Volume 23 Issue 1 Article 1 June 2021 Bibliographic Measures of Top-Tier Finance, Information Systems, Bibliographic Measures of Top-Tier Finance, Information Systems, and Management Science Journals and Management Science Journals Thomas M. Krueger Texas A&M University-Kingsville, College of Business Administration, Kingsville, USA, thomas.krueger@tamuk.edu Jack D. Shorter Texas A&M University-Kingsville, College of Business Administration, Kingsville, USA, jack.shorter@tamuk.edu Randy G. Colvin Texas A&M University-Kingsville, College of Business Administration, Kingsville, USA, randy.colvin@tamuk.edu Follow this and additional works at: https://www.ebrjournal.net/home Part of the Business Commons Recommended Citation Recommended Citation Krueger, T. M., Shorter, J. D., & Colvin, R. G. (2021). Bibliographic Measures of Top-Tier Finance, Information Systems, and Management Science Journals. Economic and Business Review, 23(1), 1-14. https://doi.org/10.15458/2335-4216.1001 This Original Article is brought to you for free and open access by Economic and Business Review. It has been accepted for inclusion in Economic and Business Review by an authorized editor of Economic and Business Review. ORIGINAL ARTICLE Bibliographic Measures of Top-Tier Finance, Information Systems, and Management Science Journals Thomas M. Krueger*, Jack D. Shorter, Randy G. Colvin Texas A&M University-Kingsville, College of Business Administration, Kingsville, USA Abstract Purpose: Faculty research is frequently the basis of pay, tenure, and promotion decisions in the university arena. Meanwhile, perceptions regarding the quantity and quality of the research produced by a faculty is often the basis of departmental, college, and university reputation. The journal in which research findings are published is often used to assess the overall research quality. In order to better benchmark journal quality, this report provides findings of a meticulous investigationofleadingjournalsin thefinance,information systemsandmanagementsciencedisciplines. It examines four different citation-based measures of quality and four journal characteristics that are exogenous to the quality of any individual piece of research. In unison, these investigative paths provide a clearer understanding of journal quality across the business realm, and hence of the quality of research appearing in business journals. Design: This study assists in the development of an accurate perception regarding business research through a careful analysis of the popular Journal Citation Reports (JCR) impact factor across leading journals in three diverse business disciplines. By considering threenewer journal qualitymetrics, a.) SCImago JournalRank (SJR), b.)Source Normalized Impact per Paper (SNIP), and c.) Percentage of articles cited, this research builds on past research. Top-tier journals in finance, information systems, and operations research and management science (referred to here as “management sci- ence”) are compared to evaluate the consistency of these measures across disciplines. The differences in journal char- acteristicsandtheirimpactonthecitation-ratebasedmeasuresofqualityarealsoanalyzed.Further,thepotentialimpact of a discipline-based variation in the acceptance rate, issue frequency, the time since journal inception, and total re- viewers are put forth as additional potential exogenous factors that may influence the perception of the overall journal quality. T-tests are applied for discipline comparisons, while correlation and multiple regression are employed in the analysis of journal characteristics. Findings:ThereisasignificantdifferenceintheJCRimpactmeasuresofhigh-qualityfinanceandmanagementscience journals versus high-quality information systems journals. However, only the JCR measures for finance journals correlatewithavarietyofjournal-specificfactors,includingthejournal'sacceptancerateandfrequencyofissue.TheSJR measures for finance and management science journals are, on the other hand, consistently higher than information systems journals, though the SJR value of any individual journal can be quite volatile. Most importantly, finance and management journals also report significant relations between the SJR measures and the journal's acceptance rate and year of initial issue. By comparison, the SNIP metric rates suggest that information systems and management science journals have higher quality. Moreover, underscoring the SNIP metrics for both the base years of the current study, articles in leading information systems and management journals are cited over twelve percentage points more than those in finance journals. Overall, results show that given the metric, the measured variance in the quality of finance, information systems, and management science journals is correlated with the identified journal-specific factors. Research limitations: The present research is limited to three business disciplines, making the examination of journals inotherbusinessdisciplinesalogicalextensionofit.Whereasthisresearchtakesjournalqualityasfixed,onecouldalso evaluate a quality measures reaction to a variation in journal characteristics (i.e. changes in acceptance rates). Further- more, one could include other measures of journal quality, comprising the h-index or the more recently-released Received 27 September 2019; accepted 8 December 2020. Available online 15 June 2021. * Corresponding author. E-mail addresses: thomas.krueger@tamuk.edu (T.M. Krueger), jack.shorter@tamuk.edu (J.D. Shorter), randy.colvin@tamuk.edu (R.G. Colvin). https://doi.org/10.15458/85451.1001 2335-4216/© 2021 School of Economics and Business University of Ljubljana. This is an open access article under the CC-BY-NC-ND license (http://creativecommons. org/licenses/by-nc-nd/4.0/). CiteScoremetric.Suchresearchwouldnotonlybuildonthepresentresearch,butalsoimprovetheaccuracyofscholarly outlets and consequently the research quality. Practical implications: Discipline-specific traits should be considered, and adjusted for, when making inferences about thelong-termvalueofrecently-publishedresearch.Ourinvestigationdemonstratesthatcitation-basedresearchmeasures and journal-specific factors vary systematically across disciplines, which is why discipline-specific differences in journal characteristics, leading to the differences in citation-based quality measures, need to be considered, when making in- ferences about the long-term value of recently-published research. As a result, this research has significant implications for the basis upon which recommendations regarding salary adjustments, retention, and promotion are made. Social implications: Research quantity and quality are two hallmarks of leading research institutions. Assessing research quality is very problematic, because its definition has changed from being based on the review process (i.e. “blind refereed”) to currently standing on acceptance rates and impact factors. Furthermore, the impact factor construct has been a lightning rod of controversy among researchers and administrators. Even journals themselves argue over which metric to employ, in the end supporting those putting them in the best light. This research assesses how impact factors and journal characteristics, which may influence the impact factors, vary by business discipline. The research is especially important and relevant to the authors who separately chair faculty departments that include finance, infor- mation systems, and management science, and are therefore in roles requiring an assessment of faculty research pro- ductivity, including quality. Originality/value:Thisstudyisadetailedanalysisofbibliographicaspectsofthetop-tierjournalsinthreequantitative businessareas.InadditiontothepopularJCR,SJR,andSNIPmeasuresofperformance,ouranalysisstudiestheseldom- examinedpercentageofarticlescitedmetric.articles-citationmetrics.Adeeperunderstandingofcitation-basedmeasures is obtained through an evaluation of changes in how journals have been rated on these metrics over time. Our research shows firstly, that there are discipline-related systematic differences in both citation-based research measures and journal-specific factors, and secondly, that these discipline-specific traits should be considered when making inferences about the long-term value of recently published research. Furthermore, discipline-specific differences in journal char- acteristics,leadingtothedifferencesincitation-basedqualitymeasures,shouldinanycasebeconsideredwhenmaking personnel and remuneration decisions. Keywords: impact actors, research quality, information systems, finance, management science, journal demographics, acceptance rates, bibliographic measures, JCR, SJR, SNIP, citation rates JEL classification: D83 Introduction F or many years, acceptance rates were viewed as the appropriate measure of scholarship quality.Presumably,thelowertheacceptancerate, thehighertheresearchquality.Beingafunctionof thenumberofmanuscriptssubmitted,leakagesin thereviewprocess,andare flection of a journal's review process, acceptance rates may in fact have littletodowith the quality ofanyindividualpiece ofresearch.Inaddition,sincesubmissionstatistics are maintained by editors, they also are heavily dependent upon the whims of these editors. Un- scrupulous editors may count re-submissions as new submissions in order to expand the accep- tance rate denominator and reduce the published acceptance rate. Being less susceptible to manip- ulation, impact factors have recently replaced acceptance rates as the primary measure of researchquality.Amorecomprehensivehistoryof journal impact factors can be found in Van Rann (2006),andArchambault and Lariviere (2009). Research extending beyond one's own narrow discipline is frequently viewed as a measure of quality (Belcher et al., 2016; Schermann et al., 2014). On one hand, joint exploration by parties from multipledisciplineshelpstoaddresscomplexissues faced in the real world. However, Bromham et al. (2016),andWilliams (2016) find that joint explora- tion is frequently funded at a level that is less than that of pure, single discipline endeavors. Krueger and Shorter (2019) contend that the joint analysis of finance journals and information systems journals facilitates an understanding of journal impact for readers within these (and other) disciplines. Reliance upon impact factors does not, in and of itself, provide a solution to the challenge that exists when one attempts to make accurate inferences regardingresearchquality.Aswillbepointedoutin the literature review below, there are a variety of journal impact measures arising from the existence of various definitions of “impact.” Contrasting impactfactors are dealt with inaseparate sectionof this paper. The initial focus here is one of assessing the robustness of the popular and most widely- disseminated Journal Citation Reports (JCR) value across business disciplines. The analysis identifies 2 ECONOMIC AND BUSINESS REVIEW 2021;23:1e14 exogenous journal characteristics which are corre- latedwiththeJCRimpactmeasureandtheextentto whichthesejournalcharacteristicsvaryacrossthree quantitativebusinessdisciplines.Thethreeresearch issues studied here, related to the research hy- potheses, alternative hypotheses, and implications of each that is evaluated in this study, are provided below. 1.1 Hypothesis concerning JCR journal impact measure variation across disciplines Hypothesis A. JCR values are similar across top- tier journals in finance, information systems, and management science disciplines. Alternative A. JCR values of top-tier journals in finance, information systems, and management science are significantly different. Variationinresearch quality itself is controlled by limiting the sample to only highly-regarded aca- demic journals. One of the most quality-conscious lists of academic journals is the Chartered Associa- tion of Business School's Academic Journal Guide (AJG). Hypothesis A supports the contention that the JCR impact factors of quality journals will be similar across business disciplines. The importance ofthisanalysisliesinthepossibilitythatresearchers may claim that their research is abnormally good based upon a higher JCR measure, however, these measures may be typical of the research topic area. 1.2 Hypothesis concerning journal characteristics correlation with JCR impact factors Hypothesis B. Research quality, when measured using the JCR values, is independent of journal specific factors (i.e. acceptance rate, frequency of issue, time since initial publication, number of re- viewers, etc.). Alternative B. JCR values are correlated with journal-specific factors. Ideally,theJCR values areindependentofjournal factors as is the factor of time since initial publica- tion. In such a case, the JCR measure tends to be a better indicator of research quality, however, jour- nal longevity may, quite on the contrary, be indic- ative of the quality of the journal and shed light on the quality of its articles. 1.3Hypothesisconcerningtherobustnessofjournal quality measures Hypothesis C. Alternative bibliometric measures of journal quality provide consistent rankings of journal quality across disciplines. Alternative C. Alternative bibliometric measures give conflicting ratings of journal quality across disciplines. To the extent that journal “quality” is an all- encompassing construct, one would detect consis- tent rankings of journal quality across disciplines. Nevertheless, differences in ranking may provide insight into the utilization of new research by the citingauthorsinagiven discipline.Researchersina given discipline will typically want to be cognizant of the bibliometric measure being employed by supervisors and champion that measure which puts their scholarly productivity in the best possible light. The literature review in the continuation fo- cuses onascholarlyperformanceassessmentacross disciplines, including past studies of impact factors and acceptance rates, and alternative measures of impact. Finally, the research method and findings are revealed in the following two sections, where implications of the findings that are relative to the research hypotheses and proper evaluation of scholarly performance are addressed and sugges- tions for future research provided. 2 Literature review 2.1 The importance of research quality in faculty assessment Numerous researchers have tackled the topic of whatconstitutesexcellenceinresearch.Thisissueis addressed by members of promotion and tenure committees,aswellasthoseregularlycalleduponto write reference letters for candidates. One major element of these evaluations is the quality and quantity of the candidate's research publications. The quality of the journals the researcher actually publishes in is frequently used as an indicator of a long-termimpactofthecandidate'sresearch.Thisis especiallytrueforthedisciplinesstudiedwithinthis paper, as demonstrated by recent articles in both finance (see, for example, Brogaard et al., 2018;and; Netter et al., 2018)and informationsystems (see,for example, Dennis et al., 2006; and; Bernardi & Collins, 2018). Even after making the heroic assumption that journal quality can be used as a surrogate for research quality, several issues remain to be resolved. A variety of measures have been used, over time, to assess the quality of journals. A pop- ular measure of journal quality has been whether submissionsarereviewedbypeers,andwhetherthe journal follows a blind review style (Blank, 1991; Crane, 1967). Double-blind reviews, wherein the identity of both the author and reviewer are ECONOMIC AND BUSINESS REVIEW 2021;23:1e14 3 unknown to the other party, are typically perceived to provide greater quality. In a comparison of the single-blind with the double-blind review process, Snodgrass (2007) found that when a double-blind review process was used, acceptance rates were lower and referees turned in more critical reviews. However, using the broad-brush requirement that an article be in a peer-reviewed journal essentially created only two classes of articles and said little about the relative quality differences of journals. Therefore, blind review was replaced by acceptance rates as a means to compare journal quality. 2.2 Past studies comparing business disciplines Perhaps the most relevant set of prior research is the analyses of acceptance rates in finance, infor- mation systems, and other areas, conducted by Krueger and Shorter. In their initial study, Krueger and Shorter (2012) investigate variation in accep- tance rates over time inthefinanceandinformation systems areas. They then add data from the ac- counting discipline (Krueger et al., 2012) and the marketing discipline (Shorter et al., 2012), while studying the acceptance rate variation across time and national boundaries. Instead of treating all journals in finance equally, the next analysis con- siders acceptance rates across seven finance sub- disciplines, among them insurance, real estate, and corporate finance, and establishes significant varia- tions across finance sub-disciplines (Krueger, 2013). Meanwhile,Shorter(2013)takesamorecareful look at the impact of time to review, manuscript length, and also how journal sponsorship impacts infor- mation system journal acceptance rates. Manage- ment journals are added to the investigation stream by Krueger (2014), whose analysis documents the relative impact of publication fees on acceptance rates. This report is a natural outgrowth of these research streams, because it firstly, investigates the analysis of JCR, SJR, SNIP, and the citation score variation across the finance and information sys- tems disciplines, limiting them to top-tier journals, and secondly, uses updated values and journal characteristics. Frequently is a journal quality measurement simplified to the requirement that a publication be included on a predetermined list of premier jour- nals. Krueger compares journals included in the CharteredAssociationofBusinessSchools'Academic Journal Guide (AJG) and Australian Business Deans Council's (ABDC) Journal Quality List with the journalsincludedinCabell'sDirectoryofPublishing Opportunities in Finance (Krueger, 2017). As with this research, demographic characteristics of journals are examined. Instead of going across list- ings of finance journals, this study compares the AJG listing for finance, information systems, and management science. This listing provides a much larger sample of journals than the Schaffer et al. (2011) bibliometric studyof 4finance journals, or La Paz et al. (2020) study of 8 information systems journals, or even La Paz et al. (2020) analysis of purely the Information Systems Journal. One precursor to this research is the comparison of bibliometric measures and journal characteristics by Krueger and Lelkes (2019). Their study in addi- tion utilizes the Journal Citation Reports (JCR), the SCImago Journal Rank (SJR), and the Source Normalized Impact per Page (SNIP) citation-based quality measures. Within their research, accounting journals tend to be older, with higher acceptance rates,fewerissues,fewerreferees,andshorterinitial reviews. JCR measures are virtually identical, while finance journal SJR ratings and accounting journal SNIP scores prove higher. In any case, this current studyaddsnotonlymanagementsciencejournalsto the list of disciplines evaluated, but also the infor- mative citation percentage metric. Another precursor to this research is the recent popular bibliometric analyses in the management science area. A timeline of bibliometric research in the management science arena is provided by Liao et al. (2019) who apply the concept of “leading” to the articles themselves, by studying only the one percent most cited manuscripts. The authors, in- stitutions, and nation representation are ranked, though little thought is given to journal character- istics or bibliometric measures. Conversely, while focusing purely on 79 leading journals in the Op- erations Research-Management Science (OR-MS) discipline, over the 2001e2011 period, Merigoand Yang (2017) present an interesting set of biblio- metric measures, including total citations, citations per article, how many of the 200 most-cited articles are in a given journal, impact factor, and h index. While noting the value of the Academic Journal Guide, they study the universe of journals in the Web of Science database and nonetheless end up with approximately the same number of journals as this study, using the Academic Journal Guide as a selection criterion. The current paper is a dramatic step forward in that it benchmarks results in Man- agement Science against two other business disciplines. 2.3 Journal impact factors What is impact? Are there a variety of impacts, such as one on the business world and one in the 4 ECONOMIC AND BUSINESS REVIEW 2021;23:1e14 realm of scholarship itself? The frequently-dis- cussed gap between research and practice in this field has been a concern of business schools, in terms of their legitimacy in the eyes of students, employers, and political entities (Kieser & Leiner, 2009; Johnson & Orr, 2020). Further, Birkinshaw et al. (2016) find that academic papers that are cited in bridge journals, such as Sloan Management Review and finance's Practical Applications, tend to have a highacademicimpactfactor.Avarietyofalternative impact measures have been created, each of which attempts to gauge the relative importance of a journal. The initial impact factor was devised by Eugene Garfield (2006), with data published yearly since 1975 in the Journal Citation Reports (JCR) and now available from Clarivate Analytics. The SCI- mago Journal Rank (SJR) is another measure of the scholarly value of journal articles based on perceived journal quality. Journal quality is defined by SJR in terms of both the number of citations and the prestige of the journals, in which a given jour- nal's articles are cited. One essentially ends up with a measure of the average prestige per article for each Scopus journal. In a ranking of 300 economics journals, Moosa reports that the Journal of Finance moves up one notch, if one uses this “prestige arti- cles in prestige journals” measure (Moosa, 2017). Meanwhile,CurrieandPandher(2020) demonstrate ameanstoenhancetheJCRandSJRratings,usinga survey of active researchers. The source normalized impact per paper (SNIP) measurewasdeveloped byMoed(2011).Thisratio's numerator is the number of citations per journal, while the denominator is a value based on what is referred to as the citation potential. The citation potential may be viewed as the average length of a list of references in a discipline (Moed, 2010, 2011). In this analysis, we initially concentrate on the JCR measure and how it estimates the impact of finance, information systems, and management science journals. We discuss how the other biblio- metric measures(SJR, SNIP,andCITE scores) affect the three journal disciplines in section 4.3 Analysis of Additional Bibliometric Measures. The Scientific Journal Ranking (SJR) provides additional “points” for prestigious journals, and may thereby be self- perpetuating, according to the Chartered Associa- tion of Business Schools (CABS). CABS also warns that the Source Normalized Impact per Paper (SNIP) does accommodate multi-disciplinary jour- nals, but is also sensitive to the number of reviews publishedandthe “gameplaying”arising fromself- citation (ABS, 2015 Academic Journal Guide, p. 11). Given the documented increase in self-citation (see, for instance, Chorus & Waltman, 2016) and the recently created CiteScore metric (see for, instance, Kim & Chung, 2018); Sugimoto & Lariviere, 2018; and Memon, 2018), the authors chose to initially concentrate on the historical standard of research quality, the JCR measure. There has been a significant amount of research regarding which bibliographic measures provide the best estimate of journal quality. In an expansive study, Mingers and Yang (2017) contrast the JCR, SRJ, and SNIP ratings of 37 business journals, includingfourfinancejournals andtwoinformation systems journals. Whereas in information systems, Lowry et al. (2013) contrast expert opinion and bibliographic measures, finding a high degree of agreement in terms of journal quality. While some researchers (i.e. Merigo et al. (2015) study a single journal's bibliometric measures across extended periods, our focus is one of analyzing and con- trasting the current environment, in which finance, information systems, and management science scholars find themselves. An important contribution of the current article is the examination of the percentage of articles cited. HuandWu(2014)notethatthecurrentliteratureon citations gives more attention to the percentage of papers that are never cited than to the time- dependent pattern of citations. Nevertheless, a highly relevant finding made by Hu and Wu is that the percentage of never-cited papers in a relative short time period begins to approach a stable value. Making the citation rates reported here, which are based on three years of a subsequent citation ac- tivity,isagoodmeasureofthepercentageofarticles whichwilleverbecited.Teixiraetal.(2020)examine 19,419 international business papers and find that only 8 (0.04%) ever gain a significant amount of attention after having been uncited for at least 5 years. The U.S.-based accounting, finance, and in- formation systems journals have higher citation- based journal quality, according to Krueger et al. (2021), while the U.S. acceptance rates tend to be lower. However, a discipline-based variation in the journal quality measures and characteristics is identified, thus supporting the evaluation of these variables in the management science discipline. 3 Research method The initial sample consisted of finance, informa- tion systems, and management science journals, included in the 2015 Academic Journal Guide (AJG), published by the Association of Business Schools. The research was completed before the 2018 AJG interim revision was released, which added rela- tivelyfewjournalstothe105finance,79information ECONOMIC AND BUSINESS REVIEW 2021;23:1e14 5 systems,and65managementsciencejournalsinthe 2015 guide, where the added journals typically have the lowest AJG ranking possible. The next compre- hensive analysis of journals is expected to be pub- lished in 2020. Though not unanimous, Bryce et al. (2020) find a high level of correlation between AJG ratings in research perception. The AJGisunfortunatelyonlyalistingofjournals, with no journal demographic information. Following the approach of Krueger (2018), we apply the editor supplied information, reported to and published by Cabell's Directory of Publishing Op- portunitiesonline.Thissinglesourceofdataisused as a means to capture journal demographics, which are generically defined and readily available, putting this research in line with the prior biblio- metric studies. Using Cabell's Directories reduced the maximum sample size to altogether 90 finance, 59informationsystems,and34managementscience journals. The sample, on which each comparison is based, varies with the availability of dependent and independent data and is provided in the tables that follow. Journal characteristics of the three disciplines in this study are presented in Table 1. The mean acceptance rates and total reviewers for manage- ment science journals align between finance and informationsystemsjournals.MostnotableinTable 1 is that management science journals are more mature or older with a mean launch year of 1978.3, 14 years before finance journals, and 8.6 years before information systems journals. For a subse- quent analysis, it might also be significant that the management science set of journals' maximum launch year is 2005, which is more than 15 years before the time of the current research. Secondly, management science also has the highest average numberofissuesperyearat7.4,withamaximumof 24. Table 2 reflects these two aspects in the corre- lation coefficients. In order to assess the multi-collinearity of the sample, Pearson product-moment correlation co- efficients were computed for the four numeric in- dependentvariables,shown in Table 2. The variable correlations across finance journals are presented in Panel A, while the correlations across information systems journals are exhibited in Panel B, and the correlations for management science are shown in Panel C. The average of the absolute value of the correlation coefficients for finance journals is 0.170, with none of the correlations being above 0.308. The Table 1. Journal characteristics. Finance (N¼ 46) Information Systems (N¼ 46) Management Science (n¼ 34) Acceptance Rates Mean 25.8% 20.0% 23.3% Median 20% 18% 20% Minimum 4% 5% 9% Maximum 80% 70% 80% Issues per Year Mean 5.1 5.9 7.4 Median 4 4 6 Minimum 1 1 4 Maximum 15 12 24 Journal Launch Year Mean 1992 1986.9 1978.3 Median 1996 1990 1980 Minimum 1921 1901 1950 Maximum 2012 2013 2005 Total Reviewers Mean 2.5 3.4 2.9 Median 2 3 2 Minimum 1 2 2 Maximum 5 6 3 Table 2. Pearson product correlation coefficients. Acceptance Rate Year of Initial Publication Issue Frequency per Year Number of Reviewers Panel A: Finance journals (n¼ 46) Acceptance Rate 1.0 Year of Initial Publication 0.308 1.0 Issue Frequency per Year 0.050 0.038 1.0 Number of Reviewers 0.165 0.293 0.160 1.0 Panel B: Information systems journals (n¼ 46) Acceptance Rate 1.0 Year of Initial Publication 0.160 1.0 Issue Frequency per Year 0.019 0.252 1.0 Number of Reviewers 0.155 0.021 0.012 1.0 Panel C: Management science journals (n¼ 34) Acceptance Rate 1.0 Year of Initial Publication 0.021 1.0 Issue Frequency Per Year 0.248 0.267 1.0 Number of Reviewers 0.324 0.150 0.250 1.0 6 ECONOMIC AND BUSINESS REVIEW 2021;23:1e14 latter value can be found in the acceptance rate columnandtheyearofinitialpublicationrow,which isessentiallythefirstcomputedvalueinTable2.The positive value means that as journal origin becomes morerecent,acceptanceratestendtorise.Apositive correlationisnotsurprising,inlightofmorerecently originatingjournalshavingtosetalowerstandardin order to attract submissions. Or, they may need to accept a higher percentage of submissions to pro- vide a perceived necessary number of articles to justifyexistence.Thecoefficientofdeterminationfor thecombinationofacceptancerateandyearofinitial issueisonly0.095(i.e.0.308 2 ),meaningthatlessthan ten percent of the variation in the finance journal acceptance rates can be explained by how long the journal has been in existence. Correlation coefficients for information systems journals are exhibited in Panel B of Table 2, where one finds lower correlation values than those exhibited in Panel A. The highest absolute value below the diagonal is the 0.252 correlation coeffi- cient for the relationship between the date of issue andissuefrequency.Theimplicationofthenegative sign is that more recent information systems jour- nals tend to have fewer issues per year. Over the years, older information systems journals might have had more of a chance to build a following, resulting in a demand for more frequent publica- tion.Supportingthiscontention,inPanelA,onecan see that the relationship between issue frequency and year of initial issue is also negative among finance journals. Squaring this information systems journals' correlation coefficient for these indepen- dent variables provides a value of 0.064 (i.e. 0.252 2 ), suggesting that only about six percent of the variation in publication frequency can be explained by when the journal first appeared. Correlation coefficients for management science areexhibitedinPanelCofTable2.PanelCdisplays negative correlation values for issue frequency paired with acceptance rate and year of initial publication, similar in direction to the values in Panel A. Most notable among the three panels, the set of correlation values for issue frequency is strongest in Panel C. The management science co- efficients indicate that leading up to 2005 (see Table 1), journals launched in later years had fewer issues per year. Relatedly, coefficients show that as issue frequency decreases, acceptance rate increases, which could support more articles per publication. In order to assess the robustness of the compari- son between finance, information systems, and management science journals, information regarding the SCImago Journal Rank (SJR indica- tor),SNIP,andcitationrateswereobtained.TheSJR indicator accounts for both the number of citations received by a journal and the prestige of the jour- nals,inwhichsuchcitationsarelocated.Further,the SCImago Lab produces the SJR index and freely provides a variety of additional journal quality metrics at www.scimagojr.com, some of which go back to 2002. As regards the Source Normalized ImpactperPaper(SNIPIndicator),itadjustscitation counts for the number of citations in a given field. The SNIP measure is issued by Scopus, which publishesSNIPdatagoingbackto2012.Inaddition, Scopus publishes the percentage of journals that have been cited over the subsequent three years, whichisthethirdbibliometricmeasurebeyondJCR that is reported in this paper. Table 3. Comparison of JCR impact factors. Finance Journals Information Systems Management Science Panel A: JCR values by discipline N4 64 63 4 Mean 1.31 2.45 1.64 Median 1.32 2.28 1.38 Minimum 0.03 0.52 0.20 Maximum 6.04 7.27 5.91 Panel B: Statistical significance of difference in JCR values Disciplines: Finance & Information Systems Finance & Management Science Information Systems & Management Science t-statistic 4.22 1.35 2.58 p-value 0.000 0.090 0.006 significance *** * *** Asterisks signify p-value significance at the 0.01 and 0.10 levels using *** and *, respectively. ECONOMIC AND BUSINESS REVIEW 2021;23:1e14 7 4 Findings 4.1 Discipline-based differences in JCR values Interestingly, as shown in the first row of Table 3 and46journalsinbothfinanceandinformationsys- tems were listed in the 2015 Academic Journal Guide (AJG) with a JCR impact measure, and only 34 for managementscience.Further,themeanJCRvalueof information systems journals is notably higher than that offinance andmanagement science journals. In addition, information systems journals have higher minimum and maximum JCR impact factors. Consequently, it is not surprising to find that the impactasmeasuredbytheJCRmetricissignificantly different at the 0.01 level. The dominance of infor- mation systems journals over finance and manage- ment science journals, in terms of JCR-measured impactfactors,isillustratedbythechartinFig.1. The implication is that quality information sys- tems articles are cited 1.87 times more than top-tier finance articles, and 1.49 times more than manage- ment science articles. Although one potential explanation for such values is that there are more information systems journals, which could have more articles citing other information systems research, and hence the higher impact factor, the counter argument is that as the number of journals rises, so too does the denominator in the JCR index, which would reduce this measure. The actual number of finance journals in the AJG listing ex- ceeds the number of information systems journals by a ratio of 1.56 to 1 (i.e. 86 ÷ 55). Regardless of the cause, the evidence does not support the first hy- pothesis, but does support the alternative hypothe- sis. That means that the JCR values of research withoutinformationregardingthedisciplineshould be used with great caution. One may wonder about the relative level of these JCR means concerning other journals. Across the 12,061 journals with JCR scores, as reported by Gann (2017), 205 journals have the score above 10. The MIS Quarterlyat7.27hasarankingthatisinthe top 3.3 percent, while the Journal of Finance with a ranking of 6.04 is in the top 4.6 percent of academic journals. With an overall score of 2.45, the average quality information systems journal has an impact ranking, which is in the top 28.6 percent of all journals. By comparison, with an overall score of 1.31,theaverageimpactofqualityfinancejournal is in the top 55.4 percent of all journals. 4.2 JCR correlation with key journal characteristics This section reveals the results discovered in a quest to identify why information systems journals have higher JCR impact values. Specifically, we studied four numeric journal characteristics: accep- tance rate, annual frequency of issue, launch date, andthetotalnumberofreviewers.Giventhelimited amountofmulti-collinearity,asexhibitedinTable2, a multiple regression analysis was completed in order to gain an understanding of the explanatory power of these journal characteristics. Multiple regression itself is required due to the testing of the impact of several journal characteristics, while the multiple regression coefficients values provide an understanding of how citation-based quality mea- sures vary across changes in journal characteristics. All together enable one to assess the overall signif- icance of the models, as well as the significance of each individual independent variable. The results of the multiple regression computa- tion are provided in Table 4, where model-related statistics are reported in the left set of columns, while the regression model coefficients with their significancearereportedintherightsetofcolumns. These results are based on the 43 finance, 37 infor- mation systems, and 34 management science jour- nalsincludedinthe AJG,withcompleteinformation available in Cabell's Directories. The multiple regression model F value is highly significant for finance journals and approaching the significance for information systems journals. The ability of these four variables to explain the JCR metric reg- isters at 25.2 percent finance journals and 8.3 percent for information systems journals, with almost no influence on management science jour- nals (1.4 percent). Multiple regression coefficients are presented on the right side of Table 4, with coefficient p-values andasteriskstohelpthereaderlocatethetermsthat are significantly different from zero. As shown in the table, no key journal characteristics are signifi- cant formanagementsciencejournals, however,the 0 0.5 1 1.5 2 2.5 3 n a i d e M n a e M Finance Informaon Systems Management Science Fig. 1. Comparison of JCR measures. 8 ECONOMIC AND BUSINESS REVIEW 2021;23:1e14 acceptance rate proves to be significant in two regression models, that is for finance and informa- tion systems journals. The negative sign of the term is expected, because it indicates that as the accep- tance rate rises, there is a decline in the JCR value. For instance, an increase in the acceptance rate of ten percent, for instance from 20 to 30 percent, is likely to reduce the JCR metric among finance journals by 0.54 and among information systems journals by 0.78. Stated in terms of citations, the numberofcitations islikelytodropbyabouthalfof a citation per top-tier finance article as the accep- tanceraterisesbytenpercent.Theoveralldeclineis about three-fourths of a citation among information systems journals. In the discussion of correlation coefficients above, itisnotedthatoneofthehighestcorrelationsamong finance journals exists between acceptance rate and yearofinitialissue.Althoughtheyearofinitialissue is approachingsignificance,one cannotsaythat this variable adds a significant contribution to the explanation of the JCR measure. The negative sign of the year of initial issue and acceptance rate cor- relation, found in Table 2, is matched by a negative sign in the regression model, computed and exhibited in Table 4. The implication, arising from Table 4, is that more recent journals tend to have a lowerJCRvalue.Anegativesignisalsofoundinthe equation with the information systems journals' year of initial issue, with the coefficient again being insignificant. There is a difference established in the signifi- cance and sign attached to the annual issue fre- quencybyfinancejournalsandinformationsystems journals. Greater frequency each year results in a higher JCR value among finance journals, with the term being significant at the 0.05 level. Among the many reasons for this positive coefficient is the possibility that journals with many issues have a greater opportunity to cite prior research appearing in the same journal. Although the information sys- tems journals' coefficient on this term is negative, it is not significant. In addition, the Number of Re- viewerstermturnsoutnotstatisticallysignificantfor journals in either discipline. 4.3 Analysis of additional bibliometric measures 4.3.1 SJR metric In light of the dichotomy of the JCR results re- ported above, journal ratings on three additional bibliometric metrics were obtained and analyzed. Comparisons based on the SCImago Journal Rank (SJR) metric, which considers both the citation and quality of the journal in which a journal is being Table 4. JCR multiple regression model results. Regression Model Significance Regression Model Coefficients F-value P-value Adjusted R2 Acceptance Rate Year of Initial Issue Annual Issue Frequency Number of Reviewers Finance Journals (n¼ 43) 4.54 0.004** 0.252 0.054 (0.000***) 0.005 (0.151) 0.081 (0.026**) 0.213 (0.526) Information Systems Journals (n¼ 37) 1.81 0.151 0.083 0.078 (0.044**) 0.003 (0.574) 0.012 (0.395) 0.093 (0.385) Management Science (N¼ 34) 1.11 0.370 0.014 0.010 ( 0.549) 0.002 ( 0.892) 0.007 (0.549) 0.452 (0.120) Asterisks signify p-value significance at the 0.01 and 0.05 levels using *** and **, respectively. ECONOMIC AND BUSINESS REVIEW 2021;23:1e14 9 cited,arereportedinPanelAofTable5.TheSource Normalized Impact per Paper (SNIP) metric, which corrects for citation frequency differences across fieldsofstudyandconsidersthreeyears,isshownin Panel B. Meanwhile, the percentage of journal arti- cles cited is shown in Panel C. To further enhance the analysis, we present both the most recent, i.e. reportedin2017,valuesofthesemeasuresandtheir level for at least one historical period. The SJR measuresarereportedfor2002,2007,2012,and2017, while SNIP and citation percentages are reported for 2012 and 2017. Table 5 includes mean, median, maximum, and minimum values for these biblio- graphic measures among premier finance, infor- mation systems, and management science journals. For ease of reading, the larger value within each period and measure is highlighted in bold. The SJR measures for finance journals are consistently higher than for information systems journals, regardless whether one is considering mean,median,ormaximumvalues.In2017,finance journal SJRs were 61 percent higher on average, thoughwiththemedianonlyelevenpercenthigher. The diminished minimum SJR rating among infor- mation systems journals may be a reflection of a diminished quality of the Information Resources Management Journal, which experienced a 58.1 percent decline, from 0.258 to 0.08, in its SJR rating. Meanwhile,themostcitedjournalappearstobethe Journal of Finance with a SJR rating that is over three times that of MIS Quarterly. From 2002 to 2017, average SJR measures of top- tier finance journals rose by fifty-nine percent, however, the 2017 SJR value was lower than it had been in 2012. By comparison, information systems journals rose by 78 percent over the period 2002e2017, but with the highest reported SJR value occurring in 2007. The median values present a picture of stability over the period 2007e2017, regardless of whether one is considering finance journals or information systems journals. In view of the journals with the maximum SJR measure on a year-by-year basis, the Journal of Finance's SJR value peaked in 2014, at a level of 21.42, while the MIS Quarterly's SJR value reached its zenith at 9.42 in 2007. Overall, while finance journals rate higher on this quality metric, the SJR value of any individual journal can be quite volatile. The 2012 and 2017 SJR measures for management science journals advance meaningful insight, con- cerning the distribution of values for its 34 journals. Compared to finance and information systems journals, from minimum values to mean and maximum values, management science journals present more linearity in the relationships between thethreevalues.Morelinearityholdsforbothyears. The stronger linearity implies that the JCR values for management science journals reflect more normality. 4.3.2 SNIP metric By comparison, the SNIP metric rates premier information systems and management science journals higher, no matter whether considering the mean, median, or minimum SNIP rating. Bold lettering in Panel B of Table 5 only exists on the finance side of the ledger, when it comes to the maximum SNIP rating, which would be the results from the Journal of Finance. The difference in the SNIP values grew over the period 2012e2017 from an average difference of 16 percent to 29 percent. In fact, the average SNIP values of all three journal Table 5. Analysis of alternative bibliometric measures across time. Finance Journals Information Systems Management Science 2012 2017 Change 2012 2017 Change 2012 2017 Change Panel A: SJR measures Mean 2.18 1.87 0.31 1.03 1.16 0.13 1.32 1.34 0.02 Median 0.90 0.89 0.01 0.77 0.80 0.03 1.21 0.95 0.26 Minimum 0.21 0.16 0.05 0.22 0.11 0.11 0.27 0.29 0.02 Maximum 19.47 18.32 1.15 5.23 5.08 0.15 3.74 5.36 1.62 Panel B: SNIP measures Mean 1.31 1.16 0.15 1.52 1.50 0.02 1.59 1.45 0.14 Median 0.91 0.96 0.05 1.48 1.42 0.06 1.30 1.28 0.02 Minimum 0.04 0.14 0.10 0.15 0.21 0.06 0.51 0.38 0.13 Maximum 5.16 5.80 0.64 5.05 4.48 0.57 2.97 2.91 0.06 Panel C: Citation rate Mean 0.50 0.54 0.04 0.63 0.66 0.03 0.63 0.67 0.04 Median 0.50 0.54 0.04 0.70 0.67 0.03 0.64 0.69 0.05 Minimum 0.06 0.17 0.11 0.18 0.29 0.11 0.33 0.34 0.01 Maximum 0.96 1.00 0.04 0.92 0.95 0.03 0.87 0.91 0.04 *Source: Scopus. https://www.scopus.com/sources.uri. The larger value within each period and measures is highlighted in bold. 10 ECONOMIC AND BUSINESS REVIEW 2021;23:1e14 disciplines declined over the five-year period. However, the median SNIP value increased among finance journals, but declined among information systems and management science journals. All else being equal, the comparison of the SJR and SNIP ratings suggests that extending the citation window anextrayearand/orconsideringtherelativelyfewer citations in information systems journals increases the SNIP-perceived perception of information sys- tems journals. 4.3.3 Citation rates Evenwithintop-tier journals, citation rates are far from spectacular, with only 54 percent of finance articles cited in 2017, 66 percent of information systems journals cited, and 67 percent of manage- ment science journals cited over the initial three- yearperiod.Forinstance,articlesin2014couldhave been cited in 2015, 2016 and 2017. Citation rates across the three journal disciplines were up about six percent from where they had been in 2012. Me- diannumbersarequitesimilar,withthetypicaltop- tier information systems article being 13 percent more likely to be cited than a finance article, but 2 percent less likely than a management science article. At the lowest extreme, in 2017, only seventeen percent of the articles in the Journal of Emerging Markets Finance were cited. By comparison, the worst showing among information systems journals in 2017 was the International Journal of Information Technology and Management, a journal with only 29 percent of its articles being cited. At the higher extreme, 95 percent of the MIS Quarterly's articles were being cited, meaning that 5 percent had not beenconsideredworthyofcitationovertheensuing three years. By comparisons, it is surprising that all of the articles in the Journal of Finance appearing in 2014werecited overthefollowingthreeyears.Even among what are considered to be top-tier journals, this evidence is consistent with the naysayer's view that a large percentage of articles are not read by more than the authors, reviewers, and editors. These results also lend support to the third alter- native hypothesis, which states that the relative measureofjournalqualityvariesacrossbibliometric measures. 4.3.4 Factors leading to differences in additional bibliometric mesures bibliometric metrics Considering the divergence in ratings given to finance, information systems, and management science journals by these alternative bibliometric measures, an important question is one of, whether the differences are tied to variation in specific Table 6. Multiple regression model results. Regression Model Significance Regression Model Coefficients F-value P-value Adjusted R2 Acceptance Rate Year of Initial Issue Annual Issue Frequency Number of Reviewers Panel A: JCR metric Finance Journals (n¼ 43) 4.54 0.004** 0.252 0.054 (0.000***) 0.005 (0.151) 0.081 (0.026**) 0.213 (0.526) Information Systems Journals (n¼ 37) 1.81 0.151 0.083 0.078 (0.044**) 0.003 (0.574) 0.012 (0.395) 0.093 (0.385) Management Science Journals (N¼ 34) 1.11 0.370 0.014 0.010 ( 0.549) 0.002 ( 0.892) 0.007 (0.549) 0.452 (0.120) Panel B: SJR metric Finance Journals (n¼ 46) 3.07 0.027* 0.235 0.127 (0.013**) 0.053 (0.070*) 0.312 (0.076*) 0.129 (0.820) Information Systems Journals (n¼ 36) 2.49 0.064 0.250 0.052 (0.009**) 0.006 (0.530) 0.024 (0.712) 0.351 (0.089*) Management Science Journals (N¼ 34) 2.72 0.048* 0.174 0.012 (0.417) 0.028 (0.039**) 0.062 (0.215) 0.229 (0.360) Panel C: SNIP metric Finance Journals (n¼ 69) 5.96 0.006** 0.275 0.019 (0.004***) 0.016 (0.008***) 0.053 (0.142) 0.046 (0.715) Information Systems Journals (n¼ 50) 2.21 0.082 0.164 0.019 (0.123) 0.004 (0.629) 0.054 (0.234) 0.114 (0.628) Management Science Journals (N¼ 34) 1.27 0.302 0.032 0.001 (0.883) 0.002 (0.792) 0.063 (0.066) 0.171 (0.319) Panel D: Citation Rate metric Finance Journals (n¼ 53) 1.28 0.291 0.096 0.027 (0.205) 0.121 (0.586) 1.310 (0.200) 0.163 (0.964) Information Systems Journals (n¼ 48) 3.84 0.009** 0.263 0.045 (0.048**) 0.071 (0.598) 0.234 (0.777) 7.372 (0.003***) Management Science Journals (n¼ 34) 0.790 0.541 0.026 0.111 (0.567) 0.168 (0.345) 0.690 (0.301) 1.205 (0.719) Asterisks signify p-value significance at the 0.01, 0.05 and 0.10 levels, using ***, **, and * respectively. ECONOMIC AND BUSINESS REVIEW 2021;23:1e14 11 journal characteristics. For ease of comparison, Panel A of Table 6 restates the JCR metric infor- mation found in Table 4. In that prior discussion, it was reported that acceptance rate is significantly related to the JCR of both finance and information systems journals. Going down the Annual Issue Frequency column in Table 6, one can see that this independent variable was only tied to the finance JCR measures, but unrelated to the variation in any of the four journal quality measures of information systems journals. Asonewouldexpect,thereareseveralsimilarities across regression equations. For instance, a signifi- cant proportion of the SJR measure variation can be explained by these independent variables. As acceptance rates rise, the SJR values drop by a sig- nificantamountforfinanceandinformationsystems journals.LookingatthethreerightcolumnsofPanel B for finance and information systems journals, one finds that the SJR is the only journal quality mea- sure that is independent of journal longevity, issue frequency, and number of reviewers. This lack of significance may make SJR a better measure of journal quality for finance and information systems journals, because perceived article quality is not correlated with these journal factors that are extra- neous to the article itself. Nonetheless, for management science journals, SJR is the only metric, where the set of exogenous factors, acceptance rate, launch, issue frequency, and the number of reviewers combine to produce a significant prediction. Launch, i.e. the year of the initial issue, is the lone significant factorda closer looklinkstotheobservationsfromTables1and2.A launch window running from 1950 to 2005 and the oldermeanof1978.3providethebasisforpredicting SJR, while the frequency of prestigious citations drives SJR. The current study indicates that the more mature management science journals are more established and thus recognized for their quality and prestige, as evidenced by the significant connection with the SJR metric. By comparison, journal longevity is significantly related to the finance SNIP ratings. With the sig- nificance of the acceptance rate and relatively large sample size, the F ratio reaches its highest level (i.e. 5.96) in the regression, wherein the finance SNIP values serve as the dependent variable. The explanatorypower(i.e.adjustedR 2 )reachesaheight of 27.5 percent for the finance SNIP measures. As regardstheindependentvariables,noneofthemare significantly related to the information systems and management science SNIP journal ratings. As was reported in Panel C of Table 5, the per- centageofarticlescitedduringthesubsequentthree yearsishigheramonginformationsystemsjournals. Further, as shown in Panel D of Table 6, the explanatory power of these independent variables among information systems journals reaches 26.3 percent,withacceptanceratebeingsignificantatthe 0.05levelandnumberofreviewersbeingsignificant at the 0.01 level. Ironically, as the number of re- viewers rises, the percentage of articles cited drops. A careful investigation of this finding revealed that several of the journals with limited reviewers being used actually found themselves among those with the highest citation ratings. Finance and manage- ment science journal citation ratings proved not significantly tied to any of the listed independent variables, resulting in low F statistic values and explanatory power. What is evident from Table 6 is that the drivers of perceived journal quality vary from discipline to discipline, which is nevertheless consistent with the third alternative hypothesis. 5 Conclusion Itisafactthatquantityandqualityofresearchare the two hallmarks of leading research institutions. Nevertheless, assessing research quality is very problematic,becauseitsdefinitionhaschangedfrom being based on a review processes (i.e. “blind refereed”) to acceptance rates and more recently to impact factors. Furthermore, the impact factor constructhasbeenalightningrodofcontroversy,as researchers, administrators, and journals argue over which metric to employ. The present research as- sesses how impact factor estimates and journal characteristics,whichmayimpacttheimpactfactors, vary by business discipline. The research proves especially important and relevant for the authors who separately chair faculty departments, which include finance and information systems, and are therefore in the roles requiring assessment of not only faculty scholarly productivity, but also quality. In order to limit the impact of journals with lesser quality on our findings, the empirical sample con- sists of journals identified by London's Association of Business Schools as having the best work in the field. Only 105 finance, 79 information systems, and 65 management science journals are listed in the most recent comprehensive Academic Journal Guide (AJG). This study uses arguably the most popular journal citation reports, or the JCR measure of impact. A subset of the AJG empirical sample com- prises of 46 finance and information systems jour- nals, along with 34 management science, journals for which JCR values are reported by Clarivate Analytics.Inaddition,aspecial sectionofthispaper is focused on briefly discussing some of the other 12 ECONOMIC AND BUSINESS REVIEW 2021;23:1e14 popular bibliometric measures, namely the SJR, SNIP, and citation rates. Using t-tests, we find that there is a significant difference in the JCR values of quality journals across disciplines, with information systems jour- nals publishing research cited more frequently. The information systems journals' domination over financejournalspersists,whenoneconsidersmean, median, minimum,or maximum impact factors. For instance,finance faculty publishing in journals with the JCR readings of 2.0 are in journals that are 53 percent above the discipline's average, while infor- mation systems faculty publishing in journals with the JCR readings of 2.0 are in journals that are 18 percent below the discipline's average. In the continuation, correlation analysis and multiple regression techniques were employed to verify that several journal characteristics can be used to explain a journal's JCR measure. Or stated another way, research quality, as measured by this factor, can be foreshadowed by quantitative factors, such as the acceptance rate and annual issue fre- quency. Further, finance faculty can court higher citation rates for their research by scouting out journals which have a lower acceptance rate, have been in existence for a longer period of time, and have more annual issues. Interestingly, regarding the latter journal characteristics, information sys- tems journals with fewer annual issues tend tohave higher JCR values. The SJR measures for finance journals are consistently higher than for information systems journals, when mean, median, or maximum values are considered. While finance journals do rate higher on this metric, the SJR value of any individ- ual journal can be quite volatile. Similarly, the mean, median, and minimum SJR values of man- agementsciencejournalsfactorhigherthanthoseof information systems journals. By comparison, the SNIP metric rates premier information systems journals higher, regardless whether considering the mean, median, or minimum SNIP rating. Other things held constant, the comparison of the SJR and SNIP ratings suggests that extending the citation window an extra year and/or considering the rela- tively fewer citations in information systems jour- nals increases the perceived perception of information systems journals. Even among top-tier journals, citation rates are far from spectacular in 2017, with over 46 percent of finance articles, 34 percent of information systems, and 33 percent of management science articles not being cited over the within three years of publication criteria. Even among what are considered to be top-tier journals, this evidence is consistent with the naysayer's view that a large percentage of articles are not read by none other than the authors, re- viewers, and journal editors. What is evident from our brief analysis of the SJR, SNIP, and citation rates,utilizingmulti-regression,isthatthedriversof perceived journal quality vary from discipline to discipline. Logical extensions of this research include exam- ining journals in other business disciplines. One could study the correlation of changes in biblio- graphic measures and journal bibliometric mea- sures across other disciplines, such as marketing and accounting. 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