• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.79-86
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• 2009

The purpose of this paper is to analyze the 24 mail center's efficiency and productivity changes from first quarter to fourth quarter of 2008 using window analysis and Malmquist productivity index. Row views of window analysis results make it possible to determine trends and/or observed behavior with the same data set, and column views to examine the stability of results across different data sets. Malmquist productivity indexes greater than unity translate into improvements in productivity, and less than unity mean deterioration in performance over time. The results of this study suggest that DEA models under dynamic situations such as window analysis and Malmquist productivity index enable us to comprehend the efficiency and productivity changes over time and to show the direction of improvements.

• Health Policy and Management
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• v.23 no.1
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• pp.78-89
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• 2013

This study empirically analyze efficiency and productivity changes of public hospitals of Korea using data envelopment analysis/Window model and global Malmquist indices model. We use the ten-year data from 2001 to 2010 of 30 regional public hospitals listed database from the Association of Korean Regional Public Hospitals. The main focuses are to reveal whether the technical inefficiency are improved as time goes by, and efficiency and productivity are affected by environmental factors. The results can be summarized as follows. First, the efficiencies of public hospitals rise in trend as time passes. Second, regional public hospitals show the different average efficiencies according to their regional type, hospital type, operational type, medicaid type, and demand and supply conditions by Mann-Whitney U-tests. Third, technical efficiency changes mainly contribute to 4.4% annual average growth rate of productivity of regional public hospitals during that period. Our findings have some policy implications. It is confirmed that there exist some environmental inefficiencies, and those inefficiencies can not be overcome through just improving the inner management system. Thus, policy and institutional changes are necessary for regional public hospitals to improve efficiency and productivity overall.

• Journal of Korea Port Economic Association
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• v.28 no.4
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• pp.59-77
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• 2012

Inland transportation system has been improving inefficiencies and structural problems due to excess of supply. Therefore, inland transportation market needs to reform its regional logistics structure in order to increase its competitiveness. To improve the solution, the research studied efficiencies and productivity of inland transportation systems in regions. In order to obtain specific facts, each cities' five years of (2005-2009) balanced panel data on inland transportation system has been studied. According to CCR and BCC analysis, Ul-San has been evaluated as the most efficient DMU during 2005-2008. In addition, in 2009, Seoul was the most efficient DMU. Also, according to Window analysis, Gwan-Ju and Gwangwon-do scored 0.062. Therefore, they were estimated as stable DMUs. According to Malmquist productivity analysis, average productivity indexes of four terms of Chungcheongnam-do and Chungcheongbuk-do haves been increased to 6.6% and 7.3%. I hope this study contributes to the improvement of regional inland transportation system.

• Journal of Korea Port Economic Association
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• v.26 no.3
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• pp.165-174
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• 2010

DEA converts multiple inputs and outputs of a decision unit into a single measure of performance, generally mentioned as relative efficiency. DEA has been applied successfully as a performance evaluation tool in many fields including manufacturing, banks, pharmacies, and hospitals to name a few. This paper applies the input-oriented DEA model, DEA/Window analysis, and Malmquist indices to the 9 regions in Korea to measure the efficiency and productivity. The empirical results show the following findings. First, the super efficiency indicate that efficiency of Group 2 is greater than Group 1. Second, Malmquist indices show that productivity of Group 2 is less than Group 1. Third, DEA/Window of Group2 show that Chungnam is most stable, while Jeonnam is most unstable.

• Journal of Korea Port Economic Association
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• v.28 no.2
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• pp.113-128
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• 2012

By strengthening the market control and expanding the networks, providers of global logistics are expanding their service scope. Warehouses connects networks to between internal and external warehouses worldwide by using employees. The paper focuses on analyzing the efficiency of the top forty Global Logistics Providers. Therefore, the study classifies the factors which specify the efficiency of a total logistics industry and verified its firmness. Furthermore, the most recent published reports by Logistics Quarterly and Armstrong Association in 2012 was used in order to guarantee credibility of the study. For scope period for analysis, this study utilizes three years of materials, from 2007 to 2010. By applying the DEA Window model and Malmquist, the trend in efficiency and stableness was analyzed. Consequently, the main purpose of the paper is evaluating the efficiency. Also, analyzing its determinants and illustrating a long-term relationship between the annual turnover and the number of Industry Focus/Key Customers was used as output measures. In addition, the number of warehouses worldwide and employees worldwide, of Logistics Providers were used as input measures.

• Journal of Information Technology Services
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• v.5 no.1
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• pp.1-16
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• 2006

This paper analyzes the technical efficiencies of 40 Korean system integration firms using data envelopment analysis (DEA) and Malmquist productivity indices. Technical efficiencies on average had been decreased over the five year period and the efficiency difference between best practice firms and catch-up firms had been increased during this period, meaning that the industry structure has become matured and the possibilities for catch-up firms to be efficient are not remained so much. The differences in efficiency by the differences in ownership structures are statistically significant. It implies that the efficiencies of group-affiliated firms have come from benefits such as the captive market umbrellas, not from their own management competencies. In addition, the technical efficiency is highly correlated with captive market sales, information productivity, sales per employees, rates of value added, returns on invested capital, and EBITDA.

• 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.

• 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 Korea Port Economic Association
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• v.28 no.1
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• pp.143-157
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• 2012

By strengthening the market control and expanding the networks, providers of global logistics are expanding their service scope. The warehouses connect networks to internal and external warehouses by using logistics providers. The paper focuses on analyzing the efficiency of warehouses on each district. Therefore, the study classifies the factors which specify the efficiency of a total logistics of warehouse industry and warehouses' employees and the number of warehouses on district. Furthermore, the most recently published reports by National Center for Statistics in 2012 was used in order to guarantee credibility of the study. This study utilizes five years of materials, which are from 2005 to 2009. By applying SBM (Slack Based Measure), DEA Window model, and the Malmquist productivity model, the trend in efficiency and stableness were analyzed. The principal purpose of the paper is evaluating the efficiency. Also, analyzing its determinants and illustrating a long-term relationship between the regional warehouses and annual turnover of the warehouses were used as output measures. In addition, the number of warehouses of each region, employees, warehouses equipments, and the Logistics Warehouses Providers were used as input measurements. As a result, Malmquist productivity model and annual stableness has shown a continuous increasing. Ultimately, to be approved as product of Korea, a new stratiges that meet the standards and Rules of Origins by FTA should be developed. Therefore, there must be a development that takes regional characteristics into consideration.

• Journal of Korea Port Economic Association
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• v.26 no.4
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• pp.188-206
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• 2010

Data Envelopment Analysis(DEA) is an operations research-based method for measuring the performance efficiency of decision units that are characterized by multiple inputs and outputs. DEA has been applied successfully as a performance evaluation tool in many fields. However, it has not been extensively applied in the shipbuilding industry. This paper applied the input-oriented DEA model, and Malmquist indices to the 7 shipbuilding firms to measure the efficiency and productivity changes during the period of 2004 to 2009. The Malmquist indices will be decomposed into three components such as pure efficiency change, scale efficiency change, and technical change. The empirical results show the following findings. First, the DEA findings indicate that main source of inefficiency is scale rather than pure technical. Second, the Malmquist indices show that an overall decrease in productivity.