# Authorship inequality and elite dominance in management and organizational research: A review of six decades

Mehmet A Orhan, Yvonne G T van Rossenberg, P. Matthijs Bal

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Mehmet A Orhan, Yvonne G T van Rossenberg, P. Matthijs Bal. Authorship inequality and elite dominance in management and organizational research: A review of six decades. International Symposium on Scientific Elites: Concentration and Inequality, Sep 2023, Copenhagen, Denmark. 10.31219/osf.io/tzx92. hal-04966164

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# Authorship inequality and elite dominance in management and organizational research:

## A review of six decades

Mehmet A. Orhan¹ ID, Yvonne G. T. van Rossenberg² ID, P. Matthijs Bal³ ID

¹ Nyenrode Business University, the Netherlands

² Radboud University Nijmegen, the Netherlands

³ University of Lincoln, United Kingdom

## Author Note

Mehmet A. Orhan ID https://orcid.org/0000-0001-7093-4085

Yvonne van Rossenberg ID https://orcid.org/0000-0002-1776-4029

P. Matthijs Bal ID https://orcid.org/0000-0002-6955-2837

Correspondence concerning this article should be addressed to Mehmet A. Orhan,

mail: m.orhan@nyenrode.nl
# Authorship inequality and elite dominance in management and organizational research:
A review of six decades

## Abstract

Ideally, the academic publication process should be meritocratic, fair, and open to diverse groups of researchers. Yet, many scholarly disciplines are far from this ideal. To investigate the extent and nature of overrepresentation in management and organizational research, we examined 60-year publication trends in three closely related subfields: Management (MNGT), Human Resource Management (HRM), and Industrial-Organizational Psychology (IOP). Analyzing over 60,000 publications from 42 top-tier journals, our study reveals an increasing trend in authorship inequalities and a growing dominance of the scientific elite. Individual-level analyses, along with journal and field-level comparisons, show that a select group of researchers has become more influential over time, leading to rising disparities in authorship. Field-level comparisons also show that the most productive IOP researchers publish significantly more articles than those in other fields. Besides rising numbers of publications, the super-elite of IOP are found to dominate more journals, as evidenced by a higher frequency of the same authors appearing on the top-10 most productive list in IOP than in the other two fields. Through network analyses, we revealed that IOP consistently shows a large giant component, indicating that a large portion of IOP authors is part of the “same connected network,” reflecting a highly collaborative field where even smaller groups are connected to the broader network. We recommend future advancements in theory, practice, and policy to address these inequalities and promote a more inclusive and equitable research environment.

Word count: 234 words

Keywords: hegemony, hyperproduction, overrepresentation, prolific scholars, scientific elites
Authorship inequality and elite dominance in management and organizational research:

A review of six decades

Authorship inequality is a worrying problem in science (Hart & Perlis, 2021). In most parts of the world, academic careers increasingly depend upon the quantity of publications in high-impact journals, resulting in heightened competition in academia. This intensified publication pressure has resulted in a surge in rejection rates for top-tier journals. For instance, the *Journal of Applied Psychology*, which had a rejection rate of 73% in 1970 (Fleishman, 1971), has experienced a staggering increase in rejection rate to 94% as of 2021 (Eby, 2022). Similarly, Antonakis et al. (2019) revealed that *The Leadership Quarterly* “desk-rejected” approximately 70% of submissions in 2018. These escalating rejection rates not only confirm the heightened global competition in academia but also signal that rigorous review processes are in place to ensure that only the most robust and credible research is accepted for publication in top journals. Consequently, journal editors convey that the limited space is reserved for authors who truly deserve it, ensuring that published research is of exceptional quality and thus reinforcing the credibility and scientific rigor associated with top-tier journals.

Journal space, especially in top-tier journals, is a scarce resource; hence, it is a great privilege. Primarily, top-tier journals are often seen as a way to legitimize research. Besides the tangible rewards of publishing in top-tier journals, those published in these outlets have a greater chance of being respected, are taken seriously by their peers, and can enjoy prestige and reputation (Aguinis et al., 2020; Highhouse et al., 2020). Nevertheless, this privilege is often unevenly distributed across individuals, genders, races, institutions, and geographical locations.

A growing body of research has confirmed that certain voices are overrepresented in the academic publishing system – from authorship to editorial positions (Angus et al., 2021; Auschra
et al., 2022; Bajwa & König, 2019; Dewidar et al., 2022; Mason et al., 2021; Murphy & Zhu, 2012; Rad et al., 2018; Roberts et al., 2020). Access to journals could be restricted by various systemic barriers, creating structural challenges to addressing diversity, equity, and inclusion (DEI) issues, including underrepresentation in research.

DEI issues have gained significant attention within academic communities in the last decade. Notably, the American Psychological Association (APA) has recently unveiled a strategic mission<fnref n="1" /> for its journals aimed at promoting equitable opportunities and representation for researchers from diverse backgrounds. Likewise, other scientific societies, such as the Academy of Management (AOM), Society for Industrial and Organizational Psychology (SIOP), and Association for Psychological Science (APS), have expressed their commitment to fostering inclusivity within research (AOM, 2021; SIOP, 2016; APS, n.d.; Gibson, et al., 2018). Despite these aspirations, top-tier journals are often at the target due to the overrepresentation of contexts and samples from Western, Educated, Industrialized, Rich, and Democratic (WEIRD) countries (Pitesa & Gelfand, 2023) in addition to overrepresentation of specific groups defined by factors such as gender, race, status, institution, and geographical location (Auschra et al., 2022; Bajwa & König, 2019; Huber et al., 2022; Nielsen & Börjeson, 2019). Consequently, this perpetuates the marginalization and underrepresentation of diverse populations while allocating a disproportionate amount of space to repetitive topics, samples, methodologies, contexts, and ideas generated by dominant groups of researchers (Bal & Dóci, 2018; Harley, 2015). Although many top journals claim to offer fair opportunities for access, the observable evidence depicts a

<footnote n="1">¹ https://www.apa.org/pubs/authors/equity-diversity-inclusion</footnote>
divergence from reality, as access alone does not necessarily result in equitable outcomes. To
explain this paradoxical condition, Lewis (2022) observes the following:

> "Issues of representation are inseparable from the science and from the stories we tell about our science and scientific institutions. What counts as 'good science' tends to be research approaches that prioritize the experiences of dominant groups, and not approaches developed to prioritize people placed on the margins of society. The topics that count are ones that fit with the 'master narratives' in the field, and not the 'counter narratives' that sometimes emerge from marginalized groups." (para. 6).

Thus, underrepresentation should not be viewed as an isolated issue that can be resolved without addressing the underlying dynamics of dominance and overrepresentation. Current discussions on DEI in research often emphasize separation and variety while neglecting the disparities shaped by prestige, status, and hierarchy (Harrison & Klein, 2007). Consequently, DEI initiatives frequently aim to enhance variety with tokenism and statistical adjustments. However, underrepresentation is not a standalone problem; they are symptoms of the broader issue of dominance by a select group of elite scholars (Bal et al., 2024). To understand the root causes of inequality in research, it is crucial to examine the impact of hierarchical disparities on scientific outputs.

The current study offers insights into the issue of overrepresentation, taking authorship inequality to the core, and underscores the need for a critical examination of existing institutional practices and publishing policies that impede fair representation and hinder progress in scientific research. Through empirical exploration and comparative analyses, we provide an examination of authorship dominance in management and organization research. By unpacking the paradigm
of overrepresentation in scholarly publications, our study contributes to a deeper understanding
of this phenomenon.

METHODS

To investigate the phenomenon of authorship inequality, our study employs a quantitative
discovery approach. This approach, which is often used to detect anomalies and unresolved
organizational problems, involves a process of abductive reasoning, and offers a middle ground
between inductive interpretive approaches and the hypothetical-deductive model (Bamberger &
Ang, 2016). We aim to reveal, describe, and diagnose disparities in production by analyzing 42
prominent journals in closely related MOR fields by examining authors’ publication records
from 1960 to 2019.

The quantitative discovery approach allows us to derive insights from our findings,
identify plausible relationships, and offer the best available explanation based on established
community standards of rigor. Our analysis of the data leads to the development of a series of
propositions. In the discussion section, we integrate these propositions with relevant theories,
highlighting their connections to prior theoretical developments and emphasizing the insights
they provide into the phenomenon under study (Bamberger & Ang, 2016). In the conclusion
section, we discuss the implications of our theoretical contributions and offer policy
recommendations.

Data Selection and Extraction

We selected journals from the 2021 Academic Journal Guide from the Chartered
Association of Business Schools (ABS List). Our inclusion criteria targeted journals rated 4*, 4,
and 3 in the fields of General Management, Ethics, Gender, and Social Responsibility (ETHICS-
CSR-MAN), Human Resource Management and Employment Studies (HRM & EMP),
Organisation Studies (ORG STUD), and Psychology-Organizational (PSYCH-WOP-OB). We excluded journals outside our research scope, those with inconsistent ratings below 3 in the last three rankings, and those not classified by the Journal Citation Report (JCR) of Clarivate Analytics. To cross-validate the journal classifications, we re-coded them based on JCR categories and created the list for each of the three fields of examination: HRM, IOP, and MNGT.

Our analysis focused on 42 top-tier journals: 13 from HRM, 15 from MNGT, and 14 from IOP. Data were collected from two primary sources. First, we used the Scopus database for its accurate records of author names and publications (Kawashima & Tomizawa, 2015). We extracted data on researchers who published “articles” and “reviews” in the selected journals between January 1960 and December 2019, excluding editorials, notes, conference papers, letters, and errata. The dataset included 60,034 documents. We analyzed researchers who published at least five papers in one of the three fields, resulting in a sample of 4,825 unique researchers. These researchers were ranked by productivity, labeled anonymously for this study, and the complete dataset is available on the Open Science Framework website<fnref n="2" />.

In addition to Scopus, we used the Web of Science (WoS) to compute historical evolution in inequalities in each field, as Wang and Waltman (2016) reported better journal and document classification accuracy. We identified all authors (N = 51,610) who published “articles” or “reviews” in the selected journals between 1960 and 2019, excluding other document types. Data were also segmented into three time frames: 1960-1979, 1980-1999, and 2000-2019.

<footnote n="2">² https://osf.io/rpbvt/?view_only=017c7afd486d49ce856d455579236517</footnote>
## Gini Coefficient Calculations

The Gini coefficient, ranging from 0 to 1, is calculated to interpret disparities in resource allocations and informs about the concentration of distribution. A Gini coefficient of 0 indicates perfect equality in distribution, 0.5 signals very high inequality, and 1 demonstrates perfect inequality. In light of this information, we used both Scopus and WoS datasets to understand the extent of dominance and how diverse the most productive researchers are in each field. The Scopus dataset was used to compare individual author productivity in each field, and the WoS dataset was used to compare total productivity and historical patterns.

## RESULTS AND FINDINGS

### How Much Space is Allocated by the Top Contributors of Each Field?

Table 1 summarizes the scope of our analyses and presents journal coverage information such as the count of articles, reviews, total count of documents analyzed, starting year of publications included, coverage period, and mean publications per year and per field. Figure 1 presents the publication trends per field. They indicate a rising number of articles published in each field from 1960 to 2019. In 2019, 655 articles were published by 14 IOP journals, 13 HRM journals published 501 articles, and the other 15 MNGT journals covered 823 articles. The current annual journal publications per field averages for HRM, IOP, and MNGT are 38.54, 46.79, and 54.87, respectively.

Table 1 about here

Figure 1 about here
Furthermore, we also compared the productivity of the most productive scholar in each journal separately. Table 2 shows the mean number of publications of each journal's top-10 most productive researchers. *JAP* takes the lead on this with an average of 38.6 published papers by the top-10. *JVB* holds the second position with a mean of 29.5 papers, followed by *LQ* with 24.2 papers. Among MNGT journals, *OrgStud* is in the leading position, with an average of 16.4 papers. In HRM, *IJHRM* is at the front with an average of 20.6 papers. We conducted a Kruskal-Wallis nonparametric ANOVA test to evaluate whether the productivity of the most productive researchers differs by field. Results indicated that the mean publication of top-10 varies significantly based on the discipline. As demonstrated in Figure 2, the mean publication count is found to be significantly higher in IOP journals than in both fields of HRM (*H* = 2.81, *p* = .015) and MNGT (*H* = 3.22, *p* = .004), with the test statistic of *H* = 12.31, *p* = .002. Results reveal that the most productive IOP researchers are significantly more productive than their counterparts publishing in the other two fields. Conversely, it can also be interpreted that top IOP journals allocate significantly more space to elite scholars than leading HRM and MNGT journals.

Table 2 about here

Figure 2 about here

Another primary purpose of this study is to understand the productivity of the most productive and to examine the differences within and between closely related fields. Figure 3
presents the ranking of the most productive researchers with a publication record of over 50 papers in top-tier journals analyzed.

Figure 3 about here

Out of the 4,825 most productive researchers, only 77 of them (1.60%) are found to publish over 50 articles in our analyses. The data show strong evidence that the researchers, who ranked at the top publish predominantly in IOP outlets. Out of these 77 researchers, 58 of them (75.32%) had more than 50% of publications records in IOP journals. Only six researchers in the most productive list (7.79%) did not possess a IOP publication. Researchers who authored over 70 articles (n = 28) recorded in total of 2,501 publication, of which 2,067 (82.65%) appeared in IOP outlets.

## Who Are the Top Contributors of Each Field?

We also provide the list of highly productive researchers publishing the most studies in each field (Table 3). The mean publication count of the top-10 most productive publishing in IOP journals is 95.2. This statistic is found as 51.3 for MNGT and 41.2 for HRM. The top IOP scholar is Researcher1 with 135 unique IOP journal publications. At the bottom of the list, Researcher13 acquired 79 publications. Researcher29 takes first place in the MNGT field with 70 publications, which is less than the record of the 10th most productive researcher of IOP. In HRM, Researcher54 tops the list with 57 publications, which shows a noteworthy disparity.

Table 3 about here
To further compare publication records, we also analyzed the frequency distribution of publication data (Table 4). Among three fields, IOP is the only field that hosts the most productive researchers with a publication record of over 80 papers in their journals. According to this, five researchers accomplished a history of between 81 and 100 papers, and two others published numerous papers between 101 and 120. Finally, the most productive researcher, Researcher1, published 135 papers in IOP journals. Twenty-two researchers published more than 60 articles in IOP journals, whereas this record is shared only by *one* scholar publishing in MNGT journals.

Table 4 about here

To better present the magnitude of inequality among the most prolific researchers in each field, Figure 4 illustrates the Lorenz curves to provide evidence that the concentrated productivity of the most prolific in organizational research. We also calculated Gini coefficients based on the top productive researchers data. Accordingly, IOP is found to be the most unequal among all domains, with Gini = .507. The Gini of MNGT is .459, and that of HRM is .407, as shown in Figure 4.

Figure 4 about here

Journal Level Comparisons

Moreover, we present evidence on the extent of the dominance by the most prolific in each journal. Figures 5-7 provide information about the publication count of the most prolific in
each of the 42 journals analyzed. We color-coded researchers based on the frequency of their appearances as the most productive contributors in their field journals.

As comparative analyses can verify, IOP appears to be dominated by a handful of most productive researchers. The most accomplished researchers of IOP not only published higher numbers of articles, but were also ranked in the list of top researchers in more journals compared to their counterparts in the other two fields. Both Researcher1 and Researcher6 are listed among the top-10 contributors in six field journals in IOP. Other two authors (Researchers7 and 10) are listed in four journals in IOP. In MNGT, five authors (Researchers 29, 56, 61, 214, and 240) are listed among the top contributors of three MNGT journals. In HRM, only two authors (Researcher210 and 244) has appeared in the most productive ten researchers of three separate journals.

Figures 5, 6, 7 about here

Figure 8 summarizes the information presented in the preceding figures for field analyses and presents the authorship concentration. We demonstrate the elite scholars' broader influence spilling over to adjacent fields. Accordingly, Researcher1 is ranked as the top-10 contributor of seven different journals, one MNGT journal (*HumRel*) and six IOP (*JMP*, *EJWOP*, *JVB*, *JOB*, *JOHP*, and *JOOP*), followed by Researcher4, who was found to be dominating in six IOP journals. Again, the majority of journals at the top belong to the IOP field, and the top-10 contributors dominate IOP journals, and *HumRel*, which has a tradition of publishing quantitative, IOP research.
Figure 8 about here

## Historical Trends of Inequalities

The last analysis investigates inequality trends over the past 60 years. Additionally, we shed light on the changes in researchers' productivity concentration, which can inform about the overall status of the fields concerned. We calculated Gini coefficients by taking a 20-year range for each domain to provide a comparative perspective, and we presented inequalities in three fields on three different time windows; 1960-1979, 1980-1999, and 2000-2019. Figure 9 shows the changes in the Gini coefficients in each field in the last 60 years for all three areas. In the last two decades, inequalities have gotten larger in all fields. Between 1960 and 1979, IOP hit a Gini coefficient of .333, which signals relatively adequate equality, but it is still with the highest disparity among all fields; MNGT ($Gini_{MNGT}$ = .146) and HRM ($Gini_{HRM}$ = .109). Authorship inequalities in each domain reached their highest levels between 2000-2019. The Gini coefficients in 2000-2019 for each field are as follows: $Gini_{MNGT}$ = .428, $Gini_{HRM}$ = .391, and $Gini_{IOP}$ = .495. Looking at the indices of all time, the current picture of IOP designates that the field is experiencing severe inequality ($Gini_{IOP}$ = .502) against the other two fields, ($Gini_{HRM}$ = .391) and ($Gini_{MNGT}$ = .453). These figures signal that the top researchers of each field are becoming more influential and dominate the publication sphere. Their research productivity represents more and more portions of entire literature.

Figure 9 about here
To better present the growing dominance of the most productive, we computed what percentage of all studies published in each domain were authored by the most productive 1%, 5%, 10%, and 20% of researchers. Table 5 shows that the top 1% most productive authored 12.6% of all studies published in IOP between 2000-2019, indicating a steady increase from the previous periods. Between 1980 and 1999, this figure was 9.8% and 7.4% in 1960-1979. The top 1% of HRM authored 11.2% of research in 2000-2019, a steep increase from the previous period, as this figure was only 6.9% of all HRM publications in 1980-1999. On the other hand, in MNGT, the top 1%’s share has risen from 7.6% to 8.8% of all publications from 1980-1999 to 2000-2019. The rising inequalities were evident in all segments of top researchers. For instance, each field’s top 10% of researchers authored 45.5% of all research in IOP, 39.3% of HRM, and 38.3% of MNGT publications. All these figures confirm that the share of publications by the bottom researchers declined in all fields. Due to the rising competition and immense influence of the most productive researchers, authorship equalities have deteriorated in all fields in the last 20 years. Figure 10 zooms into the historical trends of publication share taken by the top 1%, 5%, 10%, and 20%. Across all fields, top publication shares have risen since the 1960s. Among these three fields, the share was the largest in IOP for all top segments.

---------------------------------
Table 5 about here
---------------------------------

---

Figure 10 about here

---------------------------------
Finally, Table 5 also compares the total number of studies published, the number of researchers, and the average output per researcher in each time window for each field. Accordingly, between 2000 and 2019, the number of researchers publishing in IOP reached 14,782, with 36,071 total publications. The mean number of publications per researcher is 2.44 (SD = 4.10). During the same period, 23,085 papers from 11,730 researchers were published in HRM (M = 1.97, SD = 2.86), and 27,092 papers of 12,722 researchers in MNGT journals (M = 2.13, SD = 2.57). We conducted an ANOVA test to test whether the average number of publications per researcher is statistically different in each field. Results confirmed that the mean publication per researcher in IOP is statistically higher than those published in both fields, F(2, 25832.11) = 60.88, p = .000). Even though more research is published in IOP by more researchers, it is noteworthy to highlight that the publication concentration is getting in fewer hands.

Ultimately, historical patterns and presented statistics establish that authorship inequalities have become more concerning for all fields. Among the three fields, IOP offers the most worrisome picture with historically high and growing inequalities, increasing dominance of the most productive researchers, and ever-increasing publication counts that are unevenly distributed.

## Network Analyses

Lastly, to better understand the productivity differentials, it is also useful to analyze the network analyses of each field. The top most connected 50 authors are analyzed in this context. The networks are depicted in Figure 11. IOP tends to show higher network density compared to HRM and MNGT, particularly in the early periods (1960-1979). This suggests that in IOP, a higher proportion of potential co-authorship connections were realized earlier on, indicating that
IOP authors were more collaborative as a community, even in the early stages. In HRM and MNGT, density decreases over time as the field grows larger, which is a natural trend as more authors enter the network. However, in IOP, the density is relatively stable, which suggests a continued strong culture of collaboration across authors. IOP has a consistently high average degree, particularly from 1980 onwards, indicating that authors in IOP tend to work with a larger number of co-authors on average compared to HRM and MNGT. The clustering in IOP is significantly higher than in HRM and MNGT, particularly from 2000 onwards. A higher clustering means that co-authors of an author are more likely to collaborate with each other, forming tight-knit research groups. This trend suggests that IOP authors tend to collaborate within smaller, more interconnected groups, which could be a reflection of the specialized nature of psychological research, where niche areas may involve smaller, highly collaborative teams.

Finally, IOP consistently shows a large giant component, particularly from 1980 onwards. This indicates that a large portion of IOP authors are part of the “same connected network,” reflecting a highly collaborative field where even smaller groups are connected to the broader network.

The comparison of network centrality measures across IOP, HRM, and MNGT reveals evolving roles of these fields over time (see Figure 12). IOP shows a consistent increase in both degree and closeness centrality, indicating its growing connectivity and accessibility within the network, while maintaining a stable level of influence through eigenvector centrality. HRM, starting from a lower base, experiences significant growth in both degree and closeness centrality, catching up with IOP by 2000-2019, signaling its increasing prominence. However, both fields exhibit a decline in betweenness centrality after a peak in the 1980-1999 period, suggesting a diminished role in bridging network gaps. MNGT, despite starting with high levels across all centrality measures, shows less change over time, suggesting sustained influence but
limited growth in connectivity compared to IOP and HRM. Overall, IOP and HRM have become
more central to their networks over time, while MNGT has maintained a steady but prominent
position.

Figure 11 about here

Figure 12 about here

DISCUSSIONS

It is important to acknowledge that variations in research productivity among researchers
are to be expected to some extent. Theoretical and empirical evidence suggests that individual
performance follows a power-law distribution (O'Boyle & Aguinis, 2012), offering that it is
natural for a small proportion of researchers to contribute the majority of research output. Recent
observations also indicate a trend of accelerating publication records and accumulating citations
at disproportionate rates (Larivière & Costas, 2016; Nielsen & Andersen, 2021). Bal (2021)
argued that highly productive researchers in the field of organizational research publish an
average of more than 25 papers per year, equivalent to one paper every two weeks. However, the
emphasis on quantity by elite researchers raises concerns about the sustainability of the academic
publication system. Given that many senior academics already hold secure, tenured positions and
are less dependent on journal publications for career advancement, the current publication
system may no longer operate on a level playing field. This creates unfair competition, as
established scholars tend to outperform ECRs who face the precarious nature of contemporary academia and strive to secure permanent positions. Furthermore, elite academics often occupy significant journal space, reducing the opportunities for ECRs and potentially making them reliant on collaborations through co-authorship (Cohen & Baruch, 2022; Kwok, 2005). These observations underscore the need to address the imbalances within the academic publishing landscape. In the absence of evaluation of the unequal distribution of power and resources, efforts to increase variety alone will remain insufficient to create truly equitable and inclusive environments.

In this paper, we illustrate authorship inequality and the extent of elite dominance in organizational research, focusing on the *three* categorically distinct but closely related fields. Based on comparative analyses of authorship trends in 42 leading journals of IOP, MNGT, and HRM, we uncovered compelling evidence that (1) authorship inequality has been rising in the last six decades across all fields, and it is reaching alarming levels that threaten the sustainability of academic careers in organizational research. Especially, IOP has been grappling with issues of inequality since its inception and continues to do so. To illustrate the gravity of the situation, it is worth noting that the present authorship disparity in IOP resembles the income inequality distribution in Angola, a nation plagued by poverty and corruption for many years. Moreover, our findings also indicate that (2) IOP journals allocate significantly more space to the most productive authors than two other fields' journals, (3) the super-elite scholars of IOP do not only publish more articles on average than their counterparts in neighboring fields, but they also dominate journals to a greater extent, as we observe a higher frequency of the same authors on the top-10 most productive list in IOP than in the other two fields, and (4) the most productive
IOP scholars are more conservative in their publication venue choices. These findings have significant implications for practice, theory, and policy design.

Despite the growth in the number of scholars engaged in organizational research over the past few decades, the landscape has witnessed a concerning trend: the concentration of journal publications among a select few. This phenomenon is occurring alongside the escalation of global competition, as evidenced by the skyrocketing rejection rates experienced by researchers. This concentration of journal publications in the hands of a limited number of individuals raises important questions about the fairness and inclusivity of the academic publishing system. In addition, although not directly presented in this study, we observed that the most productive scholars share a common set of demographic characteristics such as age (mostly senior), gender (almost always male), and race (almost always white, Western), which rule journal space disproportionately. These findings complement the previous findings of Bajwa and König (2019), and Lin and Li (2023). In summary, our results indicate organizational research journals, especially top IOP journals, are under the control of a smaller number of scholars who publish significantly more articles than their counterparts active in the fields of HRM and MNGT.

Furthermore, our analysis reveals a noteworthy trend of hyperspecialization among dominant authors in the field of IOP. These authors exhibit a distinct pattern of maintaining high levels of productivity by exclusively publishing their work in IOP outlets. This finding aligns with the research of Ryan and Ford (2010), who also highlight the highly specialized nature of IOP scholars. These researchers demonstrate a strong preference for focusing on topics within the realm of IOP and display resistance to publishing in areas outside their specific field. The strategic decision of IOP scholars to concentrate their efforts within their chosen domain is a career-oriented approach that has been shown to yield higher levels of productivity, as supported
by the findings of Leahey et al. (2017). Their findings suggest that individuals who primarily
publish within a single field tend to be more productive than those who diversify their
publication domains. Consequently, the concentration of certain topics and methodologies
among dominant IOP authors may be a deliberate choice driven by a focus on *quantity* and
*productivity*. Researchers within the IOP field may exhibit reluctance to explore topics that carry
uncertain outcomes. This can be attributed to the perception that flagship journals, which are
very influential in the field, tend to favor more conservative choices regarding topics and
methodologies. As a result, researchers may opt for safer and more predictable research areas to
increase their chances of publication in these prestigious outlets. These observations shed light
on the strategic behaviors adopted by dominant authors in the field of IOP and provide insights
into the potential reasons behind their hyperspecialization and publication choices. It is essential
to further explore the implications of these patterns on the diversity and breadth of research
within the field, as well as their impact on the overall advancement of knowledge in
organizational research.

In the context of network analyses, the increasing centrality of IOP across various
network measures reflects its growing influence and prominence, closely linked to the
phenomenon of academic overproduction. The steady rise in degree and closeness centrality
indicates that IOP has expanded its connections and become more central within the academic
network, likely driven by the pressure to produce more research outputs. Overproduction pushes
scholars to collaborate more, publish frequently, and engage with emerging trends, leading to
IOP's enhanced accessibility and presence in academic discussions. However, as the field grows
and becomes more interconnected, the saturation of publications can dilute the novelty and
impact of individual research contributions.
IOP's stable Eigenvector centrality suggests its influence within key academic circles, but the decline in betweenness centrality points to a more crowded and less distinct role as an intermediary, a potential side effect of overproduction. With many researchers now working on similar topics, IOP's ability to bridge disconnected areas has diminished. Institutional pressures to publish and the increasing relevance of IOP in addressing organizational challenges have likely fueled this rise, positioning IOP as a central field in academia, but also exposing it to the risks and challenges associated with the overproduction of research.

Some of our results are inconclusive as more complex dynamics play a role in growing inequalities, and there might be legitimate reasons why some scholars might be more productive in some fields than others. Yet, our comparative analyses elucidate some crucial findings on the structural problems accumulating over decades. Reducing inequalities is one of the primary goals for scientific and societal development. The debates around academic inequalities related to race, gender, sexual orientation, religion, and social class are lively. Yet, when the intellectual space evolves to be more hegemonic over time, reducing systemic inequalities requires more succinct structural and institutional actions. By taking up a significant proportion of journal space, the most productive, elite academics keep outcompeting ECRs (and researchers in less privileged positions), who unfairly compete for the same outlets with limited resources. There are some vital takeaways for established scholars and editors to ensure equality and eliminate unfair competition at systemic and institutional levels.

The pressure to publish is an undeniable reality in academia, but the prevailing discourse on “publishing like a machine” has reached a point of absurdity in contemporary academic culture. As pointed out by Harley (2019, p.293), the glorification of the “heroic workaholic publishing machine” as a role model sets unrealistic expectations for academic careers and
provides flawed examples for early career researchers (ECRs). While dedicated and highly
productive scholars can make significant contributions to their respective fields, the current
organization of science incentivizes researchers to prioritize productivity above all else.

However, this emphasis on hyperproduction becomes problematic when considering the limited
space available in top-tier journals. It is important to note that our research focused exclusively
on these high-ranking journals, and if we were to include other field-specific journals, the
volume of publications by hyperproductive authors would multiply significantly.

The sustainability of this system is a growing concern among many scholars, leading to a
recognition of the need for change in recent years. Researchers have begun questioning the true
meaning and value of publications (Berg & Seeber, 2016; Tourish, 2020), with some expressing
regret over their own history of overproduction and acknowledging its detrimental effects on
scientific progress and academic careers (e.g., Frith, 2020). To ensure the longevity of academic
careers, it is crucial to engage in discussions about the genuine value of “high-impact” journals
and the true significance of publications. An increasing number of ECRs now perceive the
prestige and metrics of journals as more important than the actual content and contribution of
their research (Niles et al., 2020). Consequently, the academic publishing system itself becomes
progressively dysfunctional, eroding trust in the process as resources are disproportionately
allocated to a small, privileged group of individuals (Bal, 2021).

At the same time, the assessment processes of research quality require considerable
revision. Faculty hiring, promotion, and tenure committees, university leadership and
management teams, external research/grant evaluators, and policymakers should recognize that
the congested traffic in journal space is not only caused by rising competition. Elite scholars'
snowballing dominance and their hyperproductive publication patterns lead authorship
inequalities to perpetuate faster. In the current context, top-tier journals reportedly reject up to 95% of the submissions. It is quintessential to start questioning whether this small percentage of accepted studies should equate to high-quality research. Editors often signal selectivity by reporting rejection rates. Still, our analyses imply that it would not be fair to argue that only 5% is good enough and that 95% of the research submitted is below-standard, especially when only certain names keep showing up in the same scholarly domains. Acknowledging the complex nature of publishing in top journals, academic decision-makers should not treat journal names as a proxy for research quality.

Editorial teams have a substantial role in handling submissions more fairly and responsibly. Overall, our journal-level analyses present a depressing picture. Not only did elite scholars' paper production grow over time, but proportionally, the space allocated to them has inflated significantly. Not all these figures imply causality on biases, yet, more transparency about processes will help organizational research improve even further. As researchers are expected to share their data and processes for the sake of openness and transparency, the same should apply to journal editors. Ultimately, we believe there are no visible benefits of keeping submissions non-blind because prestige, hierarchy, and power could alter judgments and evaluations. Our policy recommendation that proposes triple-blind editorial review processes can be a starting point to breaking the hurdle of access and systemic discrimination. Unless editorial teams, reviewers, and authors remain blind throughout the submission process, objectivity can be compromised. Accordingly, we invite editorial teams to open up their operations and publication data, integrate transparency in their decisions, and explicitly commit to concrete action plans outlining how they address growing inequalities.
With this paper, we underline the structural problems that have been growing over decades. At the same time, we problematized the growing authorship inequalities from the overrepresentation angle. Inequality in an academic field, instilled in barriers and systemic practices, contradicts the fundamental scientific ethos and impedes scientific progress. Moreover, toxic overproduction may discourage aspiring individuals from entering academic research because ECRs would subsequently fail to follow the latest scientific findings, which grow exponentially. At the same time, with the dysfunctional publication systems, wrong incentive schemes, and growing inequalities, making scientific contributions will become unattainable for them.

## Sources of overrepresentation and overproduction in research

To establish a theoretical foundation for understanding the problematic nature of scientific inequalities, Mertonian norms provide the necessary grounds for discussion. In his book *The Sociology of Science*, Merton (1973) identified four core imperatives within the scientific ethos that are relevant to the problem we investigated in this paper: *universalism*, *communality*, *disinterestedness*, and *organized skepticism*. Universalism pertains to the evaluation of claims based solely on their validity, regardless of their source. Personal and social characteristics should be disregarded when assessing the merit of scientific arguments. Similarly, the *communality* principle argues for the freedom of science and scientific institutions from ownership and dominance. Mechanisms that exclude individuals based on their social or membership status, hindering fair access, should be discarded as they undermine scientific progress. The principle of *disinterestedness* emphasizes that scholars should primarily engage in scholarly activities driven by intellectual curiosity and a pursuit of knowledge that benefits science as a whole, rather than being motivated solely by personal gain and self-interest.
However, many activities within the current scientific landscape often contradict these norms, as the competitive nature of academia pushes individuals to conduct research for self-interest.

Network connections, group affiliations, and prestige can significantly impact resource access, making objective evaluations practically unachievable (cf. Huber et al., 2022). As a result, growing inequalities are a direct outcome of a system that has long neglected the fundamental principles of scientific norms. Lastly, the concept that no practice should be taken for granted forms the basis of *organized skepticism*. Within academia, there is a strong emphasis on individual achievements and rewards, often overemphasizing productivity. Young scholars and early-career researchers often believe that success in academia is solely determined by meritocracy (Knights & Richards, 2003; Śliwa & Johansson, 2014; Zivony, 2019).

Consequently, disparities in productivity are regarded as natural, while discussions on the true implications of overproduction and the consequences of intellectual hegemony are rarely held. In the current neoliberal academic system, most of these norms are violated, causing a toxic competition that prioritizes quantity over quality (Orhan et al., 2024).

Elite scholars' dominance leads to overrepresentation in scholarship in many ways. They are often old, white, male researchers from the Western world, enjoying a privileged position and fame gained primarily through their past research productivity in scholarly journals from the Western world. These researchers frequently occupy gatekeeper roles in academic publishing, imposing control over ontological, methodological, and epistemological approaches in research (Bal & Dóci, 2018; Dóci & Bal, 2018; Lewis, 2022). The hypercompetitive environment of academia exacerbates this issue, as top journals seek submissions from elite scholars and well-recognized institutions, further entrenching their dominance (Nielsen & Andersen, 2021).
Along the same line, the hypercompetitive environment fueled by existing forces (i.e., institutions, publishers, rankings, etc.) sets norms and expectations for continuous production. Overproduction is rewarded in the current system, and many ECRs wish to collaborate with elite to overcome the publish-or-perish barrier. Brogaard et al. (2020) found that articles co-authored with well-known, established researchers receive significantly more citations regardless of the quality of the articles. In parallel, it is highly desirable for ECRs to publish in high-impact journals, since they attract more citations (Traag, 2021). Another reason why one should publish in top journals at early stages is that the number of publications in high-impact journals is the strongest predictor of landing an academic job (Vuletich et al., 2019). Therefore, many ECRs are often dependent on established scholars. This gerontocratic privilege further allows elite scholars to keep occupying a disproportionate space, while at the same time controlling access through network power and/or editorial roles. The issue of diversity in academic research can be viewed as a complex matter because those who are new to the field (or work with relatively less known scholars) struggle and fight to get their work seen, accepted, read, and cited, while elite scholars (or the ones connected to them) often have an easier time getting their work published (Bal, 2021). In light of Mertonian norms and how they violated in the current publishing system, we theorize that three major pillars lead to toxic overproduction: (1) collaboration, network effect, and power structures, (2) editorial conservatism and favoritism, (3) gamification of publications and career obsession.

***Collaboration, network effect, & power structures***

The proportion of single-authored papers has been declining remarkably, as most publications have come from teams of researchers in the last decades (Abramo et al., 2019). Technological advancements have facilitated larger networks of researchers, resulting in an
increase in the average number of authors per article and a growing list of publications on researchers' resumés.

Established scholars often have strong connections to influential researchers in their field, which can provide long-term advantages for career advancement. Colussi (2018) found that senior researchers who become editors of leading journals tend to have productive social connections, including their doctoral students and colleagues, who often publish a greater number of articles. While it can be argued that these increased levels of productivity are not necessarily biased, it's important to acknowledge that power dynamics and political considerations can influence editorial decisions. Some editors may adjust their evaluation standards based on power imbalances, as rejecting a more powerful and well-connected senior scholar could have different consequences than rejecting an unfamiliar early-career researcher. Nevertheless, editors in influential positions often possess a deeper understanding of current trends and research directions in their field, allowing them to provide valuable guidance to their collaborators.

The dynamics of power and relational networks significantly impact researchers' success. Heffernan (2021) emphasized the advantages gained by elite researchers through access to resources and opportunities that are not publicly advertised. These individuals hold considerable power in academia, with their students, early-career researchers, and collaborators reinforcing their position. Collaborations can be mutually beneficial, but established researchers may use their position to form alliances that strengthen their ideas and bolster their influence. However, the potential for established scholars to exert coercive power over early-career researchers and doctoral students raises concerns about power abuse and exploitative practices. Such practices can perpetuate the dominance of established researchers and leave less influential collaborators
dependent on them (Cohen & Baruch, 2022; Täuber & Mahmoudi, 2022). Additionally, some researchers engage in gift authorship and publication parasitism, where they receive credit for research contributions without making substantial contributions themselves (Greenland & Fontanarosa, 2012; Ioannidis, 2014; Kwok, 2005). These practices contribute to undeserved overproduction.

***Editorial favoritism and risk aversion in scholarly publishing***

The editorial processes of academic journals play a pivotal role in shaping the diversity of published research, often influencing whose work is accepted and what ideas gain prominence. While peer-review is designed to minimize bias, editors remain the primary gatekeepers, controlling which submissions advance to review and ultimately get published. In competitive journal markets, editors may favor submissions from well-known authors or prestigious institutions to maintain the perceived quality and reputation of their journals. This tendency can lead to editorial conservatism, favoritism, and even implicit cronyism, as previous research has shown (Colussi, 2018). Such preferences contribute to an imbalance, where elite scholars are granted disproportionate space in publications, while emerging voices are marginalized.

Editors also play a crucial role in amplifying the visibility of established researchers, often granting them easier and faster review processes. This not only consolidates the power of elite scholars but can also transform legitimate journals into platforms serving self-promotion (Scanff et al., 2021). The preferential treatment of prominent researchers reinforces the hyperproduction of their work, while newer or controversial research struggles to break through editorial gatekeeping.

Moreover, most journals are operated by commercial enterprises that prioritize exclusivity and impose arbitrary limits on the publication space. To remain competitive in terms
of citations, readership, and subscriptions, editors may favor well-known authors, whose work is
likely to garner citations irrespective of the research's quality (Brogaard et al., 2014). As a result,
despite the steady increase in article submissions, rejection rates continue to rise, exacerbating
the bias against lesser-known or innovative scholars.

The prestige of many top-tier journals is often tied to their long-established reputations. However, as these journals age, editors tend to become more risk-averse, particularly when handling emerging or unconventional research problems. Petersen (2017) found that this risk aversion leads editors to favor work that aligns with the status quo, systematically excluding new, innovative, or controversial perspectives. This behavior entrenches established ideas and topics, while stifling the exploration of fresh, potentially groundbreaking approaches.

Consequently, the editorial processes of leading journals can inadvertently perpetuate intellectual conservatism and hinder the advancement of new ideas.

*Gamification of publications and career obsession*

The intense competition for academic publications has led to a proliferation of research, raising concerns about the quality and value of this output (Edwards & Roy, 2017; Kepes et al., 2022; Orhan, 2020). The current system often prioritizes the quantity of publications over their quality, as exemplified by the rise of hyperproductive researchers (Ioannidis et al., 2018). Even though Ioannidis and colleagues did not specifically cover social sciences in their analysis, this issue is pertinent to many domains as the global competition intensifies.

Under intense pressure, researchers may adopt strategies to maximize their publication success, such as specializing in narrow research areas that offer incremental findings. This trend leads to redundant publications, self-plagiarism, and the crowding out of diverse perspectives (Horbach & Halffman, 2019; Orhan, 2021). The dominance of elite scholars in prestigious
journals exacerbates this issue, limiting innovation and diminishing the impact of new theories despite rising publication rates (Park et al., 2023).

Publication pressure often leads to negative experiences such as constant rejection and burnout affecting the well-being and mental health of academics, making academic careers increasingly precarious (Jaremka et al., 2020). Fierce competition has led to a rise in deviant behaviors, including questionable research practices, gaming metrics, obsession with quantity, and opportunistic publishing (Ioannidis et al., 2018; Kepes et al., 2022). These factors diminish trust in academic institutions, especially among early career researchers (ECRs) who face tougher competition. A study by van Dalen (2021) revealed that ECRs view publication pressure as detrimental to both their careers and scientific progress, a sentiment not necessarily shared by more senior scholars. This discrepancy highlights how the elite, as survivors of the system, support its competitive nature. Just as poverty traps the majority in unequal societies, precarious conditions trap ECRs and many others in academia, while the elite enjoy their privileged positions. As Merton (1968, p.57) argued: "Eminent scientists get disproportionately great credit for their contributions to science while relatively unknown scientists tend to get disproportionately little credit for comparable contributions." Consequently, established researchers often achieve greater long-term productivity, leading to more citations and resources that further accelerate their productivity (Bosquet & Combes, 2013; Nielsen & Andersen, 2021). This unequal representation in academia affects individuals, teams, institutions, and the advancement of science, benefiting only a small fraction of well-connected, privileged academics under the current publication system (Krauss et al., 2023). Our study aims to shed light on publication inequality and the dominance of elite scholars in management and
organizational research, comparing historical trends of overrepresentation and theorizing the
sources of this imbalance.

Limitations

Our study faced several limitations, notably the incomplete coverage of databases we
relied on. Specifically, several prominent journals, such as the *British Journal of Industrial
Relations* and the *Academy of Management Journal*, had missing years in the Scopus database,
which may have influenced the comprehensiveness of our results. Therefore, actual productivity
of elite researchers could be also understated. However, this does not change the overall
conclusion of our findings. The full list of missing years in coverages are provided in the
Appendix. Additionally, while the study analyzed publications from 1960 to 2019, the coverage
of some journals was partial, and the starting dates varied. This underrepresentation of certain
years may have affected the accuracy of long-term trends in our analysis. Another limitation of
our study is the potential conflation of productivity and tenure. Since we count cumulative
publications, older researchers will naturally appear more productive due to their longer careers,
regardless of the fairness of the publication process. While younger researchers may eventually
surpass current elites, our focus remains on the dominance of established scholars and their
disproportionate influence in the academic space. Moreover, our method for analyzing growing
inequalities was based on full counting of each researcher's output, where we considered each
publication equally without adjusting for co-authorship or collaborative works. This approach
did not account for fractional counting, which could provide a more precise analysis of how
much academic space is occupied by top researchers. Given that leading researchers often
collaborate extensively, future studies should explore fractional counting to better understand the
distribution of authorship and the extent of influence exerted by top researchers in the field.
Concluding remarks

In closing, efforts to promote DEI are futile unless the essence of the underrepresentation problem is well-understood. Instead of offering an oversimplified solutions that tackle statistical adjustments to underrepresentation, we aim to draw the attention to the ever-increasing dominance of the scholarly elite as a substantial barrier in the intellectual space. While the efforts for decolonization of business school education and curricula are also gaining momentum, it is essential to examine the ways how scientific communications evolve and how research is evaluated may require a fundamental transformation for such efforts being undertaken.

We acknowledge that this study might trigger a certain level of tension, especially among elite scholars and researchers holding key positions such as editorial roles. Nonetheless, we intend to underline the systemic problems, offer recommendations, and discuss the potential solutions to improve scientific practices. Systemic exclusion of certain groups of researchers not only makes access to science more restrictive but also hinders the future of scientific progress and societal development, which, in turn, further perpetuates inequalities in academia (Tilghman et al., 2021). We hope that some concrete actions to be taken by key stakeholders to reevaluate the existing scholarly mechanisms to rectify policies and procedures that act as barriers. With this paper, we also invite researchers from other fields to examine the degree of inequality in their constituencies to initiate fruitful debates with relevant bodies and respective institutions.
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<table><caption>Table 1. List of Journals Analyzed</caption><thead><tr><th>Title</th><th>Acronym</th><th>ABS Rating (2021)</th><th>Count of Articles</th><th>Count of Reviews</th><th>Total Docs</th><th>Scopus Data from</th><th>Average Output per Year</th></tr></thead><tbody><tr><td>Human Resource Management Journal</td><td>HRMJ</td><td>4*</td><td>713</td><td>35</td><td>748</td><td>1990*</td><td>24.93</td></tr><tr><td>British Journal of Industrial Relations</td><td>BJIR</td><td>4</td><td>1,239</td><td>98</td><td>1,337</td><td>1963†</td><td>23.46</td></tr><tr><td>Human Resource Management</td><td>HRM</td><td>4</td><td>1,643</td><td>82</td><td>1,725</td><td>1961*</td><td>29.24</td></tr><tr><td>Industrial Relations: A Journal of Economy and Society</td><td>IR</td><td>4</td><td>1,588</td><td>10</td><td>1,598</td><td>1961*</td><td>27.08</td></tr><tr><td>Work, Employment and Society</td><td>WES</td><td>4</td><td>1,182</td><td>236</td><td>1,418</td><td>1987*</td><td>42.97</td></tr><tr><td>Economic and Industrial Democracy</td><td>EID</td><td>3</td><td>967</td><td>315</td><td>1,282</td><td>1980*</td><td>32.05</td></tr><tr><td>European Journal of Industrial Relations</td><td>EJIR</td><td>3</td><td>422</td><td>67</td><td>489</td><td>1995*</td><td>19.56</td></tr><tr><td>Human Resource Management Review</td><td>HRMR</td><td>3</td><td>722</td><td>11</td><td>733</td><td>1991*</td><td>25.28</td></tr><tr><td>Industrial and Labor Relations Review</td><td>ILRR</td><td>3</td><td>664</td><td>144</td><td>808</td><td>1978‡</td><td>19.24</td></tr><tr><td>Industrial Law Journal</td><td>ILJ</td><td>3</td><td>1,009</td><td>28</td><td>1,037</td><td>1972*</td><td>21.60</td></tr><tr><td>International Journal of Human Resource Management</td><td>IJHRM</td><td>3</td><td>2,872</td><td>66</td><td>2,938</td><td>1990*</td><td>97.93</td></tr><tr><td>New Technology, Work and Employment</td><td>NTWE</td><td>3</td><td>495</td><td>11</td><td>506</td><td>1986*</td><td>14.88</td></tr><tr><td>Work and Occupations</td><td>W&O</td><td>3</td><td>729</td><td>66</td><td>795</td><td>1974*</td><td>17.28</td></tr><tr><td><strong>HRM TOTAL (n = 13)</strong></td><td></td><td></td><td><strong>14,245</strong></td><td><strong>1,169</strong></td><td><strong>15,414</strong></td><td></td><td></td></tr><tr><td>Academy of Management Journal</td><td>AMJ</td><td>4*</td><td>1,505</td><td>217</td><td>1,722</td><td>1975‡</td><td>38.27</td></tr><tr><td>Academy of Management Review</td><td>AMR</td><td>4*</td><td>635</td><td>322</td><td>957</td><td>1978‡</td><td>22.79</td></tr><tr><td>Administrative Science Quarterly</td><td>ASQ</td><td>4*</td><td>496</td><td>49</td><td>545</td><td>1975‡</td><td>12.11</td></tr><tr><td>Journal of Management</td><td>JoM</td><td>4*</td><td>1,789</td><td>141</td><td>1,930</td><td>1975*</td><td>42.89</td></tr><tr><td>Organization Science</td><td>OrgSci</td><td>4*</td><td>1,422</td><td>80</td><td>1,502</td><td>1996*</td><td>62.58</td></tr><tr><td>Human Relations</td><td>HumRel</td><td>4</td><td>3,331</td><td>142</td><td>3,473</td><td>1960*</td><td>57.88</td></tr><tr><td>Journal of Management Studies</td><td>JMS</td><td>4</td><td>1,963</td><td>160</td><td>2,123</td><td>1964*</td><td>37.91</td></tr><tr><td>Organization Studies</td><td>OrgStud</td><td>4</td><td>1,774</td><td>192</td><td>1,966</td><td>1980*</td><td>49.15</td></tr><tr><td>Academy of Management Perspectives</td><td>AMP</td><td>3</td><td>228</td><td>97</td><td>325</td><td>2006*</td><td>23.21</td></tr><tr><td>British Journal of Management</td><td>BJM</td><td>3</td><td>1,032</td><td>48</td><td>1,080</td><td>1990*</td><td>36.00</td></tr><tr><td>California Management Review</td><td>CMR</td><td>3</td><td>1,475</td><td>235</td><td>1,710</td><td>1970*</td><td>34.20</td></tr><tr><td>European Management Review</td><td>EMR</td><td>3</td><td>234</td><td>14</td><td>248</td><td>2009*</td><td>22.55</td></tr><tr><td>International Journal of Management Reviews</td><td>IJMR</td><td>3</td><td>323</td><td>79</td><td>402</td><td>1999‡</td><td>19.14</td></tr><tr><td>Journal of Management Inquiry</td><td>JMI</td><td>3</td><td>924</td><td>232</td><td>1,156</td><td>1992*</td><td>41.29</td></tr><tr><td>Organization</td><td>Org</td><td>3</td><td>908</td><td>176</td><td>1,084</td><td>1994*</td><td>41.69</td></tr><tr><td><strong>MNGT TOTAL (n = 15)</strong></td><td></td><td></td><td><strong>18,039</strong></td><td><strong>2,184</strong></td><td><strong>20,223</strong></td><td></td><td></td></tr><tr><td>Journal of Applied Psychology</td><td>JAP</td><td>4*</td><td>5,728</td><td>111</td><td>5,839</td><td>1960*</td><td>97.32</td></tr><tr><td>Personnel Psychology</td><td>PPsych</td><td>4*</td><td>1,854</td><td>58</td><td>1,912</td><td>1960*</td><td>31.87</td></tr><tr><td>Journal of Occupational and Organizational Psychology</td><td>JOOP</td><td>4</td><td>1,363</td><td>62</td><td>1,425</td><td>1975*</td><td>31.67</td></tr><tr><td>Journal of Occupational Health Psychology</td><td>JOHP</td><td>4</td><td>774</td><td>39</td><td>813</td><td>1996*</td><td>33.88</td></tr><tr><td>Journal of Organizational Behavior</td><td>JOB</td><td>4</td><td>1,764</td><td>135</td><td>1,899</td><td>1981‡</td><td>48.69</td></tr><tr><td>Journal of Vocational Behavior</td><td>JVB</td><td>4</td><td>2,971</td><td>80</td><td>3,051</td><td>1971*</td><td>62.27</td></tr><tr><td>Leadership Quarterly</td><td>LQ</td><td>4</td><td>1,123</td><td>67</td><td>1,190</td><td>1990*</td><td>39.67</td></tr><tr><td>Organizational Behavior and Human Decision Processes</td><td>OBHDP</td><td>4</td><td>1,888</td><td>29</td><td>1,917</td><td>1985*</td><td>54.77</td></tr><tr><td>Applied Psychology: An International Review</td><td>AP:IR</td><td>3</td><td>1,599</td><td>104</td><td>1,703</td><td>1961*</td><td>28.86</td></tr><tr><td>European Journal of Work and Organizational Psychology</td><td>EJWOP</td><td>3</td><td>631</td><td>10</td><td>641</td><td>2005*</td><td>42.73</td></tr><tr><td>Group and Organization Management</td><td>GOM</td><td>3</td><td>1,184</td><td>45</td><td>1,229</td><td>1976*</td><td>27.93</td></tr><tr><td>Human Performance</td><td>HumPerf</td><td>3</td><td>524</td><td>60</td><td>584</td><td>1988*</td><td>18.25</td></tr><tr><td>Journal of Managerial Psychology</td><td>JMP</td><td>3</td><td>1,241</td><td>115</td><td>1,356</td><td>1986*</td><td>39.88</td></tr><tr><td>Work and Stress</td><td>W&S</td><td>3</td><td>804</td><td>34</td><td>838</td><td>1987*</td><td>25.39</td></tr><tr><td><strong>IOP TOTAL (n = 14)</strong></td><td></td><td></td><td><strong>23,448</strong></td><td><strong>949</strong></td><td><strong>24,397</strong></td><td></td><td></td></tr><tr><td><strong>TOTAL (n = 42)</strong></td><td></td><td></td><td><strong>55,732</strong></td><td><strong>4,302</strong></td><td><strong>60,034</strong></td><td></td><td></td></tr></tbody></table>

Note: †Full coverage; ‡Partial coverage with some missing years
<table><caption>Table 2. Average Publication Count of Top-10 Most Productive Researchers of Journals</caption><thead><tr><th colspan="2">IOP</th><th colspan="2">HRM</th><th colspan="2">MNGT</th></tr><tr><th>Journal</th><th>Avg</th><th>Journal</th><th>Avg</th><th>Journal</th><th>Avg</th></tr></thead><tbody><tr><td>JAP</td><td>38.6</td><td>IJHRM</td><td>20.6</td><td>OrgStud</td><td>16.4</td></tr><tr><td>JVB</td><td>29.5</td><td>ILJ</td><td>17.6</td><td>AMJ</td><td>15.4</td></tr><tr><td>LQ</td><td>24.2</td><td>BJIR</td><td>11.4</td><td>JoM</td><td>13.9</td></tr><tr><td>PPsych</td><td>19.7</td><td>IR</td><td>11.3</td><td>HumRel</td><td>13.4</td></tr><tr><td>OBHDP</td><td>19.2</td><td>HRM</td><td>11</td><td>JMS</td><td>12.1</td></tr><tr><td>W&S</td><td>16.8</td><td>HRMJ</td><td>9.6</td><td>CMR</td><td>11</td></tr><tr><td>JOB</td><td>15.7</td><td>WES</td><td>9.4</td><td>OrgSci</td><td>9.6</td></tr><tr><td>GOM</td><td>15.3</td><td>EID</td><td>9.3</td><td>Org</td><td>9.2</td></tr><tr><td>JOHP</td><td>13.7</td><td>HRMR</td><td>9.3</td><td>ASQ</td><td>8</td></tr><tr><td>JOOP</td><td>11.7</td><td>W&O</td><td>8</td><td>JMI</td><td>7.8</td></tr><tr><td>EJWOP</td><td>11.7</td><td>ILRR</td><td>7</td><td>BJM</td><td>7.6</td></tr><tr><td>JMP</td><td>11.5</td><td>EJIR</td><td>6.5</td><td>AMR</td><td>6.8</td></tr><tr><td>AP:IR</td><td>9.7</td><td>NTWE</td><td>5.9</td><td>AMP</td><td>6.2</td></tr><tr><td>HumPerf</td><td>8.3</td><td></td><td></td><td>IJMR</td><td>4</td></tr><tr><td></td><td></td><td></td><td></td><td>EMR</td><td>2.9</td></tr></tbody><tfoot><tr><td>Mean</td><td>17.54</td><td>10.53</td><td></td><td></td><td>9.62</td></tr><tr><td>(SD)</td><td>(8.38)</td><td>(4.23)</td><td></td><td></td><td>(4.02)</td></tr></tfoot></table>
<table><caption>Table 3. Top-10 Most Productive Researchers in Each Field and Publication Counts</caption><thead><tr><th rowspan="2">Rank</th><th colspan="2">IOP</th><th colspan="2">MNGT</th><th colspan="2">HRM</th></tr><tr><th>Top Publisher in the Field</th><th>Publication Count in IOP Journals</th><th>Top Publisher in the Field</th><th>Publication Count in MNGT Journals</th><th>Top Publisher in the Field</th><th>Publication Count in HRM Journals</th></tr></thead><tbody><tr><td>1</td><td>Researcher1 (156)</td><td>135</td><td>Researcher29 (70)</td><td>70</td><td>Researcher53 (57)</td><td>54</td></tr><tr><td>2</td><td>Researcher3 (130)</td><td>108</td><td>Researcher36 (63)</td><td>57</td><td>Researcher30 (68)</td><td>47</td></tr><tr><td>3</td><td>Researcher4 (112)</td><td>103</td><td>Researcher56 (56)</td><td>54</td><td>Researcher50 (57)</td><td>46</td></tr><tr><td>4</td><td>Researcher8 (94)</td><td>92</td><td>Researcher67 (52)</td><td>52</td><td>Researcher51 (57)</td><td>46</td></tr><tr><td>5</td><td>Researcher7 (95)</td><td>89</td><td>Researcher85 (49)</td><td>49</td><td>Researcher104 (46)</td><td>41</td></tr><tr><td>6</td><td>Researcher2 (138)</td><td>85</td><td>Researcher70 (52)</td><td>48</td><td>Researcher158 (39)</td><td>38</td></tr><tr><td>7</td><td>Researcher9 (90)</td><td>83</td><td>Researcher86 (49)</td><td>48</td><td>Researcher64 (53)</td><td>37</td></tr><tr><td>8</td><td>Researcher10 (87)</td><td>83</td><td>Researcher61 (54)</td><td>47</td><td>Researcher188 (37)</td><td>35</td></tr><tr><td>9</td><td>Researcher12 (84)</td><td>80</td><td>Researcher109 (45)</td><td>45</td><td>Researcher210 (35)</td><td>35</td></tr><tr><td>10</td><td>Researcher16 (79)</td><td>74</td><td>Researcher76 (51)</td><td>43</td><td>Researcher244 (33)</td><td>33</td></tr></tbody><tfoot><tr><td>Mean (SD)</td><td colspan="2">93.2 (17.95)</td><td colspan="2">51.3 (7.78)</td><td colspan="2">41.2 (6.80)</td></tr></tfoot></table>

Note: The total number of publications in all three fields is stated in parentheses.

<table><caption>Table 4. Frequency Distributions of Researchers' Publication Count</caption><thead><tr><th rowspan="2"></th><th colspan="8">Article Count</th></tr><tr><th>1-4</th><th>5-20</th><th>21-40</th><th>41-60</th><th>61-80</th><th>81-100</th><th>101-120</th><th>over 120</th></tr></thead><tbody><tr><th>HRM</th><td>14,323</td><td>1,034</td><td>54</td><td>5</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><th>MNGT</th><td>16,927</td><td>1,793</td><td>98</td><td>10</td><td>1</td><td>0</td><td>0</td><td>0</td></tr><tr><th>IOP</th><td>22,115</td><td>2,235</td><td>243</td><td>34</td><td>14</td><td>5</td><td>2</td><td>1</td></tr></tbody></table>
<table><caption>Table 5. Historical Trends of Publications Shares</caption><thead><tr><th rowspan="2"></th><th colspan="3">IOP</th><th colspan="3">HRM</th><th colspan="3">MNGT</th></tr><tr><th>2000-2019</th><th>1980-1999</th><th>1960-1979</th><th>2000-2019</th><th>1980-1999</th><th>1960-1979</th><th>2000-2019</th><th>1980-1999</th><th>1960-1979</th></tr></thead><tbody><tr><td>Top 1%</td><td>12.6%</td><td>9.8%</td><td>7.4%</td><td>11.2%</td><td>6.9%</td><td>3.4%</td><td>8.8%</td><td>7.6%</td><td>3.9%</td></tr><tr><td>Top 5%</td><td>32.7%</td><td>27.4%</td><td>22.8%</td><td>27.8%</td><td>20.4%</td><td>11.0%</td><td>25.8%</td><td>23.0%</td><td>13.5%</td></tr><tr><td>Top 10%</td><td>45.5%</td><td>39.2%</td><td>33.7%</td><td>39.3%</td><td>30.8%</td><td>20.2%</td><td>38.3%</td><td>35.1%</td><td>21.9%</td></tr><tr><td>Top 20%</td><td>60.2%</td><td>52.9%</td><td>47.3%</td><td>53.3%</td><td>44.1%</td><td>29.4%</td><td>54.2%</td><td>50.0%</td><td>33.0%</td></tr><tr><td>Total Records</td><td>36,071</td><td>13,336</td><td>3,734</td><td>23,085</td><td>5,234</td><td>327</td><td>27,092</td><td>8,932</td><td>643</td></tr><tr><td># of Researchers</td><td>14,782</td><td>7,048</td><td>2,269</td><td>11,730</td><td>3,470</td><td>288</td><td>12,722</td><td>4,888</td><td>539</td></tr><tr><td>Avg Paper per Researcher</td><td>2.44</td><td>1.89</td><td>1.65</td><td>1.97</td><td>1.51</td><td>1.14</td><td>2.13</td><td>1.83</td><td>1.19</td></tr><tr><td>SD</td><td>4.10</td><td>2.46</td><td>1.64</td><td>2.86</td><td>1.34</td><td>0.44</td><td>2.57</td><td>1.93</td><td>0.58</td></tr></tbody></table>
<figure><img src="image_2.png" /><figcaption>Figure 1. Publication Trends</figcaption></figure>
<figure><img src="image_3.png" /><figcaption>Figure 2. Violin Plot – Comparisons of Average Publication Count of the Top-10 Most Productive Researchers</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>Figure 3. Most Productive Researchers (Publication > 50) and Their Publication</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Figure 4. Lorenz Curves – Field Comparisons</figcaption></figure>
<table><caption>Figure 5. The Most Productive of HRM Journals</caption><thead><tr><th></th><th>HRMJ</th><th>BJIR</th><th>HRM</th><th>IR</th><th>WES</th><th>EID</th><th>EJIR</th></tr></thead><tbody><tr><td>1</td><td>Researcher320</td><td>Researcher1296</td><td>Researcher570</td><td>Researcher779</td><td>Researcher520</td><td>Researcher22</td><td>Researcher188</td></tr><tr><td>2</td><td>Researcher75</td><td>Researcher244</td><td>Researcher1401</td><td>Researcher244</td><td>Researcher461</td><td>Researcher218</td><td>Researcher554</td></tr><tr><td>3</td><td>Researcher434</td><td>Researcher467</td><td>Researcher47</td><td>Researcher502</td><td>Researcher443</td><td>Researcher128</td><td>Researcher311</td></tr><tr><td>4</td><td>Researcher284</td><td>Researcher289</td><td>Researcher104</td><td>Researcher210</td><td>Researcher272</td><td>Researcher3130</td><td>Researcher1102</td></tr><tr><td>5</td><td>Researcher30</td><td>Researcher833</td><td>Researcher6</td><td>Researcher1243</td><td>Researcher51</td><td>Researcher765</td><td>Researcher3260</td></tr><tr><td>6</td><td>Researcher864</td><td>Researcher335</td><td>Researcher112</td><td>Researcher585</td><td>Researcher1514</td><td>Researcher3343</td><td>Researcher662</td></tr><tr><td>7</td><td>Researcher175</td><td>Researcher262</td><td>Researcher2189</td><td>Researcher1873</td><td>Researcher141</td><td>Researcher2817</td><td>Researcher1852</td></tr><tr><td>8</td><td>Researcher282</td><td>Researcher1953</td><td>Researcher2682</td><td>Researcher610</td><td>Researcher2672</td><td>Researcher3630</td><td>Researcher1875</td></tr><tr><td>9</td><td>Researcher1026</td><td>Researcher51</td><td>Researcher468</td><td>Researcher322</td><td>Researcher281</td><td>Researcher3846</td><td>Researcher3855</td></tr><tr><td>10</td><td>Researcher281</td><td>Researcher188</td><td>Researcher146</td><td>Researcher1242</td><td>Researcher335</td><td>Researcher632</td><td>Researcher1747</td></tr></tbody></table><table><thead><tr><th></th><th>HRMR</th><th>ILRR</th><th>ILJ</th><th>IJHRM</th><th>NTWE</th><th>W&O</th></tr></thead><tbody><tr><td>1</td><td>Researcher2</td><td>Researcher585</td><td>Researcher158</td><td>Researcher53</td><td>Researcher443</td><td>Researcher309</td></tr><tr><td>2</td><td>Researcher6</td><td>Researcher665</td><td>Researcher740</td><td>Researcher50</td><td>Researcher496</td><td>Researcher599</td></tr><tr><td>3</td><td>Researcher84</td><td>Researcher210</td><td>Researcher850</td><td>Researcher147</td><td>Researcher1093</td><td>Researcher1216</td></tr><tr><td>4</td><td>Researcher351</td><td>Researcher750</td><td>Researcher972</td><td>Researcher104</td><td>Researcher50</td><td>Researcher529</td></tr><tr><td>5</td><td>Researcher179</td><td>Researcher244</td><td>Researcher967</td><td>Researcher145</td><td>Researcher2043</td><td>Researcher3234</td></tr><tr><td>6</td><td>Researcher74</td><td>Researcher952</td><td>Researcher947</td><td>Researcher369</td><td>Researcher4623</td><td>Researcher3376</td></tr><tr><td>7</td><td>Researcher634</td><td>Researcher962</td><td>Researcher1445</td><td>Researcher30</td><td>Researcher632</td><td>Researcher3194</td></tr><tr><td>8</td><td>Researcher768</td><td>Researcher578</td><td>Researcher1344</td><td>Researcher223</td><td>Researcher5532</td><td>Researcher4761</td></tr><tr><td>9</td><td>Researcher674</td><td>Researcher322</td><td>Researcher1485</td><td>Researcher588</td><td>Researcher4615</td><td>Researcher3817</td></tr><tr><td>10</td><td>Researcher210</td><td>Researcher276</td><td>Researcher1332</td><td>Researcher468</td><td>Researcher631</td><td>Researcher4756</td></tr><tr><td>11</td><td>Researcher147</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table><div><p>3 journals</p><p>2 journals</p><p>Researcher210 Researcher281</p><p>Researcher244 Researcher322</p><p>Researcher30 Researcher335</p><p>Researcher50 Researcher443</p><p>Researcher104 Researcher468</p><p>Researcher147 Researcher585</p><p>Researcher188 Researcher632</p></div>
<table><caption>Figure 6. The Most Productive of MNGT Journals</caption><thead><tr><th></th><th>AMJ</th><th>AMR</th><th>ASQ</th><th>JOM</th><th>OrgSci</th><th>HumRel</th><th>JMS</th></tr></thead><tbody><tr><td>1</td><td>Researcher154</td><td>Researcher137</td><td>Researcher183</td><td>Researcher36</td><td>Researcher1245</td><td>Researcher94</td><td>Researcher61</td></tr><tr><td>2</td><td>Researcher59</td><td>Researcher319</td><td>Researcher1752</td><td>Researcher2</td><td>Researcher1141</td><td>Researcher86</td><td>Researcher114</td></tr><tr><td>3</td><td>Researcher183</td><td>Researcher125</td><td>Researcher125</td><td>Researcher49</td><td>Researcher997</td><td>Researcher5</td><td>Researcher545</td></tr><tr><td>4</td><td>Researcher82</td><td>Researcher178</td><td>Researcher424</td><td>Researcher41</td><td>Researcher1362</td><td>Researcher679</td><td>Researcher109</td></tr><tr><td>5</td><td>Researcher36</td><td>Researcher37</td><td>Researcher622</td><td>Researcher186</td><td>Researcher240</td><td>Researcher70</td><td>Researcher1204</td></tr><tr><td>6</td><td>Researcher240</td><td>Researcher1466</td><td>Researcher1791</td><td>Researcher321</td><td>Researcher875</td><td>Researcher29</td><td>Researcher56</td></tr><tr><td>7</td><td>Researcher726</td><td>Researcher1187</td><td>Researcher1047</td><td>Researcher287</td><td>Researcher919</td><td>Researcher1</td><td>Researcher297</td></tr><tr><td>8</td><td>Researcher23</td><td>Researcher445</td><td>Researcher3221</td><td>Researcher243</td><td>Researcher214</td><td>Researcher1942</td><td>Researcher214</td></tr><tr><td>9</td><td>Researcher162</td><td>Researcher3610</td><td>Researcher240</td><td>Researcher315</td><td>Researcher459</td><td>Researcher80</td><td>Researcher70</td></tr><tr><td>10</td><td>Researcher287</td><td>Researcher48</td><td>Researcher859</td><td>Researcher47</td><td>Researcher1040</td><td>Researcher43</td><td>Researcher695</td></tr></tbody></table><table><thead><tr><th></th><th>OrgStud</th><th>AMP</th><th>BJM</th><th>CMR</th><th>EMR*</th><th>LJMR</th><th>JMI</th></tr></thead><tbody><tr><td>1</td><td>Researcher29</td><td>Researcher2347</td><td>Researcher706</td><td>Researcher670</td><td>Researcher2936</td><td>Researcher30</td><td>Researcher29</td></tr><tr><td>2</td><td>Researcher476</td><td>Researcher61</td><td>Researcher1046</td><td>Researcher1531</td><td>Researcher1507</td><td>Researcher2382</td><td>Researcher1036</td></tr><tr><td>3</td><td>Researcher540</td><td>Researcher2569</td><td>Researcher886</td><td>Researcher1567</td><td>Researcher4865</td><td>Researcher6042</td><td>Researcher176</td></tr><tr><td>4</td><td>Researcher86</td><td>Researcher4164</td><td>Researcher333</td><td>Researcher1430</td><td>Researcher1328</td><td>Researcher2468</td><td>Researcher807</td></tr><tr><td>5</td><td>Researcher85</td><td>Researcher948</td><td>Researcher1149</td><td>Researcher67</td><td>Researcher1596</td><td>Researcher3177</td><td>Researcher117</td></tr><tr><td>6</td><td>Researcher196</td><td>Researcher537</td><td>Researcher368</td><td>Researcher2143</td><td>Researcher214</td><td>Researcher324</td><td>Researcher185</td></tr><tr><td>7</td><td>Researcher340</td><td>Researcher1587</td><td>Researcher61</td><td>Researcher618</td><td></td><td>Researcher377</td><td>Researcher4008</td></tr><tr><td>8</td><td>Researcher448</td><td>Researcher4017</td><td>Researcher415</td><td>Researcher1749</td><td></td><td>Researcher8810</td><td>Researcher350</td></tr><tr><td>9</td><td>Researcher378</td><td>Researcher109</td><td>Researcher1092</td><td>Researcher502</td><td></td><td>Researcher64</td><td>Researcher458</td></tr><tr><td>10</td><td>Researcher56</td><td>Researcher683</td><td>Researcher215</td><td>Researcher2689</td><td></td><td>Researcher1092</td><td>Researcher2691</td></tr></tbody></table><table><thead><tr><th></th><th>3 journals</th><th>2 journals</th></tr></thead><tbody><tr><td>Researcher29</td><td>Researcher36</td><td>Researcher183</td></tr><tr><td>Researcher56</td><td>Researcher70</td><td>Researcher287</td></tr><tr><td>Researcher61</td><td>Researcher86</td><td>Researcher377</td></tr><tr><td>Researcher214</td><td>Researcher109</td><td>Researcher378</td></tr><tr><td>Researcher240</td><td>Researcher125</td><td>Researcher1092</td></tr></tbody></table><table><thead><tr><th></th><th>Org</th><th></th></tr></thead><tbody><tr><td>Researcher377</td><td>12</td></tr><tr><td>Researcher56</td><td>11</td></tr><tr><td>Researcher454</td><td>10</td></tr><tr><td>Researcher499</td><td>9</td></tr><tr><td>Researcher771</td><td>9</td></tr><tr><td>Researcher1081</td><td>9</td></tr><tr><td>Researcher273</td><td>8</td></tr><tr><td>Researcher378</td><td>8</td></tr><tr><td>Researcher1109</td><td>8</td></tr><tr><td>Researcher330</td><td>8</td></tr></tbody></table>
<table><caption>Figure 7. The Most Productive of IOP Journals</caption><thead><tr><th></th><th>JAP</th><th>PPsych</th><th>JOOP</th><th>JOHP</th><th>JOB</th><th>JVB</th><th>LQ</th></tr></thead><tbody><tr><td>1</td><td>Researcher8</td><td>Researcher26</td><td>Researcher1</td><td>Researcher1</td><td>Researcher117</td><td>Researcher143</td><td>Researcher16</td></tr><tr><td>2</td><td>Researcher3</td><td>Researcher8</td><td>Researcher10</td><td>Researcher98</td><td>Researcher27</td><td>Researcher201</td><td>Researcher34</td></tr><tr><td>3</td><td>Researcher12</td><td>Researcher12</td><td>Researcher124</td><td>Researcher216</td><td>Researcher19</td><td>Researcher18</td><td>Researcher24</td></tr><tr><td>4</td><td>Researcher9</td><td>Researcher9</td><td>Researcher89</td><td>Researcher375</td><td>Researcher4</td><td>Researcher58</td><td>Researcher102</td></tr><tr><td>5</td><td>Researcher13</td><td>Researcher96</td><td>Researcher307</td><td>Researcher10</td><td>Researcher57</td><td>Researcher1</td><td>Researcher38</td></tr><tr><td>6</td><td>Researcher55</td><td>Researcher11</td><td>Researcher816</td><td>Researcher21</td><td>Researcher87</td><td>Researcher384</td><td>Researcher239</td></tr><tr><td>7</td><td>Researcher14</td><td>Researcher648</td><td>Researcher13</td><td>Researcher197</td><td>Researcher66</td><td>Researcher412</td><td>Researcher212</td></tr><tr><td>8</td><td>Researcher81</td><td>Researcher55</td><td>Researcher672</td><td>Researcher7</td><td>Researcher10</td><td>Researcher93</td><td>Researcher208</td></tr><tr><td>9</td><td>Researcher83</td><td>Researcher20</td><td>Researcher498</td><td>Researcher19</td><td>Researcher1</td><td>Researcher411</td><td>Researcher825</td></tr><tr><td>10</td><td>Researcher23</td><td>Researcher680</td><td>Researcher4</td><td>Researcher4</td><td>Researcher6</td><td>Researcher521</td><td>Researcher568</td></tr></tbody></table><table><thead><tr><th></th><th>OBHDP</th><th>APIR</th><th>EJWOP</th><th>GOM</th><th>HumPerf</th><th>JMP</th><th>W&S</th></tr></thead><tbody><tr><td>1</td><td>Researcher151</td><td>Researcher1160</td><td>Researcher1</td><td>Researcher221</td><td>Researcher9</td><td>Researcher5</td><td>Researcher249</td></tr><tr><td>2</td><td>Researcher122</td><td>Researcher11</td><td>Researcher21</td><td>Researcher497</td><td>Researcher489</td><td>Researcher494</td><td>Researcher7</td></tr><tr><td>3</td><td>Researcher291</td><td>Researcher4</td><td>Researcher22</td><td>Researcher637</td><td>Researcher8</td><td>Researcher1</td><td>Researcher245</td></tr><tr><td>4</td><td>Researcher199</td><td>Researcher52</td><td>Researcher10</td><td>Researcher700</td><td>Researcher161</td><td>Researcher94</td><td>Researcher119</td></tr><tr><td>5</td><td>Researcher794</td><td>Researcher7</td><td>Researcher7</td><td>Researcher258</td><td>Researcher4</td><td>Researcher1835</td><td>Researcher45</td></tr><tr><td>6</td><td>Researcher449</td><td>Researcher5</td><td>Researcher383</td><td>Researcher2111</td><td>Researcher310</td><td>Researcher351</td><td>Researcher22</td></tr><tr><td>7</td><td>Researcher723</td><td>Researcher2560</td><td>Researcher90</td><td>Researcher43</td><td>Researcher232</td><td>Researcher2472</td><td>Researcher4</td></tr><tr><td>8</td><td>Researcher417</td><td>Researcher3291</td><td>Researcher219</td><td>Researcher2</td><td>Researcher507</td><td>Researcher1481</td><td>Researcher5</td></tr><tr><td>9</td><td>Researcher414</td><td>Researcher2131</td><td>Researcher250</td><td>Researcher1391</td><td>Researcher482</td><td>Researcher1573</td><td>Researcher485</td></tr><tr><td>10</td><td>Researcher550</td><td>Researcher2510</td><td>Researcher45</td><td>Researcher1285</td><td>Researcher531</td><td>Researcher360</td><td>Researcher219</td></tr></tbody></table><p>6 journals<br>Researcher1<br>Researcher4</p><p>5 Journals</p><p>4 Journals<br>Researcher7<br>Researcher10</p><p>3 journals<br>Researcher5<br>Researcher8<br>Researcher9</p><p>2 journals<br>Researcher11<br>Researcher12<br>Researcher13<br>Researcher19<br>Researcher21</p><p>Researcher22<br>Researcher45<br>Researcher55<br>Researcher219</p>
<table><caption>Figure 8. Journal Concentration of Top Contributors</caption><thead><tr><th>Researcher</th><th>No. of Journals as Top 10 Contributor</th><th colspan="7">Journals</th></tr></thead><tbody><tr><td>Researcher1</td><td>7</td><td>JMP</td><td>EJWOP</td><td>JVB</td><td>JOB</td><td>JOHP</td><td>JOOP</td><td>HumRel</td></tr><tr><td>Researcher4</td><td>6</td><td>W&S</td><td>HumPerf</td><td>APIR</td><td>JOB</td><td>JOHP</td><td>JOOP</td><td></td></tr><tr><td>Researcher5</td><td>4</td><td>W&S</td><td>JMP</td><td>APIR</td><td>HumRel</td><td></td><td></td><td></td></tr><tr><td>Researcher10</td><td>4</td><td>EJWOP</td><td>JOB</td><td>JOHP</td><td>JOOP</td><td></td><td></td><td></td></tr><tr><td>Researcher7</td><td>4</td><td>W&S</td><td>EJWOP</td><td>APIR</td><td>JOHP</td><td></td><td></td><td></td></tr><tr><td>Researcher29</td><td>3</td><td>JMI</td><td>OrgStud</td><td>HumRel</td><td></td><td></td><td></td><td></td></tr><tr><td>Researcher6</td><td>3</td><td>HRMR</td><td>HRM</td><td>JOB</td><td></td><td></td><td></td><td></td></tr><tr><td>Researcher240</td><td>3</td><td>OrgSci</td><td>ASQ</td><td>AMJ</td><td></td><td></td><td></td><td></td></tr><tr><td>Researcher22</td><td>3</td><td>EID</td><td>W&S</td><td>EJWOP</td><td></td><td></td><td></td><td></td></tr><tr><td>Researcher214</td><td>3</td><td>EMR</td><td>JMS</td><td>OrgSci</td><td></td><td></td><td></td><td></td></tr><tr><td>Researcher61</td><td>3</td><td>BJM</td><td>AMP</td><td>JMS</td><td></td><td></td><td></td><td></td></tr><tr><td>Researcher2</td><td>3</td><td>HRMR</td><td>GOM</td><td>JoM</td><td></td><td></td><td></td><td></td></tr><tr><td>Researcher244</td><td>3</td><td>ILRR</td><td>IR</td><td>BJIR</td><td></td><td></td><td></td><td></td></tr><tr><td>Researcher210</td><td>3</td><td>ILRR</td><td>HRMR</td><td>IR</td><td></td><td></td><td></td><td></td></tr><tr><td>Researcher8</td><td>3</td><td>HumPerf</td><td>PPsych</td><td>JAP</td><td></td><td></td><td></td><td></td></tr><tr><td>Researcher56</td><td>3</td><td>Org</td><td>OrgStud</td><td>JMS</td><td></td><td></td><td></td><td>IOP</td></tr><tr><td>Researcher30</td><td>3</td><td>IJHRM</td><td>HRMJ</td><td>IJMR</td><td></td><td></td><td></td><td>HRM</td></tr><tr><td>Researcher9</td><td>3</td><td>HumPerf</td><td>PPsych</td><td>JAP</td><td></td><td></td><td></td><td>MNGT</td></tr></tbody></table>
<figure><img src="image_6.png" /><figcaption>Figure 9. Historical Trends of Gini Coefficients</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>Figure 10. Shares of Total Publications by Most Productive over Time</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>Figure 11. Network Analyses – Top 50 Most Connected Authors</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>Figure 12. Network Analyses – Centrality Trends</figcaption></figure>
**Appendix. Journal List with Missing Years in Scopus Coverage**

Summary of the Scopus coverage for the journals you mentioned, highlighting the missing years:

1. **British Journal of Industrial Relations**: Coverage includes 1963, 1965, 1967-1968, 1970-2024.

a. **Missing years**: 1964, 1966, 1969.

2. **ILR Review**: Coverage includes 1978, 1981-1982, 1984, 1996-2024.

a. **Missing years**: 1979-1980, 1983, 1985-1995.

3. **Academy of Management Journal**: Coverage includes 1975-1987, 1989-2024.

a. **Missing years**: 1988.

4. **Academy of Management Review**: Coverage includes 1978-1987, 1989-1991, 1996-2024.

a. **Missing years**: 1988, 1992-1995.

5. **Administrative Science Quarterly**: Coverage includes 1975-1987, 1989-1990, 1993-1994, 1996-2024.

a. **Missing years**: 1988, 1991-1992, 1995.

6. **International Journal of Management Reviews**: Coverage includes 1999-2002, 2004-2024.

a. **Missing years**: 2003.

7. **Journal of Organizational Behavior**: Coverage includes 1981-1982, 1984-2024.

a. **Missing years**: 1983.