Artificial Intelligence and Supply Chain Resilience Under Persistent Disruption: Evidence from the Semiconductor Industry

The data used in this study are drawn from the article "Artificial Intelligence and Supply Chain Resilience Under Persistent Disruption: Evidence from the Semiconductor Industry." The empirical analysis is based on panel data of Chinese A-share listed companies in the semiconductor industry from 2010 to 2024. The data are collected from multiple sources, including the CSMAR database for financial information, the Wind database for government subsidies, and the CNRDS database for patent data. After excluding firms with special treatment (ST) or missing key variables, the final sample comprises 2,159 firm-year observations. Key variables include supply chain resilience (constructed via entropy method from resistance, recovery, and development dimensions), artificial intelligence adoption (measured by AI-related keyword frequency and patent counts), and a set of firm-level controls, along with moderators such as government support and trade conflict exposure.