New scientometric indicator for the qualitative evaluation of scientific production

Abstract

Purpose – This paper aims to propose a new qualitative indicator for the evaluation of the productions of researchers in any discipline. Design/methodology/approach – Based on the study of existing quantitative indicators, the authors’ approach consisted of the hybridization of two indicators. This hybridization is based on the individual H_index (Hi_index) and H_index contemporary (Hc_index) weighted by qualitative factors. The initial sources of the data are online bibliographic databases, such as Google Scholar and Publish or Perish. Findings – A new scientometric indicator was used to compare the scientific production quality of researchers and their classification (as part of a research community) as the classification of national and international research institutions. The authors have applied a new indicator to compare and classify the members of their laboratory, RIADI, according to their quality of scientific production. Practical implications – The indicator is an improvement of the H_index. It is a measure that can have an impact on society (influencing research attitudes, affecting quality of research). By this contribution, the authors measure more than one aspect by involving all the external factors that can affect the quality of research. Originality/value – This paper fulfils a gap in the literature concerning the absence of a qualitative indicator among the set of existing quantitative measures. Additionally, this paper addresses the limitations of the existing qualitative practices, such as peer review and citation analysis. In the new qualitative indicator, the authors involve all of these qualitative aspects: the influence of the age of the paper, the number of co-authors, the order of the co-authors, the impact factor of journals and the conference rankings.

Cost-effectiveness and resource allocation (CERA) 18 years of evolution: maturity of adulthood and promise beyond tomorrow

“…These limitations where emphasized in a large number of bibliographic sources over the recent decade. Furthermore, new scientometric indicators, were proposed [37], and some are undergoing broad adoption by academic community and publishers alike [38]. Typically, these are Source Normalized Impact per Paper (SNIP equals 0.636 for CERA in 2020) and SCImago Journal Rank (SJR equals 0.467 value in 2020) [39].…”

Foreign experience in evaluating the efficiency of scientific and pedagogical research

“…У публiкацiї тунiських дослiдникiв Ibrahim N., Habacha Chaibi A., Ben Ahmed M. [15] запропоновано новий показник оцiнювання дослiджень будь-якого напрямку, що є гiбридом двох показникiв -∼ 64 ∼ iндивiдуального H-iндекс i сучасного Hc-iндекс, зваженим за якiсними факторами. У роботi також розглядаються обмеження iснуючих якiсних практик, таких як: експертна оцiнка i аналiз цитування.…”

“…), використання наукометричних баз даних (НБД) у процесi оцiнювання дослiджень ( [5], [7], [22], [35] та iн. ), вимiрювання формальних наукометричних показникiв ( [15], [16], [23], [29]), використання альтметричних пiдходiв ( [1], [2], [6], [10], [17] та iн.) i використання цифрових бiблiотечних систем ( [11], [18], [28], [32]).…”

Comprehensive Researcher Achievement Model (CRAM): a framework for measuring researcher achievement, impact and influence derived from a systematic literature review of metrics and models

“…This approach requires judgements regarding the weight that should be assigned to the number of publications, their quality, where they were published and their downstream influence or impact. There are significant questions about the extent to which human judgement based on these criteria is an effective mechanism for making these complex assessments in a consistent and unbiased way 1–3. Criticisms of peer assessment, even when underpinned by relatively impartial productivity data, include the propensity for bias, inconsistency among reviewers, nepotism, group-think and subjectivity 4–7…”