• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.358-365
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• 2014

The purpose of this paper is to analyze the efficiency of government investment in the deployment and technological development of three technological areas - wind power, photovoltaic and fuel cell - of renewable energy in Korea using the DEA (data envelopment analysis). The efficiencies of government investment in renewable energies are measured and compared among three kinds of technologies using the actual data during 2007~2009. In the present DEA model, R&D investment and government subsidies for renewable energy usage promotion are selected as input variables, and the number of patents, supply level, and the production cost as output variable. As a result, it is found that the wind power is the most efficient renewable energy in Korea in the perspective of the efficiency of government investment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.81-90
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• 2018

Modern investment theory has empirically proved that stock returns can be explained by several factors such as market risk, firm size, and book-to-market ratio. Other unknown factors affecting stock returns are also believed to still exist yet to be found. We believe that one of such factors is the operational efficiency of firms in transforming inputs to outputs, considering the fact that operations is a fundamental and primary function of any type of businesses. To support this belief, this study intends to empirically study the relationship between firm efficiency and stock price performance. Firm efficiency is measured using data envelopment analysis (DEA) with inputs and outputs obtained from financial statements. We employ cross-efficiency evaluation to enhance the discrimination power of DEA with a secondary objective function of aggressive formulation. Using the CAPM-based performance regression model, we test the performance of equally weighted portfolios of different sizes selected based upon DEA cross-efficiency scores along with a buy & hold trading strategy. For the empirical test, we collect financial data of domestic firms listed in KOSPI over the period of 2000~2016 from well-known financial databases. As a result, we find that the porfolios with highly efficient firms included outperform the benchmark market portfolio after controlling for the market risk, which indicates that firm efficiency plays a important role in explaining stock returns.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.527-538
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• 2021

The purpose of the study is to determine the efficiency, position, and partner selection of securities companies via the negative super-SBM model used in data envelopment analysis (DEA). This model utilizes a variety of inputs, including current assets, non-current assets, fixed assets, liabilities, owner's equity and charter capital, and outputs including net revenue, gross profit, operating profit, and net profit after tax collected from the financial reports (Vietstock, 2020) of 32 securities companies, operating during the period from 2016 to 2019, negative data are collected as well. Empirical results determined both efficient and inefficient terms, and then further determined the position of each securities firm under consideration of every term. The overall score arrived at discovered a large performance change realizing a maximum score able to reach 20.791. In the next stage, alliancing inefficient companies was carried out based on the 2019 scores to seek out optimal partners for the inefficient companies. The tested result indicated that AAS was the best partner selection when its partners received a good result after alliancing, as with FTS (11.04469). The partner selection is deemed as a solution helpful to inefficient securities companies in order to improve their future efficiency scores.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.895-904
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• 2021

This study aims to investigate the impact of innovation on firm efficiency. Panel data of fourteen finance companies and nine technology companies from 2011 to 2019 on the Vietnam Stock Exchange Market is derived from audited financial statements, annual reports, and other crucial reports that are provided by Vietstock; macroeconomic variables are collected from the World Bank Database. A two-stage approach is used. First, use of the Data Envelopment Analysis methodology to measure firm efficiency. Second, use of the Pooled ordinary least squares, the Fixed effects model, and the Random effects model to investigate the impact of innovation on firm efficiency. Furthermore, the Generalized Method of Moments and the Tobit model are used to validate the impact of innovation on firm efficiency, and the t-test is used to confirm the difference in efficiency with and without the impact of innovation between two industries. The results show that there is a significant impact of innovation on efficiency, and innovation plays a more important in increasing the efficiency of the finance industry than the technology industry. Moreover, the relation between age and efficiency is like the U-shaped, and between size and efficiency is like the inverted U-shaped, whereas efficiency is not associated with inflation.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.167-179
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• 2024

This study addresses the challenge of objectively evaluating the performance of early-stage startups amidst limited information and uncertainty. Focusing on companies selected by TIPS, a leading private sector-driven startup support policy in Korea, the research develops a new indicator to assess technological efficiency. By analyzing various input and output variables collected from Crunchbase and KIND (Korea Investor's Network for Disclosure System) databases, including technology use metrics, patents, and Crunchbase rankings, the study derives technological efficiency for TIPS-selected startups. A prediction model is then developed utilizing machine learning techniques such as Random Forest and boosting (XGBoost) to classify startups into efficiency percentiles (10th, 30th, and 50th). The results indicate that prediction accuracy improves with higher percentiles based on the technical efficiency index, providing valuable insights for evaluating and predicting startup performance in early markets characterized by information scarcity and uncertainty. Future research directions should focus on assessing growth potential and sustainability using the developed classification and prediction models, aiding investors in making data-driven investment decisions and contributing to the development of the early startup ecosystem.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.2
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• pp.161-174
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• 2013

The purpose of this study was to examine the efficiency of senior welfare centers and the cause of differences among senior welfare centers in that regard, and to investigate influential factors for the differences in efficiency and the size of the influence of the factors. What methods would be effective at assessing the efficiency of senior welfare centers by taking into account their circumstances was reviewed, and post-hoc analyses were made by using data envelopment analysis(DEA) and Tobit analysis, which were useful tools to evaluate relative efficiency. After 24 senior welfare centers located in Seoul were selected, their yearly operating data of 2011 were utilized. In this study, we set limits to the medical welfare of the elderly welfare services business, and divided into model 2 including the elderly population in the region and model 1, input factors for only internal factors, such as full-time workers. We calculated a valid result by proceeding a BCC analysis and analysis of CCR respectively. As this study has some limitations, follow-up research should be implemented. Yet this study is of significance in that it attempted to present general norms for the efficiency analysis of senior welfare centers by using a DEA model and made various post-hoc analyses based on the efficiency data to give significant suggestions on the service of senior welfare centers.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.899-904
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• 2013

This paper proposes an efficient portfolio selection methodology for the listed construction corporations in KOSPI and KOSDAQ. For the construction 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 5 years (2007-2011) out of 53 listed corporations in KOSPI and KOSDAQ, and proved that our portfolios are superior to benchmark portfolios in terms of rate of returns.

• 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.

• 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.