sample of study included both conventional and Takaful insurance companies. The insurance sector of KSA is one of the largest sectors in the country, contributing a substantial percentage in the non-oil economy. Efficiency measurement and evaluation will provide a venue to introspect and benchmark frontiers to the sector. In the present study, we have utilized the basic Banker Charnes Cooper and Charnes Copper Rhodes models of DEA. Two inputs, namely, general & administrative expenses and policy & acquisition costs, and two outputs (Net premium earned and Investment Income & other incomes) were taken for efficiency calculations. The final outcomes of the study reveal that a good number of insurance companies operating in KSA are found to be efficient on managerial efficiency scale. Three firms remain the leader on the frontier of the managerial efficiency. And no company found with zero (0) efficiency or a negative efficiency. It is expected that the outcome of the study will provide benchmarks to managers and a road map to further improvement.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.255-260
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• 2007

The construction industry has been recognized as lagging behind other industries in the area of research and development (R&D) due primarily to the lack of R&D funds. To overcome this situation, the Korea Ministry of Construction and Transportation has a plan to expand its investments on the construction R&D up to 1.72 billion US dollars over the next 3 years. Despite this effort, it is still challenging to conduct the quantitative measurement on the efficiency of construction R&D projects, which can be utilized as the objective basis in the reasonable selection of a promising R&D team or in the consequential evaluation of a R&D performance. This study aims to conduct the efficiency analysis on the construction R&D projects to provide the basis for evaluating the performance of research and development. Toward this end, this study performs an efficiency analysis, which reflects all of the input and output data into/from the construction R&D by utilizing the Data Envelopment Analysis (DEA). The proposed methodology can be utilized to make a better decision on the priority of the R&D investments and present a sound basis to suggest the areas to be improved so as to reduce the inefficiency of R&D projects.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.165-166
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• 2015

Sea-ports in Northern Vietnam have experienced a rapid growth of container throughput volume in recent years. To accompany with such development, huge investments also have been performed to enhance local ports capacity. It becomes a crucial task for the port authorities or the port stevedoring industry to improve the ports efficiency in order to customize national resources. In this paper, Data Envelopment Analysis (DEA) is employed to evaluate the relative efficiency of container terminals in Northern Vietnam by collecting data from terminals since 2005 up to now. The development progress of the given terminals will be presented before providing a relative comparison among those year by year. The DEA result is then analyzed and suggestions with regard to changes in local economic environment in near future are contributed.

• 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 Operations Research and Management Science Society
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• v.35 no.2
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• pp.19-35
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• 2010

Many papers have used a two-stage approach of first calculating DEA efficiency scores and then seeking to correlate these scores with various environmental variables. Most of the studies have not checked whether such a two-stage approach is statistically valid for identifying significant environmental variables. Recently Simar and Wilson (2007) (SW) introduce a sensible data generating process and bootstrap procedure based on truncated regression for the two-stage approach. Banker and Natarajan (2008) (BN) provide a statistical foundation for the two-stage approach comprising a DEA followed by an ordinary least squares or maximum likelihood estimation. Researchers have to identify an approach suitable for their research circumstances in terms of properties, merits, demerits, and robustness to plausible departures from its chosen data generating process. We summarize the foundations and properties of the two-stage procedures suggested by SW and BN. And we discuss merits and demerits of those procedures. Also using Monte Carlo simulation we assess their relative performance under several misspecified settings.

• Journal of Korean Society for Quality Management
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• v.45 no.1
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• pp.65-92
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• 2017

Purpose: The performance of global major airports is evaluated and several research questions are examined relative to the measures characterizing airport performance. Methods: The two-stage internal structure of airport performance is considered by decomposing it into physical operations and revenue generation. In the physical operations stage, operating costs, number of runways, terminal area and number of employees are used as inputs, while passenger throughput, cargo throughput and aircraft movements are taken as outputs. Subsequently, in the revenue generation stage, the outputs from the preceding stage are taken as inputs, while revenue is used as output. Results: Based upon this two-stage modeling of airport performance, a multiplicative two-stage network data envelopment analysis model is employed to calculate the overall and stage efficiencies of 59 airports using the recent data in the 2014 Airport Benchmarking Report published by the Air Transport Research Society. Several internal and external factors are also considered such as airport size, airport geographical location, proportion of international passengers, ownership (listed or not) and management style, and statistical analysis is performed to examine their impacts on airport performance. Conclusion: It is shown that the airports exhibit statistically significant difference across regions, and also some statistically significant factors affecting airport performance are identified.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.8-14
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• 2019

Most of the data envelopment analysis (DEA) models evaluate the relative efficiency of a decision making unit (DMU) based on the assumption that inputs in a specific period are consumed to produce the output in the same period of time. However, there may be some time lag between the consumption of input resources and the production of outputs. A few models to handle the concept of the time lag effect have been proposed. This paper suggests a new multi-period input DEA model considering the consistent time lag effects. Consistency of time lag effect means that the time delay for the same input factor or output factor are consistent throughout the periods. It is more realistic than the time lag effect for the same output or input factor can vary over the periods. The suggested model is an output-oriented model in order to adopt the consistent time lag effect. We analyze the results of the suggested model and the existing multi period input model with a sample data set from a long-term national research and development program in Korea. We show that the suggested model may have the better discrimination power than existing model while the ranking of DMUs is not different by two nonparametric tests.