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The impact of technology transfer and knowledge spillover from Big Science: a literature review

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  • Scarrà, Deepa
  • Piccaluga, Andrea

Abstract

Big Science aims to answer fundamental questions regarding our Universe and represents a great example of how science can lead to innovations that generate a positive impact. Big Science has a great deal of scientific, economic, and social relevance. The objective of this study is to better understand how Big Science impacts innovation through transfer mechanisms and spillovers. To accomplish this objective, this study utilizes a thematic approach to review and organize academic research on Big Science. The main themes emerging from the literature are: technology transfer means and mechanisms, procurement relationships with suppliers, collaboration with public and private sectors, IP strategy and policy, impact of large shared facilities and infrastructures, and entrepreneurship as a result of technology transfer and spillover. Finally, we identify directions for future research.

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  • Scarrà, Deepa & Piccaluga, Andrea, 2022. "The impact of technology transfer and knowledge spillover from Big Science: a literature review," Technovation, Elsevier, vol. 116(C).
    • Handle: RePEc:eee:techno:v:116:y:2022:i:c:s016649721930015x
    DOI: 10.1016/j.technovation.2020.102165
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    Cited by:

    1. Becker, Bettina & Roper, Stephen & Vanino, Enrico, 2023. "Assessing innovation spillovers from publicly funded R&D and innovation support: Evidence from the UK," Technovation, Elsevier, vol. 128(C).
    2. Samuel Adomako & Nguyen Phong Nguyen, 2024. "Digitalization, inter-organizational collaboration, and technology transfer," The Journal of Technology Transfer, Springer, vol. 49(4), pages 1176-1202, August.
    3. Annamaria Demarinis Loiotile & Francesco De Nicolò & Adriana Agrimi & Loredana Bellantuono & Marianna La Rocca & Alfonso Monaco & Ester Pantaleo & Sabina Tangaro & Nicola Amoroso & Roberto Bellotti, 2022. "Best Practices in Knowledge Transfer: Insights from Top Universities," Sustainability, MDPI, vol. 14(22), pages 1-23, November.
    4. Wu, Yunna & Yong, Xingkai & Tao, Yao & Zhou, Jianli & He, Jiaming & Chen, Wenjun & Yang, Yingying, 2023. "Investment monitoring key points identification model of big science research infrastructures -- Fuzzy BWM-entropy-PROMETHEE Ⅱ method," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).

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