Why is it crucial to understand the elements of research and innovation? How can we be sure we’re focusing on the right aspects to answer key questions like: Has this funding program been successful? What’s the next generation of technology in a specific field? How does my organization compare with its peers? We know we’re on the right track when we can pinpoint where each element fits and where it’s heading within the larger mosaic of research and innovation. This clarity helps us measure success, anticipate future trends, and evaluate our position in the landscape.
Research and innovation is a puzzle made up of many diverse and seemingly unrelated pieces, yet when viewed as a whole, a clear pattern emerges. The research and innovation process is widely recognised as complex and non-linear. Developing a model to represent this process, even a general one, involves addressing several conceptual challenges, along with practical difficulties such as data collection, time delays, and intangible unobservable impacts. One effective approach for modeling the research and innovation process is to use a logic model, a tool commonly employed in policy and evaluation to articulate the rationale behind a policy or program and its broader context.
The primary advantage of using a logic model is that it makes explicit what is often implicit in the policy-making process. Additionally, it helps outline a “theory of change,” illustrating the expected pathways through which resources are transformed into outcomes and impact. It identifies key factors that may either facilitate or obstruct success at critical stages. In essence, a well-designed logic model clarifies both what a policy aims to achieve and how it intends to achieve those goals.1
Building on the traditional logic model structure2 and the framework proposed by G.B. Jordan (see footnote), we have developed a simple and generic model that organises the research and innovation process into a coherent, structured flow. This model represents a quasi-linear progression from scientific and innovative efforts to societal impact. It outlines the transition from current generation products and services that are already generating impact to the next generation, which is at various stages of planning or development and will drive future impact. This progression can also be mapped within a generic logic model framework, which moves from context to implementation and ultimately to outcomes and impact. By adopting this model, we gain clarity on why a research and innovation element is being described or evaluated, as it provides both context and clear objectives. The model follows this structure with five elements:
Capacity > Activities > Results> Outcomes > Impact
Capacity is the foundation of the research and innovation process, encompassing the resources, influences, and inputs that shape the agenda and drive R&D efforts. By setting the research agenda, governments or end-users identify key challenges, expand knowledge, and shape future R&D through initiatives like funding calls or collaborative planning. Capacity includes the existing scientific (knowledge) base, as well as essential R&D infrastructure such as facilities like linear accelerators or tools like spectroscopy and genome mapping techniques. It also relies on a skilled and educated R&D workforce, supported by networks of researchers, often referred to as communities of practice.
Key indicators: funding, policies, worksforce, infrastructure, countries, domains and disciplines, journals, and societies.
Key questions: what, when, where?
Activities refer to the implementation of basic (or frontier) and applied research. They cover experimental or theoretical work conducted with the goal of gaining new knowledge about the fundamental principles of phenomena and observable facts, without an immediate focus on practical applications. This includes activities that are more targeted, focusing on acquiring new knowledge that is directly linked to a specific practical goal or objective.
Key indicators: projects (grants).
Key questions: what, which?
Results refer to what is produced by a scientific activity, generally new knowledge. This is typically captured by the production of scholarly publications (e.g. scientific papers, conferences). Research results provide a lot of insignths about what is researched, the key actors oin the sector as well as the relationships between these actors.
Key indicators: publications, topics, organisations, teams, researchers.
Key questions: what, which, who?
Outcomes assess the immediate progress made towards desired changes in individuals, organisations, and communities. These outcomes typically arise from the rapid dissemination of knowledge, particularly within scientific and technical communities. Short-term results include the application of existing research and practical experience to develop new materials, products, generic technologies, or devices in the form of prototypes, and their testing in real-world environments. Additionally, this stage includes research aimed at understanding customer needs or improving distribution, sales, and adoption of new innovations.
Key indicators: scholarly citations, patent citations.
Key questions: what, where, which
Impact refers to long-term outcomes that result in system-level change. It involves the process by which end users, such as individuals, firms, and organisations, are convinced to adopt and continue using a technology or innovation. Impact encompasses the results of research and development (R&D) efforts that lead to the enhancement of manufacturing processes, product quality, or a deeper understanding of the effects of products, services, or policies. For example, this could include improving production techniques or evaluating the outcomes of health interventions through clinical trials. Achieving impact requires whose staff and knowledge from universities and research organisations to advance or package information about technologies and markets. This knowledge must be made available, accessible, and implementable for real-world use. At the same time, firms need to be prepared to finance, produce, distribute, and maintain new technologies or processes. Additionally, government agencies at all levels—federal, state, and local—play a key role in supporting the adoption of innovations through public policies and programs. Impact, therefore, is a collective effort involving research, industry, and policy to drive meaningful and sustained change.
Key indicators: patents, clinical trials, impact pathways, commercialisation, policy adoption.
Key questions: which, who, what?
- A theory-based logic model for innovation policy and evaluation, Jordan, G. B., Research Evaluation, 2010, Volume 19, Issue 4, Pages 263-273. DOI: 10.3152/095820210×12827366906445 ↩︎
- W.K. Kellogg Foundation Logic Model Development Guide. W.K. Kellogg Foundation, 2004. ↩︎