Coping with the Inequity and Inefficiency of the H-Index: A Cross-Disciplinary Empirical Analysis

Abstract

This paper measures two main inefficiency features (many publications other than articles; many co-authors’ reciprocal citations) and two main inequity features (more co-authors in some disciplines; more citations for authors with more experience). It constructs a representative dataset based on a cross-disciplinary balanced sample (10,000 authors with at least one publication indexed in Scopus from 2006 to 2015). It estimates to what extent four additional improvements of the H-index as top-down regulations (∆Hh = Hh − Hh+1 from H1 = based on publications to H5 = net per-capita per-year based on articles) account for inefficiency and inequity across twenty-five disciplines and four subjects. Linear regressions and ANOVA results show that the single improvements of the H-index considerably and decreasingly explain the inefficiency and inequity features but make these vaguely comparable across disciplines and subjects, while the overall improvement of the H-index (H1–H5) marginally explains these features but make disciplines and subjects clearly comparable, to a greater extent across subjects than disciplines. Fitting a Gamma distribution to H5 for each discipline and subject by maximum likelihood shows that the estimated probability densities and the percentages of authors characterised by H5 ≥ 1 to H5 ≥ 3 are different across disciplines but similar across subjects.