• Title/Summary/Keyword: Malmquist 생산성지수

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Measuring the Efficiency in Korean Railway Transport using Data Envelopment Analysis (자료포락분석 기법을 이용한 우리나라 철도수송의 효율성 측정)

  • Kim, Hyun-Woong;Kook, Kwang-Ho;Moon, Dae-Seop;Lee, Jin-Sun
    • Journal of the Korean Society for Railway
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    • v.12 no.4
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    • pp.542-547
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    • 2009
  • The objective of this paper is to measure the relative technical efficiency of Korean railway transport service. Previous studies on the efficiency in Korean railway service have carried out before the structural reform of Korean railway industry in 2004, whereas this study used the latest data which reflected the impact of reform. We analyzed the efficiency in Korean railway transport by means of measuring the technical efficiencies of other countries, these were estimated with data envelopment analysis. Using data from 22 railway operators over the period $2000{\sim}2006$, the results indicate that the Korean railway transport has been operated efficiently as compared with others.

R&D Efficiency and Productivity in Korea, Japan and China (한·중·일 연구개발투자의 효율성 및 생산성변화 비교 분석)

  • Cho, Yun Ki
    • 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.

Evaluating the Multi-Period Management Efficiency of Domestic Online-Shopping Companies (DEA와 Malmquist 생산성지수를 이용한 우리나라 온라인쇼핑업체의 다기간 경영 효율성 분석)

  • Ma, Jin-Hee;Ja, Yoon-Ho;Ahn, Young-Hyo
    • Journal of Distribution Science
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    • v.13 no.4
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    • pp.45-53
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    • 2015
  • Purpose - Online shopping enables consumers to conveniently purchase products irrespective of the time and place. As a result, several online shopping companies have emerged to cater to this growing market and, therefore, the competition among them has become increasingly intense. This paper evaluates the comparative efficiency of online shopping companies for a multi-year period (2009-2013), in order to help online shopping managers identify major drivers for enhancing management efficiency and the subsequent competitiveness. Research design, data, and methodology - The researchers collected the data from 2009 to 2013 from the distribution yearbook. This paper analyzes the marketability (sales figures), profitability (business profits), and management conditions (net profits) of domestic online shopping enterprises by incorporating information on human resources (number of employees) and material resources (total assets and capital). Therefore, the number of employees, total assets, and capital are selected as input variables, and sales figures, business profits, and net profits as the output variables. In this study, Data Envelopment Analysis (DEA) was used to measure the comparative efficiency of domestic online shopping companies. In addition, the Malmquist Productivity Index was used to evaluate the trend of change of Decision Making Units' (DMUs') efficiency for a multi-year period. Results - First, as of 2013, Interpark (2.415) was found to be the most efficient online shopping enterprise, followed by Aladdin Communications (2.117), Hyundai Home shopping (1.867), Home&Shopping (1.176), NS Home shopping (1.170), Commerce Planet (1.126), CJ O Shopping (1.105), Ebay Korea (1.088), and GS Home Shopping (1.051). Second, this study recognizes how the management efficiency has changed for the period 2009-2013. Third, the lesser the capital and employees, the more are the net profits, and the better is the management efficiency of domestic online shopping companies. Lastly, the productivity of such companies is influenced by endogenous factors rather than exogenous factors such as shifts in business environment and technological advances. Conclusions - DHC Korea influenced various distribution channels to reach customers through the Internet. Consequently, this helped in increasing the awareness about its products, in addition to an increase in sales. These achievements can be attributed to the characteristics of online shopping companies. Although it is easy for these companies to suggest goods for one-off purchases, they however have difficulties in retaining customers. Overcoming this challenge can be one of the ways to benchmark a successful case of an efficient company. For example, an online shopping company can attract customers by developing a corresponding mobile application as a convenient way to shop online. Additionally, they can satisfy customers by quick delivery of purchased products, which is possible by building an effective logistics network. Our study indicates that the productivity of an online shopping company was influenced by endogenous factors driven by improvements in managerial practices rather than exogenous factors. Accordingly, online shopping companies should adopt strategies to improve their operational efficiency rather than sales volume-oriented management.

The Comparative Study on the Efficiency of Five Largest Seaports in Korea (한국 5대 항만의 효율성에 대한 비교연구)

  • Na, Ho-Su;Lee, U;Lee, Gyeong-Su
    • Journal of Korea Port Economic Association
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    • v.24 no.4
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    • pp.25-46
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    • 2008
  • By using data envelopment analysis(DEA) this research measures the efficiency of Korea's five seaports and their Malmquist productivity from 1997 to 2006. Under the assumption of CRS(constant returns to scale) and VRS(various returns to scale), seaports' rankings of efficiency are measured. Busan port is confirmed as a best-performed port in the various measurements. Important finding facts are as follows. 1)Busan, lncheon and Ulsan seaports are efficient ports under the assumption of CRS and VRS. 2)Gwangyang port shows 4.3% lower efficiency level compared with efficient ports. 3)Pohang port shows 27.3% lower efficiency level compared with efficient ports. 4)Average total factor productivity of Korea's five ports has been lower at the rate of 3.1% during the period from 1997 to 2006. Main policy implications are 1)Busan port is more efficient than Gwangyang port, which reflects the difference of economic activities between two regional econmies. 2)During the period 1997-2006, Korea's five largest ports has experienced lower efficiency levels in the first half period because of the 1997 Korean Financial Crisis, but higher efficiency levels in the second half period because of economic recovery. In future research the more and better data will be expected to improve the understanding of Korean seaports' efficiency characteristics.

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An Analysis on the R&D Productivity and Efficiency of Korea: Focused on Comparison with the OECD Countries (우리나라의 R&D 생산성 및 효율성 분석: OECD 국가와의 비교를 중심으로)

  • Kim, Young-H.;Kim, Sun-G.
    • Journal of Technology Innovation
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    • v.19 no.1
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    • pp.1-27
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    • 2011
  • This paper aims to measure and analyze R&D productivities and efficiencies of 17 major OECD countries including Korea over the 1984-2008 period by using the Malmquist Productivity Index and Data Envelopment Analysis, classifying R&D performance into an output and outcome aspects. It also searches the Korea's current status and characteristics in each R&D stage to enhance Total Factor Productivity (TFP) compared with other developed countries. Our major findings are the followings: (i) Korea's productivity index of R&D input vis-a-vis R&D output is very high (13.39% annual growth rate) compared with those of major advanced countries, whereas the annual average of efficiency index is very low (0.33), i.e. Korea's technical efficiency index has risen to 0.83 at the last time series started at 0.10 point and come up to the level of major advanced countries. (ii) the Korea's productivity index of R&D output vis-a-vis R&D outcome is very low (14.02% annual reduction rate) compared with those of major advanced countries, whereas the annual average of efficiency index is very high (0.22), i.e. Korea's integrated frontier technical efficiency index has dropped to 0.057 at the last time series started at 1.00 point and coming up to the level of major advanced countries. (iii) The productivity of R&D input vis-a-vis R&D outcome is positively correlated with that of R&D output vis-a-vis R&D outcome and the growth of R&D input factors. In a nutshell, it implicates that the effort to take advantage of R&D outputs, namely establishing the diffusion and commercialization system of technical knowledge to the level of developed countries, should be strengthened over that on the growth of R&D investment and output for enhancing R&D productivity and efficiency in Korea.

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Impacts of R&D and Smallness of Scale on the Total Factor Productivity by Industry (R&D와 규모의 영세성이 산업별 총요소생산성에 미치는 영향)

  • Kim, Jung-Hwan;Lee, Dong-Ki;Lee, Bu-Hyung;Joo, Won
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.2 no.4
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    • pp.71-102
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    • 2007
  • There were many comprehensive analyses conducted within the existing research activities wherein factors affecting technology progress including investment in R&D vis-${\Box}$-vis their influences act as the determinants of TFP. Note, however, that there were few comprehensive analysis in the industrial research performed regarding the impact of the economy of scale as it affects TFP; most of these research studies dealt with the analysis of the non -parametric Malmquist productivity index or used the stochastic frontier production function models. No comprehensive analysis on the impacts of individual independent variables affecting TFP was performed. Therefore, this study obtained the TFP increase rate of each industry by analyzing the factors of the existing growth accounting equation and comprehensively analyzed the TFP determinants by constructing a comprehensive analysis model considering the investment in R&D and economy of scale (smallness by industry) as the influencers of TFP by industry. First, for the TFP increase rate of the 15 industries as a whole, the annual average increase rate for 1993${\sim}$ 1997 was approximately 3.8% only; during 1999${\sim}$ 2000 following the foreign exchange crisis, however, the annual increase rate rose to approximately 7.8%. By industry, the annual average increase rate of TFP between 1993 and 2000 stood at 11.6%, the highest in the electrical and electronic equipment manufacturing business and IT manufacturing sector. In contrast, a -0.4% increase rate was recorded in the furniture and other product manufacturing sectors. In the case of the service industry, the TFP increase rate was 7.3% in the transportation, warehousing, and communication sectors. This is much higher than the 2.9% posted in the electricity, water, and gas sectors and -3.7% recorded in the wholesale, food, and hotel businesses. The results of the comprehensive analysis conducted on the determinants of TFP showed that the correlations between R&D and TFP in general were positive (+) correlations whose significance has yet to be validated; in the model where the self-employed and unpaid family workers were used as proxy variables indicating the smallness of industry out of the total number of workers, however, significant negative (-) correlations were noted. On the other hand, the estimation factors of variables surrogating the smallness of scale in each industry showed that a consistently high "smallness of scale" in an industry means a decrease in the increase rate of TFP in the same industry.

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