Researchers around the world are constantly producing discoveries. But for this knowledge to lead to innovation and growth, they often need to work with industry partners. So, promoting effective collaboration between researchers and businesses is of critical importance. However, there has been surprisingly little robust testing to optimise and increase the impact of interventions in this space.
While the experimental method is used to develop new scientific knowledge, it is ironic that the same method is not being used to create new policy knowledge about what works in advancing that science to society. This is something the Innovation Growth Lab – together with researchers from the Barcelona School of Economics and Esade – sought to change with the ATTRACT NEXT project.
As part of the project and a practical test of the feasibility of using experimental approaches (and randomised experiments in particular) to boost university-industry collaboration, we set up the University-Industry Impact Accelerator. Over six months, teams from the Portuguese Innovation Agency ANI, the applied research institute CCG and a team of researchers from Northumbria, Ulster, and the Manchester Metropolitan (MMU) Universities took part in a structured training programme on the foundations of experimentation.
Through a series of seven workshops and one-to-one clinic sessions with IGL researchers, the project teams designed experiments to address key questions or challenges they were facing. The participants developed the essential elements of their experiments, including the problem definition, the theory of change, the details of the experimental design, data collection approaches and risk management strategies. This process culminated in the teams piloting different elements of their experiments.
What did we learn from running the Accelerator?
First, the projects have demonstrated that experimentation in university-industry collaboration is possible. There are numerous untested initiatives in this field, many of which target significant numbers of researchers or businesses, so there are reasonable sample sizes to work with.
In addition, there is often good consensus on what success looks like, which helps in coming up with consistent and comparable outcome measures. Since there is little robust evidence about the effects of most interventions, concerns about fairness in being allocated to a specific treatment or control group are also minimised.
Small-scale piloting has also once again proven to be crucial before trying to run a full-scale randomised study. The pilots carried out for the Accelerator have led to important learning about the levels of demand for the interventions in question, the practicalities of implementation, and the details of how to collect data.
These insights will all feed into the design of the full-scale experiments and help to make them successful. For example, the team from Northumbria, Ulster and MMU tested a training programme on knowledge exchange for academic researchers. The pilot involved offering this programme to researchers at three universities, which showed that demand was significantly lower than expected. This prompted the implementers to consider how to stimulate more interest in this area before scaling up the offer.
Read the full story at the Innovation Growth Lab blog here.
Here you can watch a video of the NEXT project:
