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Serendipity in Research and Innovation

Periodic Reporting for period 4 - SIRI (Serendipity in Research and Innovation)

Okres sprawozdawczy: 2022-12-01 do 2024-05-31

‘What is the issue being addressed?’
‘Why is it important for society?’
‘What are the overall objectives?’

The project examined the role of serendipity in research and innovation. The work is relevant to understanding how research can be used in innovation processes, and for informing public policy about research governance and its funding rationales. The objectives of the project were to identify important datasets and cases, develop new approaches and frameworks to analyse them, and provide a sense of how the nature of serendipity might vary across contexts.

Serendipity, the notion of researchers making unexpected and beneficial discoveries, has played an important role in debates about the feasibility and desirability of targeting public investments in research and development. This is the idea that, since the outcomes of research are impossible to predict, research itself is difficult (perhaps even impossible) to manage or direct towards specific social ends.

Research may be uncertain, but it is not random, and we know that industrial R&D managers fund research in areas where they expect returns and organise research to maximise its impact. With public policy, the scenario is slightly different, but there is limited evidence to draw on to support policy making.

Thus, in the SIRI project, we examined the nature of serendipity and develop techniques for its identification and measurement in order to get a sense of the prevalence of the phenomenon. We also sought to develop approaches to help evaluate the significance of serendipity, primarily through mapping techniques but also by identifying salient dimensions of analysis.

Since serendipity is likely to take different forms, we examined the phenomenon across a variety of settings. We deployed mixed quantitative and qualitative methods to generate large scale evidence as well detailed case studies. We focused on developing theory and implications to inform future policy on research and innovation.
We identified important datasets and case studies in a variety of settings, and developed approaches and frameworks to analyse them. This has allowed us to examine serendipity in different forms in US, UK and European research, and across a range of diseases. We examined cross disease spillovers, unexpectedness, misalignments, and usage of the term serendipity across the sciences. We used both manual and algorithmic classification techniques to identify and evaluate these cases. We also examined serendipity in the context of evidence-based policy, and drug development.

Despite considerable variation across contexts, the measures we have developed indicate that serendipity is common. The work has been presented at various stages to policymakers and researchers around the world, in large conferences, medium-sized workshops and small meetings.
We offered some of the first estimates for cross disease spillovers, unexpectedness in medical research, research impact alignment, and usage of the term itself across the sciences. These estimates provide important components in debates about research investments, rates of returns on those investments, and the extent to which those investments should be targeted to specific goals.

We developed approaches to map and visualise these measures and have developed ways to frame the analysis of serendipity. We explored factors that may define the scope for serendipity, and factors that may pull research towards serendipitous outcomes. Taken together, we have substantially improved understanding of serendipity in research and offered new ways of studying it.
see Aslan et al 2024 https://doi.org/10.1016/j.respol.2024.105075
see Yaqub et al 2024 https://doi.org/10.1016/j.respol.2024.105076
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