Examining the Impact of Infrastructure Financialization on Uneven Regional Development: Evidence from China

Li, Yun; Ming, Xu; Dai, Juncheng; Yang, Zhenshan; Cheng, Zhe

doi:10.3390/land12030641

Cited by 7 publications

(1 citation statement)

References 55 publications

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“…In more developed regions, this can lower the threshold for enterprises to obtain market information and provide a good foundation of network information for industrial upgrading [31]. Uneven regional development in China has caused some problems, and this can be observed in the economy, finance, technology, and industrialization [32,33]. The difference in factor endowments will lead to differences in the development processes of all industries.…”

Section: H1 Ai Expands the Positive Externality Of Wrtmentioning

confidence: 99%

Effect of Artificial Intelligence on the Development of China’s Wholesale and Retail Trade

Jian

Guo

2023

Sustainability

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The rapid development of digital technologies and massive data analytics has enabled artificial intelligence (AI), via “machine learning”, to impact many societal sectors, including the wholesale and retail trade (WRT). However, the specific impact pathway and dynamics are still unclear. Based on the panel data of 30 provinces in China from 2015 to 2021, this paper employed the “VHSD-EM” model, random forest algorithm, and partial effect analysis to build an evaluation index system of AI and WRT, then to study the impact of AI on WRT in the temporal and spatial dimensions. Our main discoveries were as follows: (1) the quality of the WRT aligned well with the relative level of AI in the provinces, although the latter developed at a relatively fast pace; (2) the shortcomings that hindered the quality of WRT development varied in different regions, with a stark mismatch between the degree of informatization and the level of economic development in the eastern coastal region, a lack of innovation in the relatively high economic presence of the northern provinces, and a weak sharing of resources in the western region; (3) AI enhanced WRT development jointly with other key factors, particularly the density of employment, the percentage of WRT employees, and the ratio of the year-end financial institution deposits to the regional GDP, which raises the importance of the transaction volume of the technology market; (4) spatial differences exist in the impact pathways of AI on the high-quality development of WRT, and, for most provinces and regions except Shanghai and Guangdong, there is still significant room for expansion in the utilization of AI in WRT.

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Section: H1 Ai Expands the Positive Externality Of Wrtmentioning

confidence: 99%

Effect of Artificial Intelligence on the Development of China’s Wholesale and Retail Trade

Jian

Guo

2023

Sustainability

View full text Add to dashboard Cite

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Estimating Daily Concentrations of Near-Surface CO, NO2, and O3 Simultaneously Over China Based on Spatiotemporal Multi-Task Transformer Model

Zeng,

Wang,

Zhu

et al. 2024

Atmospheric Environment

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From here to where: assessing the infrastructure financialization in urban China

Li,

Cheng,

Yin

et al. 2024

ECAM

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PurposeInfrastructure financialization plays a critical role in infrastructure development and urban growth around the world. However, on the one hand, the existing research on the infrastructure financialization focuses on qualitative and lacks quantitative country-specific studies. On the other hand, the spatial heterogeneity and influencing factors of infrastructure financialization are ignored. This study takes China as a typical case to identify and analyze the spatial characteristics, development process and impact factors of infrastructure financialization.Design/methodology/approachTo assess the development and characteristics of infrastructure financialization in China, this study constructs an evaluation index of infrastructure financialization based on the infrastructure financialization ratio (IFR). This study then analyzes the evolution process and spatial pattern of China's infrastructure financialization through the spatial analysis method. Furthermore, this study identifies and quantitatively analyzes the influencing factors of infrastructure financialization based on the spatial Dubin model. Finally, this study offers a policy suggestion as a governance response.FindingsThe results demonstrate that infrastructure financialization effectively promotes the development of infrastructure in China. Second, there are significant spatial differences in China’s infrastructure financialization. Third, many factors affect infrastructure financialization, with government participation having the greatest impact. In addition, over-financialization of infrastructure has the potential to lead to government debt risks, which is a critical challenge the Chinese Government must address. Finally, this study suggests that infrastructure financialization requires more detailed, tailored,and place-specific policy interventions by the government.Originality/valueThis study not only contributes to enriching the knowledge body of global financialization theory but also helps optimize infrastructure investment and financing policies in China and provides peer reference for other developing countries.

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Examining the Impact of Infrastructure Financialization on Uneven Regional Development: Evidence from China

Cited by 7 publications

References 55 publications

Effect of Artificial Intelligence on the Development of China’s Wholesale and Retail Trade

Effect of Artificial Intelligence on the Development of China’s Wholesale and Retail Trade

Estimating Daily Concentrations of Near-Surface CO, NO2, and O3 Simultaneously Over China Based on Spatiotemporal Multi-Task Transformer Model

From here to where: assessing the infrastructure financialization in urban China

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