• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.273-282
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• 2021

Nursing home plays a role in providing elderly care in the context of China's rapid population aging, but little understanding of the efficiency of the nursing homes. In this paper, we investigated the efficiency in nursing homes using Data Envelopment Analysis (DEA) and Malmquist index (MPI) for the modeling of the number of nursing home beds, fixed assets, and medical personnel as input variables, and the number of elderly people of self-care, the number of elderly people of partial self-care, the number of bed-ridden elderly people and the income of nursing homes as output variables. Stratification analysis showed that the top two provinces in the DEA-CCR yield were Beijing and Shanghai in the five-year survey period. Four provinces (Beijing, Jiangsu, Shandong, and Shanghai) scored 1.00 in terms of DEA-BCC yield. The MPI analysis showed that Hainan ranked the highest five-year average in the included provinces. In terms of resource utilization, internal management, operation scale, and other aspects, the nursing homes in the provinces with high-efficiency evaluation results show high efficiency and technological progress, whereas the areas with low-efficiency evaluation showed a feature of the improving technical efficiency.

• The Journal of the Korea Contents Association
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• v.9 no.5
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• pp.224-229
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• 2009

This study measures the relative efficiency and productivity change of the Korean Non-Life Insurance Firms using DEA model and Malmquist Index for 2004-2007. The main results of this study can by summarized as follows. First, in case of efficiency of CCR for 2004-2007, the number of efficient firms(CCR value is one) are one firm, one firm, one firm, one firm respectively. Second, in case of efficiency of BCC for 2004-2007, the number of efficient firms(BCC value is one) are five firms, five firms, six firms, six firms respectively. Third, In case of return to scale for 2004-2007, DRS are five firms, DRS are five firms, DRS are six firms, DRS are six firms respectively, Fourth, Malmquist Index representing productivity change for 2004-2007 are 0.99 in 2004-2005, 1.04 in 2005-2006, 1.06 in 2006-2007.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.470-481
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• 2020

Cultural industry's role in national economic growth has increased gradually and drawn increasing attention due to the immense window effect on other industries. Especially, China has fully pushed forward with the development of cultural industry to sophisticate industrial structure since the 2000's. In Korea, the cultural industry has played the leading role in the national economic growth through intensive investment relatively early compared with China. Under the circumstance, this study compared the cultural industry efficiency between China and Korea to examine cultural industry's impact on economic growth and its potentials. The greatest difficulty in comparing the cultural industry efficiency between China and Korea is the development of comparable statistical data. This study chose the number of businesses and the number of employees as the input variables for efficiency analysis and the sales of cultural industry, the output variable. Also, the efficiency was comparatively analyzed through DEA-Malmquist index. Integrated DB about local governments and basic data from KOSIS were used for Korean data and the National Bureau of Statistics of China's data were used for Chinese data. The analysis period was set to 2013-2017. According to analysis, the Malmquist index for Korea was 1.048 and China, 1.041. In other words, Korea improved the efficiency by 4.8% during the analyzed period and China, 4.1%. This result can be attributed to the fact that the cultural industry in Korea was reaching maturity during this period while the cultural industry in China was entering the growth period.

• Journal of Technology Innovation
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• v.11 no.2
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• pp.151-173
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• 2003

This paper analyses the efficiency and productivity of R&D system across time (1991${\sim}$2000) and 16 OECD countries using multi-output and multi-input non-parametric frontier methods such as DEA (data envelopement analysis) and Malmquist productivity indexes. Malmquist productivity indexes are decomposed into two components measures, namely technical change and efficiency change. To calculate R&D efficiency and productivity, we used R&D stock and the number or researchers as R&D input proxies and the number of adjusted SCI papers and U.S. patent applications as R&D output proxies. Empirical result shows that Switzerland, Canada, U.S., Australia's R&D efficiencies are the highest and Korea's R&D productivity growth is the highest in the sample for the period. Technical efficiency growth was a more important source of productivity growth than technological innovation.

• Journal of Navigation and Port Research
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• v.44 no.5
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• pp.400-406
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• 2020

In this study, we first measured the malmquist productivity index by DEA among the Korean public firms. Second, there are 12 public corporations whose productivity (MPI) has decreased compared to 2014. This is mainly because of a decrease in productivity, as well as a decrease in the technical efficiency change index (TECI), impacted by the internal environment, and the increase in productivity because of an increase in the technology change index (TCI) impacted by the external environment. Finally, the analysis of the impact on the management assessment scores showed that the productivity (MPI), scale efficiency (CRS), size of sales, operating profitability, and total capital investment efficiency are significantly related (+), except for the asset turnover, which is a static financial ratio. Meanwhile, the management evaluation scores between the high-productivity public corporations and low-performing public corporations were significantly discriminating. Thus, it is confirmed that the nation's state-run companies must manage their MPIs in a time series to score high in management evaluation.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.529-539
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• 2022

This study analyzed the index change in efficiency and productivity for the tax reorganization project of the regional headquarters of Korea Asset Management Corporation using panel data for 3 years from 2017 to 2019 using the DEA-Malmquist analysis model. According to the DEA analysis result, the average of the efficiency by the CCR model of the regional headquarters tax reorganization project of the Korea Asset Management Corporation was 0.671 in 2017, 0.772 in 2018, and 0.699 in 2019, and the average of the efficiency by the BCC model was 0.798 in 2017, 0.851 in 2018 and 0.771 in 2019. As a result of analyzing the Malmquist productivity index, the time series average productivity index MPI increased by 4.5%. These results appear to be attributable to the increase in technological efficiency, technological change, and scale-efficiency change rather than the decrease in net efficiency change. Looking at the change in MPI by year, it decreased by 14.6% in 2017-2018, but increased significantly to 27.8% in 2018-2019. Through the results of DEA analysis of specific tax projects of public corporations, each regional headquarters of Korea Asset Management Corporation will be able to contribute to reinforcing business capabilities through mutual benchmarking.

• Journal of Korea Port Economic Association
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• v.36 no.1
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• pp.183-196
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• 2020

Until now, there have been few studies analyzing the efficiency of the Port of Mokpo and comparing it with other seaports in the country to identify the future direction of development for the port. In this paper, we use the data envelopment analysis (DEA) model in combination with the Malmquist Productivity Index (MPI) to measure the efficiency and productivity of major ports in Korea, focusing on the Port of Mokpo. First, the study identifies which ports are efficient or inefficient based on technical or operational scale. Second, by using the MPI to overcome the shortfalls of the DEA model, the study can compare a port's performance across the years and evaluate the productivity of a port during the research period. Moreover, this study also applies fuzzy C-means (FCM) clustering to classify port groups based on the size of their infrastructure and their efficiency scores. Finally, it is possible to find ways to enhance the efficiency and future direction of development of the Port of Mokpo.

• Journal of Information Technology Applications and Management
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• v.27 no.1
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• pp.1-13
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• 2020

This study aims to measure the efficiency and productivity change of 30 domestic construction companies from 2010 to 2018 using data envelopment analysis(DEA) and Malmquist productivity index (MI). In particular, we used the number of employees, capital stock, and non-current assets as input variables, and sales and net income as ouput variables for the analysis. The dataset used for the analysis of efficiency and productivity changes is the employee profile and financial statements for the companies from 2010 to 2018. We found that the MI of the 30 companies is greater than one since 2013. This is because many years of TEC (Technical Efficiency Change) is greater than 1, which means that the productivity index increases as the TEC increases. In addition, the MI value was less than 1, which lowered the productivity of construction firms in 2018. The results of the study may help decision makers to find effective future management plans by analyzing the internal and external factors.

• The Korean Journal of Health Service Management
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• v.7 no.3
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• pp.225-235
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• 2013

This study purposed to analyze the productivity of regional medical capacity in attracting medical tourist between 2009 and 2011. Data envelopment analysis (DEA) and Malmquist productivity index (MPI) were applied to test the productivity and changes in study periods. The DEA model included a number of doctors, nurses, and beds as input factors, and a number of inpatient and outpatient, and hospital income as output factors. The result of the study were as follow. Jeju had efficiency value of 1 for three years. Seoul, Busan, Daegu, Daejeon, Ulsan, Gyeonggi, Gangwon, Jeonnam, Gyeongbuk, and Gyeongnam showed an increasing trend of efficiency value over three years. Seoul had the efficiency value, 1, in 2011. But, Incheon, Gwangju showed decreasing efficiency score during the study period. MPI showed overall productivity decrease during the period. Further studies will be needed by collecting more time-series data.

• The Journal of Fisheries Business Administration
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• v.41 no.3
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• pp.21-44
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• 2010

The paper estimates changes in total factor productivity and technical efficiency change index and technical change index using Malmquist productivity index(MPI) in fisheries wholesale products over the time period of 2006 through 2008. The model considers a number of employees and operating costs as input factors, and sales and EBIT(earnings before tax and interest) as output factors. The results indicate that, between 2006 and 2007, there is in general technical progress in which TCI(Technical Change Index) indicates 2.7994 in the sale scale of 50 million won through 100 million won, while there are no efficiency in TECI(Technical Efficiency Change Index), PECI(Pure Efficiency Change Index) and SECI(Scale Efficiency Change Index) which are estimated to be around 1. Between 2007 and 2008 technical efficiency and technical progress are generally declined, compared to those of 2006 and 2007. Wilcoxon's rank-sum test shows that there are statistically significant difference of TCI and MPI between two periods at the level of 5%, while there are statistically significant difference of TECI, PECI and SECI between two periods at the level of 5%.