关键词: 公共数据开放, 高校科技成果转化, 专利转让, 多期DID

Abstract:

Universities in China have achieved remarkable results in technological research, playing a leading role in constructing an independent knowledge system. However, university technological achievements still face the bottleneck of relatively low rates of industrial transformation. Addressing the challenge of translating university research outcomes requires multi-party collaboration, establishing a public transformation platform involving diverse actors such as universities, enterprises, and technology transfer institutions, and improving the specialized service system for technological achievement transformation. Therefore, public data openness emerges as a novel solution, offering new possibilities for technology transfer. Public data openness refers to the process by which governments integrate public data resources and make them equally accessible to the public. It grants the public the rights to know, query, and utilize data, facilitating better resource discovery and industrial upgrading by societal actors, thereby creating commercial and social value. The transformation of university technological achievements is a “university-enterprise” collaborative innovation process. For enterprises, public data openness provides access to data resources at lower cost. The data elements not only empower enterprise R&D but also reduce the uncertainties they face. For universities, public data openness helps eliminate information barriers between universities and enterprises, and facilitate the coupling of university achievements with market demand. In this regard, investigating whether and how public data openness influences the technology transfer in higher education institutions is of significant importance for enhancing university technological development.

This study employs the launch of government data platforms as a quasi-natural experiment. Based on data covering Chinese university patent transfers from 2009 to 2023, a multi-period difference-in-differences (DID) model is used to investigate the impact of public data openness on the technology transfer of universities. The research findings demonstrate that public data openness positively promotes the transformation of university technological achievements. This conclusion still holds true after passing the parallel trend test, placebo test, double machine learning causality test, psm-did test and removing other policies’ effect. The mechanism test demonstrates that (1) Public data openness facilitates the coupling of university achievements with enterprise demand, promoting transformation through university-industry collaboration. And public data openness increased the number of university-industry jointly applied patents.(2) Public data openness effectively reduces transaction costs between universities and enterprises and alleviates the time lag in technology transfer. And public data openness exerts a stronger promoting effect in regions with protracted conversion delays. Heterogeneity analysis reveals that the impact of public data openness on university achievement transformation is more pronounced in regions with higher data openness quality and better digital infrastructure. Furthermore, its promoting effect is more obvious for invention-type patents and high quality patent transformations. This study bridges a significant gap in the literature by empirically demonstrating that public data openness facilitates university technology transfer.By providing rigorous evidence on how it overcomes the “last-mile barrier” in this process, our findings expand the research horizon on open public data governance.

This study provides the following insights for leveraging public data openness to optimize university technology transfer service systems. At the government level, authorities should accelerate public data disclosure while guiding multi-stakeholder participation in platform development to establish a cross-sectoral “communication bridge”. Differentiated policy support must be implemented through targeted interventions and technical guidance for regions with inadequate digital infrastructure, thereby bridging regional divides in technology commercialization. Universities should proactively deepen industry-academia partnerships through joint R&D initiatives to boost industrial applicability of innovations, while comprehensively showcasing research outputs via dedicated platforms spanning fundamental research to market applications to enhance external visibility. Prioritizing high value patent development tightly aligned with market needs remains critical for overcoming commercialization bottlenecks. For enterprises, dynamically monitoring university research outputs and acquiring relevant technologies through patent transfers can mitigate information asymmetry induced delays. Companies must also proactively articulate technical requirements, budgetary parameters, and collaboration frameworks to establish closed-loop innovation cycles.

Key words: public data openness, technology commercialization, patent transfer, multi-period DID