scholarly journals Impact of environmental regulation policy on ecological efficiency in four major urban agglomerations in eastern China

2021 ◽  
Vol 130 ◽  
pp. 108002
Author(s):  
Man Qin ◽  
Mingxue Sun ◽  
Jun Li
Keyword(s):  
Environmental Regulation ◽  
Eastern China ◽  
Ecological Efficiency ◽  
Urban Agglomerations ◽  
Regulation Policy

scholarly journals Spatial-Temporal Differences and Influencing Factors of Tourism Eco-Efficiency in China’s Three Major Urban Agglomerations Based on the Super-EBM Model

2020 ◽  
Vol 12 (10) ◽  
pp. 4156
Author(s):  
Yiyang Sun ◽  
Guolin Hou ◽  
Zhenfang Huang ◽  
Yi Zhong
Keyword(s):  
Pearl River Delta ◽  
Yangtze River ◽  
Eastern China ◽  
Yangtze River Delta ◽  
Tourism Industry ◽  
External Factors ◽  
River Delta ◽  
Policy Implications ◽  
Pearl River ◽  
Urban Agglomerations

On the background of climate change, studying tourism eco-efficiency of cities is of great significance to promote the green development of tourism. Based on the panel data of the three major urban agglomerations in China’s Yangtze River Delta, Pearl River Delta, and Beijing–Tianjin–Hebei region from 2008 to 2017, this paper constructed an evaluation index system and measured the tourism eco-efficiency of 63 cities by using a hybrid distance model called Super-EBM (epsilon-based measure). We compared the spatial and temporal evolution characteristics of tourism eco-efficiency in the three urban agglomerations. Furthermore, the internal factors influencing tourism eco-efficiency were explored through input–output redundancy, and the external factors were analyzed by a panel regression model. The results indicate that the tourism eco-efficiency of the three urban agglomerations in China generally shows a decreasing-rising-declining trend. Among them, the Yangtze River Delta has the highest eco-efficiency, followed by the Pearl River Delta, and the lowest in the Beijing–Tianjin–Hebei region. Moreover, there is a certain gap within each urban agglomeration. The redundancy input of labor and capital is the main internal cause of low eco-efficiency. Among the external factors, the status of the tourism industry and the level of urbanization have a positive effect on eco-efficiency, while the level of tourism development, technological innovation and investment have a negative impact on it. In the future, we must attach great importance to the development quality and overall benefit value of the tourism industry so as to achieve green and balanced development of the three major urban agglomerations in eastern China. Based on the above conclusions, this paper puts forward targeted policy implications to improve the tourism eco-efficiency of cities.

scholarly journals Evaluation of the eco-efficiency of four major urban agglomerations in coastal eastern China

2019 ◽  
Vol 29 (8) ◽  
pp. 1315-1330 ◽  
Author(s):  
Yufei Ren ◽  
Chuangling Fang ◽  
Xueqin Lin ◽  
Siao Sun ◽  
Guangdong Li ◽  
...  
Keyword(s):  
Eastern China ◽  
Urban Agglomerations

scholarly journals Spatial analysis of logistics ecological efficiency and its influencing factors in China: based on Super-SBM-Undesirable and spatial Dubin models

2021 ◽  
Author(s):  
Dongling Bai ◽  
Qianli Dong ◽  
Syed Abdul Rehman Khan ◽  
Yan Chen ◽  
Dongfang Wang ◽  
...  
Keyword(s):  
Environmental Regulation ◽  
Influencing Factors ◽  
Energy Intensity ◽  
Spatial Information ◽  
Spillover Effect ◽  
Positive Influence ◽  
Energy Structure ◽  
Level Energy ◽  
Ecological Efficiency ◽  
Logistics Industry

Abstract Improving the logistics ecological efficiency (LEE) has become a significant part of ensuring a sustainable development and tackling environmental pollution. Previous studies in the logistics industry seldom considered air pollutants and the association of spatial information. Therefore, innovatively considering SO2, NOx, and PM, this study adopted the Super-SBM-Undesirable model to calculate the LEE of 30 provinces in China from 2004 to 2017, and thereafter, developed information-based matrix to explore its influencing factors by using the spatial Dubin model. The results indicated that: (1) The overall LEE during the study period was low, presenting a U-shaped trend of an initial decrease and subsequent rise, and significant regional differences with the decreasing gradient pattern of the “Eastern-Central-Western.” (2) A spatial directionality distributed from the northeast to southwest, and a significant spatial autocorrelation were observed. (3) The industrial structure had the greatest positive influence on the local LEE, followed by the urbanization level, technology innovation level, environmental regulation, while the energy intensity was identified as the main inhibiting factor, followed by the economic level, energy structure and opening level. (4) The LEE had a significant positive spillover effect; the energy intensity and environmental regulation positively affected the LEE in neighboring areas, while the opening level had negative impacts. In addition, policy recommendations for enhancing the LEE were made.

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