A dataset of AI and Industrial Chain Resilience for 275 Chinese cities from 2012 to 2022

This study proposes the following six hypotheses: Hypothesis 1: Artificial intelligence enhances industrial chain resilience. Hypothesis 2: Artificial intelligence enhances industrial chain resilience through technological innovation effects. Hypothesis 3: Artificial intelligence enhances industrial chain resilience through risk management effects. Hypothesis 4: Artificial intelligence enhances industrial chain resilience through information sharing effects. Hypothesis 6: Urban resource endowments exert a positive moderating effect on the relationship between AI and industrial chain resilience. AI denotes the independent variable—artificial intelligence, measured by the degree of AI application in enterprises. ICR denotes the dependent variable—industrial chain resilience, measured by the comprehensive score of the industrial chain resilience indicator system calculated using the entropy weight method. City denotes the control variable—urbanization level, measured by the proportion of permanent urban residents to the total permanent population. Pop denotes the control variable—population density, measured by the proportion of permanent urban residents to the city's total area. Open denotes the control variable—degree of openness, measured by the ratio of total imports and exports to regional GDP. Fin denotes the control variable—financial development level, measured by the ratio of year-end loan balances of financial institutions to regional GDP. Eco denotes the control variable for urban economic density, measured as the ratio of regional GDP to the land area of the administrative region. The panel data for 275 Chinese cities from 2012 to 2022 sourced from the China Statistical Yearbook, China Science and Technology Statistical Yearbook, China Energy Statistical Yearbook, China Urban Statistical Yearbook, and the National Bureau of Statistics Bulletin. Partially missing data was imputed using linear interpolation. ICR_adj denotes the supply chain resilience level reconstructed via principal component analysis. LOP and LTP represent data with one-period and two-period lags applied to the resilience level, respectively, for robustness testing. AI_1 indicates one-period forward AI data, while IV denotes the instrumental variable used for endogeneity testing. In heterogeneity tests, the city's regional location is denoted by Region, with samples categorized into Eastern, Central, and Western regions (1, 2, 3, respectively). City resource endowment is represented by Endowment, with resource-based cities, non-resource-based cities, and resource-depleted cities denoted as 1, 2, 3, respectively. TI denotes the technological innovation effect, measured by the number of employees in scientific research, technical services, and geological exploration industries. RM represents the risk management effect, measured by GDP growth rate. IS signifies the information sharing effect, measured by the total volume of telecommunications services.