Yiling Zhang

Yiling Zhang


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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8 March 2022 in Sustainability
Verified
Journal Article
Open access
PDF file
TZTao Zhou
Tao Zhou
RDRui Ding
Rui Ding
YDYiming Du
Yiming Du
YZYiling Zhang
Yiling Zhang
SCShihui CHEN
Shihui CHEN
TZTing Zhang
Ting Zhang
The article aims to study the coupling coordination and spatial correlation effects of green finance (GF) and high-quality economic development (HQED) in 30 Chinese provinces. The index system of GF and HQED is constructed by selecting relevant index data from 2007 to 2017. The index of GF and HQED is measured by the entropy value method. Next, the coupling coordination degree (CCD) and spatial association strength are calculated based on the index using the coupling coordination degree model and the gravity model. Then the driving factors of the CCD between GF and HQED are analyzed by using geographic detectors. Finally, the spatial association network is constructed and its robustness is studied. The research results show that the coupling coordination degree between GF and HQED in each province is generally low, with strong regional heterogeneity, and the coupling coordination degree shows a trend of decay from the eastern region to the western region, but the western region has more room for development. Green credit, green, coordination, and sharing are the strong driving factors of the CCD between GF and HQED. The network of spatial association between GF and HQED in each province is gradually tightened, making the western peripheral provinces more closely connected with the eastern provinces through the intermediate node provinces. The network robustness of GF and HQED is more influenced by provinces with higher node degree values. Accordingly, the article proposes that China should continuously improve relevant GF policies, environmental disclosure systems, enhance green innovation technology and guide private capital to enter the GF market.

JFJun Fu
Jun Fu
RDRui Ding
Rui Ding
YZYiling Zhang
Yiling Zhang
TZTao Zhou
Tao Zhou
YDYiming Du
Yiming Du
WXWenqian Xiao
Wenqian Xiao
Urban-land development and utilization is one of the main sources of carbon emissions. Improving the green and low-carbon utilization efficiency of urban land (GLUEUL) under the goal of carbon neutrality is crucial to the low-carbon transition and green development of China’s economy. Combining the concept of green and low-carbon development in urban land use, carbon emissions and industrial-pollution emissions are incorporated into the unexpected outputs of the GLUEUL evaluation system. The super-efficient slacks-based measure (SBM) model, Exploratory Spatial-Temporal Data Analysis (ESTDA) method and Geographically and Temporally Weighted Regression (GTWR) model were used to analyze the spatial-temporal transition and the influencing factors of GLUEUL in 282 cities in China from 2005 to 2020. The result shows that: (1) From 2005 to 2020, the green and low-carbon land-utilization efficiency of Chinese cities shows an increasing temporal-evolution trend, but the gap between cities is gradually widening. (2) From the spatial-temporal dynamic characteristics of Local Indicators of Spatial Association (LISA), regions with the highest GLUEUL have strong dynamics and instability, while cities at the lowest level have a relatively stable spatial structure. On the whole, the local-spatial-transfer direction of GLUEUL of each city is stable, with certain path-dependent characteristics. (3) There are differences in the degree of influence and direction of action of different factors on GLUEUL. The economic development level, industrial-structure upgrading, financial support, wealth level, and green-technology-innovation ability have positive effects on overall GLUEUL, with industrial-structure upgrading promoting GLUEUL the most, while urban population size, foreign-investment scale, and financial-development level play a negative role. This study can provide some empirical and theoretical references for the improvement of GLUEUL.

2 September 2022 in Sustainability
Verified
Journal Article
Open access
PDF file
RDRui Ding
Rui Ding
JFJun Fu
Jun Fu
YZYiling Zhang
Yiling Zhang
TZTing Zhang
Ting Zhang
YJYin Jian
Yin Jian
LDLinyu Du
Linyu Du
To investigate the spatial evolution process of economic development in the urban agglomeration and its influencing factors, the network construction method, modified gravity model, geographic detector and Geographically Weighted Regression (GWR) model are used to analyze the intensity of urban association; then, the evolution of economic, spatial pattern and its influencing factors are further discussed, and the Chengdu-Chongqing urban agglomeration of China from 2005 to 2020 is studied as an example. The results show that: (1) the economically developed zones of the Chengdu-Chongqing urban agglomeration mainly concentrated in the core cities of Chengdu and the central city of Chongqing, and the region shows an uneven spatial pattern of economic development distribution. (2) The share of economic linkages with the central city of Chengdu and Chongqing as the twin cities is significant, the intensity of Chengdu and its neighboring cities is gradually decreasing, while the central city of Chongqing has increased, but it still has an insufficient influence on the peripheral areas. (3) The intensities and directions of the factors influencing economic development in the Chengdu-Chongqing urban agglomeration are different. The total output value of the secondary industry, total social fixed asset investment, the number of beds in health institutions, and road freight turnover are significant factors with consistently strong explanatory ability for economic development. The promotion effect of these four significant factors on economic development is mainly concentrated in the eastern and western regions of Chengdu-Chongqing urban agglomeration, while the inhibiting effect is mainly on the cities in the south and north. Based on this study, relevant recommendations are made to promote the coordinated development of the Chengdu-Chongqing urban agglomeration.

RDRui Ding
Rui Ding
TZTao Zhou
Tao Zhou
YJYin Jian
Yin Jian
YZYiling Zhang
Yiling Zhang
SSSiwei Shen
Siwei Shen
SCShihui CHEN
Shihui CHEN
With the expansion of the scale of China’s economy and the acceleration of urbanization, energy consumption is increasing, and environmental degradation and other problems have arisen. In order to solve such prominent problems, China proposed the “carbon peak” and “carbon neutral” targets in 2020. Although there are research conclusions about the impact of urbanization on energy intensity (EI), conclusions about the impact of the urban agglomeration policy (UAP) on EI are still unclear. Therefore, the article studies the impact of the urban agglomeration policy on EI in 279 prefecture-level cities by constructing a Difference-In-Differences (DID) model and mediating effect model. The results show that UAP has a significant effect on reducing EI, but their effects are different with the impact of urban heterogeneity, and the urban agglomeration policy of “Core” cities is less effective than those of “Edge” cities. From the perspective of the influencing mechanism, UAP takes green innovation capability as the intermediary variable to influence EI. The placebo test, PSM-DID regression, counterfactual test, and instrumental variable method all reflect the robustness of the research conclusions. Based on this, the paper puts forward some suggestions for urban agglomeration planning and green technology innovation.

28 September 2022 in Sustainability
Verified
Journal Article
Open access
PDF file
RDRui Ding
Rui Ding
JFJun Fu
Jun Fu
YDYiming Du
Yiming Du
LDLinyu Du
Linyu Du
TZTao Zhou
Tao Zhou
SCShihui CHEN
Shihui CHEN
How to improve the partial or overall performance of rail transit route network, strengthen the connection between different rail network stations, and form corresponding communities to resist the impact of sudden or long-term external factors has earned a lot of attention recently. However, the corresponding research studies are mostly based on the rail network structure, and the analysis and exploration of the community formed by the stations and its robustness are not enough. In this article, the evolution of the China rail transit route network (CRTRN) from 2009 to 2022 is taken as the research object, and its complex network characteristics, BGLL model-based community division, and multi disturbance strategies for network robustness are analyzed in depth to better understand and optimize the rail network structure to further effectively improve the efficiency of the public transport system. It is found that CRTRN is gradually expanding following the southwest direction (with the migration distance of nearly 200 km), the distribution of routes is more balanced, and the number of network communities is steadily decreasing (it dropped from 30 communities in 2009 to 25 in 2019), making various regions become closely connected. However, it can also be found that during the COVID-19 pandemic, the CRTRN is strongly affected, and the network structure becomes relatively loose and chaotic (the number of communities became 30). To protect the railway networks, the CRTRN system should pay more attention to stations with high node degree values; if they get disturbed, more areas will be affected. The corresponding research conclusions can provide some theoretical and practical support for the construction of the rail transit network in China.

14 November 2022 in Applied Sciences
Verified
Journal Article
Open access
PDF file
RDRui Ding
Rui Ding
TZTing Zhang
Ting Zhang
YQYuanghong Qiu
Yuanghong Qiu
JFJun Fu
Jun Fu
YJYin Jian
Yin Jian
YDYiming Du
Yiming Du
Based on the associated network of passenger and freight transport in the New Western Land-Sea Corridor, the structure and characteristics of passenger and freight transport network in different years are analyzed using passenger volume and freight volume, and the resilience of the network is analyzed using the disturbance model. Finally, the coordinated development of passenger transport and logistics is discussed by applying a coupling coordination model. The results show that, from 2000 to 2018, the New Western Land-Sea Corridor has realized the evolution of the spatial pattern of passenger transport network from “two center and numerous branches” to “three centers and three auxiliaries”. Moreover, the evolution of the spatial pattern of the freight transport network changed from “two centers and one auxiliary” to “one center and multiple auxiliaries”. In terms of network tenacity, the disturbance strategy based on node degree value has the strongest damage to the performance of passenger and freight transport networks. The coupling coordination value is gradually rising from a low level and finally develops to an ordered trend. Therefore, it is proposed that passenger transport development could be supported from the “growth pole” and “zone” development modes, while the logistics development would adopt the “axis” development pattern and focus on the protection of the vital city nodes in the corresponding network. In this way, it can realize the effective connection of multiple paths, improve the tenacity of network and boost hub economy, consummate the regional coordination mechanism, and finally promote the advancement of the New Western Land-Sea Corridor.