AbstractClinical research infrastructure is one of the unsung heroes of the scientific response to the current COVID-19 pandemic. The extensive, long-term funding into research support structures, skilled people, and technology allowed the United Kingdom research response to move off the starting blocks at pace by utilizing pre-existing platforms. The increasing focus from funders on evaluating the outcomes and impact of research infrastructure investment requires both a reframing and progression of the current models in order to address the contribution of the underlying support infrastructure. The majority of current evaluation/outcome models focus on a “pipeline” approach using a methodology which follows the traditional research funding route with the addition of quantitative metrics. These models fail to embrace the complexity caused by the interplay of previous investment, the coalescing of project outputs from different funders, the underlying infrastructure investment, and the parallel development across different parts of the system. Research infrastructure is the underpinning foundation of a project-driven research system and requires long-term, sustained funding and capital investment to maintain scientific and technological expertise. Therefore, the short-term focus on quantitative metrics that are easy to collect and interpret and that can be assessed in a roughly 5-year funding cycle needs to be addressed. The significant level of investment in research infrastructure necessitates investment to develop bespoke methodologies that develop fit-for-purpose, longer-term/continual approach(es) to evaluation. Real-world research should reflect real-world evaluation and allow for the accrual of a narrative of value indicators that build a picture of the contribution of infrastructure to research outcomes. The linear approach is not fit for purpose, the research endeavour is a complex, twisted road, and the evaluation approach needs to embrace this complexity through the development of realist approaches and the rapidly evolving data ecosystem. This paper sets out methodological challenges and considers the need to develop bespoke methodological approaches to allow a richer assessment of impact, contribution, attribution, and evaluation of research infrastructure. This paper is the beginning of a conversation that invites the community to “take up the mantle” and tackle the complexity of real-world research translation and evaluation.
An Empirical Study on the Effect of Agricultural Infrastructure Investment on Economic Growth
