scholarly journals Temporal and Spatial Differentiation in Urban Resilience and Its Influencing Factors in Henan Province

2021 ◽  
Vol 13 (22) ◽  
pp. 12460
Author(s):  
Lu Liu ◽  
Yun Luo ◽  
Jingjing Pei ◽  
Huiquan Wang ◽  
Jixia Li ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Metropolitan Area ◽  
Industrial Structure ◽  
Spillover Effects ◽  
Indicator System ◽  
Henan Province ◽  
Assessment Tools ◽  
Spatial Data Analysis ◽  
Sustainable Urban Development ◽  
Urban Resilience

Building resilient cities is playing an increasingly important role in enhancing urban safety and promoting sustainable urban development. However, few scholars pay attention to urban resilience in inland provinces. Choosing Henan Province, as it is a typical representative of China’s major inland economic provinces, has practical guiding significance. This study aims to provide a systematic indicator system and evaluation tool to measure the cuity’s resilience level. Therefore, based on a multidimensional perspective, this paper dissects the urban resilience spatial and temporal evolution characteristics of 18 Henan Province cities with the entropy method, Thiel index, and ESDA (Exploratory Spatial Data Analysis) and explores influencing factors with a spatial econometric model. The main results are as follows: (1) the overall resilience in Henan Province continuously grows, and the resilience level of the Zhengzhou metropolitan area is the highest. In the urban resilience subsystem, economic and social resilience notably drive urban resilience improvement in Henan Province. (2) The spatial difference of urban resilience has been significantly reduced, but the inner metropolitan area presents the characteristics of “core–periphery”. Urban resilience presents a positive spatial correlation, and local spatial agglomeration is relatively stable. (3) Under the state of spatial interaction, urbanization rate, administrative, innovation, market, and industrial structure factors all have significant direct effects and spatial spillover effects on overall resilience, but openness exerts downward pressure on local resilience. (4) On this basis, strategies have been proposed to continuously promote the development of new urbanization, improve the regional coordinated development mechanism, increase market activity, optimize the environment for scientific and educational innovation, and promote the optimization and upgrading of industrial structure. The approach taken in this research may also be useful for developing urban resilience assessment tools in other central plains cities as well as in other cities in the interior of the world with similar conditions.

scholarly journals Study on the Spatiotemporal Evolution and Influencing Factors of Urban Resilience in the Yellow River Basin

2021 ◽  
Vol 18 (19) ◽  
pp. 10231
Author(s):  
Yu Chen ◽  
Xuyang Su ◽  
Qian Zhou
Keyword(s):  
Influencing Factors ◽  
River Basin ◽  
Yellow River ◽  
Yellow River Basin ◽  
Indicator System ◽  
Theil Index ◽  
The Yellow River ◽  
Urban Resilience ◽  
The Yellow River Basin ◽  
The Impact

The outbreak of COVID-19 has prompted consideration of the importance of urban resilience. Based on a multidimensional perspective, the authors of this paper established a comprehensive evaluation indicator system for evaluating urban resilience in the Yellow River basin (YRB), and various methods such as the entropy value method, Theil index, exploratory spatial data analysis (ESDA) model, and geographical detector model were used to measure the spatiotemporal characteristics and influencing factors of urban resilience in the YRB from 2011 to 2018. The results are as follows. (1) From 2011 to 2018, the urban resilience index (URI) of the YRB showed a “V”-shaped dynamic evolution in the time series, and the URI increased by 13.4% overall. The resilience of each subsystem showed the following hierarchical structure: economic resilience > social resilience > ecological resilience > infrastructure resilience. (2) The URI of the three major regions—upstream, midstream, and downstream—increased, and the resilience of each subsystem in the region showed obvious regional characteristics. The comprehensive difference in URI values within the basin was found to be shrinking, and intraregional differences have contributed most to the comprehensive difference. (3) There were obvious zonal differences in the URI from 2011 to 2018. Shandong Peninsula and Hohhot–Baotou–Ordos showed a “High–High” agglomeration, while the southern and southwestern regions showed a “Low–Low” agglomeration. (4) Among the humanist and social factors, economic, fiscal, market, urbanization, openness, and innovation were found to be the factors that exert a high impact on the URI, while the impacts of natural factors were found to be low. The impact of the interaction of each factor is greater than that of a single factor.

scholarly journals Measurement of the Energy Intensity of Human Well-Being and Spatial Econometric Analysis of Its Influencing Factors

2020 ◽  
Vol 17 (1) ◽  
pp. 357
Author(s):  
Ruyin Long ◽  
Qin Zhang ◽  
Hong Chen ◽  
Meifen Wu ◽  
Qianwen Li
Keyword(s):  
Energy Consumption ◽  
Influencing Factors ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Northern China ◽  
Well Being ◽  
Spillover Effects ◽  
Local Area ◽  
Energy Structure ◽  
Positive Effects

Current energy efficiency indicators (such as energy intensity) do not properly reflect the inherent relationship between “energy-environment-health”. Therefore, this study introduces the indicator of energy intensity of human well-being (EIWB) to depict the efficiency problem between energy consumption and residents’ health. In this paper, panel data of 30 provinces in mainland China from 2005 to 2016 is used to calculate the EIWB of each province and analyze its spatial distribution. Moreover, the effect of influencing factors on EIWB is investigated by using the spatial Durbin model. The results show that: (1) The EIWB presents a spatial agglomeration. The provinces with high EIWB mostly cluster in the northern China. (2) Industrial structure and energy structure have positive effects on EIWB in local area through increasing energy consumption and damaging residents’ health. (3) The effect of urbanization and income on local EIWB is significantly positive because it will promote energy consumption. (4) Industrial structure, health expenditure, foreign direct investment and technological progress have spatial spillover effects due to its significant impact on residents’ health in neighboring areas. Based on conclusions, the corresponding policy recommendations are proposed.

scholarly journals Analysis of the Spatial Distribution Characteristics of Urban Resilience and Its Influencing Factors: A Case Study of 56 Cities in China

2019 ◽  
Vol 16 (22) ◽  
pp. 4442 ◽  
Author(s):  
Zhang ◽  
Chen ◽  
Cai ◽  
Gao ◽  
Zhang ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Influencing Factors ◽  
Spatial Data ◽  
Evaluation System ◽  
Negative Impact ◽  
Positive Impact ◽  
Measurement Model ◽  
Spatial Data Analysis ◽  
Urban Resilience ◽  
Pension Insurance

The healthy development of the city has received widespread attention in the world, and urban resilience is an important issue in the study of urban development. In order to better provide a useful reference for urban resilience and urban health development, this paper takes 56 cities in China as the research object, and selects 29 indicators from urban infrastructure, economy, ecology and society. The combination weight method, exploratory spatial data analysis (ESDA) and spatial measurement model are used to explore the spatial distribution of urban resilience and its influencing factors. From 2006 to 2017, the urban resilience of prefecture-level cities in the four provinces showed a wave-like rise. During the study period, the urban resilience values, measured as Moran’s Is, were greater than 0.3300, showing a significantly positive correlation in regard to their spatial distribution. Regarding the local spatial correlation, the urban resilience of the study area had spatial agglomeration characteristics within the province, with a significant distribution of "cold hot spots" in the spatial distribution. From the perspective of the factors that affected urban resilience, the proportion of the actual use of foreign capital in GDP and carbon emissions per 10,000 CNY of GDP had a negative impact and GDP per square kilometer, the proportion of urban pension insurance coverage, the proportion of the population with higher education, and expenditure to maintain and build cities had a positive impact. The development strategy of urban resilience must be combined with the actual situation of the region, and the rational resilience performance evaluation system and the top-level design of urban resilience improvement should be formulated to comprehensively improve urban resilience.

scholarly journals Spatial–Temporal Evolution of Urban Resilience and Its Influencing Factors: Evidence from the Guanzhong Plain Urban Agglomeration

2020 ◽  
Vol 12 (7) ◽  
pp. 2593
Author(s):  
Fei Ma ◽  
Zuohang Wang ◽  
Qipeng Sun ◽  
Kum Fai Yuen ◽  
Yanxia Zhang ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Temporal Evolution ◽  
Entropy Method ◽  
Urban Agglomeration ◽  
Sustainable Urban Development ◽  
Ecological Environment ◽  
Urban Resilience ◽  
Rapid Urbanization ◽  
The Sustainable Development ◽  
Grey Correlation Analysis

Rapid urbanization places great pressure on the ecological environment and the carrying capacity of cities. Improving urban resilience has become an inherent requirement for the sustainable development of modern cities and urban agglomerations. This study constructed a comprehensive system to evaluate urban resilience from four perspectives: The ecological environment, economic level, social environment, and infrastructure services. As a case study, the extreme entropy method and panel data from about 16 cities from 2009 to 2016 were used to calculate resilience levels in the Guanzhong plain urban agglomeration (GPUA) in China. The spatial and temporal evolution of urban resilience characteristics in the GPUA were analyzed using ArcGIS. The influencing factors were further explored using a grey correlation analysis. The results showed that the urban resilience of GPUA experienced geographical differentiation in the “East-Central-Western” area and a “circle type” evolution process. Most urban resilience levels were low. The resilience of the infrastructure and the ecological environment significantly impacted the city and became its development weaknesses. Economic considerations have become one of the main factors influencing fluctuations in urban resilience. In summary, this study explored the differences in resilience in the GPUA and provided a reference for improving the urban resilience of other cities located in underdeveloped regions. The study also provided a useful theoretical basis for sustainable urban development.

Influencing factors and their influencing mechanisms on urban resilience in China

2021 ◽  
pp. 103210
Author(s):  
Dezhi Li ◽  
Guanying Huang ◽  
Dezhi Li ◽  
Xiongwei Zhu ◽  
Jin Zhu
Keyword(s):  
Influencing Factors ◽  
Urban Resilience

scholarly journals Prevalence and risk factors of worry among teachers during the COVID-19 epidemic in Henan, China: a cross-sectional survey

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e045386
Author(s):  
Yanqing Wang ◽  
Quanman Li ◽  
Clifford Silver Tarimo ◽  
Cuiping Wu ◽  
Yudong Miao ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Age Groups ◽  
Educational Status ◽  
Henan Province ◽  
Anxiety Level ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
School Location ◽  
Fear Level ◽  
Attention Level

ObjectiveTo evaluate the level of worry and its influencing factors during the COVID-19 epidemic among teachers in Henan Province in China.Study designA cross-sectional study was conducted.MethodsWe designed a cross-sectional survey that included 88 611 teachers from three cities in Henan Province, China between 4 February 2020 and 12 February 2020. Level of worry was measured using a five-item Likert scale, with 1 being ‘not worried’ and 5 being ‘very worried’. The OR and 95% CI of potential influencing factors for level of worry among study participants were estimated using ordinal logistic regression models.ResultsAbout 59% of teachers reported being ‘very worried’ about the COVID-19 epidemic. The proportion of female teachers was higher than of male teachers (60.33% vs 52.89%). In all age groups considered in this study, a ‘very worried’ condition accounted for the highest proportion. The age group 40–49 years had the lowest proportion of participants who were very worried, 52.34% of whom were men and 58.62% were women. After controlling for potential confounding factors, age, education level, type of teacher, school location, attention level, fear level, anxiety level and behaviour status were all related to level of worry (all p<0.05).ConclusionDuring the COVID-19 epidemic, there was a high proportion of teachers who were ‘very worried’ about the situation in Henan Province, China. Our study may remind policymakers to consider factors including age, educational status, type of teacher, school location, source of information on COVID-19, attention level, anxiety level, fear level and behaviour status to alleviate worry.

scholarly journals Impacts of Foreign Direct Investment and Industrial Structure Transformation on Haze Pollution across China

2021 ◽  
Vol 13 (10) ◽  
pp. 5439
Author(s):  
Chenggang Li ◽  
Tao Lin ◽  
Zhenci Xu ◽  
Yuzhu Chen
Keyword(s):  
Foreign Direct Investment ◽  
Environmental Pollution ◽  
Direct Investment ◽  
Industrial Structure ◽  
Spatial Data Analysis ◽  
Annual Data ◽  
Eastern Region ◽  
Structure Transformation ◽  
Haze Pollution ◽  
The Impact

With the development of economic globalization, some local environmental pollution has become a global environmental problem through international trade and transnational investment. This paper selects the annual data of 30 provinces in China from 2000 to 2017 and adopts exploratory spatial data analysis methods to explore the spatial agglomeration characteristics of haze pollution in China’s provinces. Furthermore, this paper constructs a spatial econometric model to test the impact of foreign direct investment (FDI) and industrial structure transformation on haze pollution. The research results show that the high-high concentration area of haze pollution in China has shifted from the central and western regions to the eastern region and from inland regions to coastal regions. When FDI increases by 1%, haze pollution in local and neighboring areas will be reduced by 0.066% and 0.3538%, respectively. However, the impact of FDI on haze pollution is heterogeneous in different stages of economic development. FDI can improve the rationalization level of industrial structure, and then inhibit the haze pollution. However, FDI inhibits the upgrading level of industrial structure to a certain extent, and then aggravates the haze pollution. The research in this paper provides an important decision-making basis for coordinating the relationship between FDI and environmental pollution and realizing green development.

scholarly journals Research on Spatiotemporal Differentiation and Influence Mechanism of Urban Resilience in China Based on MGWR Model

2021 ◽  
Vol 18 (3) ◽  
pp. 1056
Author(s):  
Yu Chen ◽  
Mengke Zhu ◽  
Qian Zhou ◽  
Yurong Qiao
Keyword(s):  
Spatial Heterogeneity ◽  
Spatial Correlation ◽  
Spatial Data ◽  
Central Area ◽  
Urban System ◽  
Entropy Method ◽  
Driving Factors ◽  
Spatial Data Analysis ◽  
Eastern Region ◽  
Urban Resilience

Urban resilience in the context of COVID-19 epidemic refers to the ability of an urban system to resist, absorb, adapt and recover from danger in time to hedge its impact when confronted with external shocks such as epidemic, which is also a capability that must be strengthened for urban development in the context of normal epidemic. Based on the multi-dimensional perspective, entropy method and exploratory spatial data analysis (ESDA) are used to analyze the spatiotemporal evolution characteristics of urban resilience of 281 cities of China from 2011 to 2018, and MGWR model is used to discuss the driving factors affecting the development of urban resilience. It is found that: (1) The urban resilience and sub-resilience show a continuous decline in time, with no obvious sign of convergence, while the spatial agglomeration effect shows an increasing trend year by year. (2) The spatial heterogeneity of urban resilience is significant, with obvious distribution characteristics of “high in east and low in west”. Urban resilience in the east, the central and the west are quite different in terms of development structure and spatial correlation. The eastern region is dominated by the “three-core driving mode”, and the urban resilience shows a significant positive spatial correlation; the central area is a “rectangular structure”, which is also spatially positively correlated; The western region is a “pyramid structure” with significant negative spatial correlation. (3) The spatial heterogeneity of the driving factors is significant, and they have different impact scales on the urban resilience development. The market capacity is the largest impact intensity, while the infrastructure investment is the least impact intensity. On this basis, this paper explores the ways to improve urban resilience in China from different aspects, such as market, technology, finance and government.

scholarly journals Spatial Spillover Effect and Influencing Factors of Information Flow in Urban Agglomerations—Case Study of China Based on Baidu Search Index

2021 ◽  
Vol 13 (14) ◽  
pp. 8032
Author(s):  
Chengzhuo Wu ◽  
Li Zhuo ◽  
Zhuo Chen ◽  
Haiyan Tao
Keyword(s):  
Influencing Factors ◽  
Information Flow ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Urban Agglomeration ◽  
Coordinated Development ◽  
Spatial Spillover ◽  
Urban Agglomerations ◽  
Search Index ◽  
Spatial Spillover Effect

Cities in an urban agglomeration closely interact with each other through various flows. Information flow, as one of the important forms of urban interactions, is now increasingly indispensable with the fast development of informatics technology. Thanks to its timely, convenient, and spatially unconstrained transmission ability, information flow has obvious spillover effects, which may strengthen urban interaction and further promote urban coordinated development. Therefore, it is crucial to quantify the spatial spillover effect and influencing factors of information flows, especially at the urban agglomeration scale. However, the academic research on this topic is insufficient. We, therefore, developed a spatial interaction model of information flow (SIM-IF) based on the Baidu Search Index and used it to analyze the spillover effects and influencing factors of information flow in the three major urban agglomerations in China, namely Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) in the period of 2014–2019. The results showed that the SIM-IF performed well in all three agglomerations. Quantitative analysis indicated that the BTH had the strongest spillover effect of information flow, followed by the YRD and the PRD. It was also found that the hierarchy of cities had the greatest impact on the spillover effects of information flow. This study may provide scientific basis for the information flow construction in urban agglomerations and benefit the coordinated development of cities.

Analyzing the Sustainability of Water-Cultural Industry and Their Influencing Factors in China

2021 ◽  
Author(s):  
Shubing Qiu ◽  
Yong Liu ◽  
Yang Ye
Keyword(s):  
Sustainable Development ◽  
Factor Analysis ◽  
Influencing Factors ◽  
Indicator System ◽  
Cultural Industry ◽  
The Sustainable Development ◽  
Relational Analysis ◽  
Analysis Theory ◽  
Cultural Ideology ◽  
Grey Relational

This study is an empirical analysis of China’s “sustainable development ability of water cultural industry” based on the attributes of water cultural industry (economic attribute and cultural ideology). First, using “factor analysis” and “grey relational analysis theory,” establish an indicator-system for the level of sustainable development of the cultural industry, then quantify the relationships between the water cultural industry and its influencing factors, and finally, propose some solutions for enhancing the sustainable development of the water cultural industry from the perspective of “improving resiliency.”

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