Big data analysis reveals an emerging change in academia-industry collaborations in the era of digital convergence

Big data analysis is increasingly being used as a decision-making support tool for science and technology policy and technology management through the understanding of the trends and structure of innovation activities and the prediction of their changes. Since diversity and convergence are generally regarded as opportunities for groundbreaking innovation, analysis of academia-industry convergence, a type of fusion among entities, using big data analysis is expected to provide useful suggestions for policy formation and technology management. Nevertheless, little quantitative analysis has been conducted to date. With the development of academia-industry collaboration in a broad sense, it has become possible to observe a certain number of cases where researchers themselves bridge academia and industry with two faces, one in academia and the other in business. In this study, we focus on academic research conducted through academia-industry collaboration and researchers who conduct academia-industry collaboration themselves ("ambidextrous researchers") and clarify the magnitude and changes of their academic impact by analyzing article citation data. Specifically, using Scopus as a dataset, we extracted papers co-authored by academia-industry and "ambidextrous researchers" using our definition and analyzed their publication and citation numbers comprehensively and over time. The results showed, first, that the average number of citations of the academia-industry co-authored papers is higher than the overall average, indicating that academia-industry collaboration enhances the quality of academic research. On the other hand, it was found that, at least up to now, academia-industry collaboration is not necessarily a suitable environment for producing home-run papers, as we cannot find such papers at the top of the citation count. Second, for papers whose authors include "ambidextrous researchers" who belong to both academic institutions and companies, we found that the number of publications and the academic attention of papers whose authors include "ambidextrous researchers" is increasing over time, especially in the field of AI (artificial intelligence), where we can safely say that the attention is structurally higher. Third, as a system in which "ambidextrous researchers" act as intermediaries for continuous technology transfer to companies has been established, it was confirmed that companies, especially platform companies, have come to play a major role in advanced AI research. This is because research resources such as computational resources and data possessed by platforms are effective in further developing academic research and so are quite attractive for researchers at universities and other institutions, which can be an incentive for them to be "ambidextrous researchers."