An Analysis on Correlations between Journal Impact Factor and Research Performance Evaluation Weight

2005 ◽  
Vol 36 (3) ◽  
pp. 1-25
Author(s):  
Hee-Yoon Yoon ◽  
Sin-Young Kim
2019 ◽  
Author(s):  
Miguel Abambres ◽  
Tiago Ribeiro ◽  
Ana Sousa ◽  
Eva Olivia Leontien Lantsoght

‘If there is one thing every bibliometrician agrees, is that you should never use the journal impact factor (JIF) to evaluate research performance for an article or an individual – that is a mortal sin’. Few sentences could define so precisely the uses and misuses of the Journal Impact Factor (JIF) better than Anthony van Raan’s. This manuscript presents a critical overview on the international use, by governments and institutions, of the JIF and/or journal indexing information for individual research quality assessment. Interviews given by Nobel Laureates speaking on this matter are partially illustrated in this work. Furthermore, the authors propose complementary and alternative versions of the journal impact factor, respectively named Complementary (CIF) and Timeless (TIF) Impact Factors, aiming to better assess the average quality of a journal – never of a paper or an author. The idea behind impact factors is not useless, it has just been misused.


2018 ◽  
Author(s):  
Miguel Abambres ◽  
Tiago Ribeiro ◽  
Ana Sousa ◽  
Eva Olivia Leontien Lantsoght

If there is one thing every bibliometrician agrees, is that you should never use the journal impact factor (JIF) to evaluate research performance for an article or an individual-that is a mortal sin'. Few sentences could define so precisely the uses and misuses of the Journal Impact Factor (JIF) better than Anthony van Raan's. This manuscript presents a critical overview on the international use, by governments and institutions, of the JIF and/or journal indexing information for individual research quality assessment. Interviews given by Nobel Laureates speaking on this matter are partially illustrated in this work. Furthermore, the authors propose complementary and alternative versions of the journal impact factor, respectively named Complementary (CIF) and Timeless (TIF) Impact Factors, aiming to better assess the average quality of a journal-never of a paper or an author. The idea behind impact factors is not useless, it has just been misused.


2021 ◽  
pp. 1-22
Author(s):  
Metin Orbay ◽  
Orhan Karamustafaoğlu ◽  
Ruben Miranda

This study analyzes the journal impact factor and related bibliometric indicators in Education and Educational Research (E&ER) category, highlighting the main differences among journal quartiles, using Web of Science (Social Sciences Citation Index, SSCI) as the data source. High impact journals (Q1) publish only slightly more papers than expected, which is different to other areas. The papers published in Q1 journal have greater average citations and lower uncitedness rates compared to other quartiles, although the differences among quartiles are lower than in other areas. The impact factor is only weakly negative correlated (r=-0.184) with the journal self-citation but strongly correlated with the citedness of the median journal paper (r= 0.864). Although this strong correlation exists, the impact factor is still far to be the perfect indicator for expected citations of a paper due to the high skewness of the citations distribution. This skewness was moderately correlated with the citations received by the most cited paper of the journal (r= 0.649) and the number of papers published by the journal (r= 0.484), but no important differences by journal quartiles were observed. In the period 2013–2018, the average journal impact factor in the E&ER has increased largely from 0.908 to 1.638, which is justified by the field growth but also by the increase in international collaboration and the share of papers published in open access. Despite their inherent limitations, the use of impact factors and related indicators is a starting point for introducing the use of bibliometric tools for objective and consistent assessment of researcher.


2020 ◽  
Vol 13 (3) ◽  
pp. 328-333
Author(s):  
Sven Kepes ◽  
George C. Banks ◽  
Sheila K. Keener

2021 ◽  
pp. 016555152110597
Author(s):  
Sumeer Gul ◽  
Aasif Ahmad Mir ◽  
Sheikh Shueb ◽  
Nahida Tun Nisa ◽  
Salma Nisar

The manuscript processing timeline, a necessary facet of the publishing process, varies from journal to journal, and its influence on the journal impact needs to be studied. The current research looks into the correlation between the ‘Peer Review Metrics’ (submission to first editorial decision; submission to first post-review decision and submission to accept) and the ‘Journal Impact Data’ (2-year Impact Factor; 5-year Impact Factor; Immediacy Index; Eigenfactor Score and Article Influence Score). The data related to ‘Peer Review Metrics’ (submission to first editorial decision; submission to first post-review decision and submission to accept) and ‘Journal Impact Data’ (2-year Impact Factor; 5-year Impact Factor; Immediacy Index; Eigenfactor Score and Article Influence Score) were downloaded from the ‘Nature Research’ journals website https://www.nature.com/nature-portfolio/about/journal-metrics . Accordingly, correlations were drawn between the ‘Peer Review Metrics’ and the ‘Journal Impact Data’. If the time from ‘submission to first editorial decision’ decreases, the ‘Journal Impact Data’ increases and vice versa. However, an increase or decrease in the time from ‘submission to first editorial decision’ does not affect the ‘Eigenfactor Score’ of the journal and vice versa. An increase or decrease in the time from ‘submission to first post-review decision’ does not affect any ‘Journal Impact Data’ and vice versa. If the time from ‘submission to acceptance’ increases, the ‘Journal Impact Data’ (2-year Impact Factor, 5-year Impact Factor, Immediacy Index and Article Influence Score) also increases, and if the time from ‘submission to acceptance’ decreases, so will the ‘Journal Impact Data’. However, an increase or decrease in the time from ‘submission to acceptance’ does not affect the ‘Eigenfactor Score’ of the journal and vice versa. The study will act as a ready reference tool for the scholars to select the most appropriate submitting platforms for their scholarly endeavours. Furthermore, the performance and evaluative indicators responsible for a journal’s overall research performance can also be understood from a micro-analytical view, which will help the researchers select appropriate journals for their future scholarly submissions. Lengthy publication timelines are a big problem for the researchers because they are not able to get the credit for their research on time. Since the study validates a relationship between the ‘Peer Review Metrics’ and ‘Journal Impact Data’, the findings will be of great help in making an appropriate journal’s choice. The study can be an eye opener for the journal administrators who vocalise a speed-up publication process by enhancing certain areas of publication timeline. The study is the first of its kind that correlates the ‘Peer Review Metrics’ of the journals and the ‘Journal Impact Data’. The study’s findings are limited to the data retrieved from the ‘Nature Research’ journals and cannot be generalised to the full score of journals. The study can be extended across other publishers to generalise the findings. Even the articles’ early access availability concerning ‘Peer Review Metrics’ of the journals and the ‘Journal Impact Data’ can be studied.


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