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This paper aims to provide a general overview, to be followed by a series of papers focusing on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases (Google Scholar, Scopus, and Web of Science) for determining the h‐index.

The paper focuses on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases (Google Scholar, Scopus and Web of Science).

The h‐index, developed by Jorge E. Hirsch to quantify the scientific output of researchers, has immediately received well‐deserved attention in academia. The theoretical part of his idea was widely embraced, and even enhanced, by several researchers. Many of them also recommended derivative metrics based on Hirsch's idea to compensate for potential distortion factors, such as high self‐citation rates. The practical aspects of determining the h‐index also need scrutiny, because some content and software characteristics of reference‐enhanced databases can strongly influence the h‐index values.

The paper focuses on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases.

The purpose of this paper is to show how bibliometrics would benefit from a stronger programme of construct validity.

The value of the construct validity concept is demonstrated by applying this approach to the evaluation of the h-index, a widely used metric.

The paper demonstrates that the h-index comprehensively fails any test of construct validity. In simple terms, the metric does not measure what it purports to measure. This conclusion suggests that the current popularity of the h-index as a topic for bibliometric research represents wasted effort, which might have been avoided if researchers had adopted the approach suggested in this paper.

This study is based on the analysis of a single bibliometric concept.

The conclusion that the h-index fails any test in terms of construct validity implies that the widespread use of this metric within the higher education sector as a management tool represents poor practice, and almost certainly results in the misallocation of resources.

This paper suggests that the current enthusiasm for the h-index within the higher education sector is misplaced. The implication is that universities, grant funding bodies and faculty administrators should abandon the use of the h-index as a management tool. Such a change would have a significant effect on current hiring, promotion and tenure practices within the sector, as well as current attitudes towards the measurement of academic performance.

The originality of the paper lies in the systematic application of the concept of construct validity to bibliometric enquiry.

This review aims to show, broadly, how the h‐index has become a subject of widespread debate, how it has spawned many variants and diverse applications since first introduced in 2005 and some of the issues in its use.

The review drew on a range of material published in 1990 or so sources published since 2005. From these sources, a number of themes were identified and discussed ranging from the h‐index's advantages to which citation database might be selected for its calculation.

The analysis shows how the h‐index has quickly established itself as a major subject of interest in the field of bibliometrics. Study of the index ranges from its mathematical underpinning to a range of variants perceived to address the indexes' shortcomings. The review illustrates how widely the index has been applied but also how care must be taken in its application.

The use of bibliometric indicators to measure research performance continues, with the h‐index as its latest addition. The use of the h‐index, its variants and many applications to which it has been put are still at the exploratory stage. The review shows the breadth and diversity of this research and the need to verify the veracity of the h‐index by more studies.

The purpose of this paper is to discuss the pros and cons of computing the h‐index using Scopus.

The paper looks at the content features and the software capabilities of Scopus from the perspective of computing a reasonable h‐index for scholars.

Although there are limitations in the content, and even in the mostly excellent, swift, powerful and innovative software of Scopus, it can produce a much more reliable and reproducible h‐index – at least for relatively junior researchers – than Google Scholar.

The paper adds insight into computing the h‐index using Scopus.

This paper aims to evaluate some of the known scientific indexes by using virtual data and proposes a new index, named multiple h-index (mh-index), for removing the limits of these variants.

Citation report for 40 researchers in Babol, Iran, was extracted from the Web of Science and entered in a checklist together with their scientific lifetimes and published ages of their papers. Some statistical analyses, especially exploratory factor analysis (EFA) and structural correlations, were done in SPSS 19.

EFA revealed three factors with eigenvalues greater than 1 and explained variance of over 96 per cent in the studied indexes, including the mh-index. Factors 1, 2 and 3 explained 44.38, 28.19 and 23.48 of the variance in the correlation coefficient matrix, respectively. The m-index (with coefficient of 90 per cent) in Factor 1, a-index (with coefficient of 91 per cent) in Factor 2 and h- and h2-indexes (with coefficients of 93 per cent) in Factor 3 had the highest factor loadings. Correlation coefficients and related comparative diagrams showed that the mh-index is more accurate than the other nine variants in differentiating the scientific impact of researchers with the same h-index.

As the studied variants could not satisfy all limits of the h-index, scientific society needs an index which accurately evaluates individual researcher’s scientific output. As the mh-index has some advantages over the other studied variants, it can be an appropriate alternative for them.

The study's main purpose is to scrutinize Google Scholar profiles and find the answer to the question, “Do authors play fair or manipulate Google Scholar Bibliometric Indicators like h-index and i10-index?”

The authors scrutinized the Google Scholar profiles of the top 50 library and science researchers claiming authorship of 21,022 publications. The bibliographic information of all the 21,022 publications like authorship and subject details were verified to identify accuracy, discrepancies and manipulation in their authorship claims. The actual and fabricated entries of all the authors along with their citations were recorded in the Microsoft Office Excel 2007 for further analyses and interpretation using simple arithmetic calculations.

The results show that the h-index of authors obtained from the Google Scholar should not be approved at its face value as the variations exist in the publication count and citations, which ultimately affect their h-index and i10 index. The results reveal that the majority of the authors have variations in publication count (58%), citations (58%), h-index (42%) and i10-index (54%). The magnitude of variation in the number of publications, citations, h-index and i10-index is very high, especially for the top-ranked authors.

The scope of the study is strictly restricted to the faculty members of library and information science and cannot be generalized across disciplines. Further, the scope of the study is limited to Google Scholar and caution needs to be taken to extend results to other databases like Web of Science and Scopus.

The study has practical implications for authors, publishers, and academic institutions. Authors must stop the unethical research practices; publishers must adopt techniques to overcome the problem and academic institutions need to take precautions before hiring, recruiting, promoting and allocating resources to the candidates on the face value of the Google Scholar h-index. Besides, Google needs to work on the weak areas of Google Scholar to improve its efficacy.

The study brings to light the new ways of manipulating bibliometric indicators like h-index, and i10-index provided by Google Scholar using false authorship claims.

Although journal rankings are important for authors, readers, publishers, promotion, and tenure committees, it has been argued that the use of different measures (e.g. the journal impact factor (JIF), and Hirsch’s h-index) often lead to different journal rankings, which render it difficult to make an appropriate decision. A hybrid ranking method based on the Borda count approach, the Standardized Average Index (SA index), was introduced to solve this problem. The paper aims to discuss these issues.

Citations received by the articles published in 85 Health Care Sciences and Services (HCSS) journals in the period of 2009-2013 were analyzed with the use of the JIF, the h-index, and the SA index.

The SA index exhibits a high correlation with the JIF and the h-index (γ > 0.9, p < 0.01) and yields results with higher accuracy than the h-index. The new, comprehensive citation impact analysis of the 85 HCSS journals shows that the SA index can help researchers to find journals with both high JIFs and high h-indices more easily, thereby harvesting references for paper submissions and research directions.

The contribution of this study is the application of the Borda count approach to combine the HCSS journal rankings produced by the two widely accepted indices of the JIF and the h-index. The new HCSS journal rankings can be used by publishers, journal editors, researchers, policymakers, librarians, and practitioners as a reference for journal selection and the establishment of decisions and professional judgment.

The 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.

Employing 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.

Analysis 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.

First, 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.

Results 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.

This 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.

A previous paper by the present author described the pros and cons of using the three largest cited reference enhanced multidisciplinary databases and discussed and illustrated in general how the theoretically sound idea of the h‐index may become distorted depending on the software and the content of the database(s) used, and the searchers' skill and knowledge of the database features. The aim of this paper is to focus on Google Scholar (GS), from the perspective of calculating the h‐index for individuals and journals.

A desk‐based approach to data collection is used and critical commentary is added.

The paper shows that effective corroboration of the h‐index and its two component indicators can be done only on persons and journals with which a researcher is intimately familiar. Corroborative tests must be done in every database for important research.

The paper highlights the very time‐consuming process of corroborating data, tracing and counting valid citations and points out GS's unscholarly and irresponsible handling of data.

The purpose of this paper is to identify the top researchers in information behaviour (IB) based on ideational and social influence indicators.

The population included papers on IB indexed in the Web of Science from 1980 to 2015. UCINET and Bibexcel were the tools used for measuring the ideational and social influence indicators. The correlations among the study variables were measured by applying SPSS and LISREL.

There was a significant relationship between IB researchers’ productivity and performance, and between ideational influence and social influence. The structural equation modelling showed that a researcher with top placement in his/her co-authorship network can gain higher ideational influence. In total, it seems that the single and traditional criteria are increasingly replacing new and integrative ones in measuring researchers’ scientific influence in fields including IB studies. Results have shown that based on total scores of the studied indicators, Spink, A., Nicholas, D., Ford, N., Huntington, P., Wilson, T.D., and Jamali, H.R. gained the high scores.

The current study used an integrative method based on influence indicators to identify the influential researchers in IB studies. None of the few studies done using bibliometric methods in the realm of IB has investigated the ideational and social influence indicators altogether.