Asymmetries between partners and the success of university-industry research collaborations

Deals of a feather… Modelling latent classes in R&D collaboration data using finite mixture analysis

This work explores if behaviour-based asymmetries are likely to impact deal valuation in the life sciences by examining positive public sentiment as a proxy for market behaviour when negotiating under asymmetric conditions to examine heterogeneity in research & development collaboration (RDC) deal data. We use public sentiment as a proxy for behaviour along with stage of development-based RDC deal data to search for latent classes in the deal data using finite mixture modelling. The analysis reveals a nuanced picture: public sentiment emerges as a significant predictor of deal value, but only for approximately 15% of the data set. This subset exclusively includes firms in the Preclinical stage, where projects have moved past discovery but are yet to commence human studies. Interestingly, the research finds that sentiment's impact on deal valuation is particularly pronounced in this stage, suggesting heightened market sensitivity. With recent research demonstrating that knowledge asymmetry and behaviour impact valuation volatility, we take this further by capturing latent classes within the data which demonstrates how behaviour is most influential in deal pricing considerations. We argue that our research demonstrates the impact of asymmetry and market behaviour on a subset of RDCs where products are known, but likelihood of success is difficult to determine.

The impact of industry-university-research projects on biopharmaceutical companies' innovation performance: moderating roles of government subsidies for innovation

Innovation holds paramount importance for both nations and businesses. This article presents a panel regression model designed to assess the fixed effects of industry-university-research (IUR) cooperation projects on innovation performance. Furthermore, it examines the moderating impact of government innovation subsidies by utilizing data spanning from 2007 to 2021, encompassing 326 listed Chinese biopharmaceutical firms. Our findings reveal that industry-university-research-cooperation projects have the potential to significantly enhance innovation performance across three key metrics: input, output, and quality for firms. The presence of government innovation subsidies as a moderator is found to have a positive influence on IUR-cooperation projects and their innovative inputs. However, it can yield adverse effects on IUR-cooperation projects with respect to innovation outputs and quality. The insights presented in this paper introduce innovative recommendations for elevating corporate innovation quality and refining the policies governing IUR cooperation.

Impact of industry-university-research collaboration and convergence on economic development: Evidence from chengdu-chongqing economic circle in China

Collaboration among industry, universities, and research is crucial for building an innovative nation. Although industry-university-research collaborative innovation (IURCI) and time-space convergence can drive innovation, increase productivity, and spur economic development, their effects on the regional economy have not been thoroughly examined in existing literature. Therefore, this study investigates the impact of industry-university-research collaborative innovation (IURCI) and time-space convergence on economic development in China. Specifically, we focus on local-level cities in the Chengdu-Chongqing Economic Circle (CCEC) and construct an evaluation index system and time-space convergence model to measure the effects of IURCI and time-space convergence on economic development from 2007 to 2021. Our findings indicate that the efficacy of IURCI on economic development in China follows an inverted U-shaped curve, meaning that the marginal impact of IURC may decrease as more creative funds are deployed. Furthermore, the positive marginal effect of inventive talent input may decrease when it surpasses a certain value in an open innovation environment. The spatiotemporal convergence of collaborative innovation and development levels of IURCI in the CCEC shows significant differences. Regionally, the development level of IURCI in different regions exhibits significant differences in state and speed of convergence. In the southern Sichuan urban agglomeration, the collaborative innovation level of industry, education, and research follows an evolutionary process from convergence to divergence and then to convergence. Policymakers should pay close attention to the spatial effect of high-level development of regional IURCI and promote regions with higher development to drive regions with relatively weak development levels.

Doing science together: Gaining momentum from long-term explorative university-industry research programs

'Doing science together' collaborations are a more intense form of university-industry interactions and are characterized by a mutual involvement and active participation of academic and company scientists in scientific research. Here, we examine the successful approach that AstraZeneca and its internationally renowned academic partners, Karolinska Institutet and Uppsala University, implemented to fully unlock the potential of all parties in long-term, explorative, truly collaborative research programs. The underlying premises of these successful research programs are three collaborative governance mechanisms (3MCs) that are required that leverage the strengths of each organization: mutual collaboration; mutually beneficial science; and a mutual governance model with senior management involvement.

Industry-research fronts – Private sector collaboration with research institutions in Latin America and the Caribbean

In which research fields is industry involved with research institutions in Latin America and the Caribbean (LAC)? To shed light on this question, we applied bibliographic coupling to 13,000+ research articles and 500,000+ references indexed in Scopus for 1996–2021 as a means of determining the research fronts in which LAC-based research institutions collaborated with knowledge-intensive companies. Fields with higher betweenness centrality were those multidisciplinary, followed by physical (e.g. computer science applications), life (e.g. genetics), health (e.g. public health, environmental and occupational health) and social sciences and humanities (e.g. strategy and management). Furthermore, the period-by-period analysis unveiled a focused venturing into the physical sciences from 1996 to 2002. However, from the 2003–2021 periods, the new fields explored were mainly in the social sciences and humanities. Finally, we identified several unexplored research fronts, particularly in health (e.g. care planning) and the social sciences and humanities (e.g. demography).