The paper focuses on the robustness of rankings of academic journal quality and research impact in general, and in Economics, in particular, based on the widely-used Thomson Reuters ISI Web of Science citations database (ISI). The paper analyses journals using quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in various RAMs which are based on alternative transformations of citations and influence. All existing RAMs to date have been static, so two new dynamic RAMs are developed to capture changes in impact factor over time and escalating journal self citations. Alternative RAMs may be calculated annually or updated daily to determine When, Where and How (frequently) published papers are cited. The RAMs are grouped in four distinct classes that include impact factor, mean citations and non-citations, journal policy, number of high quality papers, and journal influence and article influence. These classes include the most widely used RAMs, 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), Eigenfactor (or Journal Influence), Article Influence, h-index, and PI-BETA (Papers Ignored - By Even The Authors). As all existing RAMs to date have been static, two new dynamic RAMs are developed to capture changes in impact factor over time (5YD2 = 5YIF/2YIF) and Escalating Self Citations. We highlight robust rankings based on the harmonic mean of the ranks of RAMs across the 4 classes. It is argued 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 quality, impact and influence relative to the harmonic mean of the ranks.

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hdl.handle.net/1765/125315
20th International Congress on Modelling and Simulation - Adapting to Change: The Multiple Roles of Modelling, MODSIM 2013 - Held jointly with the 22nd National Conference of the Australian Society for Operations Research, ASOR 2013 and the DSTO led Defence Operations Research Symposium, DORS 2013
Department of Econometrics

Chang, C.-L., Maasoumi, E., & McAleer, M. (2020). Dynamic impact factors and escalating journal self citations. In Proceedings - 20th International Congress on Modelling and Simulation, MODSIM 2013 (pp. 1350–1356). Retrieved from http://hdl.handle.net/1765/125315