Multiple h-index: a new scientometric indicator
Purpose – 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. Design/methodology/approach – 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. Findings – 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. Originality/value – 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.