The Illusion of Academic Leadership: Why Publications Are Poor Predictors of Innovation Capacity
The Illusion of Academic Leadership: Why Publications Are Poor Predictors of Innovation Capacity
Why Selection Based on Publications Fails to Identify True Innovation Drivers
Author: Monica Bianco, Ecosystems Cooperation advisor -CRF Italy
Abstract
The dominant models for evaluating academic leadership and innovation potential have increasingly relied on publication metrics such as the number of articles, citation counts, and journal impact factors. While these indicators offer a measure of academic visibility, they represent a poor proxy for real innovation capacity, particularly when research is expected to address complex societal challenges and drive transformative territorial development. This article critically examines how metric-centric selection systems distort the identification of true innovation drivers, marginalizing those actors most capable of translating scientific knowledge into technological, social, and economic progress. A profound rethinking of research evaluation is needed to align scientific systems with missions of sustainable innovation and societal resilience.
Introduction
In contemporary research systems, particularly those influenced by European and Anglo-American funding models, publication metrics have become the dominant standard for assessing academic leadership, research quality, and eligibility for funding and strategic positions. This shift, often summarized in the “publish or perish” paradigm, has conflated academic productivity with innovation potential, assuming that quantity and visibility of publications are reliable indicators of transformative capacity. However, as Moher et al. rightly point out, “the heavy reliance on publication counts and journal impact factors risks conflating visibility with real research quality and relevance” [1], undermining the broader societal role of research.
The problem is not merely technical but structural. A system that prioritizes publication performance above all else inherently favors certain types of research outputs — mainly theoretical, disciplinary, incremental — while marginalizing interdisciplinary, applied, and mission-oriented work that often carries higher risk and longer development cycles. This systemic bias distorts the recognition of true innovation drivers, leading to leadership selection processes that reinforce academic self-referentiality rather than catalyzing societal transformation.
Publications and Innovation: A Misaligned Correlation
The assumption that strong publication records predict strong innovation outcomes is deeply flawed. Empirical studies consistently show that the skills and attributes required to excel in academic publishing are not the same as those needed to drive innovation ecosystems. As D’Este and Patel observed, “academic publishing and engagement with industry and society are often governed by different logics and reward systems” [2]. Where publications reward theoretical contributions to specialized fields, innovation demands problem-oriented, multidisciplinary collaboration capable of navigating complexity and uncertainty.
Moreover, real-world innovation is frequently born not in the most visible research hubs but in peripheral contexts, where necessity drives creative adaptation. The OECD notes that “high scientific output regions do not automatically correlate with regions that lead in technological innovation or societal transformation” [3]. Thus, evaluating innovation potential primarily through publication records leads to systematic exclusion of researchers and institutions whose strength lies in applied creativity, technological development, or societal engagement rather than academic citation accumulation.
Structural Biases Created by Metric-Centric Selection
Metric-driven evaluation systems introduce structural biases that undermine the identification of effective innovation leaders. First, they systematically favor theoretical researchers over those engaged in application, co-creation, and stakeholder collaboration. As Perkmann et al. highlight, “engagement with external partners and societal challenges often carries lower rewards in academic career systems dominated by bibliometric indicators” [4]. Researchers who invest time and energy in translating knowledge into solutions, prototypes, policies, or startups often do so at the cost of lower publication rates, and are therefore penalized in metric-based evaluations.
Second, publication-centered systems disadvantage interdisciplinary scholars. Complex societal challenges — such as climate adaptation, digital transitions, or health equity — inherently demand integration across disciplines, sectors, and knowledge systems. Yet interdisciplinary work struggles to find a place in high-impact disciplinary journals, resulting in lower visibility and career penalties. This misalignment disincentivizes systemic thinking precisely when it is most needed.
Third, the current model exacerbates geographical and institutional inequalities. Researchers from smaller universities, emerging regions, and less prestigious networks often lack the cumulative citation capital needed to compete on metric grounds, regardless of their innovation potential. As Bornmann emphasizes, “the emphasis on publication quantity promotes safe, incremental research rather than high-risk, high-reward innovation” [5], further entrenching a conservative, elitist research system.
Finally, metric-centric evaluations discourage risk-taking and experimentation. Scholars aiming to maximize publications tend to favor predictable, low-risk topics, which are more likely to yield publishable results quickly. This dynamic reduces the incentive to engage in transformative research programs whose outcomes may be uncertain but whose societal impact could be substantial.
Rethinking Selection Criteria for Innovation Leadership
A profound rethinking of research evaluation and leadership selection is urgently needed if we are to identify and empower true drivers of innovation. First, evaluations must explicitly prioritize societal impact, technological deployment, policy relevance, and territorial regeneration over mere bibliometric performance. Qualitative peer reviews, narrative CVs, and evidence of real-world outcomes must become central components of assessment.
Second, the ability to engage with diverse stakeholders — from industry to communities to policymakers — must be recognized as a core leadership competency. As Woolley et al. argue, “collective intelligence and collaborative problem-solving are stronger predictors of innovation success than individual academic prestige” [6]. Building and orchestrating diverse innovation ecosystems demands skills that pure academic publishing neither selects for nor rewards.
Third, interdisciplinary and transdisciplinary capacities must be valorized explicitly. Mission-oriented research challenges cannot be solved within narrow disciplinary boundaries. Selection systems should reward researchers who demonstrate the ability to bridge scientific domains, integrate different types of knowledge, and design holistic solutions.
Finally, a deliberate effort must be made to open leadership opportunities to emerging actors from peripheral institutions and territories. As Mazzucato emphasizes, “building transformative innovation systems requires nurturing a wide range of actors, not just those with existing academic prominence” [7]. Supporting diversity and inclusion is not only a matter of fairness but a strategic imperative for systemic resilience and creativity.
Conclusion
The reliance on publication-based metrics as proxies for innovation capacity represents a profound distortion of the research ecosystem. Far from identifying true societal innovators, current selection systems privilege academic visibility, disciplinary orthodoxy, and risk aversion, undermining the transformative potential of science and technology. To realign research with its societal mission, evaluation frameworks must move beyond simplistic bibliometric indicators and embrace a richer, more holistic approach that values impact, interdisciplinarity, stakeholder engagement, and territorial regeneration.
Only by redefining how we recognize and empower academic leadership can we cultivate the innovation ecosystems necessary to address the grand challenges of our time and to build a more inclusive, resilient, and sustainable future.
References
- Moher, D., Naudet, F., Cristea, I. A., Miedema, F., Ioannidis, J. P. A., & Goodman, S. N. (2018). “Assessing scientists for hiring, promotion, and tenure.” PLOS Biology, 16(3), e2004089.
- D’Este, P., & Patel, P. (2007). “University–industry linkages in the UK: What are the factors underlying the variety of interactions with industry?” Research Policy, 36(9), 1295–1313.
- OECD (2022). “Promoting Research for Social Impact.” OECD Publishing, Paris.
- Perkmann, M., King, Z., & Pavelin, S. (2011). “Engaging excellence? Effects of faculty quality on university engagement with industry.” Research Policy, 40(4), 539–552.
- Bornmann, L. (2013). “What is societal impact of research and how can it be assessed? A literature survey.” Journal of the American Society for Information Science and Technology, 64(2), 217–233.
- Woolley, A. W., Chabris, C. F., Pentland, A., Hashmi, N., & Malone, T. W. (2010). “Evidence for a collective intelligence factor in the performance of human groups.” Science, 330(6004), 686–688.
- Mazzucato, M. (2018). “Mission-oriented research and innovation in the European Union: A problem-solving approach to fuel innovation-led growth.” European Commission, Policy Brief.
