Cite As: Cheang, B, Chu, S.K.W., Li, C. & Lim, A. (in press) "A Multidimensional Approach to
Evaluating Management Journals: Refining PageRank via the Differentiation of Citation Types and
Identifying the Roles that Management Journals Play." Journal of the American Society for
Information Science and Technology.
A Multidimensional Approach to Evaluating Management Journals: Refining
PageRank via the Differentiation of Citation Types and Identifying the Roles that
Management Journals Play
Brenda Cheang
Division of Information and Technology Studies, Faculty of Education,
University of Hong Kong,Runme Shaw Building, Pokfulam Road, Hong Kong,
Telephone: +852 6423 3389, Fax Number: +852 2517 7194, E-mail: brendacheang@yahoo.com
Samuel Kai Wah Chu
Division of Information and Technology Studies, Faculty of Education,
University of Hong Kong, Runme Shaw Building, Pokfulam Road, Hong Kong,
Telephone: + 852 2241 5894, Fax Number：+852 2517 7194, E-mail: samchu@hku.hk
Chongshou Li*
Department of Management Sciences, College of Business,
City University of Hong Kong,Tat Chee Ave, Kowloon, Hong Kong,
Telephone: +852 6350 5292, Fax Number: +852 3442 0189, Email: chongshli2-c@my.cityu.edu.hk
Andrew Lim
Department of Management Sciences, College of Business,
City University of Hong Kong, Tat Chee Ave, Kowloon, Hong Kong,
Telephone: +852 3442 8248, Fax Number: +852 3442 0189, Email: lim.andrew@cityu.edu.hk
Abstract
In this paper, we introduce two citation-based approaches to facilitate a multidimensional
evaluation of 39 selected management journals. The first is a refined application of
PageRank via the differentiation of citation types. The second is a form of mathematical
manipulation to identify the roles that the selected management journals play. Our findings
reveal that Academy of Management Journal, Academy of Management Review, and
Administrative Science Quarterly are the clear top three management journals, respectively.
We also discover that these three journals play the role of knowledge hub in the domain.
Finally, when compared to ISI’s JCR, our results more closely matched expert opinions.
Key words: PageRank; Journals Evaluation; Citation Analysis; Journal Influence; Journal
Quality; Journal Impact; Impact Factor
_________________________________________________
*Corresponding Author.
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Introduction
Since Coe and Weinstock’s (1969) study, evaluations of management journals have
periodically been reported in print. Such efforts, although discipline-focused, are not unique
to the management academic community1. In fact, domain-specific journal evaluations are
increasingly being reported in scientific communication outlets because of the immense
practical and intellectual utility they provide for today’s academic stakeholders (DuBois &
Reeb, 2000; Leydesdorff, 2008; Xu, Cheang, Lim & Wen, 2011).
But at the same time, the concept of journal evaluation has hatched into a subject of
contentious debate (Seglen, 1997; Glanzel & Moed, 2002). For in reality, a journal’s quality
or impact may be perceived differently from stakeholder to stakeholder (Robey & Markus,
1998); while some may be planted unflinchingly on the high-citation-count bandwagon,
others may be sat on the publishing-in-a-perceived-quality-journal one, or even others who
may consider academic research to be of impact only if the undertaking culminates in
industrial applicability (Rousseau, 2002; Weingart, 2005).
Resultantly, in a recently published manuscript, Moed, Colledge, Reedijk, Moya-Anegon,
Guerrero-Bote, Plume and Amin (2012) assert that there is mounting consensus among
bibliometricians that the concept of journal evaluation is so multifaceted, and therefore
complex, that it “cannot be captured in one single metric” (p.368). Thereupon, it is with this
caveat in mind that we introduce two citation-based approaches to facilitate a
multidimensional evaluation of 39 selected management journals. The first is the
application of an emerging technique known as PageRank as recent studies have shown
how journal evaluation via this technique is not only a closer match to those of expert
opinions, the technique can also be used to further refine the assessment of management
journals via the differentiation of citation types. The second involves a form of mathematical
manipulation to establish the roles that the 39 selected management journals play.
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The remainder of the paper is organized as follows. In Section 2, a review of the
literature pertaining to PageRank and the mathematical mapping of journal roles is
provided. Section 3 describes the PageRank methodology and the extension of the
technique via the differentiation of citation types. This is followed by a description of the
methodology in identifying the roles that journals play. Section 4 establishes the
delimitations of the study. In Section 5, we present the evaluation results and highlight
insights of our analysis. This is followed by a comparison of our results to those of ISI’s.
Finally, Section 6 concludes the paper.
Literature Review
PageRank
Origins
Although it is not well known, the creators of the PageRank algorithm had been inspired by
Pinski and Narin’s (1976) work in citations analysis when researching the development of
web search engines (Page, Brin, Motwani & Winograd, 1998). In particular, Pinski and Narin
(1976) postulated that citations are not equally prized; that the value of citations by an
article published in a reputable scientific outlet (i.e. journal) should outweigh citations by
an article published in an inferior one (Xu et al., 2011). Drawing from this concept, Brin and
Page (1998) founded Google upon the development and implementation of the PageRank
algorithm to ascertain the level of importance of a given webpage in a given webgraph
network. Summarily, it is the popularity and applicability of Google’s PageRank method,
which is based on Pinski and Narin’s (1976) conjecture that citations are not equally valued,
that Pinski and Narin’s (1976) work is enjoying a renaissance in recent bibliometrics
research2(Butler, 2008).
Transposability of PageRank in Webgraph Networks and Citation Networks
With the exception of permanence in publication citations, the behavior of visiting/linking
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webpages is observed to be similar to the behavior of reading/citing scientific publications.
In the context of webgraph networks, PageRank is as an algorithm implemented on a given
webgraph network consisting vertices and edges, where vertices serve as pages on the
World Wide Web (WWW) and edges serve as hyperlinks (Page, Brin, Motwani & Winograd,
1998). Based on the algorithm and web activity, the rank value of a given webpage is
computed to indicate the level of importance of that particular webpage. Thus, a hyperlink
boosts the level of influence of a given linked webpage (Langville & Meyer, 2004). Odom
(2013) simplifies this concept by explaining that webpage P’s PageRank value is ascertained
from the following three elements:
1. The number of hyperlinks to webpage P
2. The PageRank values of the webpages that link to webpage P
3. The outgoing hyperlinks from the webpages that link to webpage P
In essence, webpage P would receive a sizable PageRank boost from webpages that
have high PageRank values themselves, and if it also makes only few links to other
webpages. Alternatively, being linked by webpages with low PageRank values but with
numerous outbound links would, in a small way, also increase webpage P’s PageRank value
assuming webpage P does not link to those webpages (Langville & Meyer, 2004). In other
words, the PageRank algorithm is built upon the principal of transitive relationships in a
given webgraph network (Cheang, 2013).
In the context of citation networks, PageRank is thus implemented on a given citations
network consisting nodes and edges, where nodes represent journals while edges represent
the citation relationship between any two journals (Cheang, 2013). Based on the algorithm
and citation activity, the derived value of a given journal is indicative of the level of prestige
of that particular journal. As it is with web activity, PageRank factors the transitive
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relationships among citations, mapping citations to their originating sources. This is
equivalent to apportioning “credit where credit is due” (Xu et al., 2011).
Refining PageRank via the Differentiation of Citation Types
Although PageRank enables the determination of a journal’s impact or quality, the
procedure to analyze the transitivity of citations does not actually establish what kind(s) of
influence or impact a journal has (Cheang, 2013). For instance, a journal may receive a
significant volume of self-citations (where articles in a journal cite the same journal)
because it is perhaps a highly specialized journal. Or, a journal may be influential because it
is not only well cited within its core discipline (known as internal citations), it is also highly
cited outside of its core discipline (known as external citations). Consequently, while we are
able to order journals based on the transitivity (and therefore, influence) of citations, we are
unable to pinpoint exactly why a journal is influential. Therefore, with Moed et al.’s (2012)
assertion in mind, we surmise that by differentiating between the various citation types (i.e.
self-citations, internal citations, and external citations), we may then pinpoint the nature of
a journal’s impact or quality; that through this differentiation process, we enable the
development of a metric flexible enough to accommodate multidimensional views (Cheang,
2013).
Identifying Journal Roles
Origins
In a recent PageRank-based study, Lim et al. (2009) proposed the manipulation of a given
journal’s PageRank value and its citation percentage to establish the role that the particular
journal plays. In their study, the authors assert that journals may be knowledge sources,
knowledge hubs, or knowledge stores. Cheang (2013) describes the characteristics of each
role in the following:
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i. Knowledge Source
A knowledge source is a journal that receives significantly more citations from other
journals in a core journals list (CJ). As well, a knowledge source is a journal that cites
very few other journals despite exerting tremendous influence in the CJ. Hence, a
knowledge source is an extremely influential journal.
ii. Knowledge Hub
As its name suggests, a knowledge hub is a journal that not only exchanges knowledge
in a particular domain, it also exchanges knowledge with other disciplines as well. Thus,
because a knowledge hub is highly cited and also cites journals in and out of the CJ, it
also exerts tremendous influence in a CJ.
iii. Knowledge Store
A knowledge store is a journal that cites a lot of journals but fewer journals cite
them. As such, review journals tend to be knowledge stores.
Identifying Roles of Management Journals
This method is an extension of PageRank in the sense that the PageRank value, along with
the citation percentage of a given journal, are mathematically manipulated to establish the
role that the given journal plays. We include this method in our paper as it produces a
different kind of evaluation that adds to our understanding, and therefore, enriches our
perception of a given journal (Cheang, 2013). Additionally, because the results of this
method are graphically captured, we would be able to visualize and grasp the results more
easily.
Methodology
PageRank for Journal Evaluation
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PageRank is a model designed to harness the various citation data available. However, the
construction of a citations network database is first required. Figure 1 is a pictorial
representation of a citations network consisting three journals.
“Insert Figure 1 here”
Construction of the Citations Graph Network
Let us provide a simple illustration when constructing a citations graph network. Figure 1 is
a citations graph network containing three journals. The nodes represent journals whilst
the edges represent the citations and directionality of the citations. Let Ci,j represent the
number of times journal i cites journal j. Thus, edge (i,j) reflects the direct influence or
impact of journal j on journal i. Thus, in the case of C1,2 in Figure 1, it simply refers to the
number of times journal 1 cites journal 2.
Formulation
To solve the problem, we can use the random walk method or matrix multiplication
iteratively. Both methods share a similar philosophy in that they are recursive in nature but
one is based on randomly selecting an initial starting point while the other is based on
matrix multiplication. Thus, for each journal i, the recursive formulation can be expressed
by the following:
𝑃𝑅𝑖𝑥+1 = ∑𝑛𝑗=1 𝑝𝑗𝑖 𝑃𝑅𝑗𝑥
The equation refers to the impact of a journal (which is denoted as PR) where i is the
sum of the product of the impact of every journal j multiplied by the proportion (p) of
citations from j to i.
We now further illustrate the inner-workings of this equation. In Figure 1, we have
three journals (J1, J2, and J3) in the citations network, where the citations and their
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directionality are as follows: C1,1 = 5, C1,2 = 2, C1,3 = 3; C2,1 = 4, C2,2 = 2, C2,3 = 4; C3,1 = 1, C3,2 =
4, C3,3 = 5.
Plugging the citation data into the equation, we get the following:
For Journal 1, we have 𝑃𝑅1𝑥+1 = (𝑝1,1 𝑃𝑅1𝑥 ) + (𝑝2,1 𝑃𝑅2𝑥 ) + (𝑝3,1 𝑃𝑅3𝑥 )
5
4
1
Which means that 𝑃𝑅1𝑥+1 = (10 𝑃𝑅1𝑥 ) + (10 𝑃𝑅2𝑥 ) + (10 𝑃𝑅3𝑥 )
For Journal 2, we have 𝑃𝑅2𝑥+1 = (𝑝1,2 𝑃𝑅1𝑥 ) + (𝑝2,2 𝑃𝑅2𝑥 ) + (𝑝3,2 𝑃𝑅3𝑥 )
2
10
Which means that 𝑃𝑅2𝑥+1 = (
2
10
𝑃𝑅1𝑥 ) + (
4
10
𝑃𝑅2𝑥 ) + (
𝑃𝑅3𝑥 )
For Journal 3, we have 𝑃𝑅3𝑥+1 = (𝑝1,3 𝑃𝑅1𝑥 ) + (𝑝2,3 𝑃𝑅2𝑥 ) + (𝑝3,3 𝑃𝑅3𝑥 )
3
4
5
Which means that 𝑃𝑅3𝑥+1 = (10 𝑃𝑅1𝑥 ) + (10 𝑃𝑅2𝑥 ) + (10 𝑃𝑅3𝑥 )
Finally, when 𝑃𝑅𝑖𝑥 stabilizes/converges at the 𝑥 𝑡ℎ iteration,
𝑃𝑅𝑖𝑥 = Journal i’s influence (JIi)
Upon determining the JIi, we calculate the Article PageRank Score (or APRS) of a journal
by dividing the JIi by the number of articles journal i publishes per year, for the period
under consideration. The APRS score for journal i, in turn, determines the rank order that
journal i would be placed in a given journals set list.
Refining PageRank via the Differentiation of Citation Types
We use the following example to illustrate the various citation types: Consider the citation
network shown in Figure 1. Let (J1) be Academy of Management Journal, (J2) be Academy of
Management Review and (J3) be Operations Research. Let us also define Academy of
Management Journal and Academy of Management Review as core journals to represent the
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domain of management. The citations between these two journals are internal citations.
Let us also define that J3 is not a core journal to management. Therefore, the citations
between J1 and J3, or, J2 and J3 are external citations. With these definitions, the citation
relationships may be summarized as shown in Table 1.
“Insert Table 1 here”
Identifying Knowledge Roles that Journals Play
Formulation
We define the percentage of citations made to core journals for journal 𝑖 as PTC𝑖 . PTC𝑖 is
thus formulated as follows:
∑
𝐶
PTC𝑖 =∑ 𝑗∈𝐶𝐽 𝐶𝑖,𝑗 × 100%.
𝑗∈𝑈𝐽 𝑖,𝑗
Based on the illustration provided in Table 1, the percentage of citations made to the
core for the three journals may be computed as follows:
For J1, PTC1 =
For J2, PTC2 =
For J3, PTC3 =
𝐶1,1 +𝐶1,2
𝐶1,1 +𝐶1,2 +𝐶1,3
𝐶2,1 +𝐶2,2
𝐶2,1 +𝐶2,2 +𝐶2,3
𝐶3,1 +𝐶3,2
𝐶3,1 +𝐶3,2 +𝐶3,3
× 100% = 70%
× 100% = 60%
× 100% = 50%
Therefore, based on its APRS value and citation percentages, a journal is positioned in
one of four quadrants in a graph. In general, journals positioned within the top left quadrant
are considered knowledge stores, while journals positioned within the top right quadrant
are considered knowledge hubs. Journals positioned within the bottom left quadrant are
indistinguishable journals while journals positioned within the bottom right quadrant are
considered knowledge sources.
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Delimitations of Study
In applying our proposed approaches, we consider three important components: (1) data
sources and datasets; (2) period and parameter settings; and (3) computing PageRank
scores. These components set the boundaries for our study and are described below:
Data Sources and Datasets
Presently, data sources are primarily available from Google Scholar, SCOPUS, and the
Institute of Scientific Information (ISI). Of these, we have elected to use citation data from
the ISI’s Journal Citation Report (JCR) for two main reasons: Firstly, in order to differentiate
between citation types, we require incoming and outgoing citations at the journal level. At
present, ISI’s database is the easiest of the three to extract data from; Secondly, ISI is not
only the oldest, most established, indexing agency in the world, its indexing criteria is
probably the most stringent, and their journals database is immense (at over 12,000
journals to date).
As for the datasets that are required for this study, we require two journal sets, namely
a universal set denoted as UJ and a core set denoted as CJ. The UJ is composed of all journals
indexed by the ISI’s JCR while the CJ is composed of 39 selected management journals based
on the number of times they appeared in previous related studies3 as well as informal
interviews with a number of management academics.
Period and Parameter Settings
Besides the UJ and CJ, we establish the various relevant parameters for our study. First, we
consider the time windows relevant to our study. In order to obtain a timely evaluation of
management journals, we focus our study on the citations from articles published in 2010
as they are quite recent. Additionally, a study on citation phenomenon by Amin and Mabe
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(2000) revealed that “Citations to articles published in a given year rise sharply to a peak
between two and six years after publication” (p. 2). Based on this finding, we concentrate our
analysis on the citations that articles received in the four years prior to 2010 as well as the
citations received in year 2010. Therefore, we consider citations from citing papers
published in 2010 to cited papers published in the time period from 2006 to publication
time of citing papers, which is 2010. The following examples clarify the period settings:

We disregard a paper published in 2010 that cites paper B published in 2005
because the cited time does not satisfy our criteria.

We disregard a paper published in 2009 that cite paper B published in 2008 because
the citing time does not satisfy our criteria.

We take into account a paper published in 2010 that cites paper B published in 2007
as the citing and cited period both satisfy our criteria.

We take into consideration a paper published in 2010 that cites paper B published
in 2010 as the citing and cited time both satisfy our criteria.
Next, we establish the citation parameter settings. In particular, we denote the selfcitation parameter as S and the external citation parameter as E. We are interested in four
parameter settings, where (S = E = 0), (S = E = 1), (S = 1, E = 0), and (S = E = 1). Having said
that, internal citations are, by default, set at 1. This is because all citations are evaluated
based on the core journals set list. Therefore, setting (S = E = 0) indicates that only internal
citations are considered, while self-citations and external citations are excluded; setting (S =
E = 1) implies that all citations are considered; setting (S = E = 1) indicates that external
citations, relative to internal citations, are considered; and setting (S = 1, E = 0) indicates
that self-citations, relative to internal citations, are considered.
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Results and Analyses
Results of 39 Selected Management Journals Based on the Differentiation of Citation
Types
Table 2 reports the ratings and APRS scores of the 39 selected management journals based
on the parameters described in Section 4 to generate the ratings.
“Insert Table 2 here”
Analysis of the Results via the Differentiation by Citation Types
Top Five Management Journals
First, we examine the top five management journals based on the results as shown in Table
2. Tagged with the ^ symbol, the top three journals, namely AMJ, AMR, ASQ, post identical
ratings on each of the four (parameter) settings. The fourth and fifth ranked journals are
not as clearly determined. For if the ratings are based on the consideration of all citation
types (S = E = 1), JAP is ranked fourth while SMJ is ranked fifth. Alternatively, if only internal
citations (S = E = 0) are considered, JM and OS would then be ranked fourth and fifth,
respectively.
Upon these findings, we note that the APRS values of all four (parameter) settings of
the top three journals are in the vicinity of 0.1 on average, while JAP and SMJ have APRS
values in the vicinity of 0.05 on average, and JM and OS post APRS values slightly lower than
0.05 on average. And because the APRS values of the top three journals are significantly
higher than the other journals in the CJ, they exert tremendous influence within the CJ
because they receive a lot of citations directly and indirectly from the CJ. Figure 2 provides a
visual representation of the relative placements of the selected journals in the CJ. Summarily,
our findings correlate with those by Podsakoff et al. (2005), where “…by 1999, AMJ and AMR
had joined ASQ at the top, and this group was followed by another group comprised of SMJ,
JAP...”(p. 487).
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Insights Related to External Citations
Next, we discuss the various journals tagged by the * symbol and the # symbol in Table 2.
First, we discuss the ones tagged with *. We note that the ratings of CMR, HBR, IEETEM, JAP,
JBR, JVB, OBHDP, ORM, and RP are around three to five placements higher when both
internal and external citations (S = 0, E = 1) are compared to ratings based on internal
citations only (S = 0, E = 0). The findings suggest that these journals are more influential
outside of the CJ. Indeed, whereas OBHDP is ranked seventh and JAP is ranked fourth overall
(S = E = 1) in this CJ, the overall placement of OBHDP is second, while JAP is third in the field
of applied psychology for the year 2010 (Journal-ranking.com, 2013). And in another
example, RP is ranked 18th overall in the CJ but is ranked sixth overall in the field of
planning and development for the year 2010 (Journal-ranking.com, 2013). Accordingly, for
this CJ, because of the better ratings of these journals when both internal and external
citations are considered, their overall placements are improved when compared to their
ratings for when only internal citations are considered.
As for the journals tagged by the # symbol (namely, BJIR, DS, IR, and MS), their various
placements noted in Table 2 suggest that they share similar rating trends as the journals
highlighted in yellow. The primary divagation is that the rating differences of these journals
are significantly higher (between 9 and 13 placements). Take DS, for example. In 2010, DS
was ranked 26th overall in the field of information systems, and ranked 10th overall in the
field of operations research and management science (Journal-ranking.com, 2013). Its
overall ratings are significantly higher in other disciplines when compared solely to its
internal rating (which is 37th) in this CJ. Consequently, DS scores an overall rating of 27th in
the CJ. Similarly, we note the journal MS, which is rated 18th when only internal citations are
considered. In 2010, MS ranked sixth overall in the field of information systems, and ranked
first overall in the field of operations research and management science (Journal-
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ranking.com, 2013). As a result, MS is ranked 9th overall in this CJ although it ranked twice
as high (18th) when considering its impact solely based on internal citations. These
examples, as well as the findings concerning all journals highlighted in green, indicate that
these journals are well regarded enough to be considered for inclusion into this CJ even
though the research published by these journals may not have as much influence compared
to the other selected journals in the CJ. They may very well be far more influential in other
disciplines, making them (pure) core journals in some other disciplines. Conversely, these
findings may also suggest that there are some journals that are actually core journals in the
domain but they are simply not influential at all. These findings are also graphically
illustrated in Figure 2, which depicts their indistinguishable or borderline indistinguishable
influence in the CJ.
Insights Related to Self-citations
In this segment, we briefly discuss the following five journals, namely JBR, LQ, LRP, MS, and
RP. Tagged with the ** symbol in the (S = 1, E = 0) column, these journals are rated between
four to five placements higher when the self-citation (S = 1, E = 0) parameter is compared to
their ratings when only internal citations (S = E = 0) are considered. These findings suggest
that the proportion of self-citations to internal citations is large. On the one hand, such a
finding is not alarming if the journal is an influential journal (determined by their APRS
values). But if a journal is not influential and still receives high self-citations, a plausible
explanation is that the journal is highly specialized. Alternatively, it exposes a journal as
playing the citation manipulation game as have been observed in numerous studies
(Weingart, 2005; Smith, 2006; Public Library of Science Medicine Editors, 2006, Lynch,
2010).
Results of the Roles that the 39 Selected Management Journals Play
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Based on their APRS scores (on the x-axis) and their citation to core percentages (on the yaxis), Figure. 2 shows the roles that the 39 selected management journals play.
“Insert Figure 2 here”
Analysis of the Roles that the 39 Selected Management Journals Play
In general, the higher the percentage of citations to the CJ and the higher the APRS values of
a particular journal, the more the particular journal plays the role of a knowledge hub. In
this case, we note from Figure. 2 that AMJ, AMR and ASQ are not only positioned in the
‘knowledge hub’ quadrant, they also visually correspond to their no. 1, 2 and 3 rankings,
respectively.
Next we note the bottom left quadrant, or the ‘indistinguishable’ quadrant. As
mentioned in our insights related to external citations, journals in this quadrant are well
regarded enough to be selected for inclusion into this CJ even though the research published
by these journals may not have as much influence compared to the other selected journals
in the CJ. And as shown with our various examples, these journals may very well be
significantly more influential in other core disciplines. Conversely, these findings may also
suggest that there are some journals that are actually core journals in the domain but they
are simply not influential at all. Reading into which category an indistinguishable journal
falls into could be based on the reader’s past experiences with a particular journal and/or
based on rankings of the journal in other fields that it is also featured in. With that being
said, we note that the position of HBR is indeterminable because it traditionally does not
publish references for its featured articles (Lim et al., 2009).
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Finally, we note the knowledge store quadrant where the remaining journals in the CJ
are full-fledged knowledge stores (i.e. LRP, GOM, JMS, ORM, JOB, PP), approaching
knowledge hubs (i.e. SMJ, OM, JM), or borderline knowledge stores (i.e. IJHRM, HRM, JVB,
OBHDP, CMR, IEETEM). We also note that there are no knowledge sources in the CJ.
A Comparison Between PageRank and ISI’s JCR Rank Orders
In this subsection, we compare our results with that of ISI’s. Table 3 in Annex 1 shows the
rankings and ranking disparities of the 39 selected journals obtained via our approach as
well as ISI’s JCR for 2010. Because the ISI’s IF method does not differentiate between
citation types, we use the results based on the parameter setting of
(S = E = 1), as this
parameter setting considers all citation types, for a comparable analysis.
First, we discuss some of the broad findings in Table 3. Overall, the journals tagged by
the * symbol indicate that PageRank’s ratings of those journals are between (at least) 5 and
(at most) 17 placements higher than those produced by ISI, while the journals tagged by the
** symbol indicate that PageRank’s ratings of those journals are between (at least) 5 and (at
most) 10 placements lower than those produced by ISI.
Next, we used Spearman’s Rank Correlation Coefficient (Spearman, 1904), Kendall’s Tau
Rank Correlation Coefficient (Kendall, 1938), Normalized Spearman’s Footrule Distance
(Dwork, Kumar, Naor & Sivakumar, 2001) and Normalized Weighted Footrule Distance
(Langville & Meyer, 2012) to analyze the ranking disparities of our results with that of ISI’s.
Through the Spearman’s Rank Correlation Coefficient and Kendall’s Tau Rank Correlation
Coefficient, the two rankings are highly correlated. Based on the Normalized Spearman’s
Footrule Distance, which considers not only the deviation but also the position where the
deviation occurs, the ranking gaps appear to be small. However, because the value of the
Normalized Weighted Footrule Distance is larger than the Normalized Spearman’s Footrule
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Distance, it suggests that the deviation between these two rankings occur towards at the
upper tier of these rankings. Table 4 is a summary of the results4.
“Insert Table 4 here”
With that being said, we note the placement of ASQ, which has consistently been
viewed as one of the top three journals in management5, is similarly ranked third via our
method but manages to rank only 9th via ISI’s JCR. Indeed, according to our results, other
top-rated journals such as SMJ, OBHDP, and MS suffer similar ranking disparities as ASQ
under the ISI’s ranking methodology. The disparity in rankings are said to be because the
ISI’s method only takes citation frequency into account, completely ignoring citation impact
(Seglen, 1997; Pendlebury, 2009; Xu et al, 2011).
Conclusions
In this study, we introduced two citation-based approaches to enable a multidimensional
evaluation of 39 selected management journals. In particular, we refined the application of
PageRank via the differentiation of citation types and identified the roles that the selected
management journals play. Our findings concur especially with those produced by
Podsakoff et al. (2005) that AMJ, AMR, ASQ have clearly remained the top three management
journals, respectively. We also discovered that these three journals play the role of
knowledge hub in the domain. This means that they not only exchange knowledge in a
particular domain, they also extensively exchange knowledge with other disciplines. In
addition, when compared to ISI’s JCR, our results more closely matched those from past
studies.
Notwithstanding, we note the limitation in terms of data sources. Presently, we are
confined to evaluating only journals indexed by ISI since their data organization allows us to
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extract citing and cited information in an efficient manner. Thus, we are unable to evaluate
journals that are not indexed by ISI.
Finally, the proposed multidimensional approach to journal evaluation is a new
concept. In this light, we aim to do three subsequent things: promote this concept to other
disciplines, get academic stakeholders to adopt/provide input on this concept, and to
improve upon or solicit/introduce new approaches that strengthen this concept.
Endnotes
See Olson (2005) for operations management journals; Rainer & Miller (2005) for
management information systems journals; Eliades & Athanasiou (2001) for biomedical
journals; Bollen, Rodriguez, & Van de Sompel (2006) for dermatology journals; Dubois and
Reeb (2000) for international business journals; and Brown (2003) for accounting and
finance journals.
For PageRank-based journal evaluations, see Bollen, et al. (2006); Chen, Xie, Maslov, and
Redner (2007); Ma, Guan, and Zhao (2008); Lim, Ma, Wen, Xu and Cheang (2009); and Xu et
al. (2011). For the assessment of author impact via PageRank, see Ding, Yan, Frazho and
Caverlee (2009); Ding (2011, a, b); and Yan and Ding (2011).
2
Namely, Coe & Weinstock, 1984; Sharplin & Mabry, 1985; Macmillan & Stern, 1987; Extejt
& Smith, 1990; Johnson & Podsakoff, 1994; Thai & Meyer, 1999; Podsakoff et al., 2005;
Singh et al, 2007; and Harris, 2008.
3
4
5
Detailed results can be found in Annex 2.
Expert surveys include: Coe and Weinstock’s (1984) study which found ASQ to be a top
two management journal; Extejt and Smith’s (1990) study which found ASQ to be a top
three behavioral-based management journal. Citations-based studies include: Johnson and
Podsakoff (1994) which found ASQ to consistently be one of two most influential journals in
management, and showed that SMJ had significantly improved its ranking; Tahai and Meyer
(1999) found that top rated SMJ had accounted for 11% of all journal citations under study;
Podsakoff, Mackenzie, Bachrach, and Podsakoff (2005) ASQ, AMR, AMJ, JAP, OBHDP and
SMJ were consistently rated as top-tier journals over the past two decades.
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impact:
A
PageRank
Annex 1
“Insert Table 3 here”
Annex 2
4 Different Distance Measures for Two Rankings
We formulate Spearman’s Rank Correlation Coefficient, Kendall’s Tau Rank
Correlation Coefficient, Normalized Spearman Footrule Distance and Normalized Weighted
Footrule Distance as follows.
Spearman’s Rank Correlation Coefficient (Spearman, 1904):
𝑟ℎ𝑜 =
∑𝑁
𝑖=1(𝑥(𝑖) − 𝑥)(𝑦(𝑖) − 𝑦)
√∑𝑖(𝑥(𝑖) − 𝑥)2 ∑𝑖(𝑦(𝑖) − 𝑦)2
where 𝑥 and 𝑦 are two full ranking lists of 𝑛 items; 𝑥(𝑖) is the rank position of item 𝑖 in
∑ 𝑥(𝑖)⁄
∑𝑖 𝑦(𝑖)⁄
ranking 𝑥; 𝑦(𝑖) is the rank position of item 𝑖 in ranking 𝑦. 𝑥 = 𝑖
𝑛,𝑦=
𝑛.
Obviously, −1 ≤ 𝑟ℎ𝑜 ≤ 1. If 𝑟ℎ𝑜 = 1, the two lists totally agree with each other; If 𝑟ℎ𝑜 =
−1, the two lists are completely reversed.
Kendall’s Tau Rank Correlation Coefficient (Kendall, 1938):
𝜏=
𝑛𝑐 − 𝑛 𝑑
𝑛(𝑛 − 1)/2
where 𝑛𝑐 is the number of concordant pairs and 𝑛𝑑 is the number of discordant pairs; 𝑛(𝑛 −
1)/2 is the total number of pairs of 𝑛 items in the ranking. Clearly, −1 ≤ 𝜏 ≤ 1. If 𝜏 = 1,
the two lists totally agree with each other; If 𝜏 = −1, the two lists are completely reversed.
Spearman Footrule Distance (Diaconis & Graham, 1977):
𝑛
𝐹(𝑙, 𝑘) = ∑|𝑙(𝑖) − 𝑘(𝑖)|
𝑖=1
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where 𝑙 and 𝑘 are two full ranking lists of 𝑛 items; 𝑙(𝑖) is the rank position of item 𝑖 in
ranking 𝑙; 𝑘(𝑖) is the rank position of item 𝑖 in ranking 𝑘.
Normalized Spearman Footrule Distance (Dwork, et al., 2001):
𝜌=
∑𝑛𝑖=1 |𝑙(𝑖) − 𝑘(𝑖)|
𝑛 2 ⁄2
This value is derived by dividing the maximum value. Thus the normalized Spearman
Footrule distance always lies between 0 and 1. 0 means that two rankings are in perfect
agreement, while 1 means two rankings completely disagree with each other.
Normalized Weighted Footrule Distance (Langville & Meyer, 2012):

Weighted Footrule Distance of two full ranking lists 𝑙 and 𝑘:
𝑛
𝜙=∑

|𝑙(𝑖) − 𝑘(𝑖)|
𝑖=1 min{𝑙(𝑖), 𝑘(𝑖)}
Normalized Weighted Footrule Distance:
𝜙̃ =
∑𝑛𝑖=1
|𝑙(𝑖) − 𝑘(𝑖)|
min{𝑙(𝑖), 𝑘(𝑖)}
𝑛
⌊ ⌋
𝑛
2
−4 ⌊2 ⌋ + 2(n + 1) ∑𝑖=1
1/𝑖
where the denominator is the maximum weighted footrule distance of two full rankings.
The normalized weighted footrule distance is always between 0 and 1. 0 indicates that two
rankings perfectly agree with each other, while 1 indicates that two rankings are completely
reversed.
List of Tables
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TABLE 1. Summary of Quantifying the Three Citation Types in FIG.1.
TABLE 2. This table displays the ratings of 39 selected management journals based
on four parameter settings. Columns 1 and 2 show the acronym and full name of the
selected management journals. Columns 3, 5, 7 and 9 show the Article PageRank
Scores (APRS) while columns 4, 6, 8, and 10 show the ratings of each journal based
on one of four parameter settings, where (S = E = 0), (S = 0, E = 1), (S = 1, E = 0), and
(S = E = 1), respectively.
TABLE. 3 Comparisons between PageRank and ISI’s JCR Rank Orders for 2010.
TABLE 4. Qualitative Deviation between Two Ranking Lists in Table 3.
List of Figures
FIG. 1. Illustration of Citations Graph Network.
FIG. 2. Roles that the 39 selected Management Journals Paly.
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TABLE 1. Summary of Quantifying the Three Citation Types in Figure 1.
Journals
Core
Journals
Non-core
Journals
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J1, Academy of Management Journal
J2, Academy of Management Review
J3, Operations Research
Internal
Citations
C2,1
C1,2
0
External
Citations
C3,1
C3,2
C1,3 + C2,3
27
SelfCitations
C1,1
C2,2
C3,3
TABLE 2. This table displays the ratings of 39 selected management journals based on
four parameter settings. Columns 1 and 2 show the acronym and full name of the
selected management journals. Columns 3, 5, 7 and 9 show the Article PageRank
Scores (APRS) while columns 4, 6, 8, and 10 show the ratings of each journal based on
one of four parameter settings, where (S = E = 0), (S = 0, E = 1), (S = 1, E = 0), and (S = E
= 1), respectively.
Journal
Parameters
Parameters
Parameters
(S = 0,E = 0)
(S = 0, E = 1)
(S = 1, E = 0)
(Internal-citation +
External-citation)
(Internal-citation
+ Self-citation)
(Internal-citation
only)
Acronym
Name
APRS
Rank
APRS
Rank
Parameters
(S = 1, E = 1)
(Internal-citation +
Self-citation+
External-citation)
APRS
Rank
APRS
Rank
AMJ ^
Academy of Management Journal
0.1469
1
0.1115
1
0.1472
1
0.1157
1
AMR ^
Academy of Management Review
0.1207
2
0.0991
2
0.0984
2
0.0898
2
ASQ ^
Administrative Science Quarterly
0.1041
3
0.0833
3
0.0848
3
0.0746
3
BJIR #
British Journal of Industrial
Relations
0.0035
36
0.0113
25
0.0041
37
0.0109
22
BJM
British Journal of Management
0.0059
30
0.0068
33
0.0048
34
0.0060
35
CMR*
California Management Review
0.0085
26
0.0120
23
0.0070
28
0.0105
26
DS #
Decision Sciences
0.0026
37
0.0113
24
0.0030
38
0.0104
27
ETP
Entrepreneurship Theory and
Practice
0.0148
19
0.0154
21
0.0152
21
0.0161
21
GOM
Group and Organization
Management
0.0100
23
0.0097
29
0.0102
22
0.0108
23
HBR*
Harvard Business Review
0.0050
32
0.0102
28
0.0057
31
0.0103
28
HR
Human Relations
0.0119
21
0.0123
22
0.0095
23
0.0107
25
HRM
Human Resource Management
0.0072
27
0.0057
35
0.0056
32
0.0049
36
IEETEM*
IEEE Transaction on Engineering
Management
0.0015
39
0.0048
36
0.0014
39
0.0044
39
IJHRM
International Journal of Human
Resource Management
0.0048
34
0.0047
37
0.0048
35
0.0046
37
IR #
Industrial Relations
0.0048
33
0.0217
14
0.0069
29
0.0221
17
JAP*
Journal of Applied Psychology
0.0450
7
0.0539
4
0.0522
6
0.0563
4
JBR*
Journal of Business Research
0.0025
38
0.0058
34
0.0049
33**
0.0065
34
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JBV
Journal of Business Venturing
0.0183
14
0.0212
15
0.0205
16
0.0229
16
JIBS
Journal of International Business
Studies
0.0181
16
0.0194
16
0.0274
14
0.0236
14
JM
Journal of Management
0.0542
4
0.0436
7
0.0405
7
0.0372
10
JMI
Journal of Management Inquiry
0.0154
17
0.0103
27
0.0158
19
0.0108
24
JMS
Journal of Management Studies
0.0286
12
0.0226
13
0.0284
12
0.0234
15
JOB
Journal of Organizational Behavior
0.0298
11
0.0303
12
0.0240
15
0.0275
12
JOOP
Journal of Occupational and
Organizational Psychology
0.0112
22
0.0108
26
0.0083
25
0.0091
30
JPIM
Journal of Production Innovation
Management
0.0055
31
0.0086
31
0.0063
30
0.0092
29
JVB*
Journal of Vocational Behavior
0.0133
20
0.0181
17
0.0158
20
0.0183
20
JWB
Journal of World Business
0.0085
25
0.0088
30
0.0074
26
0.0079
31
LQ
Leadership
0.0182
15
0.0180
18
0.0311
10**
0.0259
13
LRP
Long Range Planning
0.0061
28
0.0046
38
0.0084
24**
0.0067
33
ML
Management Learning
0.0039
35
0.0038
39
0.0047
36
0.0045
38
MS #
Management Science
0.0153
18
0.0413
8
0.0280
13**
0.0388
9
OBHDP*
Organizational Behavior and Human
Decision Process
0.0342
10
0.0486
6
0.0305
11
0.0423
7
ORM*
Organizational Research Methods
0.0391
9
0.0504
5
0.0369
8
0.0517
6
OS
Organization Science
0.0541
5
0.0388
11
0.0533
5
0.0404
8
OST
Organization Studies
0.0184
13
0.0170
20
0.0204
17
0.0184
19
PP
Personnel Psychology
0.0397
8
0.0389
10
0.0316
9
0.0348
11
RP*
Research Policy
0.0095
24
0.0176
19
0.0163
18**
0.0190
18
SMJ
Strategic Management Journal
0.0529
6
0.0411
9
0.0716
4
0.0555
5
SMR
Sloan Management Review
0.0059
29
0.0068
32
0.0071
27
0.0075
32
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TABLE. 3 Comparisons between PageRank and ISI’s JCR Rank Orders for 2010.
Journal
Acronym
Name
PageRank
ISI’s JCR
Disparity
(S = E = 1)
IF 2010
(PageRank – IF)
Ranking
Ranking
Positions
AMJ
Academy of Management Journal
1
2
-1
AMR
Academy of Management Review
2
1
1
ASQ*
Administrative Science Quarterly
3
9
-6
BJIR*
British Journal of Industrial Relations
22
37
-15
BJM
British Journal of Management
35
31
4
CMR
California Management Review
26
28
-2
DS**
Decision Sciences
27
20
7
ETP
Entrepreneurship Theory and Practice
21
19
2
GOM**
Group and Organization Management
23
16
7
HBR
Harvard Business Review
28
25
3
HR
Human Relations
25
29
-4
HRM
Human Resource Management
36
33
3
IEETEM**
IEEE Transaction on Engineering Management
39
32
7
IJHRM
International Journal of Human Resource
Management
37
39
-2
IR*
Industrial Relations
17
34
-17
JAP
Journal of Applied Psychology
4
5
-1
JBR**
Journal of Business Research
34
26
8
JBV*
Journal of Business Venturing
16
22
-6
JIBS**
Journal of International Business Studies
14
4
10
JM
Journal of Management
10
8
2
JMI*
Journal of Management Inquiry
24
35
-11
JMS**
Journal of Management Studies
15
6
9
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JOB*
Journal of Organizational Behavior
12
17
-5
JOOP*
Journal of Occupational and Organizational
Psychology
30
38
-8
JPIM**
Journal of Production Innovation
Management
29
23
6
JVB**
Journal of Vocational Behavior
20
13
7
JWB**
Journal of World Business
31
24
7
LQ
Leadership
13
12
1
LRP**
Long Range Planning
33
27
6
ML
Management Learning
38
36
2
MS*
Management Science
9
21
-12
OBHDP*
Organizational Behavior and Human Decision
Process
7
15
-8
ORM
Organizational Research Methods
6
3
3
OS
Organization Science
8
7
1
OST
Organization Studies
19
18
1
PP
Personnel Psychology
11
11
0
RP
Research Policy
18
14
4
SMJ*
Strategic Management Journal
5
10
-5
SMR
Sloan Management Review
32
30
2
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TABLE 4. Qualitative Deviation between Two Ranking Lists in Table 3.
Measures
Spearman’s Rank Correlation Coefficient
Kendall’s Tau Rank Correlation Coefficient
Normalized Spearman’s Footrule Distance
Normalized Weighted Footrule Distance
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Value
0.828
0.644
0.271
0.431
32
FiG. 1. Illustration of Citations Graph Network
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FiG. 2. Roles that the 39 selected Management Journals Paly
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