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Cost–benefit analysis of applied research infrastructure. Evidence from health care

Author

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  • Battistoni, Giuseppe
  • Genco, Mario
  • Marsilio, Marta
  • Pancotti, Chiara
  • Rossi, Sandro
  • Vignetti, Silvia

Abstract

The present study aims at offering empirical evidence to improve existing knowledge and theory building on research infrastructure evaluation. Through an inductive case study research strategy, an innovative cost–benefit analysis framework has been used to assess the impact of an applied research infrastructure. The case study is the National Hadrontherapy Centre for Cancer Treatment (CNAO) located in Pavia (Italy). CNAO is an applied research facility specialised in hadrontherapy, an advanced oncological treatment showing clinical advantages as compared to traditional radiotherapy, at the same time being more expensive as it exploits non-commercial accelerators technology and sophisticated control and dose delivery systems. The analysis shows that with a fairly high probability the Centre provides a positive net contribution to society's welfare. Source of benefits are mainly health treatments to patients, for whom gains in terms of longer or better lives are guaranteed as compared to a counterfactual situation where they are treated with conventional therapies or they have no alternatives. Such benefits are the direct consequences of the application to end users of the knowledge developed in the Centre with research activities and are quantified and assessed on the basis of conventional cost–benefit analysis (CBA) approaches for health benefits. Additional benefits generated by the Centre are typical of research infrastructures in different scientific domains and refer to technological spillovers (namely creation of spin-offs, technological transfer to companies in the supply chain and to other similar facilities), knowledge creation (production of scientific outputs), human capital formation (training of doctoral students, technicians and professionals in the field of hadrontherapy) and cultural outreach (students, researchers and wider public visiting the facilities). Evidences show that the adopted CBA framework is a promising avenue as compared to existing alternative methodologies informing decision-making. Further research is however needed to fine tune the methodology, in particular for what concerns technological spillovers and knowledge creation benefits.

Suggested Citation

  • Battistoni, Giuseppe & Genco, Mario & Marsilio, Marta & Pancotti, Chiara & Rossi, Sandro & Vignetti, Silvia, 2016. "Cost–benefit analysis of applied research infrastructure. Evidence from health care," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 79-91.
  • Handle: RePEc:eee:tefoso:v:112:y:2016:i:c:p:79-91
    DOI: 10.1016/j.techfore.2016.04.001
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    References listed on IDEAS

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    Cited by:

    1. Massimo FLORIO & Francesco GIFFONI, 2019. "L’impatto sociale della produzione di scienza su larga scala: come governarlo?," Departmental Working Papers 2019-05, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    2. Massimo FLORIO & Francesco GIFFONI, 2017. "Willingness-to-Pay for Science as a Public Good: A Contingent Valuation Experiment," Departmental Working Papers 2017-17, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    3. Wenchao Xu & Yanmei Xu & Junfeng Li, 2017. "A Study of RI Clusters Based on Symbiosis Theory," Sustainability, MDPI, Open Access Journal, vol. 9(3), pages 1-13, March.
    4. repec:eee:tefoso:v:134:y:2018:i:c:p:169-177 is not listed on IDEAS
    5. repec:eee:respol:v:47:y:2018:i:9:p:1853-1867 is not listed on IDEAS
    6. Massimo FLORIO & Andrea BASTIANIN & Paolo CASTELNOVO, 2017. "The Socio–Economic Impact of a Breakthrough in the Particle Accelerators’ Technology: A Research Agenda," Departmental Working Papers 2017-18, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.

    More about this item

    Keywords

    Cost–benefit analysis; Applied research infrastructures; Healthcare; Hadrontherapy;

    JEL classification:

    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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