• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.245-251
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• 2006

This is paper aims to evaluate allocation order of SRU using Analytic Network Process. For evaluation, in this paper, assess about person, ship and environment related risk by fuzzy logic and AHP(Analytic hierarchy Process). Also, quantity and quality operation efficiency assess by DEA (Data Envelopment Analysis) and Liquate scale. finally total weight calculate by ANP. At the result, Rescue Units of MP, YS RCC/RSC is order higher. Thus, it needs to have more rescue ships and rescue devices for relieving the risk in the future.

• Advances in Energy Research
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• v.5 no.2
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• pp.147-177
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• 2017

This study aims to evaluate and prioritize ten different sites in Iran's Khorasan provinces for the construction of wind farm. After studying the geography of the sites, nine criteria; including wind power, topography, wind direction, population, distance from power grid, level of air pollution, land cost per square meter, rate of natural disasters, and distance from road network-are selected for the analysis. Prioritization is performed using data envelopment analysis (DEA). The developed DEA model is validated through value engineering based on the results of brainstorming sessions. The results show that the order of priority of ten assessed candidate sites for installing wind turbines is Khaf, Afriz, Ghadamgah, Fadashk, Sarakhs, Bojnoord, Nehbandan, Esfarayen, Davarzan, and Roudab. Additionally, the outcomes extracted from the value engineering method identify the city of Khaf as the best candidate site. Six different wind turbines (7.5 to 5,000 kW) are considered in this location to generate electricity. Regarding an approach to produce and store hydrogen from wind farm installed in the location, the AREVA M5000 wind turbine can produce approximately $337ton-H_2$ over a year. It is an enormous amount that can be used in transportation and other industries.

• Korean Management Science Review
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• v.29 no.3
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• pp.23-43
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• 2012

Enacted for enhancing the competitiveness of the Korean capital market and financial industry, Capital Market Consolidation Act (CMCA) was intended to induce considerable changes such as adopting the concept of financial investment products, regulating financial investment functionally, extending financial investors' business areas and intensifying protection for investors. Employing DEA (Data Envelopment Analysis), this study measures and compares the efficiencies of domestic financial companies between the before and after the enactment of the Consolidation Act. We categorize the financial companies into 4 groups (banks, life insurance companies, property and casualty insurance companies and securities companies) depending on their business types, and evaluate how much and in which direction the Consolidation Act affects the efficiency of each group respectively. The study shows that there is no significant difference between the average efficiency of banks and that of property and casualty insurance companies due to the trade-off between opportunities and threats of the Act. To the contrary, it shows that the respective average efficiencies of life insurance companies and securities companies moved in the opposite directions to a considerable extent. Through empirical tests, we demonstrate the effect of the Act on the efficiency of Korean financial companies, and suggest the countermeasures for each financial group against the Act.

• Journal of Information Technology Services
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• v.15 no.2
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• pp.51-63
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• 2016

In this study, we conducted a comparative analysis of R&D investment efficiency and operational efficiency of IT firms using Data Envelopment Analysis (DEA). We categorized thirteen sample firms into two groups-IT manufacturing and IT service-after an extensive literature review on IT industry classification. We adopted an output-oriented two-stage DEA model suggested by Banker et al. (1984) with total asset and R&D investment as input variables. Then, we constructed investment efficiency and operational efficiency by using Return on Equity (ROE) and Return on Asset (ROA) as intervening variables and operating income and Earnings Per Share (EPS) as output variables. The outcome of the analysis is summarized as follows. First of all, IT manufacturing firms were more efficient (57% on average) than IT service firms. To be specific, IT service firms showed decreasing returns to scale (DRS) with diseconomy of scale. In contrast, IT service firms showed higher operational efficiency (81.5% on average) than IT manufacturing firms. Also, we conducted a Mann-Whitney U test to compare the output of IT service firms and IT manufacturing firms. Lastly, we found a negative correlation ($R^2$ = -.754) between R&D investment efficiency and operational efficiency which infers the trade-off between two constructs

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1551-1556
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• 2012

This study proposes an efficient portfolio selection methodology for the listed corporations in KOSPI with consideration of managerial efficiency. For each industrial sector classified by KRX(Korea Exchange), the proposed method carries out an efficiency analysis using DEA (Data envelopment analysis) approach and for the efficient corporations filtered by DEA, construct portfolio using Markowitz's Model. In order to show the effectiveness of the proposed method, we constructed annually portfolios for 4 years (2007-2010) out of 600 listed corporations in KOSPI and KOSDAQ, and proved that our portfolios are superior to benchmark portfolios in terms of rate of returns.

• Journal of Information Technology and Architecture
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• v.11 no.1
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• pp.75-80
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• 2014

At the time the interest and love of the Korean professional baseball is increasing, the need for effective recruiting method rising. Recruiting existing methods were scheme based on expert evaluation, to obtain the players of each team. However, the existing method does not reflect only objective rating but also subjective way of school tie and delays are effect. Therefore the conventional method could not be the efficient. Therefore this paper analyze Korea baseball player's efficiency based on entire team and each team by using DEA (Data Envelopment Analysis) method, and use this efficiency to discuss effective way of recruiting players. Finally, the validity of experiment is confirmed by the matters of actual sell of players who are scouted by experiment.

• Knowledge Management Research
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• v.13 no.5
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• pp.43-64
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• 2012

Emerging technologies have significant implications in establishing competitive advantages and are characterized by continuous rapid development. Efficient benchmarking is more and more important in the development of emerging technologies. Similar input level and importance are two necessary criteria need to be considered for emerging technology's benchmarking. In this study, we proposed a sequential use of self-organizing map(SOM), data envelopment analysis(DEA) and analytical hierarchy process(AHP) method for the stepwise benchmarking of emerging technology. The proposed method uses two-level SOM to cluster the emerging technologies with similar required input levels together, then, in each cluster, uses DEA-BCC model to evaluate the efficiencies of the emerging technologies and do tier analysis to form tiers. On each tier, AHP rating method is used to calculate each emerging technology's importance priority. The optimal benchmarking path of each cluster is established by connecting the emerging technologies with the highest importance priority. In order to validate the proposed method, we apply it to a case of biotechnology. The result shows the proposed method can overcome difficulties in benchmarking, select suitable benchmarking targets and make the benchmarking process more efficient and reasonable.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.323-326
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• 2008

Data Envelopment Analysis (DEA) is a theoretically sound framework for performance analysis that offers many advantages over traditional methods such as performance ratios and regression analysis. Largely the result of multidisciplinary research during the last three decades in economics, engineering and management, DEA is best described as an effective new way of visualizing and analyzing performance data. Besides, overseas information technology companies have aggressively tried to enter the domestic market. In the age of globalization and high competition, it is imperative that the system integration (SI) companies need to introduce the performance evaluation models of SI projects, including Capability Maturity Model and Software Process Improvement and Capability Determination, to gain a competitive advantage. Therefore, it makes our research regarding evaluation of SI projects very opportune. The purpose of the study is not only to evaluate efficiency of each project by DEA but also to gain insight into various factors such as project complexity, team members' man-months structure, and process index(project management index) that link to the projects performance.

• International Journal of Highway Engineering
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• v.20 no.2
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• pp.109-118
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• 2018

PURPOSES : This study evaluates the efficiency of snow removal operation resources using data envelopment analysis (DEA). The results of this study can help decision-making strategies, especially for resource allocation for snow removal works on national highways. METHODS : First, regional road management offices (DMUs) for efficiency evaluation were set up, and a database (for years 2012-2016) for analysis was formed. Second, DEA was carried out by selecting input and output variables based on the constructed database. Lastly, based on the results of the DEA, the efficiency of each regional road management office was evaluated. In addition, the potential for future improvement was determined. RESULTS : The results showed that there was a large variation in efficiency of snow removal operation resources by regional offices. CONCLUSIONS : The results of this study imply that the evaluation of efficiency for snow removal operation resources is important when decisions related to snow-removal strategies are made by road management offices.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.8-15
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• 2019

Korea's R&D investment has significantly increased in recent years and the quantitative outputs such as number of papers and patents have also increased with the investment. However, the quality of R&D outputs has not been fully addressed. In particular, quality of technical performance, such as the quality of patents, has attracted little attention. In this paper, a Data Envelopment Analysis (DEA) method was used to construct models for efficiency analysis of R&D investment, focused on quality of technical performance. Indices were proposed to analyze the quantitative and qualitative efficiencies of R&D investment. In order to effectively analyze R&D efficiencies, the measurement units of the input and output variables were standardized. Based on cases of livestock quarantine R&D projects of Korea, the quantitative and qualitative efficiencies of national R&D projects were analyzed and factors that would influence R&D efficiencies were identified. This paper suggests that both quantitative and qualitative efficiencies should be considered when measuring R&D efficiency. Also, it is recommended to carefully consider the characteristics of R&D projects during project selection stage.