Analysis of sustainability of Chinese cities based on network big data of city rankings

Background: Achieving urban sustainability is the ultimate destination of urban development. City rankings as one of the sustainability assessment tools have received increasing attention from the scientific community. However, few study assesses Chinese cities’ sustainability performance using the...

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Bibliographic Details
Main Authors: Lin, M. (Author), Lin, T. (Author), Liu, J. (Author), Sun, C. (Author), Xing, L. (Author), Zeng, Z. (Author), Zhang, G. (Author), Zhao, Y. (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2021
Subjects:
Online Access:View Fulltext in Publisher
LEADER 03847nam a2200493Ia 4500
001 10.1016-j.ecolind.2021.108374
008 220427s2021 CNT 000 0 und d
020 |a 1470160X (ISSN) 
245 1 0 |a Analysis of sustainability of Chinese cities based on network big data of city rankings 
260 0 |b Elsevier B.V.  |c 2021 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1016/j.ecolind.2021.108374 
520 3 |a Background: Achieving urban sustainability is the ultimate destination of urban development. City rankings as one of the sustainability assessment tools have received increasing attention from the scientific community. However, few study assesses Chinese cities’ sustainability performance using the big data of existing city rankings. Aim: This study aims to assess Chinese cities’ sustainability performances based on the outcomes of the existing internet big data of city rankings. Methods: The outcomes of city rankings were used as the raw dataset. The “sustainability” of city rankings, city's appearance frequency, and its ranking place were comprehensively considered during evaluation processes. By considering the above factors, the scores of different cities were calculated in terms of overall sustainability and domain sustainability. Furthermore, the GeoDetector was applied to explore the association between social-economic and overall ranking scores as well as the interrelation among TBL dimensions. Results: Chinese cities’ sustainability performance was extremely uneven in spatial distribution. In terms of overall and domain sustainability, well-performing cities were aggregated in the Beijing-Tianjin-Hebei, the Yangtze River Delta, and the Pearl River Delta metropolitan regions. The top ten sustainable cities were Hangzhou, Beijing, Shenzhen, Guangzhou, Zhuhai, Hong Kong, Tianjin, Suzhou, and Xiamen. Most cities did not reach good coordination among the TBL dimensions, instead of developing well in one or two aspects. The results also revealed that current city rankings eyeing more economic and social development, while considering less environmental dimension. Moreover, TBL dimensions mutually reinforce each other in sustainable city construction. The environmental pillar played a critical role and interacting with other dimensions significantly enhanced urban sustainability. Conclusion: The outcomes of existing city rankings can be used as a new resource to evaluate cities’ sustainability performance. Current city rankings in China are not systematically considered in terms of TBL dimensions. Cities should enhance the coordination among TBL pillars, and increase the attention on environmental dimension. More empirical studies involving big data of city rankings will contribute to a new perspective to promote the practice of sustainable urbanization in China. © 2021 The Authors 
650 0 4 |a Big data 
650 0 4 |a Big data 
650 0 4 |a China 
650 0 4 |a Chinese cities 
650 0 4 |a Chinese city 
650 0 4 |a City ranking 
650 0 4 |a City rankings 
650 0 4 |a 'current 
650 0 4 |a data set 
650 0 4 |a Line dimensions 
650 0 4 |a sustainability 
650 0 4 |a Sustainability 
650 0 4 |a Sustainability performance 
650 0 4 |a Sustainable cities 
650 0 4 |a Sustainable development 
650 0 4 |a Tianjin 
650 0 4 |a Triple bottom line 
650 0 4 |a Triple bottom line (TBL) 
650 0 4 |a urban agriculture 
650 0 4 |a urban area 
650 0 4 |a Urban growth 
650 0 4 |a Urban sustainability 
650 0 4 |a urbanization 
700 1 |a Lin, M.  |e author 
700 1 |a Lin, T.  |e author 
700 1 |a Liu, J.  |e author 
700 1 |a Sun, C.  |e author 
700 1 |a Xing, L.  |e author 
700 1 |a Zeng, Z.  |e author 
700 1 |a Zhang, G.  |e author 
700 1 |a Zhao, Y.  |e author 
773 |t Ecological Indicators