This study utilizes digital transformation and patent data from A-share listed companies on the Shanghai and Shenzhen stock exchanges in China between 2011 and 2021 to examine the influence of digital transformation on the quality of cross-regional collaborative innovation. The findings reveal that the cooperative innovation network exhibits pronounced small-world characteristics. In terms of spatio-temporal evolution, China’s urban collaborative innovation network demonstrates a notable quadrilateral spatial structure and has evolved toward a multicenter pattern. Moreover, the advancement of digital transformation positively contributes to both the quality and quantity of cross-regional cooperative innovation. By enhancing the relational embeddedness among cities, digital transformation facilitates improved outcomes in collaborative innovation. Furthermore, when the volume of digital patent applications surpasses a certain threshold, its positive effect on the quality of cross-regional collaborative innovation accelerates. These results provide empirical evidence from a major emerging economy, offering insights that can inform policies and strategies in other regions undergoing digital transition. The mechanisms identified, such as network structure evolution and relational embeddedness, contribute to a broader understanding of how digital transformation shapes innovation dynamics across geographical boundaries in a globalized knowledge economy.

科技人才队伍建设是支撑中国新时代人才强国战略实施的重要保障，也是推动中国式现代化和实现高水平科技自立自强的强有力支撑。论文基于2010—2019年1832名国家杰出青年科学基金项目获资助人(简称杰青人才)的履历信息，建立杰青人才流动理论分析框架，并采用社会网络分析法和负二项回归模型对杰青人才流动网络的结构特征和驱动因素进行分析。 结果表明：① 拓扑结构特征上，学习阶段网络主体以国内城市相互流动为主，呈现以北京、上海双核心的网络拓扑结构，工作阶段网络主体以国内与国外城市之间流动为主，呈现以北京、上海为双核心的网络拓扑结构，并展现出国外向国内一线城市集聚式流动的迁移特征，人才回流效应显著。② 核心—边缘特征上，相较于学习阶段，工作阶段的核心—边缘结构特征更为显著，强半边缘城市、弱半边缘城市及边缘城市之间呈现出一定的更迭特征。地理空间特征上，杰青人才国内流动网络呈现以北京为核心的轴辐式网络结构特征，并未表现出明显的“孔雀东南飞”的地理迁移特征。③ 城市属性要素回归结果表明，各阶段人才迁移的驱动因素具有一定差异性，其中教育资源、经济水平是影响杰青人才流动的关键要素。④ 邻近性因素上，“硕士—博士”阶段，人才的流动主要受文化邻近性和社会邻近性的影响，“杰青立项前一次工作—杰青立项”阶段，人才的流动主要受制度邻近性和社会邻近性的影响，“杰青立项—现工作”阶段，人才的流动主要受地理邻近性的影响。

Digital platforms are now central to local policy communication, but greater visibility does not always produce a more favorable public response. This study examines talent-policy news attention in Chinese cities, where competition for talent is increasingly conducted online. The analysis draws on a balanced panel of 232 cities from 2014 to 2023. Talent Policy Attention (TPA) is measured from talent-related news coverage. The talent policy sentiment-interaction (TPSI) index is constructed from messages posted on the Message Board for Leaders and combines sentiment composition with the intensity of institutionalized interaction. Two-way fixed-effects models with a quadratic term show a U-shaped association between TPA and TPSI. The estimated turning point corresponds to about 94 talent-related news reports per city-year in this sample. The pattern holds for alternative specifications of TPSI and for the participation dimension taken alone. Measures built on sentiment composition alone do not turn within the observed range, which places the reversal in participation rather than in sentiment polarity: sustained attention is associated with more talent-policy messages, not with a more favorable balance of expression. Mediation and heterogeneity results are consistent with possible conditioning roles for digital economy development and public service capacity in the association between TPA and TPSI. The design is observational at the city level, so the estimates describe associations rather than causal effects.