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Sustainability 2017, 9(10), 1723;

A New Framework for Understanding Urban Social Vulnerability from a Network Perspective

1,*, 2 and 3,*
State Key Laboratory of Pollution Control & Resource Re-use, School of the Environment, Nanjing University, Nanjing 210093, China
School of Transportation, Southeast University, Nanjing 210018, China
School of Government, Center for Risk, Disaster & Crisis Research, Nanjing University, Nanjing 210093, China
Authors to whom correspondence should be addressed.
Received: 17 August 2017 / Revised: 21 September 2017 / Accepted: 24 September 2017 / Published: 26 September 2017
PDF [2489 KB, uploaded 26 September 2017]


Rapid urbanization in China has strengthened the connection and cooperation among cities and has also led urban residents to be more vulnerable in adverse environmental conditions. Vulnerability research has been an important foundation in urban risk management. To make cities safe and resilient, it is also necessary to integrate the connection among cities into a vulnerability assessment. Therefore, this paper proposed a new conceptual framework for urban social vulnerability assessment based on network theory, where a new dimension of social vulnerability (connectivity) was added into the framework. Using attribute data, the traditional social vulnerability index of a city (SVInode) was calculated via the projection pursuit cluster (PPC) model. With the relational data retrieved from the Baidu search index, a new dimension (connectivity) of social vulnerability (SVIconnectivity) was evaluated. Finally, an integrated social vulnerability index (SVIurban) was measured combined with SVInode and SVIconnectivity. This method was applied in the Yangtze River Delta region of China, where the top three high values of SVInode belonged to the cities of Taizhou (Z), Jiaxing, and Huzhou. The three lowest cities were Hangzhou, Nanjing, and Shanghai. For SVIurban, the social vulnerability of cities in different hierarchies behaved differently. For Hierarchies 2 and 3, when compared to SVInode, the SVIurban was significantly reduced. However, the variation between SVInode and SVIurban in Hierarchy 4 was slight. Furthermore, an increase for the city of Taizhou (J) in its social vulnerability was achieved after connecting to the network. Huzhou, in Hierarchy 5, increased its social vulnerability the most when adding connectivity in the social vulnerability assessment. Based on the results of our case study, a conclusion was drawn that network connectivity had an influence on social vulnerability. However, when connectivity was strong enough, it could help cities to mitigate their traditional social vulnerability, whereas a loose connection in the network aggregated their traditional social vulnerability. Hence, the latter should be emphasized in future urban risk management. View Full-Text
Keywords: social vulnerability; connectivity; network; city; the Yangtze River Delta (YRD) region social vulnerability; connectivity; network; city; the Yangtze River Delta (YRD) region

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Ge, Y.; Dou, W.; Zhang, H. A New Framework for Understanding Urban Social Vulnerability from a Network Perspective. Sustainability 2017, 9, 1723.

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