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

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dc.contributor.authorChang, C-L.
dc.contributor.authorMcAleer, M.
dc.date.accessioned2015-02-16T22:50:12Z
dc.date.available2015-02-16T22:50:12Z
dc.date.issued2013en
dc.descriptionWORKING PAPER No. 10/2013en
dc.description.abstractExperts possess knowledge and information that are not publicly available. The paper is concerned with forecasting academic journal quality and research impact using a survey of international experts from a national project on ranking academic finance journals in Taiwan. A comparison 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 Research 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 answer 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 Threshold 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 analysed 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 factor of a journal, which partly answers the question as to When published papers are cited, to the exclusion 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-formation about a journal. The robustness of the rankings is also analysed.en
dc.identifier.citationChang, C-L., McAleer, M. (2013) What Do Experts Know About Forecasting Journal Quality? A Comparison with ISI Research Impact in Finance..en
dc.identifier.urihttp://hdl.handle.net/10092/10171
dc.language.isoen
dc.publisherUniversity of Canterbury. Department of Economics and Financeen
dc.rights.urihttps://hdl.handle.net/10092/17651en
dc.subjectExpert scoresen
dc.subjectJournal qualityen
dc.subjectRAMsen
dc.subjectImpact factoren
dc.subjectIFIen
dc.subjectC3POen
dc.subjectPI-BETAen
dc.subjectSTARen
dc.subjectEigenfactoren
dc.subjectArticle Influenceen
dc.subjecth-indexen
dc.subjectharmonic meanen
dc.subjectrobustnessen
dc.subject.anzsrcField of Research::14 - Economics::1499 - Other Economics::149999 - Economics not elsewhere classifieden
dc.subject.anzsrcFields of Research::46 - Information and computing sciences::4610 - Library and information studies::461005 - Informetricsen
dc.titleWhat Do Experts Know About Forecasting Journal Quality? A Comparison with ISI Research Impact in Financeen
dc.typeDiscussion / Working Papers
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