• International Area Studies Review
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• v.14 no.2
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• pp.43-60
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• 2010

This paper measures R&D efficiency and productivity changes of 24 nations including Korea, Japan and China by the non-parametric Malmquist productivity index. The principle findings of this study are as follows. First, R&D efficiency scores of Korea and Japan are 0.837 and 0.834 respectively. Meanwhile China shows 0.420, the worst performance among the selected countries. Second, Korea marked annual productivity increase of 25%, highest among the selected countries', for 2000-2005. R&D productivity in Japan and China, however, decreased 1.9% and 0.9% respectively. Third, annual rates of technology change and technical efficiency change in Japan are 0.6% and -2.5%. Therefore decrease of productivity in Japan is mainly due to technical inefficiency. In case of China, improvement of technical efficiency is the main contributor to productivity growth but technical progress has edged downward in the sample period. In Korea, with annual rate of technology change and technical efficiency change being 5.2% and 18.2% respectively, both efficiency improvement and technical progress has pulled the R&D productivity growth.

• International Commerce and Information Review
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• v.14 no.3
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• pp.323-350
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• 2012

This study analyzes the efficiency of 25 shipping companies in Korea over the period 2005-2009, using Data Envelopment Analysis (DEA). Among 31 companies that listed in order of decreasing sales volume for the period 2006-2010, the sample companies has been selected on the ground of data availability. This study computes the companies' efficiency, estimates their year-on-year Malmquist productivity index, and analyzes the cause leads to the changes in the productivity, In particular, this study attempts, by dividing the companies into two group, listed or not, to compare the changes in the productivity and analyze the reasons. The results from static analysis based on CCR and BCC model indicate that listed companies are higher efficient than unquoted companies. The results from tests on the productivity changes based on the Malmquist productivity index show that 19 unquoted companies increase their average productivity by 16.2 percent year after year during the period but 6 listed companies increase by 0.5% during the same period.

• Journal of the Korean Society for Railway
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• v.19 no.3
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• pp.397-407
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• 2016

This study analyzed the efficiency change and the factors affecting productivity change for the six railway operation corporations that are local public enterprises; study was performed with the DEA-CCR Model and Malmquist Productivity Index, using data collected from 2010 to 2014. Since it was not feasible to collect data on the operating expenses and the number of employees of each of the lines, the efficiencies of each operation corporation were analyzed by integrating the operation corporations, and the Malmquist Productivity Index was used to investigate the trend of the periodical productivity change. Average efficiency for urban railway operation corporations was found to be higher in the case of the bigger corporations. In 2014, the Seoul Metro and the Daejeon Metropolitan Express Transit Corporations were analyzed and found to be the most efficient operation corporations. The Malmquist Productivity Index was used to determine the periodical change; the average MPI was 1.06, with a continuous increase of productivity. The analysis showed that changes of technology were generally more obvious than change of technology efficiency for all six operation corporations.

• Environmental and Resource Economics Review
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• v.19 no.4
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• pp.733-752
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• 2010

This study applies the Luenberger indicator approach to estimate productivity of the Korean fossil-fueled power plants. A panel data set of 25 power plants was used. The method incorporates $CO_2$ emission as an undesirable output and shows that ignoring $CO_2$ emission overestimates the productivity change. There are two sources of overestimation. First, the usual method estimates productivity change ignoring the increase in $CO_2$ emission that occurred during the study period. Second, the productivity change estimated by the usual method that does not incorporate $CO_2$ emission is very sensitively affected by the change in operation rate. The paper decomposes the productivity change into the efficiency change and the technical change. The results show that the two sources contribute to the productivity change almost equally. It is also shown that the size and the pattern of productivity change are dependent on the plants' fuel types. Non-LNG power plants which saved their energy consumption and thereby reduced their $CO_2$ emission have achieved relatively high rate of productivity improvement.

• Environmental and Resource Economics Review
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• v.21 no.4
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• pp.947-980
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• 2012

This study analyzes the long-run impacts of climate change on Korean agriculture and economy. We estimate the impacts of climate change on the productivities of major agricultural products including rice, dairy and livestock using both a simulation approach and a semiparametric econometric model. The former predicts a decline in productivity while the latter predicts an increase in productivity due to climate change, especially for rice. A recursive dynamic CGE model is used to analyze the general equilibrium impacts of productivity change under the two different scenarios, derived from the two productivity analysis approaches. The loss of GDP in 2050 is 0.2% or 0.02% of total GDP depending on the scenario. It is shown that the losses in dairy and livestock sectors are larger than that in rice sector, although the losses in those two non-rice sectors have been ignored by most existing works.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.91-102
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• 2020

This study constructed production frontiers of inputs and outputs in a sequential manner, measured inefficiencies by applying a non-radial sequential weighted Russell directional distance function to these frontiers, and analyzed Luenberg productivity indices and the contribution of each of input and output factor based on these distances. The results are as follows. First, the productivity of banks increased due to technical changes after the global financial crisis. Second, productivity growth decreased between 2009 and 2014 due to technical changes after the recession, as previous studies have shown that technology progressed before the global financial crisis but then largely decreased or remained the same thereafter. After 2014, the productivity of banks improved. This result may be due to both technology improvement after 10 years of stagnation and reduction of inputs and non-performing loans. Third, the 3.6% annual of productivity growth for 10 years was comprised of 1.77% household loans, 0.67% corporate loans, 0.98% manpower, 1.18% non-performing loans, -0.5% total deposits, and -1.25% securities. Finally, this study has limitations since it could not control risks such as capital structure and interest volatility.

• Journal of Labour Economics
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• v.33 no.1
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• pp.85-107
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• 2010

In this article, since the financial crisis, Korean employment movement to service market, productivity gap between manufacturing and service industry was significant compared with other countries. The results from productivity decomposition show that negative structural changes, which employment increase is contrary to the productivity, have been intensified since the financial crisis. It is caused from a different developing pattern. While the proportion of employment was reduced, productivity has improved in manufacturing industry. While the developing was due to the high increase of the employment proportion in service industry, productivity was not improved significantly. This tendency is clearly revealed in international comparisons. In Korea the negative trend of structural changes in service industry are intensified compared to manufacturing industry after the financial crisis.

• Journal of Practical Agriculture & Fisheries Research
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• v.20 no.1
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• pp.107-123
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• 2018

The global impact of climate change on agriculture is now increasing. The purpose of this study was to investigate the effect of climate change on livestock productivity. The variables that have the greatest influence on climate change factors were examined through previous studies and expert surveys. We also used the actual productivity data of livestock farmers to investigate the relationship with climate change. In order to evaluate the climate for changes in livestock productivity, national representative data (such as bullocks, dairy, pigs, laying hens, and broilers) were surveyed in Korea. Also, to select and classify evaluation indexes, we selected climate change factor variables as prior studies and studied the weighting factor of climate variable factors. In this study, the researchers of industry, academia, and farmers in the livestock sector conducted questionnaires on the indicators of vulnerability to climate change using experts, and then weighed the selected indicators using the hierarchical analysis process (AHP). In order to verify the validity of the evaluation index, was examined using domestic climate data (temperature, precipitation, humidity, etc.). Correlation and regression analysis were performed. The empirical relationship between climate change and livestock productivity was examined through this study. As a result, we used data with high reliability of statistical analysis and found that there are significant variables.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4177-4183
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• 2014

This study estimated and decomposed the productivity changes into technological change and efficiency change components for the photonics industry and examined ways of imporving the productive efficiency. Unlike most previous studies, this study employed a non-oriented Malmquist productivity index, which is a non-radial method and deals directly with the input surpluses and output shortfalls. The empirical results show that the productivity of the photonics industry has increased. The main reason for this is the increase in technical efficiency. In addition, there was a statistically significant difference in the productivity changes according to the firm's geographic location and participation in government support programs. These findings suggest that the government's regional strategic industry promotion policy has contributed to improvements in the productive efficiency of photonics industry. The approach presented in this study could be used as a practical reference guide to help enhance the competitiveness of the photonics industry.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.1
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• pp.49-57
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• 2006

In order to strengthen the competitiveness of port against calling for the huge vessel and reducing the shipping service time, the productivity of container terminal must be improved. This productivity variously results according to the kinds of productivity evaluation model, input elements like yard, equipment, employee, facility, etc,. But, it is discussed that the productivity is measured by partial productivity evaluation model or general input elements. Therefore, we measured for the productivity of the container terminal using the Developed the data Envelopment Analysis (DEA), which is developed in order to evaluate the relative efficiency of decision making units - it's difficult to clear cause and effect between input and output. We measured the whole productivity of container terminal in Busan according to decision of the correct input elements. And we investigated the change of the productivity measurement result according to input elements, presents more accurate productivity evaluation model in container terminal.