AI-UGT: AI's Impact on Urban Green Transition in the Yangtze River Delta, 2012-2024

Panel data from 40 cities in the Yangtze River Delta between 2012 and 2024 quantifies the role of artificial intelligence in the urban green transition. The research by Linlin Zheng uses benchmark regression, non-linear effect, and spatial econometric models to analyze AI's influence through production, consumption, and agglomeration channels. Findings indicate a significant positive effect with spatial autocorrelation and heterogeneous impacts based on urban hierarchy and resource endowment.

Use Cases

• Modeling the non-linear marginal effects of AI on green transition based on productive services and agricultural agglomeration thresholds.
• Analyzing spatial autocorrelation and spillover effects in urban green development using spatial econometric models.
• Investigating the mediating roles of fixed capital stock, industrial structure, and consumption levels in the AI-UGT relationship.
• Assessing heterogeneity in AI's impact based on urban hierarchy, geography, and institutional development factors mentioned in the study.

Strengths

• Data covers a 13-year time range from 2012 to 2024.
• Analysis is based on panel data from 40 cities within a defined urban agglomeration.
• The study employs multiple analytical models including spatial econometrics.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The 676.0 KB file size suggests a limited scope of underlying data.

Provenance

Source

Linlin Zheng via figshare.

Collection Method

Likely compiled from statistical yearbooks or official reports for the 40 cities.

Time Range

2012 to 2024

Freshness

Last updated 2026-05-03 14:41:57; freshness should be verified.

Geography

40 cities in the Yangtze River Delta (YRD) Urban Agglomeration, China.