Measuring environmental efficiency in transportation sector based on a meta-frontier SBM approach: focusing on the Yangtze River Economic Belt (YEB) and Beijing–Tianjin–Hebei (JingJinJi)
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
The purpose of this study is to analyze the environmental efficiency level and trend of the transportation sector in the upper–mid–downstream of the Yangtze River Economic Belt and the JingJinJi region in China and assess the effectiveness of policies for protecting the low-carbon environment.This study uses the meta-frontier slack-based measure (SBM) approach to evaluate environmental efficiency, which targets and classifies specific regions into regional groups. First, this study employs the SBM with the undesirable outputs to construct the environmental efficiency measurement models of the four regions under the meta-frontier and group frontiers, respectively. Then, this study uses the technology gap ratio to evaluate the gap between the group frontier and the meta-frontier. The analysis reveals several key findings: (1) the JingJinJi region and the downstream of the YEB had achieved the overall optimal production technology in transportation than the other two regions; (2) significant technology gaps in environmental efficiency were observed among these four regions in China; and (3) the downstream region of the YEB exhibited the lowest levels of energy consumption and excessive CO 2 emissions. To evaluate the differences in environmental efficiency resulting from regions and technological gaps in transportation, this study employs the meta-frontier model, which overcomes the limitation of traditional environmental efficiency methods. Furthermore, in the practical, the study provides the advantage of observing the disparities in transportation efficiency performed by the Yangtze River Economic Belt and the Beijing–Tianjin–Hebei regions.
Abstract
The purpose of this study is to analyze the environmental efficiency level and trend of the transportation sector in the upper–mid–downstream of the Yangtze River Economic Belt and the JingJinJi region in China and assess the effectiveness of policies for protecting the low-carbon environment.This study uses the meta-frontier slack-based measure (SBM) approach to evaluate environmental efficiency, which targets and classifies specific regions into regional groups. First, this study employs the SBM with the undesirable outputs to construct the environmental efficiency measurement models of the four regions under the meta-frontier and group frontiers, respectively. Then, this study uses the technology gap ratio to evaluate the gap between the group frontier and the meta-frontier. The analysis reveals several key findings: (1) the JingJinJi region and the downstream of the YEB had achieved the overall optimal production technology in transportation than the other two regions; (2) significant technology gaps in environmental efficiency were observed among these four regions in China; and (3) the downstream region of the YEB exhibited the lowest levels of energy consumption and excessive CO 2 emissions. To evaluate the differences in environmental efficiency resulting from regions and technological gaps in transportation, this study employs the meta-frontier model, which overcomes the limitation of traditional environmental efficiency methods. Furthermore, in the practical, the study provides the advantage of observing the disparities in transportation efficiency performed by the Yangtze River Economic Belt and the Beijing–Tianjin–Hebei regions.
참고문헌 (40)
- "Statistical review of world energy 2022" (2022)[URL]
- Chang, Y. T., "Environmental efficiency analysis of transportation system in China : a non-radial DEA approach", Energy Policy, 58, pp.277~283 (2013)[DOI]
- Charnes, A., "Measuring the efficiency of decision making units", European Journal of Operational Research, 2(6), pp.429~444 (1978)[DOI]
- Chen, X., "Efficiency measure on the truck restriction policy in China : a nonradial data envelopment model", Transportation Research Part A : Policy and Practice, 129, pp.140~154 (2019)
- Cui, Q., "The evaluation of transportation energy efficiency : an application of threestage virtual Frontier DEA", Transportation Research Part D : Transport and Environment, 29, pp.1~11 (2014)[DOI]
- Dahlke, S., "Advances in Clean Energy Technologies", pp.451~485 (2021), Academic Press
- Feng, C., "Analysis of energy efficiency and energy savings potential in China’s provincial industrial sectors", Journal of Cleaner Production, 164, pp.1531~1541 (2017)[DOI]
- Feng, C., "Analysis of energy efficiency in China’s transportation sector", Renewable and Sustainable Energy Reviews, 94, pp.565~575 (2018)[DOI]
- Heinold, A., "Emission rates of intermodal rail", road and road-only transportation in Europe : a comprehensive simulation study, 2018, pp.65, 421~437
- Hepburn, C., "Policy brief—encouraging innovation that protects environmental systems : five policy proposals", Review of Environmental Economics and Policy, 12(1), pp.154~169 (2018)[DOI]
- Hu, J. L., "Total-factor energy efficiency of regions in China", Energy Policy, 34(17), pp.3206~3217 (2006)[DOI]
- Jiang, X., "Based on DEA Model to Analysis Transportation System Efficiency in China", pp.2022
- Li, Y., "CO2 emission performance evaluation of Chinese port enterprises : a modified meta-frontier non-radial directional distance function approach", Transportation Research Part D : Transport and Environment, 89, pp.102605~ (2020)[DOI]
- Lin, L. C., "Operational performance evaluation of international major airports : an application of data envelopment analysis", Journal of Air Transport Management, 12(6), pp.342~351 (2006)[DOI]
- Lin, B., "Energy conservation in China’s light industry sector : evidence from interfactor and inter-fuel substitution", Journal of Cleaner Production, 152, pp.125~133 (2017)[DOI]
- Lin, B., "Technology gap and regional energy efficiency in China’s textile industry : a non-parametric meta-frontier approach", Journal of Cleaner Production, 137, pp.21~28 (2016)[DOI]
- Liu, Q., "Toxic air pollution and container port efficiency in the USA", Maritime Economics and Logistics, 19(1), pp.94~105 (2017)[DOI]
- Merkert, R., "The impact of strategic management and fleet planning on airline efficiency–A random effects Tobit model based on DEA efficiency scores", Transportation Research Part A : Policy and Practice, 45(7), pp.686~695 (2011)[DOI]
- Mostafa, M. M., "Modeling the efficiency of top Arab banks : a DEA–neural network approach", Expert Systems with Applications, 36(1), pp.309~320 (2009)[DOI]
- Na, J. H., "Environmental efficiency analysis of Chinese container ports with CO2 emissions : an inseparable input-output SBM model", Journal of Transport Geography, 65, pp.13~24 (2017)[DOI]
- O’Donnell, C. J., "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios", Empirical Economics, 34(2), pp.231~255 (2008)[DOI]
- Park, Y. S., "Environmental efficiency assessment of US transport sector : a slack-based data envelopment analysis approach", Transportation Research Part D : Transport and Environment, 61, pp.152~164 (2018)[DOI]
- Scheraga, C. A., "The relationship between operational efficiency and customer service : a global study of thirty-eight large international airlines", Transportation Journal, 43(3), pp.48~58 (2004)
- Song, M., "Railway transportation and environmental efficiency in China", Transportation Research Part D : Transport and Environment, 48, pp.488~498 (2016)[DOI]
- Tone, K., "A slacks-based measure of efficiency in data envelopment analysis", European Journal of Operational Research, 130(3), pp.498~509 (2001)[DOI]
- Dealing with undesirable outputs in DEA: a slacks-based measure SBM approach, "Tone, K.", GRIPS, ~ (2003)
- Wang, Z., "An empirical research on the influencing factors of regional CO2 emissions : evidence from Beijing city, China", Applied Energy, 100, pp.277~284 (2012)
- Wang, Q., "Energy efficiency and production technology heterogeneity in China : a meta-frontier DEA approach", Economic Modelling, 35, pp.283~289 (2013)[DOI]
- Wang, P., "Measuring regional energy efficiencies in China : a metafrontier SBM-Undesirable approach", Natural Hazards, 85(2), pp.793~809 (2017)[DOI]
- Wang, L., "Green efficiency evaluation and improvement of Chinese ports : a cross-efficiency model", Transportation Research Part D : Transport and Environment, 88, pp.102590~ (2020)[DOI]
- Wei, F., "Energy and environmental efficiency of China’s transportation sectors considering CO2 emission uncertainty", Transportation Research Part D : Transport and Environment, 97, pp.102955~ (2021)[DOI]
- "World Bank open data" (2023)[URL]
- Yao, X., "Regional energy efficiency, carbon emission performance and technology gaps in China : a meta-frontier non-radial directional distance function analysis", Energy Policy, 84, pp.142~154 (2015)[DOI]
- Zhang, N., "Measuring ecological total-factor energy efficiency incorporating regional heterogeneities in China", Ecological Indicators, 51, pp.165~172 (2015)[DOI]
- Zhang, N., "Total-factor carbon emission performance of the Chinese transportation industry : a bootstrapped non-radial Malmquist index analysis", Renewable and Sustainable Energy Reviews, 41, pp.584~593 (2015)[DOI]
- Zhang, Y., "Collaborative planning for intermodal transport with eco-label preferences", Transportation Research Part D : Transport and Environment, 112, pp.103470~ (2022)[DOI]
- Zhao, S., "Spatial difference of China’s regional logistics development and construction of information network platform based on artificial intelligence technology under the background of new economy", Frontiers in Psychology, 13, pp.871538~ (2022)[DOI]
- Zhimin, P., "Research on Total Factor Productivity in China’s Transportation Industry under the Constraints of Resource and Environment", pp.2019
- Zhou, Y., "Environmental efficiency analysis of power industry in China based on an entropy SBM model", Energy Policy, 57, pp.68~75 (2013)[DOI]
- Zhou, G., "Measuring energy efficiency performance of China’s transport sector : a data envelopment analysis approach", Expert Systems with Applications, 41(2), pp.709~722 (2014)[DOI]
