• Journal of Korea Port Economic Association
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• v.28 no.2
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• pp.155-177
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• 2012

This paper aims at measuring the changes of Malmquist productivity and technical efficiency of Korean shipbuilding Industry and examinig their determinants utilizing the panel analysis. The increase of the technological progress was greater than technical efficiency, resulting in the increase of the total factor productivity for the period of 2004-2010. This study also employs the panel technique to analyse the effects of Employee, Dock, and Length on the changes of Malmquist productivity and technical efficiency. The dependent variables are obtained from three combinations, which are (Employee, Dock, and CGT), (Employee, Length, and CGT), and (Dock, and Length, and CGT). The empirical results show that all of the explanatory variables have a positive effect on the change of Malmquist productivity and technical efficiency.

• 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.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.1
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• pp.99-111
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• 2016

This paper presents a framework to analyze the change in the research and development (R&D) efficiency of government-funded research institutes (GRIs) in Korea. Cumulative data envelopment analysis/Malmquist index method is utilized to analyze the changes in R&D efficiency of GRIs. Data analysis of the R&D activities of 10 GRIs in Korea Research Council of Fundamental Science & Technology showed that the average R&D efficiency of the 10 GRIs improved from 2009 to 2013. However, the efficiency of a few GRIs decreased in terms of the catch-up index. The proposed framework can help management teams diagnose the current state of R&D activities and determine the efficacy of strategic actions by comparing efficiencies in the past.

• The Korean Journal of Health Service Management
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• v.9 no.3
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• pp.43-55
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• 2015

Objectives : This study analyzed the managerial efficiency of hospitals and identified the productivity trends for three years. Methods : Data were collected from 44 tertiary hospitals and 32 university hospitals from 2009 to 2011. Efficiency scores and productivity trends were evaluated with the DEA (Data Envelopment Analysis) method. The input variables were the numbers of beds, doctors, nurses, and health personnel, and the medical costs. The output variables were the numbers of outpatients, and inpatients, and the medical revenues. Along with the traditional input-oriented DEA analysis, the Malmquist Productivity Index(MPI) was calculated. Results : First, the mean values of the study variables showed gradual increases in all the variables for all the study years. Second, technical efficiency scores varied depending on the study year. Third, MPI decreased from 2009 to 2010 (MPI=0.986), and then increased from 2010 to 2011(MPI=1.011). The contributions of the Efficiency Change Index and Technical Change Index on the MPI varied depending on the study year. Conclusions : This study provides information to hospital managers about changes in hospital performances. External environments had more influence on hospital performances, and hospital managers will need to manage these influences from factors surrounding the hospitals.

• 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.

• 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.

• Journal of Digital Convergence
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• v.16 no.6
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• pp.75-84
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• 2018

Although many logistics companies are interested in project logistics, the existing research has been limited to the growth potential of project logistics market and the high barrier and importance of project logistics. This study analyzes using DEA the operational efficiency of forwarding companies registered in major overseas construction EPC companies and performing logistics services for overseas plant construction projects. For efficiency analysis, Super-SBM analysis and Malmquist analysis are used among DEA analysis techniques. As a result of the Super-SBM analysis, DMU 5 ranked first at 1.807. DMU 5 is more efficient than the other large corporations because it has the stable supply of its parent company H and the smallest input and output variables among the large corporations. As a result of Malmquist analysis, TCI, which is a technological development, showed a fluctuation while TECI showed a relatively stable variation. In addition, there is a difference in scale between major companies and small and medium sized companies. So, it is necessary to identify the efficiency improvement strategy for each group and apply it to the practical work.

• The Journal of the Korea Contents Association
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• v.10 no.10
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• pp.456-463
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• 2010

This study measured the relative efficiency and productivity change of the Korean professional sport teams using DEA model and Malmquist Index for 2006-2009. The main results of this study can be summarized as follows. First, in case of efficiency of CCR for 2006-2009, the number of efficient professional sport teams(CCR value is one) are two(Daejeon Citizen, Incheon United), three(Daejeon Citizen, Incheon United, FC Seoul), two(Daejeon Citizen, Incheon United), three(Kyungnam FC, Incheon United, FC Seoul) respectively. Second, Malmquist Index representing productivity change for 2006-2009 are 1.035, 0.9658, 1.5331 for Kyungnam FC, 1.2514, 0.8948, 0.9056 for Daegu FC, 1.1768, 0.8620, 0.9722 for Daejeon Citizen, 0.9368, 1.2609, 0.7714 for Incheon United, 1.0000, 1.0000, 1.0000 for FC Seoul, respectively. This result will be used by inefficient professional sport teams to improve inefficiency.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.323-330
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• 2009

This study measures the relative efficiency and productivity change of the Korean 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 six firms, five firms, four firms, seven firms respectively. Second, in case of efficiency of BCC for 2004-2007, the number of efficient firms(BCC value is one) are eight firms, nine firms, ten firms, twelve firms respectively. Third, In case of return to scale for 2004-2007, DRS are nine firms and IRS are two firms, DRS are five firms and IRS are five firms, DRS are five firms and IRS are four firms, DRS are five firms and IRS are two firms respectively, Fourth, Malmquist Index representing productivity change for 2004-2007 are 1.12 in 2004-2005, 0.97 in 2005-2006, 1.05 in 2006-2007.

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.303-313
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• 2010

The purpose of this study is to evaluate the performance efficiency and productivity change of the regional public hospital in Korea. We use DEA(Data Envelopment Analysis) for CCR, BCC model, and MPI(Malmquist Productivity Index). DEA is a useful nonparametric technique for measurement of efficiency of a DMU(Decision Making Unit) and MPI is a evaluation method to measure DMU's productivity change. We utilize 34 regional public hospital's time-series data over 6 years from 2003 to 2008.The results of this study were as follows. First, technical efficiency(TE) shows that approximately 3.6% of inefficiency exists on the regional public hospitals and it reveals that the cause for technical inefficiency is due to scale inefficiency. Second, MPI's results show that regional public hospital made effort to improve total factor productivity change to raise technical efficiency. In order to raise efficiency, the regional public hospitals should deploy internal innovation and the government should support welfare policies.