制造企业人工智能创新如何赋能高质量发展 ——来自中国上市公司的经验证据

制造企业作为人工智能创新战略的重要载体，在经济高质量发展过程中发挥着举足轻重的作用。基于2015—2019年596家制造业上市公司数据，从组织外部竞争和内部生产要素视角，通过构建个体固定效应非平衡面板模型，探讨人工智能创新驱动制造企业高质量发展的内在机制和边界条件。结果表明：人工智能创新能够有效推动制造企业高质量发展，人工智能创新双元性对高质量发展的影响无显著差异，而行业竞争能够强化人工智能创新对高质量发展的促进作用。进一步地，不同子行业人工智能创新对高质量发展的影响存在差异，劳动密集型企业和技术密集型企业人工智能创新能够促进高质量发展，而资本密集型企业人工智能创新对高质量发展的影响不显著。结论不仅有助于揭示人工智能对制造企业高质量发展的影响机制，还可为企业制定人工智能创新战略提供重要启示。

How Manufacturing Companies' AI Innovation Enable High Quality Development:Empirical Evidence from Chinese Listed Companies

In recent years, China's manufacturing industry is facing challenges such as fading demographic dividend, low value-added products, increasingly fierce international competition, and the intelligent transformation of enterprises has become an important direction for the high-quality development of the manufacturing industry. Artificial intelligence (AI) as a strategic technology is bringing disruptive changes to many fields in the economy and society, and how AI innovation affects manufacturing companies in different industries and different production factor is an important practical issue that needs to be studied urgently. #br#In addition, as international relations become more delicate and tense, events such as Brexit, the Sino-US trade war, the financial crisis makes the external environment of enterprises full of uncertainties and risks, and the innovation activities of enterprises are closely related to the external context. Manufacturing companies obtain new resources and information from the external environment for technological innovation to avoid environmental uncertainties and risks, so dissecting the complex relationship between AI innovation and high-quality development in the competitive industry context is of crucial strategic importance to the Chinese manufacturing industry at this stage. Therefore this paper explores the intrinsic mechanism and boundary conditions of AI innovation-driven high-quality development of manufacturing companies from the perspective of external industry competition and internal production factors.#br#Firstly, we select manufacturing listed companies in Shanghai and Shenzhen A-shares from 2015-2019 as the research sample, and collate an unbalanced panel dataset of five years in length, with a total of 2 888 sample data, including 596 manufacturing listed companies in 26 industries. Secondly, we comprehensively consider the dataset of this study and select the individual fixed-effects model for analysis, and discuss the relationship between high-quality development and each control variable, the relationship between high-quality development and AI innovation, and introduce the degree of industry competition into the regression equation to analyze the moderating effect of industry competition on the relationship between AI innovation and high-quality development. Further, we investigate the differences in AI innovation effects across industries and different production factor-intensive firms. Finally, we examine the difference between AI exploratory innovation effect and AI exploitative innovation effect based on dual innovation theory and prove that the above findings are stable through a series of robustness tests.#br#The research results show that, first, AI innovation can effectively promote the high-quality development of manufacturing companies, and there is no significant difference in AI dual innovation effect. Therefore, manufacturing companies should invest more in AI technology innovation to improve the digital and intelligent development. Second, industry competition can strengthen the positive impact of AI innovation on the high-quality development of manufacturing companies. Therefore, manufacturing companies should make AI innovation plans according to their competitive situation and the specific industry they are in, and allocate AI innovation resources in a market-oriented manner. Third, there are differences in the impact of AI innovation on high-quality development in different sectors of the manufacturing industry. Therefore, manufacturing companies should fully consider the difficulty of AI technology development and application prospect, and carry out AI innovation in stages and steps. Fourth, the characteristics of production factors have an obvious heterogeneous influence on AI innovation and high-quality development, among which AI innovation in labor-intensive enterprises and technology-intensive enterprises can promote high-quality development, while the influence of AI innovation in capital-intensive enterprises on high-quality development is not significant. Therefore, labor-intensive enterprises should actively exert the AI substitution effect and promote the transformation of production factor structure; while technology-intensive enterprises should continue to maintain the AI innovation effect and strengthen the R&D of AI advanced technology; capital-intensive enterprises should optimize the capital factor allocation and promote the transformation of AI innovation results into productivity.#br#In this paper, we reveal the positive role of AI innovation in promoting the high-quality development of manufacturing companies, which theoretically extends the application boundary of AI and provides empirical support for the intelligent transformation and upgrading of enterprises. Then we examine the impact of external competition on AI innovation to promote high-quality development, and the results show that external competition is more helpful for firms to exert AI innovation effects, which theoretically enriches the contextual variables of AI innovation and provides a new perspective for future research in the field of the AI. Third, we further reveal the industry heterogeneity of AI innovation effects through industry data, which expands and deepens the research framework in the AI field and provides important insights for different industry firms to develop AI innovation strategies. Fourth, we identify the differences in the AI innovation effects of manufacturing companies with different production factors, further enriching and expanding theoretically the application boundary of AI innovation.#br#