In economics, infrastructure is a long-term investment aimed at the delivery of essential services to a large number of users, such as those in the field of transport, energy, or telecommunications. A research infrastructure (RI) is a single-sited, distributed, virtual, or mobile facility, designed to deliver scientific services to communities of scientists. In physical sciences (including astronomy and astrophysics, particle and nuclear physics, analytical physics, medical physics), the RI paradigm has found several large-scale applications, such as radio telescopes, neutrino detectors, gravitational wave interferometers, particle colliders and heavy ion beams, high intensity lasers, synchrotron light sources, spallation neutron sources, and hadrontherapy facilities. These RIs require substantial capital and operation expenditures and are ultimately funded by taxpayers. In social cost–benefit analysis (CBA), the impact of an investment project is measured by the intertemporal difference of benefits and costs accruing to different agents. Benefits and costs are quantified and valued through a common metric and using the marginal social opportunity costs of goods (or shadow price) that may differ from the market price, as markets are often incomplete or imperfect. The key strength of CBA is that it produces information about the project’s net contribution to society that is summarized in simple numerical indicators, such as the net present value of a project. For any RIs, consolidated cost accounting should include intertemporal capital and operational expenditure both for the main managing body and for experimental collaborations or other external teams, including in-kind contributions. As far as social intertemporal benefits are concerned, it is convenient to divide them into two broad classes. The first class of benefits accrue to different categories of direct and indirect users of infrastructure services: scientists, students, firms benefiting from technological spillovers, consumers of innovative services and products, and citizens who are involved in outreach activities. The empirical estimation of the use value of an RI depends on the scientific specificities of each project, as different social groups are involved to different degrees. Second, there are benefits for the general public of non-users: these benefits are associated with social preferences for scientific research, even when the use of a discovery is unknown. In analogy with the valuation of environmental and cultural goods, the empirical approach to non-use value aims at eliciting the willingness to pay of citizens for the scientific knowledge that is created by an RI. This can be done by well-designed contingency valuation surveys. While some socio-economic impact studies of RIs in physics have been available since the 1980s, the intangible nature of some benefits and the uncertainty associated with scientific discoveries have limited the diffusion of CBA in this field until recently. Nevertheless, recent studies have explored the application of CBA to RIs in physics. Moreover, the European Commission, the European Strategy Forum on Research Infrastructures, the European Investment Bank, and some national authorities suggest that the study of social benefits and costs of RIs should be part of the process leading to funding decisions.
Massimo Florio and Chiara Pancotti
The development of physics over the past few centuries has increasingly enabled the development of numerous technologies that have revolutionized society. In the 17th century, Newton built on the results of Galileo and Descartes to start the quantitative science of mechanics. The fields of thermodynamics and electromagnetism were developed more gradually in the 18th and 19th centuries. Of the big physics breakthroughs in the 20th century, quantum mechanics has most clearly led to the widest range of new technologies. New scientific discovery and its conversion to technology, enabling new products, is typically a complex process. From an industry perspective, it is addressed through various R&D strategies, particularly those focused on optimization of return on investment (ROI) and the associated risk management. The evolution of such strategies has been driven by many diverse factors and related trends, including international markets, government policies, and scientific breakthroughs. As a result, many technology-creation initiatives have been based on various types of partnerships between industry, academia, and/or governments. Specific strategies guiding such partnerships are best understood in terms of how they have been developed and implemented within a particular industry. As a consequence, it is useful to consider case studies of strategic R&D partnerships involving the semiconductor industry, which provides a number of instructive examples illustrating strategies that have been successful over decades. There is a large quantity of literature on this subject, in books, journal articles, and online.