Knowledge transfer in open innovation: a scientometrics analysis

Abstract Over the past decade or so, the relationship between open innovation and knowledge transfer has continued to receive widespread academic attention. Although a substantial body of literature has reviewed each domain separately, there remains a lack of quantitative and systematic examination of their interconnection. Thus, this study employs a bibliometric analysis based on 1508 publications from the Web of Science Core Collection and conducts visualization analyses using CiteSpace and VOSviewer to systematically reveal the intellectual structure and evolutionary trajectory of research linking open innovation and knowledge transfer. The results indicate that the intellectual landscape of this field consists of seven major research themes, reflecting its core knowledge structure and primary research hotspots. The temporal evolution analysis further identifies three key stages: the conceptual emergence stage (2003–2007), the theoretical development stage (2008–2014), and the diversified expansion stage (2015–present). Building on these findings, this study develops a multi-level analytical framework encompassing the macro-level (institutional and ecosystem contexts), meso-level (organizational capabilities and structures), and micro-level (individual motivations and behaviors) to elucidate the multi-layered pathways through which knowledge transfer operates within open innovation. The findings contribute to a more systematic understanding of the relationship between knowledge flows and collaborative innovation, offering practical implications for firms and policymakers seeking to optimize collaboration mechanisms and institutional design across different stages of innovation.