智慧供应链建设是否有助于企业全要素生产率提升？——基于供应链创新试点的经验证据
Does the Construction of Smart Supply Chain Contribute to the Improvement of Total Factor Productivity of Enterprises?—Based on Empirical Evidence from Supply Chain Innovation Pilots

智慧供应链建设对提高供应链韧性，提升企业生产力具有重要意义，同时也是实现“安全”与“发展”新发展格局的必然要求。本文选取2014~2022年沪深A股上市公司作为研究样本，采用双重差分模型探究智慧供应链建设对企业全要素生产率的政策影响以及作用机制。研究发现：智慧供应链建设能显著提升试点企业全要素生产率，数字化转型与成本管控水平在其中起到部分中介效应，该结论在经过一系列稳健性检验后依然成立。异质性分析表明，供应链创新试点对非国有企业与重点行业具有更高的政策影响。依据本文研究结论提出政策建议：(1) 总结供应链创新试点中的经验，加快推动数字化、智能化供应链体系建设。(2) 以智慧供应链建设为抓手，促进企业成本管控水平提升，协助企业降本增效。(3) 关注不同行业供应链优化目标的差异性，提高政策的靶向效果。
Intelligent supply chain construction is of great significance to improve the resilience of supply chain and enhance the productivity of enterprises, and it is also an inevitable requirement to realize the new development pattern of “security” and “development”. This paper selects A-share listed companies in Shanghai and Shenzhen from 2014 to 2022 as research samples, and uses double-difference models to investigate the policy impact and mechanism of smart supply chain construction on enterprise total factor productivity. It is found that smart supply chain construction can significantly improve the total factor productivity of pilot enterprises, and digital transformation and cost control level play a partial mediating effect, which is still valid after a series of robustness tests. Heterogeneity analysis shows that the supply chain innovation pilot has a higher policy impact on non-state-owned enterprises and key industries. Based on the findings of this paper, we propose the following policy recommendations: (1) Summarize the experience in the supply chain innovation pilot and accelerate the construction of digital and intelligent supply chain system. (2) Take the construction of intelligent supply chain as a hand, promote the improvement of enterprise cost control level, and assist enterprises to reduce costs and increase efficiency. (3) Pay attention to the differences in supply chain optimization goals of different industries to improve the targeting effect of policies.