Intelligent Manufacturing and Total Factor Productivity of Export Enterprises

基于2011~2023年具有出口行为的A股上市公司的面板数据进行研究，以智能制造试点示范行动作为准自然实验，构建双重差分模型，系统考察了智能制造对出口企业全要素生产率的影响。研究结果表明，智能制造能够显著提升出口企业全要素生产率，且这一结论在经过内生性处理和稳健性检验后依然成立。异质性分析进一步发现，智能制造对全要素生产率的提升作用在非国有企业、劳动力密集型企业以及西部地区中更为显著，而对国有企业、资本密集型企业、中部及东部地区的影响相对较弱。机制分析表明，智能制造主要通过提升企业创新能力、人力资本水平以及ESG水平等渠道，促进出口企业全要素生产率的增长。本研究结论不仅为理解智能制造赋能企业高质量发展的路径提供了新的经验证据，还对下一阶段智能制造产业政策的优化设计与有效实施具有重要的借鉴意义，同时也为推动制造业智能化转型、实现制造强国战略目标提供了理论支撑和实践启示。Based on the panel data of A-share listed companies with export behavior from 2011 to 2023, this study employs the pilot demonstration action of intelligent manufacturing as a quasi-natural experiment and constructs a difference-in-differences (DID) model to comprehensively investigate the impact of intelligent manufacturing on the total factor productivity (TFP) of export enterprises. The findings indicate that intelligent manufacturing significantly enhances the TFP of export enterprises, and this conclusion remains robust after addressing endogeneity concerns and conducting various robustness tests. Heterogeneity analysis further reveals that the positive effect of intelligent manufacturing on TFP is more pronounced in non-state-owned enterprises, labor-intensive enterprises, and firms located in the western region, whereas its influence on state-owned enterprises, capital-intensive enterprises, and firms in the central and eastern regions is relatively weaker. Mechanism analysis demonstrates that intelligent manufacturing primarily boosts TFP growth in export enterprises through channels, such as improving enterprise innovation capabilities, enhancing human capital levels, and elevating environmental, social, and governance (ESG) performance. The results of this study not only provide novel empirical evidence for understanding the pathways through which intelligent manufacturing drives high-quality enterprise development but also offers critical insights for the optimization and effective implementation of intelligent manufacturing industrial policies in the future. Additionally, the study provides theoretical support and practical guidance for advancing the intelligent transformation of the manufacturing sector and achieving the goal of becoming a global manufacturing powerhouse.