University-business R&D collaborations and innovation in light of Artificial Intelligence: a new AI-based open innovation paradigm

This study investigates the impact of artificial intelligence (AI) technologies on university- business (UB) R&D collaborations. Digital technologies, including AI, are widely regard- ed as key factors fostering Open Innovation collaborations. However, contrary to common understanding, their effects on collaborations remain controversial. According to authors, AI technologies might provide limited advantages to firms, and they can even hamper the creativity process. To test our hypotheses, we assume that Artificial Intelligence in- teracts with individual digital skills, acting as moderators of collaboration between part- ners. Considering the complexity of open innovation collaborations, we also hypothesize that relationships between constructs are U-shaped (non-linear or curvilinear). Hypotheses were tested using a mixed methodology on a large-scale dataset related to firms in the European Union. Our findings confirm that UB collaborations positively impact innova- tion effectiveness. At the same time, evidence shows that digital skills and AI technologies might alter creativity and engagement dynamics in a non-linear fashion. Hence, this study contributes new insights in the research field, by proposing a curvilinear interpretation of the impact of AI on OI dynamics and on new knowledge creation.

This study investigates the impact of artificial intelligence (AI) technologies on university-business (UB) R&D collaborations. Digital technologies, including AI, are widely regarded as key factors fostering Open Innovation collaborations. However, contrary to common understanding, their effects on collaborations remain controversial. According to authors, AI technologies might provide limited advantages to firms, and they can even hamper the creativity process. To test our hypotheses, we assume that Artificial Intelligence interacts with individual digital skills, acting as moderators of collaboration between partners. Considering the complexity of open innovation collaborations, we also hypothesize that relationships between constructs are U-shaped (non-linear or curvilinear). Hypotheses were tested using a mixed methodology on a large-scale dataset related to firms in the European Union. Our findings confirm that UB collaborations positively impact innovation effectiveness. At the ...