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      부정산출요소를 고려한 중국 경제권의 효율성 평가 = Efficiency Evaluation of Economic Zones in China Considering the Undesirable Output

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      https://www.riss.kr/link?id=A108055276

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      With the development of China, air pollutants are also growing rapidly in recent decades, especially in big cities of the country. To better understand the relationship between economic conditions and air pollutants in big cities, this study combined the carbon dioxide (CO2) emissions of 17 provinces in China’s four key economic development zones (the Beijing-Tianjin-Hebei Region, the Bohai Economic Rim, the Pearl River Delta, and the Yangtze River Delta) for the first time and explored the decoupling of economic growth from CO2 emissions. To achieve the research purpose, this paper constructs an economic benefit evaluation index system with employees, fixed investments, main energy productions as inputs, and gross domestic product (GDP) as output. In addition, the trend of economic efficiency changed from 2016 to 2020 was analyzed and compared by combining CO2 emissions and set as undesirable output based on slacks-based measure (SBM) model and undesirable output model. The results show that from the perspective of provincial economic efficiency, the economic efficiency considering the undesirable output is lower than the traditional economic efficiency from 2016 to 2020. In terms of regional economic efficiency, the Bohai Economic Rim (BER) and the Beijing-Tianjin-Hebei Region (BTHR) are the most economically efficient of the four economic development zones (EDZs). Additionally, the mean value of regional green economic efficiency, in descending order, is the BER, the BTHR, the Pearl River Delta (PRD), and the Yangtze River Delta (YRD). In general, it is suggested that the government set different CO2 emission reductiontargets for different areas in order to achieve rapid economic growth, taking into consideration the disparities in industrial structure and economic development levels of different EDZs.
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      With the development of China, air pollutants are also growing rapidly in recent decades, especially in big cities of the country. To better understand the relationship between economic conditions and air pollutants in big cities, this study combined ...

      With the development of China, air pollutants are also growing rapidly in recent decades, especially in big cities of the country. To better understand the relationship between economic conditions and air pollutants in big cities, this study combined the carbon dioxide (CO2) emissions of 17 provinces in China’s four key economic development zones (the Beijing-Tianjin-Hebei Region, the Bohai Economic Rim, the Pearl River Delta, and the Yangtze River Delta) for the first time and explored the decoupling of economic growth from CO2 emissions. To achieve the research purpose, this paper constructs an economic benefit evaluation index system with employees, fixed investments, main energy productions as inputs, and gross domestic product (GDP) as output. In addition, the trend of economic efficiency changed from 2016 to 2020 was analyzed and compared by combining CO2 emissions and set as undesirable output based on slacks-based measure (SBM) model and undesirable output model. The results show that from the perspective of provincial economic efficiency, the economic efficiency considering the undesirable output is lower than the traditional economic efficiency from 2016 to 2020. In terms of regional economic efficiency, the Bohai Economic Rim (BER) and the Beijing-Tianjin-Hebei Region (BTHR) are the most economically efficient of the four economic development zones (EDZs). Additionally, the mean value of regional green economic efficiency, in descending order, is the BER, the BTHR, the Pearl River Delta (PRD), and the Yangtze River Delta (YRD). In general, it is suggested that the government set different CO2 emission reductiontargets for different areas in order to achieve rapid economic growth, taking into consideration the disparities in industrial structure and economic development levels of different EDZs.

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      참고문헌 (Reference)

      1 임병학, "컨테이너항만 네트워크가 항만 생산성에 미치는 영향에 대한 연구: 사회 네트워크 분석을 중심으로" 한국로지스틱스학회 19 (19): 19-35, 2011

      2 Vincova, K., "Using DEA models to measure efficiency" 13 (13): 24-28, 2005

      3 Vincova, K., "Using DEA models to measure efficiency" 13 (13): 24-28, 2005

      4 Hu, J. L., "Total-factor energy efficiency of regions in China" 34 (34): 3206-3217, 2006

      5 Zhang, X. P., "Total-factor energy efficiency in developing countries" 39 (39): 644-650, 2011

      6 Zhou, P., "Total factor carbon emission performance : a Malmquist index analysis" 32 (32): 194-201, 2010

      7 Pestana Barros, C., "The Measurement of efficiency of Portuguese Sea Port Authorities with DEA" 1000-1020, 2003

      8 Yin, J., "Study on urban efficiency measurement and spatiotemporal evolution of cities in Northwest China based on the DEA–malmquist model" 11 (11): 434-, 2019

      9 Chen, J., "Stochastic frontier analysis of productive efficiency in China’s Forestry Industry" 28 : 87-95, 2017

      10 Cooper, W. W., "Sensitivity and stability analysis in DEA: some recent developments" 15 : 217-246, 2001

      1 임병학, "컨테이너항만 네트워크가 항만 생산성에 미치는 영향에 대한 연구: 사회 네트워크 분석을 중심으로" 한국로지스틱스학회 19 (19): 19-35, 2011

      2 Vincova, K., "Using DEA models to measure efficiency" 13 (13): 24-28, 2005

      3 Vincova, K., "Using DEA models to measure efficiency" 13 (13): 24-28, 2005

      4 Hu, J. L., "Total-factor energy efficiency of regions in China" 34 (34): 3206-3217, 2006

      5 Zhang, X. P., "Total-factor energy efficiency in developing countries" 39 (39): 644-650, 2011

      6 Zhou, P., "Total factor carbon emission performance : a Malmquist index analysis" 32 (32): 194-201, 2010

      7 Pestana Barros, C., "The Measurement of efficiency of Portuguese Sea Port Authorities with DEA" 1000-1020, 2003

      8 Yin, J., "Study on urban efficiency measurement and spatiotemporal evolution of cities in Northwest China based on the DEA–malmquist model" 11 (11): 434-, 2019

      9 Chen, J., "Stochastic frontier analysis of productive efficiency in China’s Forestry Industry" 28 : 87-95, 2017

      10 Cooper, W. W., "Sensitivity and stability analysis in DEA: some recent developments" 15 : 217-246, 2001

      11 Bian, Y., "Resource and environment efficiency analysis of provinces in China : A DEA approach based on Shannon’s entropy" 38 (38): 1909-1917, 2010

      12 Wang, K., "Regional allocation of CO2 emissions allowance over provinces in China by 2020" 54 : 214-229, 2013

      13 Tao, X., "Provincial green economic efficiency of China : A non-separable input –output SBM approach" 171 : 58-66, 2016

      14 Shuai, S., "Modeling the role of environmental regulations in regional green economy efficiency of China : Empirical evidence from super efficiency DEA-Tobit model" 261 : 110227-, 2020

      15 Geys, B., "Measuring local government technical(in)efficiency : an application and comparison of FDH, DEA, and econometric approaches" 32 (32): 499-513, 2009

      16 Zhou, P., "Measuring environmental performance under different environmental DEA technologies" 30 (30): 1-14, 2008

      17 Zhou, P., "Linear programming models for measuring economy-wide energy efficiency performance" 36 (36): 2911-2916, 2008

      18 Wu, F., "Industrial energy efficiency with CO2 emissions in China : A nonparametric analysis" 49 : 164-172, 2012

      19 Li, Y., "How to reduce energy intensity in China : A regional comparison perspective" 61 : 513-522, 2013

      20 Wu, H., "How do environmental regulation and environmental decentralization affect green total factor energy efficiency : Evidence from China" 91 : 104880-, 2020

      21 Cooper, W. W., "Handbook on data envelopment analysis" Springer 1-39, 2011

      22 Guo, X. D., "Evaluation of potential reductions in carbon emissions in Chinese provinces based on environmental DEA" 39 (39): 2352-2360, 2011

      23 왕관 ; 안승범, "Evaluating Performance and Efficiency of Logistics in Chinese Provinces and Cities along the Belt and Road Initiative" 한국로지스틱스학회 28 (28): 13-26, 2020

      24 Liu, Y., "Environmental regulation, green technological innovation, and eco-efficiency : The case of Yangtze river economic belt in China" 155 : 119993-, 2020

      25 Wang, K., "Energy and emissions efficiency patterns of Chinese regions : a multi-directional efficiency analysis" 104 : 105-116, 2013

      26 Hu, J. L., "Efficient three industrial waste abatement for regions in China" 15 (15): 132-144, 2008

      27 Hu, J. L., "Efficient energy-saving targets for APEC economies" 35 (35): 373-382, 2007

      28 Jemric, I., "Efficiency of banks in Croatia : A DEA approach" 44 (44): 169-193, 2002

      29 Ahn, T., "Efficiency characterizations in different DEA models" 22 (22): 253-257, 1988

      30 Tone, K., "Dynamic DEA: A slacks-based measure approach" 38 (38): 145-156, 2010

      31 Tone, K., "Dynamic DEA with network structure : A slacks-based measure approach" 42 (42): 124-131, 2014

      32 Charnes, A., "Data envelopment analysis theory, methodology and applications" 48 (48): 332-333, 1997

      33 박차미 ; 김태승, "DEA-SBM을 이용한 국내 물류산업의 효율성 분석" 한국로지스틱스학회 22 (22): 27-46, 2014

      34 Sala-Garrido, R., "Comparing the efficiency of wastewater treatment technologies through a DEA metafrontier model" 173 (173): 766-772, 2011

      35 Shi, G. M., "Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs" 38 (38): 6172-6179, 2010

      36 Pan, H., "China’s provincial industrial energy efficiency and its determinants" 58 (58): 1032-1039, 2013

      37 Kočišová, K., "Application of the DEA on the measurement of efficiency in the EU countries" 61 (61): 51-62, 2015

      38 Nazarko, J., "Application of DEA method in efficiency evaluation of public higher education institutions" 20 (20): 25-44, 2014

      39 Long, Y., "Analysis on regional difference and convergence of the efficiency of China’s green economy based on DEA [J]" 2 : 46-54, 2010

      40 Liu, D., "Analysis of China’s coastal zone management reform based on land-sea integration" 2019

      41 Wei, Y. M., "An empirical analysis of energy efficiency in China’s iron and steel sector" 32 (32): 2262-2270, 2007

      42 Martić, M., "An application of DEA for comparative analysis and ranking of regions in Serbia with regards to social-economic development" 132 (132): 343-356, 2001

      43 Tone, K., "A slacks-based measure of efficiency in data envelopment analysis" 130 (130): 498-509, 2001

      44 Banker, R. D., "A note on returns to scale in DEA" 88 (88): 583-585, 1996

      45 Tone, K., "A hybrid measure of efficiency in DEA" GRIPS 2004

      46 Yeh, T. L., "A comparative study of energy utilization efficiency between Taiwan and China" 38 (38): 2386-2394, 2010

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2026 평가 재인증평가 신청대상 (재인증)
      2020-01-01 등재 등재학술지 유지 (재인증) KCI등재
      2017-01-01 등재 등재학술지 유지 (계속평가) KCI등재
      2013-01-01 등재 등재학술지 유지 (등재유지) KCI등재
      2010-01-01 등재 등재 1차 FAIL (등재유지) KCI등재
      2007-01-01 등재 등재학술지 선정 (등재후보2차) KCI등재
      2006-01-01 등재 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2004-01-01 등재 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 1.06 1.06 0.95
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.84 0.81 0.849 0.26
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