How do partner selection strategies affect the amount of funding in collaborative research projects? Evidence using the dual-projection approach
The selection of partners plays a crucial role in determining the success of collaborative projects. This study makes a valuable contribution to the existing literature on collaborative research and development by examining the impact of different partner selection strategies on the funding received in collaborative research projects. Previous studies have not shown sufficiently how collaborating with new partners as opposed to existing ones influences the amount of funding received. To bridge this gap, we use the innovative dual-projection approach from Social Network Analysis. Specifically, we analyze the network structure of projects funded by Horizon 2020, the eighth European Framework Programme. Our findings show that compared to collaborating with established partners, collaborating with new ones increases the likelihood of securing more funding when entering a new project. Moreover, projects coordinated by private or public organizations rather than research centers and higher education institutions have a higher probability of obtaining greater funding. However, the significance of partner connections diminishes with decreasing proximity to the focal organization. Ultimately, our results offer valuable insights into the effectiveness of the European Research and Technological Development Policy in fostering excellent science through cross-collaboration among a diverse group of actors. • Novel approach from Social Network Analysis to investigate collaborative projects. • Focus on how selecting new over existing partners affects the amount of funding. • Analysis of the network of collaborative research projects funded by Horizon 2020. • Partnering with unrelated actors increases the likelihood of securing more funding. • Projects coordinated by private or public actors tend to obtain higher funding.
Authors
- Rosanna Grassi (ORCID: https://orcid.org/0000-0001-5292-1723)
- Andrea Ancona (ORCID: https://orcid.org/0000-0003-4795-8753)
- Roy Cerqueti (ORCID: https://orcid.org/0000-0002-1871-7371)
Institutions
- Université d'Angers (FR)
- University of Milano-Bicocca (IT)
- Sapienza University of Rome (IT)
Publication Details
- Journal
- Technological Forecasting and Social Change
- Published
- 2024-09-08
- DOI
- https://doi.org/10.1016/j.techfore.2024.123744
- Citations
- 2
- Primary Topic
- Innovation and Knowledge Management
- Type
- article
- Field-Weighted Citation Impact
- 1.11