Evaluation of research group visibility, governance, and engagement in the top 500 global universities

Introduction: This exploratory quantitative study examines how the visibility of Research Groups (RGs) is structured, supported, and applied across the QS Top 500 universities (2026), reflecting a global shift toward research groups that serve society rather than solely academic prestige.

Methods: The analysis investigates the presence of formal governance frameworks, dedicated resources, visibility, interdisciplinary and international collaboration, student involvement, and external engagement with industry, government, and communities. It also compares patterns across global regions and between top-200 and 201–500 ranked universities.

Results: Findings revealed that while most universities host RGs with defined leaders, themes, and student participation, fewer than 40% employ formal policies or centralized oversight. Less than half of RGs build active partnerships beyond academia, secure external funding, or systematically share their achievements publicly. Mid-ranked universities display higher RG visibility and structured integration than many elite universities, which often rely on legacy laboratories and reputation rather than formal group frameworks.

Discussion: Universities are encouraged to strengthen RG policies, expand collaboration, and improve visibility to enhance both research impact and alignment with their broader missions.

1 Introduction

Scientific research has always been meant to improve lives and address real problems, not merely to pad academic promotions. For decades, however, many universities treated research primarily as a means to secure promotions, funding, or prestige within academia (Kawalilak, 2017). The result was a competitive “publish-or-perish” culture that often narrowed the focus of scholarly work away from practical impact. In such an environment, the conviction that research should do more than advance careers was largely missing; ideally, should benefit communities, inform public policy, and solve pressing global challenges (van Dalen and Henkens, 2012). In recent years, this mindset has begun to shift. Around the world, leading universities and policymakers are increasingly recognizing that academia must play a role in creating social and economic value—essentially becoming an “embedded brain” in society (Munk et al., 2017). In other words, universities are being called to leverage their rich knowledge and resources not only to publish research, but also to drive positive social change and deliver tangible benefits to society.

One clear indicator of this shift is the rise of the research group (RG) as a fundamental unit of innovation in universities. In this context, an RG is more than a professor with a few graduate students; it is a structured team of scholars, often interdisciplinary and sometimes spanning multiple countries or universities, working together on well-defined challenges (Vabø et al., 2016). The logic behind this model is that impactful research in the 21st century must be organized, collaborative, inclusive, and globally aware. Within effective RGs, students are integrated not just as assistants but as essential contributors to knowledge creation, gaining mentorship and hands-on experience. Many groups intentionally include international or cross-sector collaborators who broaden the group’s vision and help translate findings into practice (Vabø et al., 2016). In short, when done right, RGs are not isolated academic silos; they are dynamic engines of innovation and education.

Studies consistently find that research involving diverse, long-term collaborations tends to achieve greater scientific impact and productivity. For example, internationally co-authored papers on average earn higher citation impact than those by single-nation teams (Cheol Shin et al., 2013). Similarly, RGs that sustain long-term partnerships (even with industry) show improved scientific performance (Garcia et al., 2020). In essence, organized collaboration expands a university’s ability to produce knowledge that truly matters.

The organization and visibility of research groups (RGs) in universities are grounded in several interrelated theoretical perspectives. One of the dominant frameworks is the Mode 2 knowledge production model, which argues that contemporary research increasingly occurs in context-driven, problem-oriented, and interdisciplinary environments, rather than in traditional disciplinary silos (Gibbons et al., 1994). Within this model, RGs function as flexible, collaborative units capable of integrating diverse expertise to address complex societal challenges. This shift also aligns with the Triple Helix Theory, which positions universities, industry, and government as co-producers of innovation, making research groups essential vehicles for translating academic knowledge into societal and economic value (Etzkowitz and Leydesdorff, 2000).

From a governance perspective, RGs are shaped by principles of organizational learning, distributed leadership, and knowledge governance. Universities increasingly rely on structured research environments to enhance coordination, accountability, and strategic alignment. According to Oancea (2019), research governance requires explicit frameworks that define responsibilities, communication channels, and evaluation systems, enabling RGs to operate as coherent and high-performing units. Visibility, in turn, is supported by theories of institutional signaling, where transparent dissemination of research activities enhances credibility, competitiveness, and public trust (Stensaker and Benner, 2013). Together, these theories suggest that well-governed, visible, and collaborative RGs are more likely to secure funding, attract partners, and contribute to global knowledge systems.

This study shows from the global shift in thinking about the purpose and organization of research. It takes a close look at how the world’s top 500 universities are structuring and supporting their RGs. These universities represent a broad range of geographic and institutional contexts. By examining such a large and diverse sample, the study seeks to capture a global snapshot of current best practices (and shortcomings) in how academic research is organized for impact.

The objective of this study is to examine how visible and structured RGs are across the QS Top 500 universities (2026). Whether these groups have formal universities frameworks (policies, governance, or dedicated offices). How much they show clear structure (leaders, research foci, student inclusion). To what extent are they visible to external audiences (public profiles, documented achievements, partnerships). How these patterns differ by global region and ranking tier (top-200 vs. 201–500). The main goal is to map the current state of RG visibility and organization globally and highlight where universities are excelling or lagging, providing a foundation for improving transparency and strategic alignment without assessing research quality or societal impact directly.

2 Methodology

2.1 Study design and data collection

A cross-sectional descriptive study design was conducted to investigate the presence, visibility, and characteristics of RGs within universities ranked in the QS World University Rankings 2026. The study population covered the top 500 universities listed in the QS World University Rankings 2026. Data were obtained from the official QS World University Rankings website,¹ from which the official Excel file containing the rankings of the first 500 universities was downloaded. Universities were selected based on their INDEX number (1–500) rather than their RANK position, as multiple universities often share identical rank positions, while the Index provides a unique sequential identifier for each institution.

3 Definitions of core concepts

3.1 Evaluation of research group

Evaluation of research groups refers to the systematic assessment of their structure, performance, and contribution to institutional goals. According to HCERES (2014), RG evaluation includes criteria such as leadership, research output, funding, collaboration, and societal relevance. Effective evaluation frameworks ensure accountability, identify strengths and weaknesses, and guide strategic development.

3.2 Visibility

Visibility refers to the extent to which an RG publicly communicates its identity, activities, outputs, and achievements. Visibility encompasses online presence, publication dissemination, partnerships, and engagement in academic events. Stensaker and Benner (2013) argue that visibility acts as an institutional signal that enhances credibility and strengthens competitive positioning in global rankings.

3.3 Governance

Governance in RGs involves the policies, structures, and processes that guide their formation, operations, leadership, accountability, and resource allocation. Oancea (2019) defines research governance as the coordinated set of rules and managerial systems that ensure quality, transparency, and alignment with institutional strategies.

3.4 Engagement

Engagement refers to the meaningful interaction between RGs and external stakeholders, including industry, government agencies, civil society, and local communities. It involves collaborative research, knowledge exchange, and capacity-building activities. Engagement is recognized as essential for societal impact and innovation ecosystems (Wanjiru and Xiaoguang, 2021).

Data Collection Procedure: Phase 1: RG Identification: For each of the 500 universities, the official institutional website (as listed on the QS rankings) was systematically searched to identify the presence of RGs. The search strategy employed multiple relevant keywords, including: “RGs,” “Research teams,” “Research clusters,” “Research consortiums.” Phase 2: RG Evaluation Criteria: Universities underwent further evaluation using a comprehensive 15-criterion assessment tool Research Group Visibility Score (RGVS). Each criterion was evaluated based on its visibility and explicit mention on the university’s official website.

The evaluation criteria included:

1. Presence of a policy/framework for the establishment and administration of the RGs (HCERES, 2014).

2. Presence of office/unit administering the RG (HCERES, 2014).

3. Presence of regular meetings of RG members and reporting mechanisms (Inpharma, 1975).

4. Presence of Principal Investigator or group leader (Oancea, 2019).

5. Presence of multidisciplinary or cross-faculty membership (Wernli and Ohlmeyer, 2023).

6. Presence of International RG members (Prchal and Messas, 2016).

7. Presence of graduate students’ membership (Australian Government Department of Education, 2023).

8. Presence of clear research interests of the RG (Wharf and Kingdom, 2011).

9. Presence of partnerships (public, private/industry, community, international partners) (Wanjiru and Xiaoguang, 2021).

10. Publication records of RG (Garcia et al., 2020; Oancea, 2019; University-Industry Collaboration, 2019).

11. External research funding secured (national or international) (Garcia et al., 2020; University-Industry Collaboration, 2019).

12. The registering of the significant achievements of the RG (Inpharma, 1975).

13. Participation in conferences, workshops, seminars, and activities (Australian Government Department of Education, 2023).

14. Joint research with students (publications, theses, projects) (Wanjiru and Xiaoguang, 2021).

15. Social media presence (Stohl et al., 2017).

Each criterion was scored binarily (1 = present or visible on the website, 0 = absent or not publicly disclosed). The total score, referred to as the RG Visibility Score (RGVS), ranged from 1 to 15 for each university. The RGVS was then categorized into three tiers based on the 33.3rd and 66.6th percentiles, corresponding to total scores of 9 and 13, respectively.

Based on both the presence of RGs and the RGVS, universities were classified into four categories: No Visible RGs, Low Visibility (RGVS 1–8), Medium Visibility (RGVS = 9–12), and High Visibility (RGVS = 13–15).

All universities were further classified according to six categorical variables.

1. Ranking category: Universities were categorized into: Top 200 (Universities with Index 1–200) and Others (Universities with Index 201–500).

2. Geographic region: Universities were categorized by continents into: Asia, Latin America, North America, Africa, Oceania, and Europe.

3. Institution size: Universities were categorized based on full-time equivalent (FTE) degree-seeking student enrollment into: XL (Extra Large): >30,000 students, L (Large): ≥12,000 students, M (Medium): ≥5,000 students, S (Small): <5,000 students.

4. Subject range (focus): Universities were categorized based on program provision across five broad faculty areas into: FCO (Full Comprehensive): All 5 faculty areas with or without medical school, FO (Focused): 3 or 4 faculty areas, SP (Specialist): 2 or fewer faculty areas.

5. Research intensity: Four levels of research activity evaluated based on the number of documents retrievable from Scopus in the five-year period preceding the application of the classification. The thresholds required to reach the different levels are different depending on the institution’s pre-classification on aspects 1 and 2. (VH) Very High, (HI) High, (MD) Medium, (LO) Low.

6. Institution status: Universities were categorized into: Public University and Private University.

We classified points 2–6 based on the categorization of the QS in the structured excel file. Statistical analysis was conducted using IBM SPSS Statistics version 29.0 (IBM, 2009). Descriptive statistics were calculated for all variables, with continuous variables presented as means ± standard deviations and categorical variables as frequencies and percentages. Relationships between the six categorical variables and RG characteristics were examined using Chi-square tests. A significance level was set at p < 0.05.

4 Results

Out of the 500 QS universities studied, 347 (69.4%) had a visible RG (RGs) presence on their official websites, while 153 (30.6%) showed no visible evidence of RGs presence.

Table 1 presents the prevalence of the 15 specific criteria indicating the visibility and formalization of RGs in universities (N = 500). Higher percentages suggest a practice is common globally, whereas lower percentages indicate a relatively rare or less visible practice. A total of 22 universities met all the 15 criteria of the RG Visibility Score (RGVS), representing 4.4% of the entire sample.

Table 1

Table 1. The prevalence of 15 specific criteria indicating the visibility and formalization of RGs in universities (N = 500).

Among the top 500 universities, research group (RG) structures differ in terms of organization and visibility. Roughly between one-third and half of these universities have established formal systems, including administrative support and regular reporting routines. Assigning a Principal Investigator (PI) to lead each research group is a common practice, appearing in more than 60% of the cases. More than half of the universities report that their RGs bring together members from different disciplines and nationalities. Also, nearly two-thirds involve graduate students in the research work carried out by these groups. Most RGs have specific research areas and show a record of academic publications. However, less than half of the universities mention having external partnerships, outside funding, or formally recorded accomplishments. Taking part in academic conferences and events is somewhat common. On the other hand, maintaining an active presence on social media platforms is still limited, with only around one-third of universities mentioning such efforts.

Out of the total sample, 347 universities demonstrated a visible presence of research groups (RGs) on their official websites. The Research Group Visibility Score (RGVS) among these institutions showed an average of (10.82 ± 3.64), with a median score of 11 out of a maximum of 15. The distribution of scores ranged from 2 to 15. Based on calculated percentiles, universities scoring below 9 were classified as having low visibility, those between 9 and 13 were considered to have medium visibility, and scores above 13 indicated high visibility. Accordingly, 30.6% of the universities fell into the “not visible” category, 19.4% were classified as having low visibility, 22.0% showed medium visibility, and 28.0% had high visibility of their RGs online.

There is a highly significant association (p < 0.001) between a university’s global rank and its RG visibility category as shown in Table 2. Notably, top-ranked universities show markedly different RG visibility patterns compared to lower-ranked ones. Among Top 200 universities, a substantial proportion fell into the lowest visibility categories: 37% of top 200 universities had “Not visible” RG status and an additional 35% had only Low Visibility. Over 70% of the elite universities had little or low visible RG structure. Only 3% of Top 200 universities were in the High Visibility category. In contrast, universities ranked 201–500 tended to have much greater RG visibility: only 26.3% of this 201–500 group were “Not visible,” and a very small fraction (9%) fell in Low Visibility. The majority of mid-ranked universities had strong RG visibility, with 44.7% classified as High Visibility; in fact, this group had the largest share of High Visibility universities in the sample, and another 20% in the Medium category. Second-tier universities (ranked 201–500) are significantly more likely to openly display formal RG features than the top-tier universities.

Table 2

Table 2. Cross-tabulates the RGVS categories with various institutional characteristics.

There are also significant differences by region (p = 0.002) in RG visibility. Universities in North America (N = 90) generally showed strong RG visibility: only 11.1% of North American universities fell into the Not visible category (the lowest of any region), and 34.4% achieved High Visibility (the highest proportion of high visibility among the larger regions). European universities (N = 208) had a more even distribution: about 31.2% of European universities had no visible RGs, while 26.9% were highly visible, with the remainder split between Low (18.3%) and Medium (23.6%). Asian universities (N = 144) tended to have lower visibility overall: a striking 42.4% of Asian universities were classified as having not-visible RGs; the highest “Not visible” percentage among major regions, and only 26.4% reached the High Visibility category. Oceania (N = 36, largely Australia/New Zealand) showed an intermediate pattern: about 22.2% not visible and 25% high, with the rest roughly split (27.8% low, 25% medium). The sample for Africa was very small (N = 7), a majority (57.1%) of these African universities had High RG Visibility (4 out of 7), with very few in the not-visible or low categories (each 14%, representing 1 university each). Latin America (N = 15) had over half (53.3%) of its universities with no visible RGs and only 13.3% in the high category.

When comparing universities by size (categorized as Small, Medium, Large, and Extra Large), there were no statistically significant differences (p = 0.16) in RG visibility distributions. In other words, the proportion of universities falling into each visibility category does not vary in a clear, systematic way with institutional size. Similarly, there was no significant association (p = 0.84) between research intensity category and RG visibility levels. The analysis found no significant differences by focus (p = 0.40) in RG visibility category distributions. All types of universities (broad or specialized) appear to have similar proportions of low, medium, and high RG visibility. Finally, the data compared private (N = 70) and Public (N = 430) universities. The distribution of RG visibility categories did not differ significantly by ownership/status (p = 0.33).

5 Discussion

Research groups (RGs) represent a central feature of how top universities organize and present their research, yet their visibility and institutional integration remain inconsistent across the QS Top 500. This study aimed to examine the current state of RG visibility by analyzing publicly available information from university websites, strategic documents, and online directories. The goal was to identify how these universities structure, display, and support their research groups, and to reveal patterns across regions and ranking tiers without evaluating the quality or impact of their research output. The analysis focused on whether universities have formal frameworks, dedicated offices, clear leadership structures, and transparent online profiles for their research groups. It also explored how these patterns vary by global region and ranking tier, particularly between top-200 universities and those ranked 201–500.

Analysis of the QS Top 500 universities for 2026 shows a pattern of partial organization, while 63% of universities assign group leaders and define research focus, only 37% have formal policies and 42% maintain oversight units to guide their development. This imbalance reflects a broader tension between internal coherence and external legitimacy. Prior work has demonstrated that informal, faculty driven research clusters can spark local innovation, but they frequently lack the resources, governance, and performance structures needed to sustain their contributions or align with university strategies (Nguyen, 2013). For RGs to fulfill a strategic role, universities must adopt flexible yet explicit frameworks that incorporate evaluation cycles, leadership development, and institutional incentives.

Interdisciplinary and international collaboration within RGs appears to be widespread, with 58% of groups spanning multiple faculties and 53% including scholars from other countries. These attributes position groups to attract competitive funding and produce research with greater societal relevance, as supported by recent studies showing the advantages of cross-disciplinary and multicultural teams in achieving high-impact outcomes (Jinnah and Dove, 2025). Interdisciplinary research groups offer significant advantages to universities and the broader research ecosystem. Such groups bring together diverse expertise, enabling innovative solutions to complex problems that single-discipline approaches often cannot address. Studies have shown that interdisciplinary collaborations produce research with broader societal relevance and higher long-term citation impact compared to traditional disciplinary work. They also strengthen institutional capacity by fostering cross-departmental collaboration, attracting international partners, and providing students with exposure to varied methods and perspectives. Universities that nurture these groups through internal funding, structured mentorship, and support for external partnerships can position themselves as leaders in addressing global challenges and advancing research with lasting influence (Australian Government Department of Education, 2023).

The study also highlights significant weaknesses in the visibility and societal engagement of RGs. Less than half (47%) report partnerships with industry, community, or government stakeholders, and only 46% secure external funding. These figures signal a misalignment with the Triple Helix framework, which emphasizes dynamic collaboration among universities, industry, and government as a cornerstone of contemporary innovation ecosystems. Research-intensive systems such as those supported by Research Councils UK show that formalized interfaces between RGs and external partners significantly enhance translational research and public impact.² Universities that neglect such structures risk allowing their RGs to remain internally effective but externally invisible, undermining opportunities to demonstrate relevance and attract funding or policy influence.

Funding emerges as a particularly decisive factor in determining the success and sustainability of RGs. The finding that fewer than half secure external resources reflects not only competition for grants but also a lack of institutional capacity to support grant acquisition. Prior studies demonstrate that external collaborations strongly correlate with both researcher productivity and institutional performance (Abramo et al., 2018). This relationship suggests that building grant readiness capacities through workshops, mentoring, and consortium facilitation can create a feedback loop where funded groups gain legitimacy, visibility, and access to larger opportunities. Without such institutional investments, universities risk perpetuating a cycle in which only a small subset of RGs thrive while others remain dependent on internal budgets.

Documentation and communication of RG achievements remain strikingly limited. Only 35% of groups systematically report their accomplishments, and just 34.6% maintain a public presence through websites or social media. In an era when quality assurance and accreditation frameworks increasingly emphasize transparency, accountability, and societal relevance, this lack of visibility undermines the strategic value of RGs. European quality models, such as those promoted by SUHF (The Association of Swedish Higher Education Institutions), stress the integration of research outputs into annual institutional reviews as evidence of coherent, managed research environments. Without visible reporting, universities may struggle to demonstrate their research quality to accreditors, funders, and ranking bodies, limiting the reputational and operational returns on their RG investments³ (IAEQES, 2013).

The paradox of low RG visibility among elite universities is particularly noteworthy. Universities in the QS top-200, many of which are historic, research-intensive universities in North America and Europe, exhibit far less public structuring of RGs than their mid-ranked counterparts. These universities often rely on legacy arrangements, including departmental laboratories and the prominence of star investigators, to sustain their research reputations. While these structures have historically been effective, they risk becoming liabilities as global science places greater emphasis on interdisciplinarity, mission-driven agendas, and measurable collaboration. Recent evidence suggests that graduates from interdisciplinary programs face significant challenges in securing academic positions at elite universities, highlighting an organizational inertia that may undermine the evolution of more adaptive knowledge production frameworks (Zheng et al., 2025). For leading universities to maintain competitiveness, they must modernize their research architectures, ensuring that RGs serve as visible, flexible units aligned with institutional strategies and external demands.

This study’s reliance on observable indicators policies, structures, and visibility represents a methodological limitation. While these metrics reveal important organizational patterns, they do not capture the full quality or impact of RGs, such as research outcomes, citation influence, societal benefits, or innovation outputs. Future work should explore these dimensions, examining whether formalized RGs consistently outperform informal arrangements in tangible outcomes. It is also essential to account for disciplinary variation, as RG design and function may differ significantly between STEM fields (Science, Technology, Engineering, and Mathematics), each of which has unique funding models, collaboration norms, and societal interfaces.

Taken together, these findings suggest a roadmap for universities seeking to leverage RGs as engines of research excellence and societal engagement. Clear institutional policies and charters should establish the expectations and strategic roles of RGs, linking them explicitly to university priorities and annual review processes. Seed funding and internal grants should provide the runway for interdisciplinary and international groups, ensuring their survival and maturation before they compete for external resources. Dedicated offices must broker partnerships with industry, government, and communities, embedding RGs into the broader innovation ecosystem. Grant readiness programs, including mentorship and consortium building initiatives, can amplify RG success in securing external support, while systematic documentation and centralized online profiles can enhance visibility to stakeholders and accreditors. These steps would transform RGs from isolated clusters into strategic assets that contribute directly to institutional missions, reputational capital, and societal impact. Universities that align their RG strategies with these global agendas stand to gain not only in visibility and funding but also in the relevance and resilience of their research enterprises.

Recent literature on research groups (RGs) highlights their growing importance in shaping university research ecosystems. An emerging body of work shows that formal RG structures enhance research productivity, interdisciplinary collaboration, and institutional competitiveness (Vabø et al., 2016). Studies from Europe and North America demonstrate that universities adopting structured RG frameworks—accompanied by clear leadership, evaluation mechanisms, and strategic alignment—tend to produce more coherent research agendas and attract external funding (Wernli and Ohlmeyer, 2023). In contrast, institutions relying on informal or loosely connected research units often face fragmentation, limited visibility, and difficulty demonstrating impact to stakeholders.

Global evidence further suggests that visibility is a critical dimension of RG effectiveness. Transparency in research outputs, partnerships, and achievements not only enhances institutional reputation but also enables RGs to integrate into broader innovation and policy networks (Stohl et al., 2017). Scholars emphasize that visibility supports international collaboration, which is shown to correlate strongly with higher citation impact and greater scientific influence (Cheol Shin et al., 2013).

Governance has also become a central theme in the literature. Universities worldwide are experimenting with policies, charters, and administrative structures to improve performance monitoring, support interdisciplinary work, and foster sustainable research cultures (HCERES, 2014). However, studies consistently highlight significant regional variation: while North American and European universities tend to maintain stronger governance and reporting structures, institutions in Asia, Latin America, and parts of Africa show uneven implementation due to resource constraints or decentralized research traditions.

Finally, research engagement—particularly with industry, government, and communities—remains an area of persistent challenge. OECD reports show that many universities struggle to build long-term partnerships, although such collaborations significantly strengthen innovation capacity and external funding success (OECD, 2019). Therefore, recent literature calls for more integrated models of research planning, evaluation, and communication to enhance the societal relevance and sustainability of RGs.

Therefore, RGs represent more than administrative units or clusters of scholars; they embody the transformation of the university into a dynamic, networked institution capable of addressing local and global challenges. Universities that formalize, support, and promote their RGs will be better equipped to navigate shifts in funding, accreditation, and rankings, while also enhancing their contributions to society. In contrast, universities that rely solely on legacy structures and individual prestige risk falling behind in an academic landscape increasingly defined by collaboration, interdisciplinarity, and demonstrable impact. By institutionalizing RGs with robust policies, strategic funding, external engagement, quality integration, and visible communication, higher education universities can ensure that these groups function as true engines of scholarly innovation and societal value in the decades to come.

6 Conclusion

While this study provides a comprehensive analysis of RG visibility and governance across QS Top 500 universities, several limitations should be acknowledged. First, the study relies solely on publicly available information from university websites, which may not fully reflect internal RG structures, undocumented collaborations, or emerging research activities. Second, the assessment does not capture the quality, impact, or productivity of RGs, focusing instead on visibility indicators. Third, the study does not account for disciplinary differences that may influence how RGs are organized or evaluated.

Future research should examine RG performance using mixed methods, including interviews with research leaders, analysis of collaborative outputs, and mapping of partnership networks. In addition, expanding the framework to include collaborative research practices and knowledge governance mechanisms would provide a more holistic understanding of how RGs contribute to institutional excellence and societal impact. Developing longitudinal datasets would also help universities track progress and evaluate the effectiveness of governance reforms over time.

7 Future suggestion

We strongly encourage the adoption of this comprehensive 15-criteria RG Visibility Score (RGVS) framework as a standard for evaluating research groups in universities. This framework has been carefully synthesized from multiple established evaluation measures and informed by numerous scholarly studies (e.g., references 6, 8–19), ensuring that its criteria are both evidence-based and broadly applicable. By integrating diverse elements from institutional policies and dedicated RG administration to interdisciplinary membership, funding success, publication records, and outreach activities; the RGVS provides a holistic assessment tool that captures the visibility and performance of research groups across key dimensions. Therefore, using this literature-backed criterion as a standard will not only promote consistency in how universities assess their research groups, but also enhance the reliability and credibility of the evaluation process, given that it draws on best practices identified in multiple studies.

Data availability statement

Publicly available datasets were analyzed in this study. This data can be found at: QS world University ranking 2026 official website.

Ethics statement

This study did not involve human participants, animals, or any personal data collection; therefore, formal institutional review board (IRB) approval was not required. All data analyzed were publicly available from university websites and documents.

Author contributions

FS: Conceptualization, Investigation, Methodology, Software, Writing – review & editing. NO: Supervision, Validation, Writing – review & editing. HG: Data curation, Supervision, Validation, Writing – original draft, Writing – review & editing.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was not used in the creation of this manuscript.

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Footnotes

¹^https://www.topuniversities.com

²^https://www.ukri.org/councils/

³^https://suhf.se/in-english/

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