• International Commerce and Information Review
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• v.16 no.4
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• pp.55-75
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• 2014

Non-parametric method such as technology efficiency, DEA/Window model and Malmquist Productivity Index (MPI) are used to measure efficiency and productivity of ICT (Information and Communication Technology) manufacturing industry and service industry over the period 2007-2011. The results of this paper indicate following: (1) Technology efficiency of the ICT manufacturing industry were found as the range of 0.34 and 0.39 over the sample period. Technology efficiency of the ICT service industry were found as the range of 0.16 and 0.20 over the sample period. (2) The geometric average of the Malmquist TFP indexes on ICT manufacturing industry indicated the productivity improvement an average of 8.3 percent. The geometric average of the Malmquist TFP indexes on ICT service industry indicated the productivity improvement an average of 1.6 percent. (3) TIER analysis result on ICT manufacturing industry showed that optimal bench marking made by storage devices${\rightarrow}$wireless communication equipment${\rightarrow}$broadcasting equipment${\rightarrow}$radio, recording and playback devices${\rightarrow}$computers, printers, video and audio-visual equipment path. TIER analysis result on ICT service industry indicated that optimal bench marking made by computers and packaged software${\rightarrow}$wired communication${\rightarrow}$communication, information, detection equipment${\rightarrow}$consulting and construction for computer systems integration${\rightarrow}$industrial machinery and equipment rental${\rightarrow}$telecommunications reseller${\rightarrow}$system software development and delivery${\rightarrow}$hosting path.

• Journal of Korea Port Economic Association
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• v.34 no.1
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• pp.51-64
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• 2018

The purpose of this paper is to analyze the productivity change of the Korean shipbuilding industry between 2001-2008 and 2008-2015 by using MPI(Malmquist Productivity Index) to decompose the sources of total factor productivity growth into technical efficiency change, scale efficiency change, pure efficiency change, technical change. The empirical results are as follows. In the first half of the year (2001-2008), productivity increased by 2.8%, which was due to technological advances rather than technical efficiency. In the second half (2008-2015), productivity change declined by -3.4%. This is attributable to the technical efficiency deterioration and technological degeneration caused by a decrease in shipbuilding orders due to the global economic downturn after the global financial crisis and the rise of Chinese shipbuilding industry. In the first half of the period, productivity change was higher than in the second half. Especially, the difference between the two periods is attributed to the technical change and it was proved by statistical verification. The policy implications of this paper suggest that the government and each DMU need to develop new technologies to cope with changes in the global shipbuilding industry environment and strategies to eliminate inefficiencies in order to increase productivity in the future.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.79-98
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• 2004

Despite its contribution to the Korean medical service industry the question of how efficiently the Korean public hospitals have operated has been unresolved. This study gauges and analyzes the overall efficiency and the Malmquist productivity index in the industry over the period 1992 through 2001. In addition to cost efficiency. we also measure technical, allocative, pure technical and scale efficiencies. Furthermore. the Malmquist index is decomposed into efficiency and frontier changes. We identify several important factors which seem to have strong relationship with various inefficiency estimates. The results indicate that on average the public hospitals has wasted a significant amount of resources and costs over the period. Unlike many other industries, the low level of cost efficiency of the public hospital industry is mainly due to allocative inefficiency rather than technical inefficiency. The Maimquist productivity indices seem both due to the frontier change and efficiency change, but with more effect by the former. The results also indicate that the turnover of hospital beds has played an important role in determining efficiency and productivity of this important industry.

• Journal of Distribution Science
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• v.11 no.8
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• pp.5-14
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• 2013

Purpose - We live in a world of constant change and competition. Many airports have specific competitiveness goals and strategies for achieving and maintaining them. The global economic recession, financial crises, and rising oil prices have resulted in an increasingly important role for facility investment and renewal and the implementation of appropriate policies in ensuring the competitive advantage for airports. It is thus important to analyze the factors that enhance efficiency and productivity for an airport. This study aims to determine the efficiency levels of 20 major airports in East Asia, Europe, and North America. Further, this study also suggests suitable policies and strategies for their development. Research design, data, and methodology - This paper employs the DEA-CCR, DEA-BCC, and DEA-Malmquist production index analysis models to determine airport efficiency. The study uses data on the efficiency and productivity of the world's leading airports between 2006 and 2010. The input variables include the airport size, the number of runways, the size of passenger terminals, and the size of cargo terminals. The output variables include the annual number of passengers and the annual cargo volume. The study uses basic data from the 2010 World Airport Traffic Report (ACI). The world's top 20 airports (as rated by the ACI report) are investigated. The study uses the expanded DEA Model and the Super Efficiency Model to identify the most effective airports among the top 20. The Malmquist productivity index analysis is used to measure airport effectiveness. Results - This study analyzes longitudinal and cross-sectional data on the world's top 20 airports covering 2006 to 2010. A CCR analysis shows that the most efficient airports in 2010 were Gatwick Airport (LGW), Zurich Airport (ZRH), Vienna Airport (VIE), Leonardo da Vinci Fiumicino Airport (FCO), Los Angeles International Airport (LAX), Seattle-Tacoma Airport (SEA), San Francisco Airport (SFO), HongKong Airport (HKG), Beijing Capital International Airport (PEK), and Shanghai Pudong Airport (PVG). We find that changes in airport productivity are affected more by technical factors than by airport efficiency. Conclusions - Based on the study results, we offer four airport development proposals. First, a benchmark airport needs to be identified. Second, inefficiency must be reduced and high-cost factors need to be managed. Third, airport operations should be enhanced through technical innovation. Finally, scientific demand forecasting and facility preparation must become the focus of attention. This paper has some limitations. Because the Malmquist productivity index is based on the hypothesis of the, the identified production change could be over- or under-estimated. Further, as DEA estimates the relative efficiency. It also cannot generalize to include all airport conditions because the variables are limited. To measure airport productivity more accurately, other input variables and environmental variables such as financial and policy factors should be included.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.35-47
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• 2004

Using data envelopment analysis, this paper annually estimates Malmquist total factor productivity indices and decomposes them into productive efficiency change, technical change, and scale change components for three publicly-owned rail transit properties: the Seoul Subway Corporation(SSC), the Seoul Metropolitan Electrified Railways Sector of Korea National Railroad (SMESRS) and the Busan Urban Transit Authority (BUTA). The paper then conceptualizes that the property produces a single output(car-kilometers) using four inputs(labor, electricity, car and maintenance, and track) and uses unbalanced panel data consisted of annual observations on SSC, SMESRS and BUTA. The results show that the average annual growth rate of productivity of the three properties is 6.6 percent, which is 0.5 percent less than the average annual increasing rate of their labor price. They also show that the greatest part of the growth in productivity is explained by technical change and to a lesser degree by scale change and changes in productive efficiency though each of the three components contributes more than 20 percent to the growth in productivity, These results suggest that the three properties should base the increasing rate of their wages on the growth rate of their productivity and utilize existing technologies more efficiently prior to introducing new ones to raise their productivity, and that all the three components should be considered to evaluate their productivity more correctly.

• Proceedings of the Korean Statistical Society Conference
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• 2001.11a
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• pp.199-204
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• 2001

1997년 IMF 경제위기 이후 우리나라의 금융산업은 급격한 변화를 겪고 있다. 지난 4년간 은행들을 비롯한 금융기관들이 대형화를 통한 경쟁력 강화를 위해 합병이 실시되었다. 은행합병의 궁극적인 목적은 합병에 의해 규모를 대형화하고 업무범위를 다양화하여 수익규모를 증대시키고 수익원을 다원화하는 한편, 경영자원의 투입과 활용을 효율화하고 시장지배력을 확충하여 경영성과를 제고함으로써 기업가치를 증진시키는데 있다고 할 수 있다. 본 연구에서는 1997년 이후에 본격적으로 이루어진 합병은행들을 대상으로 맘퀴스트 ${\ulcorner}$Malmquist${\lrcorner}$ 총요소생산성(Total Factor Productivity) 지수를 사용하여 그 성과를 측정해 보았다.

• Korea Journal of Hospital Management
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• v.10 no.4
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• pp.51-74
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• 2005

This paper presents an analysis of the current status of domestic hospital industry which went trough the time of new hospitals operated by chaebols from 1994 to 2003 and the dramatic changes of medical service environment such as IMF relief loan in 1997 and the separation of prescription and dispensing (SPD) in 2000. For the sake of righteous policy-making in the future, this paper presents a productivity analysis of the management and administration of 38 tertiary hospitals nationwide in the past 10 years. The analysis is based on the Malmquist index approach using linear programming. d prepare a productivity index that measures not merely efficiency but the technological evolution and adjustment to changing environments.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.547-553
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• 2022

This study analyzed the changes in the operational productivity of fourteen Korean container lines from 2019 to 2021 using MP I(Malmquist Productivity Index). The results indicated that the operational productivity of the shipping companies has increased by 38.4% annually, representing the TCI (Technical Change Index) increasing by 58.3% and the TECI (Technical Efficiency Change Index) decreasing by 12.6%. The increase in the operational productivity of the container shipping lines was mainly attributed to the high rise in ocean freight rates rather than an increase in fleet size or ship technical efficiency. However, the deep-sea shipping lines (i.e. HMM and SM lines) experienced increases in both the TCI and TECI, which was not the case for other shipping lines(i.e. Intra-Asian short-sea shipping lines). The intra-Asian short-sea shipping lines enhance their productivity due to the TCI but failed to appreciate the cost savings of the increased fleet effects due to the low SECI(Scale Efficiency Change Index) values.

• 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 the Korea Contents Association
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• v.12 no.8
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• pp.330-342
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• 2012

Most of professional baseball teams are not good for business condition because of operation costs in spite of support of mother company. This study measured the relative efficiency and productivity change of the Korean professional baseball teams using DEA model and Malmquist Index for 2006-2008. The main results of this study can be summarized as follows. First, in case of efficiency of CCR for 2006-2008, the number of efficient professional baseball teams(CCR value is one) are two(Doosan Bears, Samsung Lions), two(Doosan Bears, SK Wyberns), two(Lotte Giants, LG Twins) respectively. Second, in case of efficiency of BCC for 2006-2008, the number of efficient professional baseball teams(BCC value is one) are three(Doosan Bears, Samsung Lions, LG Twins ), four(Doosan Bears, SK Wyberns, Samsung Lions, Kia Tigers), four(Lotte Giants, LG Twins, SK Wyberns, Samsung Lions) respectively. Third, average of Malmquist Index representing productivity change for 2006-2008 are 1.0615, 1.0293 respectively. These values mean increase of productivity. Results of this study can be used by inefficient professional baseball teams to improve inefficiency.