Measurement and Influencing Factors of Regional Economic Resilience in China DOI Open Access
Xinyu Zhang,

Congying Tian

Sustainability, Год журнала: 2024, Номер 16(8), С. 3338 - 3338

Опубликована: Апрель 16, 2024

The COVID-19 outbreak in 2020 has underscored the paramount importance of regional economies’ capacities to withstand and adapt external shocks. Enhancing economic resilience mitigating adverse impacts on both economy society have emerged as critical imperatives for ensuring sustainable development transformation national economy. This paper employs an improved counterfactual method measure index across 31 Chinese provinces cities from 2001 2021, coupled with empirical analysis using a dynamic panel model identify influencing factors resilience. Building upon this foundation, study delves into heterogeneous effects various different degrees marketization regions. Research Findings: (1) There been significant improvement levels China’s provinces, differences between regions far exceeding those levels, indicating substantial internal disparities. (2) Factors such index, industrial structure, level informatization, labor force size, quality, innovation capacity, degree government intervention all impact exhibit heterogeneity. Policy Recommendations: It is crucial address disparities while formulating strategies enhancing Regions should accelerate market-oriented reforms, promote rational mobility, strengthen investment human capital, foster innovation, adjust intervention.

Язык: Английский

Impact of high-speed rail operation on urban economic resilience: Evidence from local and spillover perspectives in China DOI
Ruimin Li, Meng Xu, Huiyu Zhou

и другие.

Cities, Год журнала: 2023, Номер 141, С. 104498 - 104498

Опубликована: Июль 27, 2023

Язык: Английский

Процитировано

40

Are shrinking populations stifling urban resilience? Evidence from 111 resource-based cities in China DOI

Ying Sun,

Yanan Wang, Xue Zhou

и другие.

Cities, Год журнала: 2023, Номер 141, С. 104458 - 104458

Опубликована: Июль 1, 2023

Язык: Английский

Процитировано

37

Technological Innovations for Enhancing Disaster Resilience in Smart Cities: A Comprehensive Urban Scholar’s Analysis DOI Open Access
Aravindi Samarakkody, Dilanthi Amaratunga, Richard Haigh

и другие.

Sustainability, Год журнала: 2023, Номер 15(15), С. 12036 - 12036

Опубликована: Авг. 6, 2023

Despite advancements, Smart Cities encounter hazards. Cities’ higher reliance on interconnected systems and networks makes them susceptible to risks beyond conventional ones, leading cascading effects. Hence, the effective use of technological innovations is vital. This involves understanding existing technology for resilience making in wise utilisation as suitable different contexts. However, there a research gap fundamental study that synthesises emerging disruptive technologies are being used improve disaster how they can be classified. Therefore, this aimed address need, so City evaluating technologies/tools could wisely utilise available resources prioritise most their context-specific needs. Following comprehensive literature review, identified 24 and/or tools creating, sustaining, enhancing within Cities. In doing so, should collect manage citywide geodata foster public participation. While feasible measure smartness City, findings suggested four key factors with which these assessed. These included impact society, adoption speed by Cities, maturity technology, capabilities offered community.

Язык: Английский

Процитировано

30

Digital finance and regional economic resilience: Evidence from 283 cities in China DOI Creative Commons

Shiying Hou,

Yining Zhang, Liangrong Song

и другие.

Heliyon, Год журнала: 2023, Номер 9(10), С. e21086 - e21086

Опубликована: Окт. 1, 2023

Digital technology provided a new driver for the rapid recovery of global economy in post-COVID-19 era. This study examined how digital financing affected regional economic resilience. First, this constructs multidimensional resilience evaluation system and measures levels 283 Chinese cities 2012-2021-using entropy value method. Then, panel data, mediation effect, threshold effect models were constructed to empirically test impact mechanism finance (DF) on The results show that DF improves resilience, which is more evident central western cities. Capital allocation efficiency, innovation, consumption are effective paths, whereas affects by enhancing capital strengthening innovation capacity, promoting resident consumption. It worth noting excessive financialization can mask role DF. These conclusions provide evidence clarifying

Язык: Английский

Процитировано

23

The impact of digital finance on regional economic resilience DOI
Yang Yang,

Zibo Lin,

Zhaoyi Xu

и другие.

Pacific-Basin Finance Journal, Год журнала: 2024, Номер 85, С. 102353 - 102353

Опубликована: Апрель 2, 2024

Язык: Английский

Процитировано

14

Can innovative industrial clusters enhance urban economic resilience? A quasi-natural experiment based on an innovative pilot policy DOI
Shulin Xu, Min Zhong, Yan Wang

и другие.

Energy Economics, Год журнала: 2024, Номер 134, С. 107544 - 107544

Опубликована: Апрель 24, 2024

Язык: Английский

Процитировано

13

Spatial differences and dynamic evolution of economic resilience: from the perspective of China’s eight comprehensive economic zones DOI

Kaiming Cheng,

Xinyu Wang, Liu Shucheng

и другие.

Economic Change and Restructuring, Год журнала: 2024, Номер 57(2)

Опубликована: Март 21, 2024

Язык: Английский

Процитировано

12

Spatial-temporal evolution of driving mechanisms of city resilience: A Sichuan-based case study DOI
Panyu Peng, Mingyang Li, Yibin Ao

и другие.

Land Use Policy, Год журнала: 2024, Номер 143, С. 107210 - 107210

Опубликована: Май 25, 2024

Язык: Английский

Процитировано

10

A study of the coupling between the digital economy and regional economic resilience: Evidence from China DOI Creative Commons

Jingshan Gu,

Z. Liu

PLoS ONE, Год журнала: 2024, Номер 19(1), С. e0296890 - e0296890

Опубликована: Янв. 19, 2024

The contemporary economic landscape has placed significant emphasis on the digital economy and resilience, progressively emerging as pivotal focal points for examining high-quality development of systems. However, there remains to be more research several critical topics. This includes characteristics coordinated between resilience systems their interdependence. In response, this study formulates a comprehensive evaluative framework regional grounded in intrinsic mechanisms both domains. It conducts thorough evaluation employing entropy weight-TOPSIS methodology. Additionally, leveraging coupling theory, coordination model’s degree serves foundational scrutinizing symbiotic advancement along with interdependent nature. sample comprises data from 31 provinces municipalities China (excluding Hong Kong, Macao, Taiwan) 2011 2020. Spatial autocorrelation Geodetector methodologies probe evolutionary traits driving factors underlying developmental relationship these two findings indicate an upward trajectory China’s annual index (from 0.233 0.458) 0.393 0.497). systems, measured 0.504 0.658 2020, demonstrate consistent growth pattern average increase 3.01%. These levels exhibit continuous improvement, zones manifesting hierarchical results within range [0.5, 0.8]. Notably, agglomeration evinces pronounced spatial positive correlation, while local Moran scattering are primarily concentrated localized migration leaps. Factors such foreign-funded enterprises’ total import export volume, online payment capability, fiber-optic cable length greatly influence relationship. contrast, other variables lower fluctuating weighted impact. establishes foundation synergistic effective Chinese region. Simultaneously, it offers valuable insights related subjects global contexts.

Язык: Английский

Процитировано

9

Predicting economic resilience: A machine learning approach to rural development DOI

Shun Du,

Yiwen Xu, Lei Wang

и другие.

Alexandria Engineering Journal, Год журнала: 2025, Номер 121, С. 193 - 200

Опубликована: Фев. 27, 2025

Язык: Английский

Процитировано

1