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

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.