• Journal of Digital Convergence
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• v.19 no.5
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• pp.353-363
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• 2021

This study analyzed to provide information for business improvement by analyzing the management efficiency of start-up investment companies so that startup investment companies can operate efficiently and by presenting information on inefficient factors. From 2014 to 2018, 83 start-up investment companies were analyzed using the DEA model. Input variables were he number of employees, capital, and output variables were selected for start-up investment assets, operating income, and net profit. As a result of the analysis, technical efficiency and pure technical efficiency showed a pattern with an increase in average, but scale efficiency repeatedly increased and decreased. It is believed that the decline in technology efficiency was due to the decrease in pure technology efficiency, and the inefficiency of start-up investment companies seems to have influenced the inefficiency of start-up investment companies rather than the inefficiency of scale. In addition, the size revenue shows that the DRS value is gradually decreasing, and the IRS value is generally increasing. It is believed that efficiency can be improved if operational inefficiency is improved based on the results and efficiency measures are established through scale expansion.

• International Area Studies Review
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• v.15 no.3
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• pp.307-324
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• 2011

The global economic crisis made most of governments to overcome the economic depression as well as the challenging tasks for global warming. It is not easy political vision to harmonize these two rabbits race, and thus it needs to be developed new paradigm for the sustainable development. Unfortunately, the traditional cost-approach based productivity could not resolve this trade-off relation. Therefore, the paper is aimed to develop new approach on the green productivity index with the DEA models in the 1st stage, and then based on these green productivity scores, the paper is analyzed the determinants of these green productivity in the 2nd stage among the G 20 countries. The empirical result shows that the effect of GDP, carbon intensity, and capital and labor intensity toward the green growth is positive on the green productivity, while the level of government efforts is not significant on the green productivity.

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

• Journal of Korean Society of Water and Wastewater
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• v.35 no.2
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• pp.121-133
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• 2021

This study set up the estimates of leakage management efficiency evaluation and leakage management goal that could be used in local water distribution networks efficiency business and modernization business. The data were analyzed using data envelopment analysis and multiple regression analysis. To this end, with leakage management input indices concerning leakage reduction activities (e.g., aged pipe replacement, water meter replacement, leakage restoration, and leakage detection) and leakage management calculation indices (e.g., the increase of revenue water ratio and the reduction of leakage ratio), the data on 22 K-water consignment local water supply systems were analyzed for the years from 2004 through 2018. Using the results of efficiency analysis by data envelopment analysis, the other DMUs (Decision Making Unit) benchmarked the DMU with the highest efficiency to maximize the leakage management efficiency for all DMUs. Through this, leakage management goal estimates were drawn with the input indices of four leakage reduction activities and calculation indices of the increase of revenue water ratio and the reduction of leakage ratio by multiple regression analysis for each group based on the revenue water ratio and leakage ratio. The correlation coefficients of the leakage management goal estimate for the criteria for the revenue water ratio amounted to 0.553 and 0.771. The correlation coefficients of the leakage management goal estimate for the criteria for leakage ratio were 0.397 and 0.865. Accordingly, we estimated the quantity and priority of four leakage reduction activities for the target leakage ratio and revenue water ratio.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.50-59
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• 2021

The defense venture support program supports development so that it can be applied to the defense sector based on their technology and ideas to revitalize the private advancement of small and medium-sized enterprises to the defense sector. Since 2015, it has been operated with contributions from the Defense Acquisition Program Administration and has supported 84 projects. Moreover, it is an early stage in which results have been derived after 2018. In this study, the R&BD efficiency derived according to the budget for each project was compared using data envelopment analysis and classified and analyzed according to the characteristics of each project to identify the performance factors for each outstanding project. Based on the analysis results, this study considered support plans for efficient support programs and continuous performance creation in the future. As a result, it is expected that the effectiveness of the defense venture support project will be strengthened, and excellent performance will be expanded based on this study.

• International Area Studies Review
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• v.12 no.2
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• pp.79-97
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• 2008

After entering into the WTO in October, 2001, China started opening her bank industry on a full scale and her financial markets from the end of 2006. It is true that the Chinese commercial banks should make efforts to enhance their operational efficiency for adapting the rapid change of financial environments. In this paper, the efficiency of 4 Chinese state-owned commercial banks and 11 share holding commercial banks has been estimated. Our Tobit model to find out the determinants of these banks' efficiency. The results are as follows: The efficiency of these banks kept being improved from 1999 to 2003. With regard to the relationship between the determinants and the bank efficiency, their capital ratios, ownership structures and government subsidies are significant at the 5% level while the return on asset(ROA) is significant at the 10% level. The relationship between the determinants and the efficiency has showed that the size, capital ratios, ROA and ownership structure showed significantly before the entry to WTO, on the other hand, after WTO their capital ratios are the only factor to determine their efficiencies.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.1-14
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• 2021

It is highly challenging to measure the efficiency of electric vehicle charging stations (EVCSs) because factors affecting operational characteristics of EVCSs are time-varying in practice. For the efficiency measurement, environmental factors around the EVCSs can be considered because such factors affect charging behaviors of electric vehicle drivers, resulting in variations of accessibility and attractiveness for the EVCSs. Considering dynamics of the factors, this paper examines the technical efficiency of 622 electric vehicle charging stations in Seoul using data envelopment analysis (DEA). The DEA is formulated as a multi-period output-oriented constant return to scale model. Five inputs including floating population, number of nearby EVCSs, average distance of nearby EVCSs, traffic volume and traffic congestion are considered and the charging frequency of EVCSs is used as the output. The result of efficiency measurement shows that not many EVCSs has most of charging demand at certain periods of time, while the others are facing with anemic charging demand. Tobit regression analyses show that the traffic congestion negatively affects the efficiency of EVCSs, while the traffic volume and the number of nearby EVCSs are positive factors improving the efficiency around EVCSs. We draw some notable characteristics of efficient EVCSs by comparing means of the inputs related to the groups classified by K-means clustering algorithm. This analysis presents that efficient EVCSs can be generally characterized with the high number of nearby EVCSs and low level of the traffic congestion.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.51-70
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• 2021

This study measured the environmental efficiency of 21 international airports based on sustainability reports issued by each airport for 2018. As many sectors in the industry paid attention to social and environmental responsibilities, airport operators comprise one of the leading sectors that streamlined their facilities to become increasingly sustainable and environmental. Nevertheless, studies on the environmental operations of airports are insufficient compared with studies on economic or operational efficiency. Therefore, the current study aims to determine any possible improvement in the environmental inefficiency of airports with the utilization of directional distance function (DDF) and to examine operational efficiency with the application of the data envelopment analysis (DEA). The majority of airports have operated their facilities efficiently, but not all have effectively managed pollutants generated by airports. Furthermore, many airports can still potentially reduce CO₂ and water consumption. This study suggests several implementable environmental improvements to the aviation sector. Moreover, other industrial sectors may use the research as a benchmark for enhancing environmental efficiency.

• Journal of Korea Port Economic Association
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• v.38 no.2
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• pp.123-138
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• 2022

Korea has been huge investments in its port system, annually upgrading its infrastructure to turn the ports into Asian hub port. However, while Busan port is ranked fifth globally for container throughput, Other Korean ports are ranked much lower. This article applies Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI) to evaluate selected major Korean seaports' operational efficiency and productivity from 2010 to 2018. It further integrates Principal Component Analysis (PCA) into DEA, with the PCA-DEA combined model strengthening the basic DEA results, as the discriminatory power weakens when the variable number exceeds the number of Decision Making Units(DMU). Meanwhile, MPI is applied to measure the seaports' productivity over the years. The analyses generate efficiency and productivity rankings for Korean seaports. The results show that except for Gwangyang and Ulsan port, none of the selected seaports is currently efficient enough in their operations. The study also indicates that technological progress has led to impactful changes in the productivity of Korean seaports.

• Journal of Technology Innovation
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• v.31 no.1
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• pp.175-213
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• 2023

As the importance of industry-university cooperation continues to increase in a knowledge-based society, the government is implementing various projects related to industry-university cooperation. However, despite the government's support, it has not achieved satisfactory results, and the need for empirical performance analysis to diffuse the results of industry-university cooperation is increasing. In this study, DEA was used to analyze the Industry-University cooperation performance of universities participating in LINC+ program. Efficiency analysis was performed using the CCR model and the BCC model, and the return to scale and causes of inefficiency were analyzed through the scale efficiency analysis. As a result of the analysis, it was found that there were differences in LINC+ performance depending on the region where the university is located and that each university had different goals for inefficiency improvement. The results of this study will contribute to improving the university's operational efficiency and strengthening competitiveness, and are expected to be utilized in the establishment of follow-up program plans for LINC+.