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introduction of h index by Hirsch ( 2005 ) has provided enormous impetus in finding tools to quantify the research output of individual scientists, university faculties and research institutions. The Hirsch index h is defined as the highest number of papers
Imperial and Rodríguez-Navarro ( 2007 ), where the authors propose a version of h -index that only takes into account the papers in which the author is listed as first (therefore interpretating the authors’ order as an explicit statement about the
Abstract
We extend the pioneering work of J. E. Hirsch, the inventor of the h-index, by proposing a simple and seemingly robust approach for comparing the scientific productivity and visibility of institutions. Our main findings are that i) while the h-index is a sensible criterion for comparing scientists within a given field, it does not directly extend to rank institutions of disparate sizes and journals, ii) however, the h-index, which always increases with paper population, has an universal growth rate for large numbers of papers; iii) thus the h-index of a large population of papers can be decomposed into the product of an impact index and a factor depending on the population size, iv) as a complement to the h-index, this new impact index provides an interesting way to compare the scientific production of institutions (universities, laboratories or journals).
). Alternative indicators of assessing quality has been proposed such as using Google Scholar (Harzing and Van der Wal 2007 ), the G index (Egghe 2006 ), and the h index (Hirsch 2005 ) which has also been applied to journals and SCImago journal rank (SJR
, citations, and the h index, we show that measuring and assessing the research outputs of B scholars with WoS significantly underestimate the research performances of scholars in the fields of business and management. The results of this study also provide
used to identify groups of journals sharing similar characteristics in a multivariate indicator space, that is, a number of different indicators shall be used in the analysis, e.g., SJR, H-index, ISI impact factor, Eigenfactor Score, Article Influence
Abstract
We rank economics departments in the Republic of Ireland according to the number of publications, number of citations, and successive h-index of research-active staff. We increase the discriminatory power of the h 1-index by introducing three generalizations, each of which is a rational number. The first (h 1 +) measures the excess over the actual h-index, while the other two (h 1*, h 1 Δ) measures the distance to the next h-index. At the individual level, h* and h Δ coincide while h + is undefined.
Abstract
The g index was introduced by Leo Egghe as an improvement of Hirsch’s index h for measuring the overall citation record of a set of articles. It better takes into account the highly skewed frequency distribution of citations than the h index. I propose to sharpen this g index by excluding the self-citations. I have worked out nine practical cases in physics and compare the h and g values with and without self-citations. As expected, the g index characterizes the data set better than the h index. The influence of the self-citations appears to be more significant for the g index than for the h index.
Abstract
Internet has made it possible to move towards researcher and article impact instead of solely focusing on journal impact. To support citation measurement, several indexes have been proposed, including the h-index. The h-index provides a point estimate. To address this, a new index is proposed that takes the citation curve of a researcher into account. This article introduces the index, illustrates its use and compares it to rankings based on the h-index as well as rankings based on publications. It is concluded that the new index provides an added value, since it balances citations and publications through the citation curve.
Abstract
From a list of papers of an author, ranked in decreasing order of the number of citations to these papers one can calculate this author’s Hirsch index (or h-index). If this is done for a group of authors (e.g. from the same institute) then we can again list these authors in decreasing order of their h-indices and from this, one can calculate the h-index of (part of) this institute. One can go even further by listing institutes in a country in decreasing order of their h-indices and calculate again the h-index as described above. Such h-indices are called by Schubert [2007] “successive” h-indices. In this paper we present a model for such successive h-indices based on our existing theory on the distribution of the h-index in Lotkaian informetrics. We show that, each step, involves the multiplication of the exponent of the previous h-index by 1/α where α > 1 is a Lotka exponent. We explain why, in general, successive h-indices are decreasing. We also introduce a global h-index for which tables of individuals (authors, institutes,...) are merged. We calculate successive and global h-indices for the (still active) D. De Solla Price awardees.
