A validation of the individual annual h-index (hIa): application of the hIa to a qualitatively and quantitatively different sample

Ryan, James C.

doi:10.1007/s11192-016-1972-8

Cited by 7 publications

(9 citation statements)

References 31 publications

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“…The quantification of research performance for individual academics, research units, academic journals and universities is a reality of the modern academic environment (Ryan, 2016). Glänzel (2010) highlights the shift of scientometrics from a tool in scientific information toward a tool for research evaluation.…”

Section: Theoretical Developmentmentioning

confidence: 99%

Retaining, resigning and firing: bibliometrics as a people analytics tool for examining research performance outcomes and faculty turnover

Ryan

2020

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PurposeThe purpose of this paper is to shed light on the use of bibliometric indicators as a people analytics tool for examining research performance outcome differences in faculty mobility and turnover.Design/methodology/approachEmploying bibliometric information from research databases, the publication, citations, h-index and newly developed individual annualized h-index (hIa-index) for a sample of university faculty is examined (N = 684). Information relating to turnover decisions from a human resource (HR) information system and bibliometric data from a research database are combined to explore research performance differences across cohorts of retained, resigned or terminated faculty over a five-year period in a single university.FindingsAnalysis of variance (ANOVA) results indicate traditional bibliometric indicators of h-index, publication count and citation count which are limited in their ability to identify performance differences between employment status cohorts. Results do show some promise for the newly developed hIa-index, as it is found to be significantly lower for terminated faculty (p < 0.001), as compared to both retained and resigned faculty. Multinomial logistic regression analysis also confirms the hIa metric as a predictor of terminated employment status.Research limitations/implicationsFirst, the results imply that the hIa-index, which controls for career length and elements of coauthorship is a superior bibliometric indicator for comparison of research performance.Practical implicationsResults suggest that the hIa metric may serve as a useful tool for the examination of employment decisions for universities. It also highlights the potential usefulness of bibliometric indicators for people analytics and the examination of employment decisions, performance management and faculty turnover in research-intensive higher education contexts.Originality/valueThis empirical paper is entirely unique. No research has previously examined the issue of turnover in a university setting using the bibliometric measures employed here. This is a first example of the potential use of hIa bibliometric index as an HR analytics tool for the examination of HR decisions such as employee turnover in the university context.

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Section: Theoretical Developmentmentioning

confidence: 99%

Retaining, resigning and firing: bibliometrics as a people analytics tool for examining research performance outcomes and faculty turnover

Ryan

2020

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“…We found that whereas the h-index privileged full over associate professors and academics in the Life Sciences and Natural Sciences over the three other disciplines, using the hIa-index leveled the playing field both between junior and senior academics, and between the disciplines. The disciplinary effect is shown in Figure 1. Recently, Ryan (2016) conducted an exact replication of our study with a much larger, but substantially different, and arguably more representative, sample: academics at all levels, with an average academic age of 12 years, in a leading Middle Eastern University. He found both the career stage and the disciplinary effect to be almost identical to our original study, the only difference being the relatively low performance of Science academics in his sample.…”

Section: Learning From Success: When Replication Supports the Adoptiomentioning

confidence: 85%

“…The disciplinary effect in Ryan's study is shown in Figure 2. Figure 1: h-index compared with hIa index for different disciplines (Harzing et al 2014) Figure 2: h-index compared with hIa index for different disciplines (Ryan, 2016) Although the average h-index of the Middle Eastern sample is only just over a third of that of the Australian sample, the average hIa-index for the Middle Eastern is nearly two thirds of that of the Australian sample. This reflects the fact the hIa-index corrects for the very different academic age distribution in Ryan's sample and thus provides us with further evidence that the hIa-index is more suitable than the h-index in comparing heterogeneous groups of researchers.…”

Section: Learning From Success: When Replication Supports the Adoptiomentioning

confidence: 99%

Why replication studies are essential: learning from failure and success

Harzing

2016

CCSM

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Purpose The purpose of this paper is to discuss the pervasive problem of a lack of replication studies in international business based on van Witteloostuijn’s (2016) commentary “What happened to Popperian Falsification?” Design/methodology/approach The author presents two short case studies from her own research, one in which no replication studies took place, and one in which a replication study was conducted shortly after the original study was published. Findings The author shows how the lack of replication in the first case study example resulted in the creation of research myths, whereas the judicious replication in her second case study strengthened arguments for a new – less biased – measure of research performance. The author also discusses why most journals in the field are not open to replication studies and provides recommendations on how to move forward. Originality/value Using two real-life case studies provides a vivid illustration of the problems created by a lack of replications and illustrates the benefits of good replication studies.

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“…See Liu & Yang (2014) for an application of the H index to show a scientist's dynamic research trajectory and scientific performance during different periods. Note that I will rely on the numbers of citations per author and per year in the cited articles, although these normalizations have only been supported by statistical analyses of small samples (Harzing & Alakangas, 2016;Ryan, 2016). In the context of nested indices, the Hirsch index (H), which is based on the number of publications and citations in different journals and disciplines, can be coupled with the Gini index (G), which accounts for differences between journals and disciplines (i.e., dispersion of articles among journals and disciplines).…”

Section: Methodsmentioning

confidence: 99%

Scientific Production and Productivity in Curriculum Vitae Characterisation: Simple and Nested H Indices that Support Cross-Disciplinary Comparisons

Zagonari

2017

SSRN Journal

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In this study, I developed operational versions of Hirsch's H index that can be applied to each researcher's curriculum vitae (CV) to allow cross-disciplinary comparisons. The revised indices account for anomalies that potentially arise from tactical or opportunistic citation and publication behaviours by authors and editors, and can be calculated from readily available information. I split the original H index into nested indices to isolate networking activity, distinguish scientific production and productivity, and used nested Gini indices to identify intentional and successful inter-topical and inter-disciplinary research. I applied the most popular normalisations (i.e., per author and per year) using simple methodologies (i.e., least-squares linear and cubic interpolation fitting, whole-career vs. sub-periods, two-dimensional graphs) to solve empirical problems (e.g., sensitivity to citations, the "fashion" effect, attribution to disciplines, life cycle of articles) as well as open questions (e.g., the attribution of an article to a given discipline) associated with the original H index. I provided three numerical examples based on a representative heterodox, a representative orthodox multi-disciplinary, and a representative orthodox uni-disciplinary CV: the first CV includes 17 Scopus publications, and shows a highly heterodox (i.e., 5.8%), but no interdisciplinary research career, with a tiny networking component (i.e., 0.9%); the second CV includes 24 Scopus publications, and shows a slightly heterodox (i.e., 0.3%), but highly interdisciplinary (i.e., 53.9%) research career, with a small networking component (i.e., 14.3%); the third CV includes 16 Scopus publications, and shows slightly heterodox (i.e., 0.1%) and no interdisciplinary research career, with no networking component.

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A validation of the individual annual h-index (hIa): application of the hIa to a qualitatively and quantitatively different sample

Cited by 7 publications

References 31 publications

Retaining, resigning and firing: bibliometrics as a people analytics tool for examining research performance outcomes and faculty turnover

Retaining, resigning and firing: bibliometrics as a people analytics tool for examining research performance outcomes and faculty turnover

Why replication studies are essential: learning from failure and success

Scientific Production and Productivity in Curriculum Vitae Characterisation: Simple and Nested H Indices that Support Cross-Disciplinary Comparisons

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