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The Application of Artificial Intelligence and the Resilience of Manufacturing Enterprises: Mechanisms of Action and Heterogeneity Boundaries

2026-08-18 · Highlights in Business Economics and Management

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One-line summary

An autonomous driving research paper: The Application of Artificial Intelligence and the Resilience of Manufacturing Enterprises: Mechanisms of Action and Heterogeneity Boundaries.

Engineering notes

The findings reveal that AI application significantly enhances the resilience of manufacturing enterprises, with conclusions remaining robust even after substituting core variables, adjusting model specifications, controlling for cluster standard errors at the firm level, incorporating provincial fixed effects, and employing instrumental variable methods.

Chinese explanation / 中文解读

中文解读待补充:本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Against the backdrop of increasing external environmental uncertainties and accelerated intelligent transformation in the manufacturing sector, enhancing the resilience of manufacturing enterprises has become a critical issue for ensuring the security of industrial and supply chains and promoting high-quality development in manufacturing. This study uses China A-share listed manufacturing companies from 2015 to 2024 as research samples, constructs an indicator of corporate AI application levels based on annual report text mining methods, and measures corporate resilience across three dimensions: resistance capacity, recovery capacity, and innovation capacity, empirically examining the impact of AI application on manufacturing enterprise resilience and its underlying mechanisms. The findings reveal that AI application significantly enhances the resilience of manufacturing enterprises, with conclusions remaining robust even after substituting core variables, adjusting model specifications, controlling for cluster standard errors at the firm level, incorporating provincial fixed effects, and employing instrumental variable methods. Mechanism tests indicate that AI primarily strengthens corporate resilience by improving talent incentives, fostering technological innovation, and reducing management costs, with technological innovation serving as the primary transmission pathway; while internal control is partially influenced by AI, its mediating effect fails the Bootstrap robustness test. Further heterogeneity analysis demonstrates that the impact of AI on corporate resilience varies across ownership structures, firm size, regional differences, and industry attributes. This study enriches research on factors influencing corporate resilience in the digital economy context and provides empirical evidence for manufacturing enterprises to rationally advance AI adoption and enhance risk resistance and recovery capabilities.

5.0Engineering value
7.0Research novelty
5.0Business relevance

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