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What Do Experts Know About Forecasting Journal Quality? A Comparison with ISI Research Impact in Finance

Chia-Lin Chang () and Michael McAleer

Working Papers in Economics from University of Canterbury, Department of Economics and Finance

Abstract: Experts possess knowledge and information that are not publicly available. The paper is con¬cerned with forecasting academic journal quality and research impact using a survey of inter¬na¬tion¬al experts from a national project on ranking academic finance journals in Taiwan. A com¬par¬i¬son is made with publicly available bibliometric data, namely the Thomson Reuters ISI Web of Sci¬ence citations database (hereafter ISI) for the Business - Finance (hereafter Finance) category. The paper analyses the leading international journals in Finance using expert scores and quantifiable Re¬search Assessment Measures (RAMs), and highlights the similarities and differences in the expert scores and alternative RAMs, where the RAMs are based on alternative transformations of citations taken from the ISI database. Alternative RAMs may be calculated annually or updated daily to an¬swer the perennial questions as to When, Where and How (frequently) published papers are cited (see Chang et al. 2011a,b,c). The RAMs include the most widely used RAM, namely the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Immediacy (or zero-year impact factor, 0YIF), Eigenfactor, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, PI-BETA (Papers Ignored - By Even The Authors), 2-year Self-citation Thresh¬old Approval Ratings (2Y-STAR), Historical Self-citation Threshold Approval Ratings (H-STAR), Impact Factor Inflation (IFI), and Cited Article Influence (CAI). As data are not available for 5YIF, Article Influence and CAI for 13 of the leading 34 journals considered, 10 RAMs are ana¬lysed for 21 highly-cited journals in Finance. The harmonic mean of the ranks of the 10 RAMs for the 34 highly-cited journals are also presented. It is shown that emphasizing the 2-year impact fac¬tor of a journal, which partly answers the question as to When published papers are cited, to the ex¬clu¬sion of other informative RAMs, which answer Where and How (frequently) published papers are cited, can lead to a distorted evaluation of journal impact and influence relative to the Harmonic Mean rankings. A linear regression model is used to forecast expert scores on the basis of RAMs that capture journal impact, journal policy, the number of high quality papers, and quantitative in¬form¬ation about a journal. The robustness of the rankings is also analysed.

Keywords: Expert scores; Journal quality; RAMs; Impact factor; IFI; C3PO; PI-BETA; STAR; Eigenfactor; Article Influence; h-index; harmonic mean; robustness (search for similar items in EconPapers)
JEL-codes: C18 C81 C83 (search for similar items in EconPapers)
Date: 2013-02-13
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15) Track citations by RSS feed

Downloads: (external link)
http://www.econ.canterbury.ac.nz/RePEc/cbt/econwp/1310.pdf (application/pdf)

Related works:
Journal Article: WHAT DO EXPERTS KNOW ABOUT FORECASTING JOURNAL QUALITY? A COMPARISON WITH ISI RESEARCH IMPACT IN FINANCE (2013) Downloads
Working Paper: What Do Experts Know About Forecasting Journal Quality? A Comparison with ISI Research Impact in Finance? (2013) Downloads
Working Paper: What Do Experts Know About Forecasting Journal Quality? A Comparison with ISI Research Impact in Finance (2013) Downloads
Working Paper: What do Experts know about Forecasting Journal Quality? A Comparison with ISI Research Impact in Finance (2013) Downloads
Working Paper: What Do Experts Know About Forecasting Journal Quality? A Comparison with ISI Research Impact in Finance (2013) Downloads
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