【摘要】 数字经济背景下，以数实融合赋能实体经济创新发展，是实现经济高质量发展的重要着力点。基于2011—2019年中国A股制造业上市公司等数据，本文构造了数实融合指标体系，系统考察数实融合对制造业企业创新质量的影响及作用机制。研究发现，数实融合提高了企业创新质量，上述效应在国有企业、高科技企业以及位于政府数字关注度较高和公共数据开放地区的企业中更为明显。机制分析结果表明，企业研发强度增强、信息透明度提高和市场竞争加剧构成了数实融合影响创新质量的作用渠道。本文的研究为推进数实融合、促进制造业企业提升创新质量和实现高质量发展提供了事实依据与政策启示。更多还原

【Abstract】 Against the background of the rapid development of the digital economy, empowering the innovative development of the real economy through the integration of the digital economy and the real economy(known as digital-real integration) is a key focus for achieving high-quality economic development. Innovation serves as the primary driver for achieving high-quality development, and high-quality innovation is essential to guiding such development. As enterprises are the main players in digital-real integration and innovation, this paper explores the impact of the integration of physical enterprises and the digital economy on innovation quality.Based on data from China’s A-share listed manufacturing companies from 2011 to 2019 and relevant data on the prefectural-level digital economy, this paper constructs a digital-real integration index system from three aspects: digital economy integration, digital-real integration process, and environmental conditions for such integration. Then, it systematically investigates the impact of digital-real integration on the innovation quality of manufacturing companies and its mechanism. The results show that digital-real integration can improve enterprise innovation quality, and this positive effect is more pronounced in large-scale enterprises, state-owned enterprises, and high-tech enterprises. At the same time, enterprises located in areas with high government digital attention and open public data can promote their innovation quality by leveraging favorable external digital conditions to facilitate digital-real integration. Mechanism analysis identifies three transmission channels: enhanced R&D intensity, improved information transparency, and intensified market competition. Methodologically, this paper employs three machine learning methods, namely the random forest(RF) algorithm, the least absolute shrinkage and selection operator(LASSO), and the support vector machine(SVM), to solve benchmark results. The results still hold after conducting a series of robustness checks, including alternative innovation metrics, sample exclusion, and cluster adjustments.This paper provides empirical evidence and policy enlightenment for China to promote digital-real integration, enhance the innovation quality of manufacturing enterprises, and achieve high-quality development. The government should attach great importance to promoting the construction of digital ecosystems, facilitate the integration of digital economy factors and advanced digital technologies into all stages of enterprise production, sales, and operations, and reinforce digital infrastructure, including communication networks, data computing power, and transaction platforms. At the same time, the government should incentivize digital talents to engage in R&D activities, improve enterprise innovation efficiency, continue to deepen the strategy of opening public data, accelerate the cultivation of data factor markets, stimulate the innovation and entrepreneurship vitality of micro market players, and better promote the high-quality development of the real economy.更多还原