Information Technologies

Systematizing serendipity for big science infrastructures

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Big Science Research Infrastructures (BSRIs) are tremendous sources of ‘deep-tech’ with the potential to foment alternative commercial applications in diverse industries. Yet, cultivating novel applications of BSRI technologies is not straightforward due to misalignment between their scientific mission, large technological risks, market uncertainties, and long development times. Given these challenges, research is needed to understand if- and how-serendipitous innovations can be purposefully developed from BSRIs. In this study, we analyse ATTRACT, a novel initiative funded by the European Commission's Horizon 2020 program, which funded 170 projects with €100,000 each to develop a proof-of-concept commercial application of BSRI technologies within one year. Our analysis of this dataset identifies three modes employed by researchers to come up with alternate applications: (1) combining different technologies, (2) applying technology into a different field, and (3) using artificial intelligence or machine learning. In a second step, we conducted multinomial logistic regressions using the project data, expert evaluations, and a questionnaire to identify the antecedents associated with the pursuit of each of the three modes. Our findings suggest that scientists and engineers develop many new ideas about novel potential applications of BSRI technologies in their daily work. The main value of ATTRACT is in facilitating project development through financial resources, brokering relationships with industrial partners, and facilitating the applications of technologies in domains outside of the immediate purview of BSRIs.
Bibliographic citation: WAREHAM, J., PUJOL, L., KENNETH ROMASANTA, A., WAREHAM MATHIASSEN, T., NORDBERG, M., GARCIA TELLO, P. (2022). Systematizing serendipity for big science infrastructures. The ATTRACT project. TECHNOVATION, 116, Article 102374. doi:10.1016/j.technovation.2021.102374.

Reference: 10.1016/j.technovation.2021.102374 (DOI)
Date: 01/08/2022
Author(s): Jonathan Wareham; Laia Pujol; Angelo Kenneth Romasanta; Thomas Wareham Mathiassen; Markus Nordberg; Pablo Garcia Tello
Document type: Article in Journal (refereed)
Department: Information Systems
Languages: English