Open Access

The Academic Midas Touch: A citation-based indicator of research excellence

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Jul 10, 2025

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Purpose

This paper introduces a novel perspective on academic excellence, focusing on a researcher’s consistent ability to produce highly-cited publications, and demonstrates its utility in distinguishing high-achieving scientists compared to traditional scientometric indicators.

Design/methodology/approach

We formulate this new perspective using a simple yet effective indicator termed the “Academic Midas Touch” (AMT). We then empirically analyze how AMT aligns with or diverges from popular scientometrics such as the H-index, i10-index, and citation counts. We further evaluate AMT’s effectiveness in identifying award-winning scientists, using these awards as a proxy for recognized academic excellence.

Findings

Our empirical analysis reveals that the AMT offers a distinct measure of academic excellence that does not fully correlate with commonly used scientometrics. Furthermore, AMT favorably compares to these traditional metrics in its ability to accurately identify award-winning scientists.

Research limitations

The AMT emphasizes short-term citation accumulation, thus it may overlook long-term dynamics such as “sleeping beauties”. Additionally, mindful parameter tuning and contextual interpretation within a specific discipline or a meaningful cohort of peers are necessary. Finally, the AMT does not seek to fully capture the multidimensional complexities of research excellence such as collaborations, mentoring, and societal impact.

Practical implications

The findings suggest that AMT can serve as a valuable complementary tool for evaluating researchers, particularly in contexts such as excellence recognition, award nominations, grant applications, and faculty promotions, providing an under-explored view of a researcher’s consistent ability to produce highly-influential publications.

Originality/value

This work introduces a unique conceptualization and measurement of academic excellence, shifting the focus from cumulative impact to the consistent propensity for producing highly-cited publications. The resulting AMT indicator provides a fresh perspective that complements existing scientometrics, offering a more nuanced understanding and recognition of research excellence.

Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Computer Sciences, Information Technology, Project Management, Databases and Data Mining