Public research spending has soared, but demand for proof of impact is also on the rise. Performance-based funding (PBF) resolves this, tying a share of core budgets to demonstrable excellence while respecting institutional autonomy. This Viewpoint outlines PBF’s archetypes, benefits, and pitfalls, offering practical guidance for policymakers and stakeholders working to turn R&D outlays into strategic, innovation-driven dividends.
Scientific research requires substantial resources (financial, human, infrastructural, and institutional), making it an increasingly expensive and complex undertaking. Since World War II, governments worldwide have adopted research funding as a core function, recognizing knowledge as a fundamental driver of societal advancement and economic prosperity. According to Organisation for Economic Co-operative and Development (OECD) estimates, governments spent US $504 billion on R&D in 2023, an amount that nearly doubled over the past 20 years, reflecting an expanding commitment to R&D activities.
Modern public research funding ecosystems operate through three distinct yet interconnected channels (see Figure 1). First, institutional funding provides the foundation for research capacity and infrastructure. Second, grants and awards funding enable researchers to pursue specific investigations through research councils and similar bodies. Third, strategic initiative funding targets national priorities and emerging fields. Traditionally, institutional funding (the largest of these streams) was allocated based on historical patterns or simple input metrics such as student enrollment, with minimal connection to research outcomes or quality.
Today, research ecosystems worldwide are being reshaped by intensifying demands for accountability, productivity gains, and increased competition. With the quality of research output increasingly determining national competitiveness and resilience, governments are seeking more effective approaches to allocate their significant research investments.
PBF is a strategic response to these challenges. By linking a portion of institutional funding directly to measured research performance, PBF creates powerful incentives for excellence while preserving institutional autonomy in implementation. This approach complements rather than replaces competitive grants or strategic initiatives, ensuring that the substantial base funding that institutions receive drives continuous improvement across their research portfolio.
If well-designed, PBF addresses these demands by transforming research support into a strategic investment that fuels knowledge creation, talent development, and innovation-driven growth — paying dividends in economic resilience, societal well-being, and a nation’s long-term capacity to tackle future crises.
This Viewpoint explores how performance thinking entered research policy, the main approaches to PBF, what advantages it can unlock, the pitfalls that sometimes accompany it, and the considerations stakeholders should account for when designing or reshaping any research funding scheme.
Historically, governments around the world, particularly in Europe, provided research institutions with institutional funding based on historical factors and size, essentially as a block grant without conditions. These systems followed the Humboldtian university tradition, in which autonomous professors play a central role and collectively decide on institutional-resource allocation. As environmental historian Sverker Sörlin observed, such systems entailed little oversight or external evaluation of how resources were spent and what was achieved.
Higher education management consultant Marcel Herbst and Sörlin both note that, following World War II, many higher education systems faced increased international economic competition and tighter government budgets, prompting shifts in their managerial and funding paradigms. As documented by Daniele Checchi et al. in Higher Education Quarterly and Sörlin, these shifts often entailed a move toward performance-based regimes rooted in New Public Management (NPM), introducing PBF systems and business-oriented management practices.
NPM emphasizes efficiency, competition, and outcome-based measurement within public sector organizations. For research and innovation, this meant a move away from trusting institutions to allocate lump-sum budgets in favor of frameworks that track outputs and impacts. This laid the foundation for PBF.
PBF is used to allocate a portion of core institutional funding (also known as “recurrent” or “base” funding, which is often the largest share of a research institution’s revenue from public funding). Unlike its predecessor, PBF distributes resources based on rigorous assessments of performance through a dual-component structure: a comprehensive assessment process measuring research quality across multiple dimensions and a funding process that incorporates these assessments into allocation formulas. These evaluations may incorporate both quantitative indicators (publications, citations, and external funding success) and qualitative peer reviews, introducing a competitive element to institutional funding while maintaining the essential funding required for operation.
The UK’s RAE
The Research Assessment Exercise (RAE), introduced in the UK in 1986 under Prime Minister Margaret Thatcher, was the world’s first PBF system, replacing historically determined block grants with funding based on peer evaluation of research quality. RAE was introduced to concentrate limited resources on the strongest research programs at a time of severe public spending cuts and fears of a brain drain. Developed amid economic constraints, it aimed to preserve research excellence by avoiding indiscriminate cuts. This approach also aligned with growing demands for accountability in public expenditure.
Expert panels evaluated departments’ research outputs, and the results determined the allocation of “quality-related” research funding. Despite a relatively modest financial impact, RAE profoundly influenced institutional behavior through its effect on prestige and reputation. Over multiple iterations (from 1989 to 2008), the methodology became increasingly sophisticated before evolving into the Research Excellence Framework (REF) in 2014. This model has since been adapted by numerous countries, each implementing variants that reflect their contexts and priorities.
Having established the concepts and background of PBF systems, we next examine how these principles translate into practice. PBF systems vary considerably in their design and implementation, but three main approaches have emerged:
PBF systems are based on several assumptions: transparency in allocating public resources fosters public trust, competition sparks innovation, and aligning funding with performance helps institutions achieve national strategic goals. Although the degree of reliance on PBF varies across countries, the underlying rationale remains consistent — to maximize the quality and impact of publicly funded research.
One of PBF’s most powerful features is its capacity to steer the research ecosystem. By explicitly rewarding research outputs in predefined priority areas (e.g., renewable energy, cybersecurity, advanced manufacturing), governments can guide institutions to align their strategic plans with high-priority fields. Over time, this alignment ensures that the national research, development, and innovation (RDI) agenda remains at the forefront of institutional decision-making, channeling talent and resources into areas deemed critical for socioeconomic progress. For example, the PBF model for public research institutes in Norway groups institutions into four distribution arenas (environmental, primary industry, social science, and technical-industrial) based on their professional activity to stimulate competition and drive quality in specific sectors.
Because PBF frameworks often prioritize high-impact publications and other indicators of excellence, institutions are motivated to invest in talent recruitment, research infrastructure, and cross-disciplinary collaboration. Departments that consistently underperform may see reduced budgets, propelling internal reforms (e.g., improved mentorship of junior faculty, strategic hires in emerging fields). In this manner, PBF can elevate overall research quality, provided that “quantity-based” metrics are balanced with rigorous quality assessments to discourage superficial “paper inflation.”
For instance, the UK’s REF and the Norwegian publication indicators work in a nonlinear way, with every increment in excellence rewarded (see Figure 5). Because each upward quality step carries a multiplicative gain (4→1 in the UK; 3→1 in Norway), universities see a steep return on converting “good” outputs into “excellent” ones.
As global challenges multiply, policymakers seek research that delivers tangible benefits beyond academic circles. By incorporating impact-focused measures (e.g., commercialization activities, community engagement, collaboration with public agencies), PBF frameworks encourage researchers to translate knowledge into practice. Whether that involves launching a start-up or receiving external funding, the system’s reward structure can expedite the real-world application of academic discoveries. Several countries (Croatia, Estonia, UK, Italy, Finland, Norway) reward external research income from industry and other societal stakeholders to improve academic industry research links, serving as a proxy indicator for impact.
Despite its advantages, PBF carries inherent risks if implemented in a simplistic or overly rigid manner. Awareness of these pitfalls helps policymakers craft well-designed systems that strike a balance between accountability and academic freedom.
When funding is tied to numerical targets (e.g., publication counts), institutions may artificially boost output at the expense of quality. “Salami slicing” (splitting one significant study into multiple small papers) or favoring quantity over impact are classic examples.
Mitigation: Combine bibliometric indicators with peer reviews and/or journal quality metrics and ensure robust checks for data integrity. A balanced indicator set discourages narrow strategies that inflate metrics.
Australia
Australia’s early performance-based research funding system led to increased publication quantity but decreased citation impact. Well-cited research by Linda Butler documents how universities dramatically increased output in low-impact journals after publication counts were tied to funding.
Overemphasis on well-established fields (where publication rates are high) could sideline areas that are critical yet slower to yield publications, such as emerging interdisciplinary fields or niche humanities scholarship.
Mitigation: Employ diversified indicators and weighting schemes that recognize different disciplines’ typical output, including qualitative measures of societal relevance.
Norway
The Norwegian publication indicator initially faced criticism for disadvantaging humanities disciplines. As Gunnar Sivertsen notes in Journal of Data and Information Science, humanities scholars publish more frequently in their national language and produce more books than journal articles, patterns that were initially undervalued in the metrics-based system. Norway addressed this by creating a comprehensive national research information system that registers all peer-reviewed scholarly publications across all fields, not just those in international citation databases.
If a large percentage of core funding is subject to annual performance fluctuations, institutions can face budget unpredictability, hampering long-term commitments to large-scale projects and stable hiring.
Mitigation: Use multiyear rolling averages so performance changes are more gradual. Introduce minimum funding floors or “safety nets” for vulnerable institutions, preserving mission-critical research capacity.
Finland
Finland addressed potential instability by designing its PBF model to include multiyear averages for research indicators. As described by Charles Mathies et al. in Higher Education, its system uses four-year evaluation periods for outputs, creating smoother transitions between funding cycles and allowing institutions to plan with greater certainty.
PBF is only a tool — its value depends entirely on how thoughtfully it is designed and implemented. Because no funding formula is perfect, policymakers should approach PBF with a clear view of its potential limitations and build in safeguards from the outset. Metric gaming, disciplinary imbalances, and funding volatility are three common examples to be cognizant of; others also deserve attention (e.g., administrative burden or unintended effects on collaboration). Keeping a broad risk landscape in mind helps ensure that a PBF scheme promotes constructive behavior, genuine excellence, and — crucially — the continued confidence of the research community.
The push toward PBF has been fueled by the quest to improve accountability, competitiveness, and relevance in publicly funded research. Drawing on the principles of NPM, PBF systems aim to reward excellence, encourage strategic alignment with national priorities, and accelerate the real-world impact of scientific discoveries. As countries explore or refine such funding models, several key considerations must guide their design and implementation to ensure long-term success and institutional sustainability.
There is no universal template for effective PBF. What works in one context may be counterproductive in another. Each country’s historical trajectory, academic culture, institutional diversity, and governance structures will profoundly shape how PBF systems are developed, interpreted, and received. Recognizing and respecting this variability is essential to building a system that is both effective and legitimate.
Before implementing or revising PBF, policymakers must clearly articulate why and how they expect performance-based mechanisms to serve national interests, be it improving research excellence, fueling innovation-driven economic growth, tackling pressing social challenges, or a combination.
Stakeholder engagement is crucial for successful implementation. University leaders, academic staff, industry partners, and community representatives should be involved in open discussions to define system elements. Collaborative processes build legitimacy, ensure that diverse research missions are recognized, and help institutions understand and accept the underlying goals of PBF.
When launching PBF initiatives, it’s advisable to start small by piloting PBF in selected institutions. Use feedback loops to refine metrics, weigh out unintended consequences, and adjust thresholds. It is especially important to test the results against the abovementioned risks to ensure the mitigation strategies embedded into the design of the model are effective. Additionally, periodic evaluations (every three to five years) help align the system with evolving national priorities and research environments.
When carefully implemented, PBF can create a research ecosystem capable of pushing the frontiers of knowledge and meeting pressing societal challenges. To do so, policymakers should:
Through an adaptive approach, policymakers can ensure their PBF systems will drive excellence, empower innovation, and yield tangible societal benefits.
By Adnan Merhaba, Eddy Ghanem, Karim Diab, Aleya Farhoud, Kiseki Hirakawa, Parth Gupta, Mohammed Al Baqshi, Joseph El Hajj, Ben Thuriaux-Aleman
In collaboration with Dr. Yazeed Alaskar, Vice Governor, Research, Development, and Innovation Authority (RDIA), Kingdom of Saudi Arabia (KSA); and Dr. Mohammed Al Thamer, General Manager, Institutional Funding Department, RDIA, KSA.
We would like to acknowledge Ben Thuriaux-Aleman for his contribution to the development of this Viewpoint.
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