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Peer-reviewed

Research Article

Twenty years of gender equality research: A scoping review based on a new semantic indicator

Contributed equally to this work with: Paola Belingheri, Filippo Chiarello, Andrea Fronzetti Colladon, Paola Rovelli

Roles Conceptualization, Formal analysis, Funding acquisition, Visualization, Writing – original draft, Writing – review & editing

Affiliation Dipartimento di Ingegneria dell’Energia, dei Sistemi, del Territorio e delle Costruzioni, Università degli Studi di Pisa, Largo L. Lazzarino, Pisa, Italy

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Visualization, Writing – original draft, Writing – review & editing

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Engineering, University of Perugia, Perugia, Italy, Department of Management, Kozminski University, Warsaw, Poland

Roles Conceptualization, Formal analysis, Funding acquisition, Writing – original draft, Writing – review & editing

Affiliation Faculty of Economics and Management, Centre for Family Business Management, Free University of Bozen-Bolzano, Bozen-Bolzano, Italy

• Paola Belingheri, 
• Filippo Chiarello, 
• Andrea Fronzetti Colladon, 
• Paola Rovelli

• Published: September 21, 2021
• https://doi.org/10.1371/journal.pone.0256474
• Reader Comments

9 Nov 2021: The PLOS ONE Staff (2021) Correction: Twenty years of gender equality research: A scoping review based on a new semantic indicator. PLOS ONE 16(11): e0259930. https://doi.org/10.1371/journal.pone.0259930 View correction

Gender equality is a major problem that places women at a disadvantage thereby stymieing economic growth and societal advancement. In the last two decades, extensive research has been conducted on gender related issues, studying both their antecedents and consequences. However, existing literature reviews fail to provide a comprehensive and clear picture of what has been studied so far, which could guide scholars in their future research. Our paper offers a scoping review of a large portion of the research that has been published over the last 22 years, on gender equality and related issues, with a specific focus on business and economics studies. Combining innovative methods drawn from both network analysis and text mining, we provide a synthesis of 15,465 scientific articles. We identify 27 main research topics, we measure their relevance from a semantic point of view and the relationships among them, highlighting the importance of each topic in the overall gender discourse. We find that prominent research topics mostly relate to women in the workforce–e.g., concerning compensation, role, education, decision-making and career progression. However, some of them are losing momentum, and some other research trends–for example related to female entrepreneurship, leadership and participation in the board of directors–are on the rise. Besides introducing a novel methodology to review broad literature streams, our paper offers a map of the main gender-research trends and presents the most popular and the emerging themes, as well as their intersections, outlining important avenues for future research.

Citation: Belingheri P, Chiarello F, Fronzetti Colladon A, Rovelli P (2021) Twenty years of gender equality research: A scoping review based on a new semantic indicator. PLoS ONE 16(9): e0256474. https://doi.org/10.1371/journal.pone.0256474

Editor: Elisa Ughetto, Politecnico di Torino, ITALY

Received: June 25, 2021; Accepted: August 6, 2021; Published: September 21, 2021

Copyright: © 2021 Belingheri et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its supporting information files. The only exception is the text of the abstracts (over 15,000) that we have downloaded from Scopus. These abstracts can be retrieved from Scopus, but we do not have permission to redistribute them.

Funding: P.B and F.C.: Grant of the Department of Energy, Systems, Territory and Construction of the University of Pisa (DESTEC) for the project “Measuring Gender Bias with Semantic Analysis: The Development of an Assessment Tool and its Application in the European Space Industry. P.B., F.C., A.F.C., P.R.: Grant of the Italian Association of Management Engineering (AiIG), “Misure di sostegno ai soci giovani AiIG” 2020, for the project “Gender Equality Through Data Intelligence (GEDI)”. F.C.: EU project ASSETs+ Project (Alliance for Strategic Skills addressing Emerging Technologies in Defence) EAC/A03/2018 - Erasmus+ programme, Sector Skills Alliances, Lot 3: Sector Skills Alliance for implementing a new strategic approach (Blueprint) to sectoral cooperation on skills G.A. NUMBER: 612678-EPP-1-2019-1-IT-EPPKA2-SSA-B.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The persistent gender inequalities that currently exist across the developed and developing world are receiving increasing attention from economists, policymakers, and the general public [e.g., 1 – 3 ]. Economic studies have indicated that women’s education and entry into the workforce contributes to social and economic well-being [e.g., 4 , 5 ], while their exclusion from the labor market and from managerial positions has an impact on overall labor productivity and income per capita [ 6 , 7 ]. The United Nations selected gender equality, with an emphasis on female education, as part of the Millennium Development Goals [ 8 ], and gender equality at-large as one of the 17 Sustainable Development Goals (SDGs) to be achieved by 2030 [ 9 ]. These latter objectives involve not only developing nations, but rather all countries, to achieve economic, social and environmental well-being.

As is the case with many SDGs, gender equality is still far from being achieved and persists across education, access to opportunities, or presence in decision-making positions [ 7 , 10 , 11 ]. As we enter the last decade for the SDGs’ implementation, and while we are battling a global health pandemic, effective and efficient action becomes paramount to reach this ambitious goal.

Scholars have dedicated a massive effort towards understanding gender equality, its determinants, its consequences for women and society, and the appropriate actions and policies to advance women’s equality. Many topics have been covered, ranging from women’s education and human capital [ 12 , 13 ] and their role in society [e.g., 14 , 15 ], to their appointment in firms’ top ranked positions [e.g., 16 , 17 ] and performance implications [e.g., 18 , 19 ]. Despite some attempts, extant literature reviews provide a narrow view on these issues, restricted to specific topics–e.g., female students’ presence in STEM fields [ 20 ], educational gender inequality [ 5 ], the gender pay gap [ 21 ], the glass ceiling effect [ 22 ], leadership [ 23 ], entrepreneurship [ 24 ], women’s presence on the board of directors [ 25 , 26 ], diversity management [ 27 ], gender stereotypes in advertisement [ 28 ], or specific professions [ 29 ]. A comprehensive view on gender-related research, taking stock of key findings and under-studied topics is thus lacking.

Extant literature has also highlighted that gender issues, and their economic and social ramifications, are complex topics that involve a large number of possible antecedents and outcomes [ 7 ]. Indeed, gender equality actions are most effective when implemented in unison with other SDGs (e.g., with SDG 8, see [ 30 ]) in a synergetic perspective [ 10 ]. Many bodies of literature (e.g., business, economics, development studies, sociology and psychology) approach the problem of achieving gender equality from different perspectives–often addressing specific and narrow aspects. This sometimes leads to a lack of clarity about how different issues, circumstances, and solutions may be related in precipitating or mitigating gender inequality or its effects. As the number of papers grows at an increasing pace, this issue is exacerbated and there is a need to step back and survey the body of gender equality literature as a whole. There is also a need to examine synergies between different topics and approaches, as well as gaps in our understanding of how different problems and solutions work together. Considering the important topic of women’s economic and social empowerment, this paper aims to fill this gap by answering the following research question: what are the most relevant findings in the literature on gender equality and how do they relate to each other ?

To do so, we conduct a scoping review [ 31 ], providing a synthesis of 15,465 articles dealing with gender equity related issues published in the last twenty-two years, covering both the periods of the MDGs and the SDGs (i.e., 2000 to mid 2021) in all the journals indexed in the Academic Journal Guide’s 2018 ranking of business and economics journals. Given the huge amount of research conducted on the topic, we adopt an innovative methodology, which relies on social network analysis and text mining. These techniques are increasingly adopted when surveying large bodies of text. Recently, they were applied to perform analysis of online gender communication differences [ 32 ] and gender behaviors in online technology communities [ 33 ], to identify and classify sexual harassment instances in academia [ 34 ], and to evaluate the gender inclusivity of disaster management policies [ 35 ].

Applied to the title, abstracts and keywords of the articles in our sample, this methodology allows us to identify a set of 27 recurrent topics within which we automatically classify the papers. Introducing additional novelty, by means of the Semantic Brand Score (SBS) indicator [ 36 ] and the SBS BI app [ 37 ], we assess the importance of each topic in the overall gender equality discourse and its relationships with the other topics, as well as trends over time, with a more accurate description than that offered by traditional literature reviews relying solely on the number of papers presented in each topic.

This methodology, applied to gender equality research spanning the past twenty-two years, enables two key contributions. First, we extract the main message that each document is conveying and how this is connected to other themes in literature, providing a rich picture of the topics that are at the center of the discourse, as well as of the emerging topics. Second, by examining the semantic relationship between topics and how tightly their discourses are linked, we can identify the key relationships and connections between different topics. This semi-automatic methodology is also highly reproducible with minimum effort.

This literature review is organized as follows. In the next section, we present how we selected relevant papers and how we analyzed them through text mining and social network analysis. We then illustrate the importance of 27 selected research topics, measured by means of the SBS indicator. In the results section, we present an overview of the literature based on the SBS results–followed by an in-depth narrative analysis of the top 10 topics (i.e., those with the highest SBS) and their connections. Subsequently, we highlight a series of under-studied connections between the topics where there is potential for future research. Through this analysis, we build a map of the main gender-research trends in the last twenty-two years–presenting the most popular themes. We conclude by highlighting key areas on which research should focused in the future.

Our aim is to map a broad topic, gender equality research, that has been approached through a host of different angles and through different disciplines. Scoping reviews are the most appropriate as they provide the freedom to map different themes and identify literature gaps, thereby guiding the recommendation of new research agendas [ 38 ].

Several practical approaches have been proposed to identify and assess the underlying topics of a specific field using big data [ 39 – 41 ], but many of them fail without proper paper retrieval and text preprocessing. This is specifically true for a research field such as the gender-related one, which comprises the work of scholars from different backgrounds. In this section, we illustrate a novel approach for the analysis of scientific (gender-related) papers that relies on methods and tools of social network analysis and text mining. Our procedure has four main steps: (1) data collection, (2) text preprocessing, (3) keywords extraction and classification, and (4) evaluation of semantic importance and image.

Data collection

In this study, we analyze 22 years of literature on gender-related research. Following established practice for scoping reviews [ 42 ], our data collection consisted of two main steps, which we summarize here below.

Firstly, we retrieved from the Scopus database all the articles written in English that contained the term “gender” in their title, abstract or keywords and were published in a journal listed in the Academic Journal Guide 2018 ranking of the Chartered Association of Business Schools (CABS) ( https://charteredabs.org/wp-content/uploads/2018/03/AJG2018-Methodology.pdf ), considering the time period from Jan 2000 to May 2021. We used this information considering that abstracts, titles and keywords represent the most informative part of a paper, while using the full-text would increase the signal-to-noise ratio for information extraction. Indeed, these textual elements already demonstrated to be reliable sources of information for the task of domain lexicon extraction [ 43 , 44 ]. We chose Scopus as source of literature because of its popularity, its update rate, and because it offers an API to ease the querying process. Indeed, while it does not allow to retrieve the full text of scientific articles, the Scopus API offers access to titles, abstracts, citation information and metadata for all its indexed scholarly journals. Moreover, we decided to focus on the journals listed in the AJG 2018 ranking because we were interested in reviewing business and economics related gender studies only. The AJG is indeed widely used by universities and business schools as a reference point for journal and research rigor and quality. This first step, executed in June 2021, returned more than 55,000 papers.

In the second step–because a look at the papers showed very sparse results, many of which were not in line with the topic of this literature review (e.g., papers dealing with health care or medical issues, where the word gender indicates the gender of the patients)–we applied further inclusion criteria to make the sample more focused on the topic of this literature review (i.e., women’s gender equality issues). Specifically, we only retained those papers mentioning, in their title and/or abstract, both gender-related keywords (e.g., daughter, female, mother) and keywords referring to bias and equality issues (e.g., equality, bias, diversity, inclusion). After text pre-processing (see next section), keywords were first identified from a frequency-weighted list of words found in the titles, abstracts and keywords in the initial list of papers, extracted through text mining (following the same approach as [ 43 ]). They were selected by two of the co-authors independently, following respectively a bottom up and a top-down approach. The bottom-up approach consisted of examining the words found in the frequency-weighted list and classifying those related to gender and equality. The top-down approach consisted in searching in the word list for notable gender and equality-related words. Table 1 reports the sets of keywords we considered, together with some examples of words that were used to search for their presence in the dataset (a full list is provided in the S1 Text ). At end of this second step, we obtained a final sample of 15,465 relevant papers.

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https://doi.org/10.1371/journal.pone.0256474.t001

Text processing and keyword extraction

Text preprocessing aims at structuring text into a form that can be analyzed by statistical models. In the present section, we describe the preprocessing steps we applied to paper titles and abstracts, which, as explained below, partially follow a standard text preprocessing pipeline [ 45 ]. These activities have been performed using the R package udpipe [ 46 ].

The first step is n-gram extraction (i.e., a sequence of words from a given text sample) to identify which n-grams are important in the analysis, since domain-specific lexicons are often composed by bi-grams and tri-grams [ 47 ]. Multi-word extraction is usually implemented with statistics and linguistic rules, thus using the statistical properties of n-grams or machine learning approaches [ 48 ]. However, for the present paper, we used Scopus metadata in order to have a more effective and efficient n-grams collection approach [ 49 ]. We used the keywords of each paper in order to tag n-grams with their associated keywords automatically. Using this greedy approach, it was possible to collect all the keywords listed by the authors of the papers. From this list, we extracted only keywords composed by two, three and four words, we removed all the acronyms and rare keywords (i.e., appearing in less than 1% of papers), and we clustered keywords showing a high orthographic similarity–measured using a Levenshtein distance [ 50 ] lower than 2, considering these groups of keywords as representing same concepts, but expressed with different spelling. After tagging the n-grams in the abstracts, we followed a common data preparation pipeline that consists of the following steps: (i) tokenization, that splits the text into tokens (i.e., single words and previously tagged multi-words); (ii) removal of stop-words (i.e. those words that add little meaning to the text, usually being very common and short functional words–such as “and”, “or”, or “of”); (iii) parts-of-speech tagging, that is providing information concerning the morphological role of a word and its morphosyntactic context (e.g., if the token is a determiner, the next token is a noun or an adjective with very high confidence, [ 51 ]); and (iv) lemmatization, which consists in substituting each word with its dictionary form (or lemma). The output of the latter step allows grouping together the inflected forms of a word. For example, the verbs “am”, “are”, and “is” have the shared lemma “be”, or the nouns “cat” and “cats” both share the lemma “cat”. We preferred lemmatization over stemming [ 52 ] in order to obtain more interpretable results.

In addition, we identified a further set of keywords (with respect to those listed in the “keywords” field) by applying a series of automatic words unification and removal steps, as suggested in past research [ 53 , 54 ]. We removed: sparse terms (i.e., occurring in less than 0.1% of all documents), common terms (i.e., occurring in more than 10% of all documents) and retained only nouns and adjectives. It is relevant to notice that no document was lost due to these steps. We then used the TF-IDF function [ 55 ] to produce a new list of keywords. We additionally tested other approaches for the identification and clustering of keywords–such as TextRank [ 56 ] or Latent Dirichlet Allocation [ 57 ]–without obtaining more informative results.

Classification of research topics

To guide the literature analysis, two experts met regularly to examine the sample of collected papers and to identify the main topics and trends in gender research. Initially, they conducted brainstorming sessions on the topics they expected to find, due to their knowledge of the literature. This led to an initial list of topics. Subsequently, the experts worked independently, also supported by the keywords in paper titles and abstracts extracted with the procedure described above.

Considering all this information, each expert identified and clustered relevant keywords into topics. At the end of the process, the two assignments were compared and exhibited a 92% agreement. Another meeting was held to discuss discordant cases and reach a consensus. This resulted in a list of 27 topics, briefly introduced in Table 2 and subsequently detailed in the following sections.

https://doi.org/10.1371/journal.pone.0256474.t002

Evaluation of semantic importance

Working on the lemmatized corpus of the 15,465 papers included in our sample, we proceeded with the evaluation of semantic importance trends for each topic and with the analysis of their connections and prevalent textual associations. To this aim, we used the Semantic Brand Score indicator [ 36 ], calculated through the SBS BI webapp [ 37 ] that also produced a brand image report for each topic. For this study we relied on the computing resources of the ENEA/CRESCO infrastructure [ 58 ].

The Semantic Brand Score (SBS) is a measure of semantic importance that combines methods of social network analysis and text mining. It is usually applied for the analysis of (big) textual data to evaluate the importance of one or more brands, names, words, or sets of keywords [ 36 ]. Indeed, the concept of “brand” is intended in a flexible way and goes beyond products or commercial brands. In this study, we evaluate the SBS time-trends of the keywords defining the research topics discussed in the previous section. Semantic importance comprises the three dimensions of topic prevalence, diversity and connectivity. Prevalence measures how frequently a research topic is used in the discourse. The more a topic is mentioned by scientific articles, the more the research community will be aware of it, with possible increase of future studies; this construct is partly related to that of brand awareness [ 59 ]. This effect is even stronger, considering that we are analyzing the title, abstract and keywords of the papers, i.e. the parts that have the highest visibility. A very important characteristic of the SBS is that it considers the relationships among words in a text. Topic importance is not just a matter of how frequently a topic is mentioned, but also of the associations a topic has in the text. Specifically, texts are transformed into networks of co-occurring words, and relationships are studied through social network analysis [ 60 ]. This step is necessary to calculate the other two dimensions of our semantic importance indicator. Accordingly, a social network of words is generated for each time period considered in the analysis–i.e., a graph made of n nodes (words) and E edges weighted by co-occurrence frequency, with W being the set of edge weights. The keywords representing each topic were clustered into single nodes.

The construct of diversity relates to that of brand image [ 59 ], in the sense that it considers the richness and distinctiveness of textual (topic) associations. Considering the above-mentioned networks, we calculated diversity using the distinctiveness centrality metric–as in the formula presented by Fronzetti Colladon and Naldi [ 61 ].

Lastly, connectivity was measured as the weighted betweenness centrality [ 62 , 63 ] of each research topic node. We used the formula presented by Wasserman and Faust [ 60 ]. The dimension of connectivity represents the “brokerage power” of each research topic–i.e., how much it can serve as a bridge to connect other terms (and ultimately topics) in the discourse [ 36 ].

The SBS is the final composite indicator obtained by summing the standardized scores of prevalence, diversity and connectivity. Standardization was carried out considering all the words in the corpus, for each specific timeframe.

This methodology, applied to a large and heterogeneous body of text, enables to automatically identify two important sets of information that add value to the literature review. Firstly, the relevance of each topic in literature is measured through a composite indicator of semantic importance, rather than simply looking at word frequencies. This provides a much richer picture of the topics that are at the center of the discourse, as well as of the topics that are emerging in the literature. Secondly, it enables to examine the extent of the semantic relationship between topics, looking at how tightly their discourses are linked. In a field such as gender equality, where many topics are closely linked to each other and present overlaps in issues and solutions, this methodology offers a novel perspective with respect to traditional literature reviews. In addition, it ensures reproducibility over time and the possibility to semi-automatically update the analysis, as new papers become available.

Overview of main topics

In terms of descriptive textual statistics, our corpus is made of 15,465 text documents, consisting of a total of 2,685,893 lemmatized tokens (words) and 32,279 types. As a result, the type-token ratio is 1.2%. The number of hapaxes is 12,141, with a hapax-token ratio of 37.61%.

Fig 1 shows the list of 27 topics by decreasing SBS. The most researched topic is compensation , exceeding all others in prevalence, diversity, and connectivity. This means it is not only mentioned more often than other topics, but it is also connected to a greater number of other topics and is central to the discourse on gender equality. The next four topics are, in order of SBS, role , education , decision-making , and career progression . These topics, except for education , all concern women in the workforce. Between these first five topics and the following ones there is a clear drop in SBS scores. In particular, the topics that follow have a lower connectivity than the first five. They are hiring , performance , behavior , organization , and human capital . Again, except for behavior and human capital , the other three topics are purely related to women in the workforce. After another drop-off, the following topics deal prevalently with women in society. This trend highlights that research on gender in business journals has so far mainly paid attention to the conditions that women experience in business contexts, while also devoting some attention to women in society.

https://doi.org/10.1371/journal.pone.0256474.g001

Fig 2 shows the SBS time series of the top 10 topics. While there has been a general increase in the number of Scopus-indexed publications in the last decade, we notice that some SBS trends remain steady, or even decrease. In particular, we observe that the main topic of the last twenty-two years, compensation , is losing momentum. Since 2016, it has been surpassed by decision-making , education and role , which may indicate that literature is increasingly attempting to identify root causes of compensation inequalities. Moreover, in the last two years, the topics of hiring , performance , and organization are experiencing the largest importance increase.

https://doi.org/10.1371/journal.pone.0256474.g002

Fig 3 shows the SBS time trends of the remaining 17 topics (i.e., those not in the top 10). As we can see from the graph, there are some that maintain a steady trend–such as reputation , management , networks and governance , which also seem to have little importance. More relevant topics with average stationary trends (except for the last two years) are culture , family , and parenting . The feminine topic is among the most important here, and one of those that exhibit the larger variations over time (similarly to leadership ). On the other hand, the are some topics that, even if not among the most important, show increasing SBS trends; therefore, they could be considered as emerging topics and could become popular in the near future. These are entrepreneurship , leadership , board of directors , and sustainability . These emerging topics are also interesting to anticipate future trends in gender equality research that are conducive to overall equality in society.

https://doi.org/10.1371/journal.pone.0256474.g003

In addition to the SBS score of the different topics, the network of terms they are associated to enables to gauge the extent to which their images (textual associations) overlap or differ ( Fig 4 ).

https://doi.org/10.1371/journal.pone.0256474.g004

There is a central cluster of topics with high similarity, which are all connected with women in the workforce. The cluster includes topics such as organization , decision-making , performance , hiring , human capital , education and compensation . In addition, the topic of well-being is found within this cluster, suggesting that women’s equality in the workforce is associated to well-being considerations. The emerging topics of entrepreneurship and leadership are also closely connected with each other, possibly implying that leadership is a much-researched quality in female entrepreneurship. Topics that are relatively more distant include personality , politics , feminine , empowerment , management , board of directors , reputation , governance , parenting , masculine and network .

The following sections describe the top 10 topics and their main associations in literature (see Table 3 ), while providing a brief overview of the emerging topics.

https://doi.org/10.1371/journal.pone.0256474.t003

Compensation.

The topic of compensation is related to the topics of role , hiring , education and career progression , however, also sees a very high association with the words gap and inequality . Indeed, a well-known debate in degrowth economics centers around whether and how to adequately compensate women for their childbearing, childrearing, caregiver and household work [e.g., 30 ].

Even in paid work, women continue being offered lower compensations than their male counterparts who have the same job or cover the same role [ 64 – 67 ]. This severe inequality has been widely studied by scholars over the last twenty-two years. Dealing with this topic, some specific roles have been addressed. Specifically, research highlighted differences in compensation between female and male CEOs [e.g., 68 ], top executives [e.g., 69 ], and boards’ directors [e.g., 70 ]. Scholars investigated the determinants of these gaps, such as the gender composition of the board [e.g., 71 – 73 ] or women’s individual characteristics [e.g., 71 , 74 ].

Among these individual characteristics, education plays a relevant role [ 75 ]. Education is indeed presented as the solution for women, not only to achieve top executive roles, but also to reduce wage inequality [e.g., 76 , 77 ]. Past research has highlighted education influences on gender wage gaps, specifically referring to gender differences in skills [e.g., 78 ], college majors [e.g., 79 ], and college selectivity [e.g., 80 ].

Finally, the wage gap issue is strictly interrelated with hiring –e.g., looking at whether being a mother affects hiring and compensation [e.g., 65 , 81 ] or relating compensation to unemployment [e.g., 82 ]–and career progression –for instance looking at meritocracy [ 83 , 84 ] or the characteristics of the boss for whom women work [e.g., 85 ].

The roles covered by women have been deeply investigated. Scholars have focused on the role of women in their families and the society as a whole [e.g., 14 , 15 ], and, more widely, in business contexts [e.g., 18 , 81 ]. Indeed, despite still lagging behind their male counterparts [e.g., 86 , 87 ], in the last decade there has been an increase in top ranked positions achieved by women [e.g., 88 , 89 ]. Following this phenomenon, scholars have posed greater attention towards the presence of women in the board of directors [e.g., 16 , 18 , 90 , 91 ], given the increasing pressure to appoint female directors that firms, especially listed ones, have experienced. Other scholars have focused on the presence of women covering the role of CEO [e.g., 17 , 92 ] or being part of the top management team [e.g., 93 ]. Irrespectively of the level of analysis, all these studies tried to uncover the antecedents of women’s presence among top managers [e.g., 92 , 94 ] and the consequences of having a them involved in the firm’s decision-making –e.g., on performance [e.g., 19 , 95 , 96 ], risk [e.g., 97 , 98 ], and corporate social responsibility [e.g., 99 , 100 ].

Besides studying the difficulties and discriminations faced by women in getting a job [ 81 , 101 ], and, more specifically in the hiring , appointment, or career progression to these apical roles [e.g., 70 , 83 ], the majority of research of women’s roles dealt with compensation issues. Specifically, scholars highlight the pay-gap that still exists between women and men, both in general [e.g., 64 , 65 ], as well as referring to boards’ directors [e.g., 70 , 102 ], CEOs and executives [e.g., 69 , 103 , 104 ].

Finally, other scholars focused on the behavior of women when dealing with business. In this sense, particular attention has been paid to leadership and entrepreneurial behaviors. The former quite overlaps with dealing with the roles mentioned above, but also includes aspects such as leaders being stereotyped as masculine [e.g., 105 ], the need for greater exposure to female leaders to reduce biases [e.g., 106 ], or female leaders acting as queen bees [e.g., 107 ]. Regarding entrepreneurship , scholars mainly investigated women’s entrepreneurial entry [e.g., 108 , 109 ], differences between female and male entrepreneurs in the evaluations and funding received from investors [e.g., 110 , 111 ], and their performance gap [e.g., 112 , 113 ].

Education has long been recognized as key to social advancement and economic stability [ 114 ], for job progression and also a barrier to gender equality, especially in STEM-related fields. Research on education and gender equality is mostly linked with the topics of compensation , human capital , career progression , hiring , parenting and decision-making .

Education contributes to a higher human capital [ 115 ] and constitutes an investment on the part of women towards their future. In this context, literature points to the gender gap in educational attainment, and the consequences for women from a social, economic, personal and professional standpoint. Women are found to have less access to formal education and information, especially in emerging countries, which in turn may cause them to lose social and economic opportunities [e.g., 12 , 116 – 119 ]. Education in local and rural communities is also paramount to communicate the benefits of female empowerment , contributing to overall societal well-being [e.g., 120 ].

Once women access education, the image they have of the world and their place in society (i.e., habitus) affects their education performance [ 13 ] and is passed on to their children. These situations reinforce gender stereotypes, which become self-fulfilling prophecies that may negatively affect female students’ performance by lowering their confidence and heightening their anxiety [ 121 , 122 ]. Besides formal education, also the information that women are exposed to on a daily basis contributes to their human capital . Digital inequalities, for instance, stems from men spending more time online and acquiring higher digital skills than women [ 123 ].

Education is also a factor that should boost employability of candidates and thus hiring , career progression and compensation , however the relationship between these factors is not straightforward [ 115 ]. First, educational choices ( decision-making ) are influenced by variables such as self-efficacy and the presence of barriers, irrespectively of the career opportunities they offer, especially in STEM [ 124 ]. This brings additional difficulties to women’s enrollment and persistence in scientific and technical fields of study due to stereotypes and biases [ 125 , 126 ]. Moreover, access to education does not automatically translate into job opportunities for women and minority groups [ 127 , 128 ] or into female access to managerial positions [ 129 ].

Finally, parenting is reported as an antecedent of education [e.g., 130 ], with much of the literature focusing on the role of parents’ education on the opportunities afforded to children to enroll in education [ 131 – 134 ] and the role of parenting in their offspring’s perception of study fields and attitudes towards learning [ 135 – 138 ]. Parental education is also a predictor of the other related topics, namely human capital and compensation [ 139 ].

Decision-making.

This literature mainly points to the fact that women are thought to make decisions differently than men. Women have indeed different priorities, such as they care more about people’s well-being, working with people or helping others, rather than maximizing their personal (or their firm’s) gain [ 140 ]. In other words, women typically present more communal than agentic behaviors, which are instead more frequent among men [ 141 ]. These different attitude, behavior and preferences in turn affect the decisions they make [e.g., 142 ] and the decision-making of the firm in which they work [e.g., 143 ].

At the individual level, gender affects, for instance, career aspirations [e.g., 144 ] and choices [e.g., 142 , 145 ], or the decision of creating a venture [e.g., 108 , 109 , 146 ]. Moreover, in everyday life, women and men make different decisions regarding partners [e.g., 147 ], childcare [e.g., 148 ], education [e.g., 149 ], attention to the environment [e.g., 150 ] and politics [e.g., 151 ].

At the firm level, scholars highlighted, for example, how the presence of women in the board affects corporate decisions [e.g., 152 , 153 ], that female CEOs are more conservative in accounting decisions [e.g., 154 ], or that female CFOs tend to make more conservative decisions regarding the firm’s financial reporting [e.g., 155 ]. Nevertheless, firm level research also investigated decisions that, influenced by gender bias, affect women, such as those pertaining hiring [e.g., 156 , 157 ], compensation [e.g., 73 , 158 ], or the empowerment of women once appointed [ 159 ].

Career progression.

Once women have entered the workforce, the key aspect to achieve gender equality becomes career progression , including efforts toward overcoming the glass ceiling. Indeed, according to the SBS analysis, career progression is highly related to words such as work, social issues and equality. The topic with which it has the highest semantic overlap is role , followed by decision-making , hiring , education , compensation , leadership , human capital , and family .

Career progression implies an advancement in the hierarchical ladder of the firm, assigning managerial roles to women. Coherently, much of the literature has focused on identifying rationales for a greater female participation in the top management team and board of directors [e.g., 95 ] as well as the best criteria to ensure that the decision-makers promote the most valuable employees irrespectively of their individual characteristics, such as gender [e.g., 84 ]. The link between career progression , role and compensation is often provided in practice by performance appraisal exercises, frequently rooted in a culture of meritocracy that guides bonuses, salary increases and promotions. However, performance appraisals can actually mask gender-biased decisions where women are held to higher standards than their male colleagues [e.g., 83 , 84 , 95 , 160 , 161 ]. Women often have less opportunities to gain leadership experience and are less visible than their male colleagues, which constitute barriers to career advancement [e.g., 162 ]. Therefore, transparency and accountability, together with procedures that discourage discretionary choices, are paramount to achieve a fair career progression [e.g., 84 ], together with the relaxation of strict job boundaries in favor of cross-functional and self-directed tasks [e.g., 163 ].

In addition, a series of stereotypes about the type of leadership characteristics that are required for top management positions, which fit better with typical male and agentic attributes, are another key barrier to career advancement for women [e.g., 92 , 160 ].

Hiring is the entrance gateway for women into the workforce. Therefore, it is related to other workforce topics such as compensation , role , career progression , decision-making , human capital , performance , organization and education .

A first stream of literature focuses on the process leading up to candidates’ job applications, demonstrating that bias exists before positions are even opened, and it is perpetuated both by men and women through networking and gatekeeping practices [e.g., 164 , 165 ].

The hiring process itself is also subject to biases [ 166 ], for example gender-congruity bias that leads to men being preferred candidates in male-dominated sectors [e.g., 167 ], women being hired in positions with higher risk of failure [e.g., 168 ] and limited transparency and accountability afforded by written processes and procedures [e.g., 164 ] that all contribute to ascriptive inequality. In addition, providing incentives for evaluators to hire women may actually work to this end; however, this is not the case when supporting female candidates endangers higher-ranking male ones [ 169 ].

Another interesting perspective, instead, looks at top management teams’ composition and the effects on hiring practices, indicating that firms with more women in top management are less likely to lay off staff [e.g., 152 ].

Performance.

Several scholars posed their attention towards women’s performance, its consequences [e.g., 170 , 171 ] and the implications of having women in decision-making positions [e.g., 18 , 19 ].

At the individual level, research focused on differences in educational and academic performance between women and men, especially referring to the gender gap in STEM fields [e.g., 171 ]. The presence of stereotype threats–that is the expectation that the members of a social group (e.g., women) “must deal with the possibility of being judged or treated stereotypically, or of doing something that would confirm the stereotype” [ 172 ]–affects women’s interested in STEM [e.g., 173 ], as well as their cognitive ability tests, penalizing them [e.g., 174 ]. A stronger gender identification enhances this gap [e.g., 175 ], whereas mentoring and role models can be used as solutions to this problem [e.g., 121 ]. Despite the negative effect of stereotype threats on girls’ performance [ 176 ], female and male students perform equally in mathematics and related subjects [e.g., 177 ]. Moreover, while individuals’ performance at school and university generally affects their achievements and the field in which they end up working, evidence reveals that performance in math or other scientific subjects does not explain why fewer women enter STEM working fields; rather this gap depends on other aspects, such as culture, past working experiences, or self-efficacy [e.g., 170 ]. Finally, scholars have highlighted the penalization that women face for their positive performance, for instance when they succeed in traditionally male areas [e.g., 178 ]. This penalization is explained by the violation of gender-stereotypic prescriptions [e.g., 179 , 180 ], that is having women well performing in agentic areas, which are typical associated to men. Performance penalization can thus be overcome by clearly conveying communal characteristics and behaviors [ 178 ].

Evidence has been provided on how the involvement of women in boards of directors and decision-making positions affects firms’ performance. Nevertheless, results are mixed, with some studies showing positive effects on financial [ 19 , 181 , 182 ] and corporate social performance [ 99 , 182 , 183 ]. Other studies maintain a negative association [e.g., 18 ], and other again mixed [e.g., 184 ] or non-significant association [e.g., 185 ]. Also with respect to the presence of a female CEO, mixed results emerged so far, with some researches demonstrating a positive effect on firm’s performance [e.g., 96 , 186 ], while other obtaining only a limited evidence of this relationship [e.g., 103 ] or a negative one [e.g., 187 ].

Finally, some studies have investigated whether and how women’s performance affects their hiring [e.g., 101 ] and career progression [e.g., 83 , 160 ]. For instance, academic performance leads to different returns in hiring for women and men. Specifically, high-achieving men are called back significantly more often than high-achieving women, which are penalized when they have a major in mathematics; this result depends on employers’ gendered standards for applicants [e.g., 101 ]. Once appointed, performance ratings are more strongly related to promotions for women than men, and promoted women typically show higher past performance ratings than those of promoted men. This suggesting that women are subject to stricter standards for promotion [e.g., 160 ].

Behavioral aspects related to gender follow two main streams of literature. The first examines female personality and behavior in the workplace, and their alignment with cultural expectations or stereotypes [e.g., 188 ] as well as their impacts on equality. There is a common bias that depicts women as less agentic than males. Certain characteristics, such as those more congruent with male behaviors–e.g., self-promotion [e.g., 189 ], negotiation skills [e.g., 190 ] and general agentic behavior [e.g., 191 ]–, are less accepted in women. However, characteristics such as individualism in women have been found to promote greater gender equality in society [ 192 ]. In addition, behaviors such as display of emotions [e.g., 193 ], which are stereotypically female, work against women’s acceptance in the workplace, requiring women to carefully moderate their behavior to avoid exclusion. A counter-intuitive result is that women and minorities, which are more marginalized in the workplace, tend to be better problem-solvers in innovation competitions due to their different knowledge bases [ 194 ].

The other side of the coin is examined in a parallel literature stream on behavior towards women in the workplace. As a result of biases, prejudices and stereotypes, women may experience adverse behavior from their colleagues, such as incivility and harassment, which undermine their well-being [e.g., 195 , 196 ]. Biases that go beyond gender, such as for overweight people, are also more strongly applied to women [ 197 ].

Organization.

The role of women and gender bias in organizations has been studied from different perspectives, which mirror those presented in detail in the following sections. Specifically, most research highlighted the stereotypical view of leaders [e.g., 105 ] and the roles played by women within firms, for instance referring to presence in the board of directors [e.g., 18 , 90 , 91 ], appointment as CEOs [e.g., 16 ], or top executives [e.g., 93 ].

Scholars have investigated antecedents and consequences of the presence of women in these apical roles. On the one side they looked at hiring and career progression [e.g., 83 , 92 , 160 , 168 , 198 ], finding women typically disadvantaged with respect to their male counterparts. On the other side, they studied women’s leadership styles and influence on the firm’s decision-making [e.g., 152 , 154 , 155 , 199 ], with implications for performance [e.g., 18 , 19 , 96 ].

Human capital.

Human capital is a transverse topic that touches upon many different aspects of female gender equality. As such, it has the most associations with other topics, starting with education as mentioned above, with career-related topics such as role , decision-making , hiring , career progression , performance , compensation , leadership and organization . Another topic with which there is a close connection is behavior . In general, human capital is approached both from the education standpoint but also from the perspective of social capital.

The behavioral aspect in human capital comprises research related to gender differences for example in cultural and religious beliefs that influence women’s attitudes and perceptions towards STEM subjects [ 142 , 200 – 202 ], towards employment [ 203 ] or towards environmental issues [ 150 , 204 ]. These cultural differences also emerge in the context of globalization which may accelerate gender equality in the workforce [ 205 , 206 ]. Gender differences also appear in behaviors such as motivation [ 207 ], and in negotiation [ 190 ], and have repercussions on women’s decision-making related to their careers. The so-called gender equality paradox sees women in countries with lower gender equality more likely to pursue studies and careers in STEM fields, whereas the gap in STEM enrollment widens as countries achieve greater equality in society [ 171 ].

Career progression is modeled by literature as a choice-process where personal preferences, culture and decision-making affect the chosen path and the outcomes. Some literature highlights how women tend to self-select into different professions than men, often due to stereotypes rather than actual ability to perform in these professions [ 142 , 144 ]. These stereotypes also affect the perceptions of female performance or the amount of human capital required to equal male performance [ 110 , 193 , 208 ], particularly for mothers [ 81 ]. It is therefore often assumed that women are better suited to less visible and less leadership -oriented roles [ 209 ]. Women also express differing preferences towards work-family balance, which affect whether and how they pursue human capital gains [ 210 ], and ultimately their career progression and salary .

On the other hand, men are often unaware of gendered processes and behaviors that they carry forward in their interactions and decision-making [ 211 , 212 ]. Therefore, initiatives aimed at increasing managers’ human capital –by raising awareness of gender disparities in their organizations and engaging them in diversity promotion–are essential steps to counter gender bias and segregation [ 213 ].

Emerging topics: Leadership and entrepreneurship

Among the emerging topics, the most pervasive one is women reaching leadership positions in the workforce and in society. This is still a rare occurrence for two main types of factors, on the one hand, bias and discrimination make it harder for women to access leadership positions [e.g., 214 – 216 ], on the other hand, the competitive nature and high pressure associated with leadership positions, coupled with the lack of women currently represented, reduce women’s desire to achieve them [e.g., 209 , 217 ]. Women are more effective leaders when they have access to education, resources and a diverse environment with representation [e.g., 218 , 219 ].

One sector where there is potential for women to carve out a leadership role is entrepreneurship . Although at the start of the millennium the discourse on entrepreneurship was found to be “discriminatory, gender-biased, ethnocentrically determined and ideologically controlled” [ 220 ], an increasing body of literature is studying how to stimulate female entrepreneurship as an alternative pathway to wealth, leadership and empowerment [e.g., 221 ]. Many barriers exist for women to access entrepreneurship, including the institutional and legal environment, social and cultural factors, access to knowledge and resources, and individual behavior [e.g., 222 , 223 ]. Education has been found to raise women’s entrepreneurial intentions [e.g., 224 ], although this effect is smaller than for men [e.g., 109 ]. In addition, increasing self-efficacy and risk-taking behavior constitute important success factors [e.g., 225 ].

Finally, the topic of sustainability is worth mentioning, as it is the primary objective of the SDGs and is closely associated with societal well-being. As society grapples with the effects of climate change and increasing depletion of natural resources, a narrative has emerged on women and their greater link to the environment [ 226 ]. Studies in developed countries have found some support for women leaders’ attention to sustainability issues in firms [e.g., 227 – 229 ], and smaller resource consumption by women [ 230 ]. At the same time, women will likely be more affected by the consequences of climate change [e.g., 230 ] but often lack the decision-making power to influence local decision-making on resource management and environmental policies [e.g., 231 ].

Research gaps and conclusions

Research on gender equality has advanced rapidly in the past decades, with a steady increase in publications, both in mainstream topics related to women in education and the workforce, and in emerging topics. Through a novel approach combining methods of text mining and social network analysis, we examined a comprehensive body of literature comprising 15,465 papers published between 2000 and mid 2021 on topics related to gender equality. We identified a set of 27 topics addressed by the literature and examined their connections.

At the highest level of abstraction, it is worth noting that papers abound on the identification of issues related to gender inequalities and imbalances in the workforce and in society. Literature has thoroughly examined the (unconscious) biases, barriers, stereotypes, and discriminatory behaviors that women are facing as a result of their gender. Instead, there are much fewer papers that discuss or demonstrate effective solutions to overcome gender bias [e.g., 121 , 143 , 145 , 163 , 194 , 213 , 232 ]. This is partly due to the relative ease in studying the status quo, as opposed to studying changes in the status quo. However, we observed a shift in the more recent years towards solution seeking in this domain, which we strongly encourage future researchers to focus on. In the future, we may focus on collecting and mapping pro-active contributions to gender studies, using additional Natural Language Processing techniques, able to measure the sentiment of scientific papers [ 43 ].

All of the mainstream topics identified in our literature review are closely related, and there is a wealth of insights looking at the intersection between issues such as education and career progression or human capital and role . However, emerging topics are worthy of being furtherly explored. It would be interesting to see more work on the topic of female entrepreneurship , exploring aspects such as education , personality , governance , management and leadership . For instance, how can education support female entrepreneurship? How can self-efficacy and risk-taking behaviors be taught or enhanced? What are the differences in managerial and governance styles of female entrepreneurs? Which personality traits are associated with successful entrepreneurs? Which traits are preferred by venture capitalists and funding bodies?

The emerging topic of sustainability also deserves further attention, as our society struggles with climate change and its consequences. It would be interesting to see more research on the intersection between sustainability and entrepreneurship , looking at how female entrepreneurs are tackling sustainability issues, examining both their business models and their company governance . In addition, scholars are suggested to dig deeper into the relationship between family values and behaviors.

Moreover, it would be relevant to understand how women’s networks (social capital), or the composition and structure of social networks involving both women and men, enable them to increase their remuneration and reach top corporate positions, participate in key decision-making bodies, and have a voice in communities. Furthermore, the achievement of gender equality might significantly change firm networks and ecosystems, with important implications for their performance and survival.

Similarly, research at the nexus of (corporate) governance , career progression , compensation and female empowerment could yield useful insights–for example discussing how enterprises, institutions and countries are managed and the impact for women and other minorities. Are there specific governance structures that favor diversity and inclusion?

Lastly, we foresee an emerging stream of research pertaining how the spread of the COVID-19 pandemic challenged women, especially in the workforce, by making gender biases more evident.

For our analysis, we considered a set of 15,465 articles downloaded from the Scopus database (which is the largest abstract and citation database of peer-reviewed literature). As we were interested in reviewing business and economics related gender studies, we only considered those papers published in journals listed in the Academic Journal Guide (AJG) 2018 ranking of the Chartered Association of Business Schools (CABS). All the journals listed in this ranking are also indexed by Scopus. Therefore, looking at a single database (i.e., Scopus) should not be considered a limitation of our study. However, future research could consider different databases and inclusion criteria.

With our literature review, we offer researchers a comprehensive map of major gender-related research trends over the past twenty-two years. This can serve as a lens to look to the future, contributing to the achievement of SDG5. Researchers may use our study as a starting point to identify key themes addressed in the literature. In addition, our methodological approach–based on the use of the Semantic Brand Score and its webapp–could support scholars interested in reviewing other areas of research.

Supporting information

S1 text. keywords used for paper selection..

https://doi.org/10.1371/journal.pone.0256474.s001

Acknowledgments

The computing resources and the related technical support used for this work have been provided by CRESCO/ENEAGRID High Performance Computing infrastructure and its staff. CRESCO/ENEAGRID High Performance Computing infrastructure is funded by ENEA, the Italian National Agency for New Technologies, Energy and Sustainable Economic Development and by Italian and European research programmes (see http://www.cresco.enea.it/english for information).

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Higher research productivity = more pay? Gender pay-for-productivity inequity across disciplines

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• Volume 128 , pages 1395–1407, ( 2023 )

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• Charissa Samaniego 1 ,
• Peggy Lindner 2 ,
• Maryam A. Kazmi 1 ,
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• Dejun Tony Kong 4 ,
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• Christiane Spitzmueller   ORCID: orcid.org/0000-0003-0549-0259 1 , 5  

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Gender pay equity for academics continues to be elusive. Adding to scholarship around structural barriers to gender equity in academic settings, we investigate the link between scholarly performance and compensation. We expect high research productivity to be differentially associated with compensation outcomes for men and women. Building on social role theory, we hypothesize that these relationships are contingent upon whether researchers are inside or outside of Science, Technology, Engineering, and Mathematics (STEM). Using the h-index, compensation, and researcher demographics for 3033 STEM and social and behavioral sciences (SBS) researchers from 17 R1 universities, we applied multilevel modeling techniques and showed that cumulative research productivity was more strongly related to compensation for men versus women researchers. However, these effects only held in STEM disciplines but not in SBS disciplines. Based on these results, we recommend that institutions consider changing how pay analyses are conducted and advocate for adding explicit modeling of scientific performance-compensation links as part of routine pay equity analyses.

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The pervasive under-representation of women researchers, specifically in tenured and tenure-earning faculty positions in Science, Technology, Engineering and Mathematics (STEM) (Bilen-Green et al., 2008 ; Lariviere et al., 2013 ; Shen, 2013 ), along with various challenges women face in their academic career progression (Bedi et al., 2012 ; Clauset et al., 2015 ; Edmunds et al., 2016 ; Handelsman et al., 2005 ; Moss-Racusin et al., 2012 ; Quadlin, 2018 ), calls for continued research on gender equity in academic settings. One important form of gender inequity is pay inequity. Academic researchers are expected to be paid equitably based on their research productivity (i.e., pay-for-productivity). Nonetheless, are men and women really paid equally for the same level of research productivity? Or is pay-for-productivity just a myth for women in tenured and tenure track faculty positions? If gender inequity of pay-for-productivity exists, women are likely discouraged to continue their careers in academia, which may help explain the “leaky pipeline” (Clark Blickenstaff, 2005 ) problem seen in STEM as compared to Social and Behavioral Sciences (SBS) disciplines. To date, many studies only examine gender differences in academic salary while controlling for productivity (Bellas, 1997 ; Euwals & Ward, 2005 ; Ginther, Donna K. & Hayes, Kathy J., 2003 ; Umbach, 2007 ) and the results are mixed, leaving gender differences in the strength of the pay-for-productivity relationship unexamined. In other words, it is unclear if the gender pay gap depends on a faculty member’s productivity level. Drawing from theory and research on social roles, we further examine gender differences in pay-for-productivity in STEM and SBS disciplines.

In the present research, we aim to address three questions regarding pay-for-productivity in academic settings: (1) whether, and if so, how strongly, research productivity is positively related to researcher pay (i.e., the intensity of pay-for-productivity), (2) whether productivity is more strongly tied to pay for men than for women (i.e., interaction of gender and pay-for-productivity), and (3) whether gender inequity of pay-for-productivity, if any, is more severe in the STEM disciplines than in the SBS disciplines (i.e., disciplinary difference in gender inequity of pay-for-productivity).

Pay-for-productivity

Pay-for-productivity, from a work motivation perspective, is deemed fair by many workers and motivates them to achieve desired results (Lawler, 1971 ; Maier, 1955 ). Meta-analytic studies suggest performance-contingent pay is among the best methods for boosting performance levels (Rynes et al., 2004 , 2005 ). In academic institutions classified as R1 by the Carnegie Classification of Institutions of Higher Education, research constitutes the most important job responsibility and is a significant factor determining tenure success, promotions, and pay raises across a host of academic disciplines (Fairweather, 2005 ). Thus, besides their intrinsic motivation, academic researchers’ extrinsic motivation to produce research is, to some degree, driven by the extent to which their research productivity is linked to their pay. The University of Arkansas for Medical Sciences introduced a performance-based incentive plan for its College of Medicine in 2005 (Reece et al., 2008 ). With faculty pay directly linked to productivity, performance increased drastically, leading to a total compensation increase of about 20%, in addition to increases in external funding and researchers’ morale and satisfaction (Reece et al., 2008 ).

Some previous studies focused on whether men and women researchers receive equal pay while controlling for factors such as academic ranks, leadership positions (Jagsi et al., 2012 ), and raises (Lindley et al., 1992 ) as proxies for research productivity. Others have controlled productivity by controlling for the number of publications (e.g., number or articles or books; Bellas, 1997 ; Euwals & Ward, 2005 ; Ginther et al., 2003 ; Levin & Stephan, 1998 ; Umbach, 2007 ), without any measure of quality of the publications. In contrast, we explicitly measure research productivity with h-index and investigate whether higher research productivity (and quality) translates into higher pay to the same extent for men and women in academia (i.e., pay-for-productivity). A researcher’s h- index has become one of the most widely used and common metrics to quantify scholarly productivity. Introduced 15 years ago by Hirsch, it refers to the number of publications ( h ) that have received at least h citations each (Hirsch, 2005 ). For example, a researcher who has ten publications with at least ten citations (with all other publications having less than ten citations each), would have an h -index of 10. Although the popularity of this index has skyrocketed, researchers have acknowledged its’ shortcomings including: the susceptibility of inflation due to self-citations (Bartneck & Kokkelmans, 2011 ; Zhivotovsky & Krutovsky, 2008 ), favoring more established researchers (Hirsch, 2005 ), no adjustment for multiple-authorship or order of authors, and no normalization of differential citation practices between disciplines (Alonso et al., 2009 ). Regardless of these drawbacks, the h -index is a single, easily calculable number that incorporates both a measure of quantity in the number of publications, and a proxy for quality in terms of number of citations, and is widely used as a decision-making tool within higher education for hiring and tenure (Barnes, 2017 ; Scruggs et al., 2019 ). Therefore, its effect on compensation should be examined to determine the full utility of this metric.

Hypothesis 1

Research productivity is positively related to researcher salary in STEM and SBS disciplines.

Gender differences in pay-for-productivity

Researchers who identify as men earn around 20% more than their women peers (Carlin et al., 2013 ; Jagsi et al., 2012 ; Lindley et al., 1992 ). Despite shifts in the distribution of men and women researchers in faculty rank, the gender pay gap has not diminished in the last 10 years. In 2020, on average across all disciplines, assistant professors who identify as women make $7605 less than their peers who identify as men, and this difference more than doubles at the full professor level, with women full professors making $19,030 less than full professors who are men ( The Annual Report on the Economic Status of the Profession, 2019–2020 , 2020). Disparities between disciplines may partly explain these gender differences as higher paying disciplines (i.e., biological sciences, engineering, and mathematics) tend to have more researchers who are men versus lower paying disciplines (i.e., English, sociology, and gender studies) with more women researchers(Shulman et al., 2017 ). However, even in disciplines with a high proportion of women, there is still gender pay inequity and thus differences in average discipline pay cannot entirely explain gender pay inequity. One study reported men in disciplines one standard deviation above the mean in representation of women will earn approximately $75,0000 versus women earning $69,000 (Umbach, 2007 ).

Another partial explanation for gender pay inequity has focused on the “productivity puzzle” of women having lower average productivity levels (Cole & Zuckerman, 1984 ; West et al., 2013 ; Xie & Shauman, 1998 ). A plethora of contributing factors have been examined to possibly explain women’s lower productivity levels including family responsibilities (Ceci & Williams, 2011 ; Fox, 2005 ; Hunter & Leahey, 2010 ), resource allocations (Duch et al., 2012 ), and research specialization (Leahey, 2006 ). However, recent analyses of archival data suggest no gender differences in journal acceptance of publications, nor in productivity levels when controlling for structural differences, implying that when given equal resources, men and women publish equally well (Ceci & Williams, 2011 ; Huang et al., 2020 ). While investigating gender differences in productivity levels is an important research topic, in the current study we are not examining why differences may occur, but instead if men and women are paid equitably for their individual productivity level. Research on whether the gender salary gap in academia disappears after controlling for productivity is mixed (Bellas, 1997 ; Euwals & Ward, 2005 ; Ginther et al., 2003 ; Umbach, 2007 ). Only one study to date has examined gender differences in pay-per-performance relationship in specific STEM disciplines (physics, earth science and physiology), and found women were paid more per publication than men, but only for physics (Levin & Stephan, 1998 ). In addition to the data being from the 1970’s, the authors only examined the change in salary in a two-year period, likely missing crucial overall salary differences.

Gender differences in pay-for-productivity can manifest in two ways. First, social role theory grounded expectations for women’s performance may emphasize their communal roles as mentor, rather than their productivity or agentic characteristics (Cejka & Eagly, 1999 ; Koenig & Eagly, 2014 ). In cases where women do not adhere to gender role expectations, social role theory grounded expectations may still lead them to be perceived as less productive and competent and perceived as having lower status than men (England, 1992 ; Heilman, 2001 ); therefore, women are not paid as much as men when they perform well. Second, although women are encouraged to negotiate their salary and other employment terms, compared to men, women researchers’ salary negotiations or requests for salary adjustments are less likely to succeed (Leibbrant & List, 2015 ). Women tend to anticipate backlash for their salary negotiation/request attempts; therefore, they may either opt to not initiate their salary negotiations/requests or lower their aspirations if they decide to do so (Amanatullah & Morris, 2010 ; Amanatullah & Tinsley, 2013 ). Women’s salary negotiation attempts are sometimes viewed as aggressive acts, and frequently invite hostile reactions from others (Rudman et al., 2012 ). Because of gender bias in salary negotiations disfavoring women, we argue that research productivity does not translate into women researchers’ pay as much as men researchers’ pay.

In the current study we focus on research productivity in STEM and SBS fields and examine the gender differences in the strength of pay-per-productivity, that is look at gender differences in the relationship between h-index and salary (not just changes in salary). Looking at gender differences in pay-per-productivity, allows us to examine if gender pay inequity differs across levels of productivity. If women are paid according to stereotypes, then women who have low productivity will be paid the correct amount, but high producing women will be underpaid because they are assumed to be underproductive (i.e., perceived productivity mismatches actual productivity). Thus, we expect that there will be gender salary differences at high performance levels and not at low performance levels.

Hypothesis 2

The link between research productivity and researcher salary is stronger among men researchers than among women researchers. Such that, men are paid more per h-index and gender pay inequity is larger at higher levels of productivity.

STEM vs SBS

Our final inquiry pertains to the disciplinary difference in gender inequity of pay-for-productivity. If this inequity does exist, does it vary across academic disciplines? Specifically, is the hypothesized inequity more severe in disciplines where women are traditionally under-represented than in other disciplines? Women are less likely to enter STEM, feel less welcomed in these disciplines, and are less likely to stay in tenure or tenure-earning positions in these disciplines (Clauset et al., 2015 ; Edmunds et al., 2016 ; Handelsman et al., 2005 ). Furthermore, some evidence suggests that the gender pay gap is larger in STEM disciplines (Umbach, 2007 ; Xu, 2015 ) than in other disciplines, even when researchers control for gender differences in productivity. We postulate women having difficulty to effectively negotiate compensation to be more pronounced in STEM disciplines than in other disciplines such as social and behavioral sciences (SBS) where we expect this gender inequity to be less severe.

In support of our expectations, social role theory (Eagly, 1987 ) suggests that gender roles prescribe what men and women should be like and provide gendered rules and norms based on which behaviors are judged and rewarded or socially sanctioned. Men are expected to be achievement-oriented, competitive, and analytic, whereas women are expected to be warm, considerate, and accommodating (Eagly & Karau, 2002 ; Heilman, 2001 ). Women are not expected to pursue STEM; instead, they are more expected to pursue SBS such as psychology, communication, sociology, etc. (Clark Blickenstaff, 2005 ; Handelsman et al., 2005 ). Women in STEM disciplines violate such gender role expectations and thus face unfavorable evaluations and other social sanctions. In contrast, women researchers in SBS disciplines are less likely to violate gender role expectations and thus may face fewer negative consequences. Such gender role expectations are particularly strong in fields dominated by men such as STEM disciplines as the norms are shaped by men. Women researchers who are achievement-oriented, competitive, and analytic inevitably violate gender role expectations and thus face social sanctions including unfavorable evaluations and social exclusion. These gender role expectations coupled with stereotypes of women as low performers could result in lower female salaries relative to male salaries, but only for high performing women in STEM disciplines, as women with lower productivity are meeting prescriptive gender stereotypes. Thus, we would expect stereotyping of productivity and gender differences in negotiation tactics to affect the salaries of highly productive women in academic STEM disciplines.

Hypothesis 3

The gender difference in the link between research productivity and researcher salary is larger in STEM versus SBS disciplines.

Materials and methods

We collected research productivity and salary data of 3033 tenured and tenure-earning faculty members from 17 universities across the United States. Department chairs were excluded from the analyses. Our criteria for the university selection were based on a study conducted for a National Science Foundation ADVANCE institutional transformation project. The selected data collection sites were large public universities in urban settings that were classified as R1 institutions (i.e., highest research activity by the Carnegie Classification of Institutions of Higher Education). Among these universities, we selected those that made salary data publicly available. In the first step, coders manually searched department websites of all 17 universities, and created a database combining researchers’ gender and discipline information and their demographic information retrieved from their publicly available CVs. In the second step, we used an automated approach to scrape each researcher’s research productivity information ( h -index) from Google Scholar, and collected salary data from websites reporting current 9-month faculty salaries.

The coders utilized a combination of photographs available on departmental websites and names to code each researcher’s gender (1 = woman, 0 = man).

Research productivity

Research productivity was indicated by the h -index in 2019 (Hirsch, 2005 ), which was scraped from each tenured and tenure-earning faculty member’s Google Scholar website. The h -index is the most used metric for research productivity, with h being the number of papers a researcher has authored or co-authored that has accumulated at least h citations (Hirsch, 2005 ).

We collected the 9-month faculty salary data from various websites containing university-published current faculty salaries, as noted earlier.

We controlled for the number of years since the attainment of Ph.D. (i.e., post-Ph.D. years) at the individual level and the following department level controls by utilizing group-mean centering in our multilevel models: proportion of women in department, average department years since the attainment of Ph.D. (i.e., post-Ph.D. department tenure); and mean of h -indices within each department. Our random intercepts multilevel model inherently controlled for the average salary level of the department. We controlled for post-Ph.D. years to ensure that salary increases were attributed to increases in research productivity rather than just researchers’ tenure in their discipline. Our multilevel controls ensured we controlled for university and discipline differences because department averages will be affected by both.

Descriptive statistics

Table 1 presents descriptive statistics and correlations among post-Ph.D. years, the h -index, and salary. Correlations are presented separately for men and women researchers. The average amounts of men and women researchers’ salary were $133,092.40 and $118,459.20, respectively. Women, on average, made 89 cents for every dollar made by men. With 95% confidence, the average salary for men was $10,850.63 to $18,415.71 more than that of women researchers (i.e., 9.16% to 15.55% more than the average salary for women). Gender difference in the h -index may partially explain this gender gap of salary. With 95% confidence, we found that men’s average h -index was 5.32 to 8.33 higher than that of women. The gender difference in the h -index could partially be explained by the gender difference in post-Ph.D. years. Also, with 95% confidence, we found that men had 3.80 to 5.51 more post-Ph.D. years than women.

Multilevel regression analyses

We tested our hypotheses by conducting multilevel regression analyses, given that our data were nested within academic departments (e.g., Psychology department at the University of Houston). We centered gender, post-PhD years, and h-index by their respective group (department) means (Enders & Tofighi, 2007 ) (mean of gender is a proportion). In all reported models, for the sake of parsimony, we did not enter the department means of gender, post-Ph.D. years, and the h -index as predictors because (a) we did not hypothesize the effects of these department means, and (b) inclusion or exclusion of these department means did not change the result patterns, presumably because we group-mean centered. The ICC of salary estimate of 22.47% (i.e., 22.47% of the variance in salary could be explained by cross-department differences) further justified our use of multi-level regression analyses. Department-level salary variability can be explained by both university and discipline differences. Table 2 presents the results of the multi-level regression analyses, with profile confidence intervals being reported in the main text. The baseline model included two control variables: post-Ph.D. years and gender (1 = woman, 0 = man), with the former being a significant predictor of salary ( B  = 2,186.66, t  = 35.22, p  < 0.01).

In line with Hypothesis 1, researchers’ h- index, indicative of their research productivity, was positively related to their salary level (see Model 1, Table 2 ). On average, a one-point increase in the h -index translated into a salary increase of $1,000.46 ( t  = 22.17, p  < 0.01), with its 95% confidence interval [$912.01, $1,088.90]. We did not find support for Hypothesis 2. Specifically, the interaction between gender and the h -index was not significant (Model 2: B  =—120.70, t  = -1.17, p  = 0.24). In other words, pay-for-productivity did not differ significantly between men and women researchers when examining both STEM and SBS discipline simultaneously. Finally, we found support for Hypothesis 3 regarding gender inequity of pay-for-productivity in STEM versus SBS disciplines; the three-way interaction among gender, the h -index, and academic discipline dummy (STEM vs. SBS) was negatively related to researchers’ salary level (Model 3: B  = -397.75, t  = − 1.86, p  = 0.063).

We then probed the two-way interaction between gender and the h -index separately for STEM and SBS disciplines. For the latter, gender inequity of pay-for-productivity was not significant ( B  = 141.80, t  = 0.76, p  = 0.45). However, for the former, pay-for-productivity was unfavorable to women versus men ( B  = -266.66, t  = -2.13, p  = 0.03). On average, in STEM disciplines, men were paid $266.66 (95% confidence interval [$20.95, $512.61]) more than women for each one-point increment in h -index. Figure  1 shows the interaction between gender and the h -index for both STEM (Fig.  1 a) and SBS (Fig.  1 b) disciplines using group mean centered variables. As demonstrated, for STEM disciplines, as h -index increases, predicted salary for men is higher than for women.

Relationship between h-index and salary for STEM and SBS researchers. Plots were generated using group mean centering for h-index and gender. Ranges for both axes have been fixed to allow for comparison

The present research reveals gender inequity of pay-for-productivity in STEM disciplines. Consistent with work motivation theories (Rynes et al., 2004 , 2005 ), we did find that researchers’ salary is coupled with their research productivity as intended, but this pay-productivity coupling was more favorable to men versus women, particularly in STEM disciplines. It is interesting to note that previous research demonstrated high performing women in STEM may need to overcompensate (i.e., build more relationships, acquire more knowledge, or put in more research hours) to achieve the same level of productivity indicators as their male colleagues (Aguinis et al., 2018 ). Thus, not only is the road to becoming a “star” performer more difficult for women, they may not also see the same returns in compensation for their research investments. Women researchers in STEM with a h-index of 49 (one standard deviation above the mean) made around six thousand dollars less than men researchers in STEM with the same h-index. Our study did not follow researchers longitudinally, but we can tentatively extrapolate how a six-thousand-dollar salary gap can add up over the years (i.e., over a ten-year-period this difference would add up to sixty-thousand-dollars). Depending on how their h-index develops over one’s career, a highly productive woman researcher in STEM could experience even more pay inequity.

As with any paper, our study is not without limitations. In contract to studies examining pay differences in non-Western cultural contexts (Takahashi et al., 2018 ) our study focused on North American academics, we expect basic social psychological processes grounded in role theory expectations and gender differences in negotiation behaviors and negotiation outcomes to be similar across cultural contexts. However, in countries where compensation is more strongly driven by federally or locally imposed pay rates, productivity-compensation differences should be weaker across gender. We recommend subsequent research account for cultural contexts and structural differences in compensation structures in academic settings to examine the external validity of our findings across cultural contexts. Also note that in our paper, we aimed to determine linear relationships between productivity and compensation and the moderating role of gender. Hence, for more nuanced analyses, including analyses of star performers’ performance (Aguinis et al., 2018 ) and compensation, or non-linear effects to be determined, we recommend researchers build large, multi-university consortium structures to access large enough data sets to conduct meaningful analyses of a non-linear nature or on subsets (e.g. star performers, faculty of color, faculty with intersectional identities).

Our finding renders support for funding agencies’ (i.e., National Science Foundation) efforts for reducing gender inequity in STEM disciplines (Ceci & Williams, 2011 ) and yet reveals the lingering challenge inherent in these efforts. Given that our analyses relied on archival data, we could not accurately code the race/ethnicity of researchers and thus did not include this demographic factor in our analyses. However, we speculate that pay-for-productivity may further disadvantage those with intersectional identities, such as women of color in STEM disciplines. Given that our focus was on determining whether there is a gender inequity of pay-for-productivity across disciplines, we offer some plausible explanations without testing these explanatory mechanisms. Future research should hence shed light on these possible mechanisms to ultimately identify ways to close gaps. For example, why, when, and how pay-for-productivity relationships are weaker for women in STEM may be a result of fewer women attempting to continuously renegotiate their salary. Alternatively, men may be more likely to seek offers from other institutions and their salary may benefit as a result. Last, it may be possible that women’s attempts to renegotiate their salary based on incremental performance results in negative reactions from administrators at the departmental, college, and university levels.

In our analyses we used the h -index as an indicator of research productivity. We encourage future researchers aiming the productivity-pay link to use broader or supplemental indices of productivity, such as external funding records and total citations. Even though the h -index is a widely known metric for research productivity and is used as a decision-making tool, it is not without weaknesses. For instance, intentional manipulation of the h -index by researchers through self-citations or inclusion of work authored by others may render the metric problematic for exclusive use as a research productivity indicator.

We further urge universities to regularly conduct internal analyses to adjust potential gender inequity of pay-for-productivity. Likewise, professional associations in STEM disciplines should regularly conduct such analyses to reduce the more limited pay-for-performance relationships we observed for women in our study. Notably, we do not intend to assert that the h -index should be treated as the benchmark for research productivity, as it is not problem- or concern-free. However, the h -index is to the measurement of scholarly productivity what democracy is to forms of government: the least problematic. We also urge universities to continuously assess whether high levels of research productivity translate into high pay at similar rates for men and women—the alternative may be to continue to lose women scientists despite high productivity levels and potential. The dearth of women, especially in senior academic/faculty positions in STEM, continues to pose a significant challenge for the science and technology workforce in the twenty-first century. To attract more women to enter STEM disciplines and help them be more engaged and thrive in these disciplines and their organizations, universities should, first and foremost, effectively address the ostensibly “sticky” problem of gender inequity of pay-for-productivity.

Data availability

All data used in this analysis can be found at: https://osf.io/6drsp/?view_only=d92db8841232491baaa107d0bd96c873 .

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We received funding from the National Science Foundation in support of this research (ADVANCE Institutional Transformation Grant #1409928, 2014–2019). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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Samaniego, C., Lindner, P., Kazmi, M.A. et al. Higher research productivity = more pay? Gender pay-for-productivity inequity across disciplines. Scientometrics 128 , 1395–1407 (2023). https://doi.org/10.1007/s11192-022-04513-4

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Why the Gender Pay Gap Persists in American Businesses

By Molly Mitchell

Women have progressed a lot in terms of workplace gender equity since the days of Rosie the Riveter, but elements of inequity remain stubbornly in place. In 2024, for example, women still earn around 84 cents for every dollar a man earns for the same job on average in the US – almost the same as it was twenty years ago.

The Darden Report recently caught up with Professor Allison Elias , author of “ The Rise of Corporate Feminism ,” to explore the history of this continuing gender pay gap, where things stand today and new research on this dynamic.

Allison Elias’s 2022 book, “The Rise of Corporate Feminism,” was named a Best Summer Book of 2023: Business by the Financial Times .

What is the gender pay gap?

The gender pay gap refers to the difference in earnings between women and men. Specifically, it is the ratio of women’s to men’s median earnings, according to the U.S. Census Bureau, for full-time workers. And importantly, the often-cited 80 percent statistic provides an incomplete picture of women’s experiences in the labor market since the gap is exacerbated for many women of color. Hispanic and Black women experience the largest gaps relative to white, non-Hispanic men.

Why does the gender pay gap happen?

There are many reasons that the gender pay gap exists. Economists label these reasons as supply side (women’s choices) and demand side (employers’ choices), although it can be difficult to untangle the two or categorize them neatly as one or the other.

Traditionally, women have had lower educational attainment, been segregated into jobs that paid lower wages and had less continuous experience in the labor force. But we cannot attribute these trends to women’s choices alone. Legal constraints, economic structures and gender norms have also played a role in shaping women’s preferences and choices. Sociologists may even argue that career preferences emerge in childhood from gender-specific socialization processes.

On the demand side, gender discrimination (at the point of hire and beyond) has contributed to lower pay and fewer promotional opportunities for women. However, it is difficult to measure the extent to which implicit and explicit attitudes of employers account for the wage gap.

Do certain professions/fields experience the gap more than others?

The gender pay gap tends to increase as pay increases, in part because the minimum wage creates a floor for lower earners. People in managerial and professional work, where jobs are more gender integrated, see higher wage gaps than those in jobs requiring a high school degree.

Regarding MBA graduates, the gender wage gap tends to increase over time. Researchers at one top program examined multiple cohorts of MBA graduates 13 years following graduation and found that parenthood impacted women’s earnings more so than men’s. At 13 years out from graduation, women were earning 56 percent of what their male classmates earned. Factors like taking time away from work and working even a few hours fewer per week were found to have tremendous impact on women’s earnings later in their careers. Caregiving responsibilities have a negative influence on women’s earnings (e.g., the motherhood penalty), whereas men have been shown to actually earn more upon becoming fathers! For those in the highest-paid jobs, the returns for what sociologists call overwork are huge, and contribute significantly to sustaining the wage gap.

At a more micro level, we also know from experimental research in social psychology that women receive less credit—and also claim less credit—for their work when engaged in joint tasks with men. I have a recent paper coauthored with Jirs Meuris at Wisconsin where we examine almost two decades of data to demonstrate the effect on the gender wage gap of a job’s interdependence, meaning the extent to which a job requires working on a team or coordinating with others. Over time and across industries and occupations, jobs that are rated as more interdependent, meaning they require two or more people to sequentially complete tasks, have higher gender wage gaps.

This makes sense given what we know from social psychology about credit for joint work: In mixed gender groups, women receive and claim less credit, which could influence reward allocation. But also, we find that the gender of the task matters. The gender wage gap is exacerbated in male-dominated occupations and is lessened in female-dominated occupations.  Rewarding individual contributions in interdependent work settings is more complex and can sustain and worsen gender inequality, particularly in traditionally male settings.

Managers who wish to address this trend should revisit their performance evaluation systems, which were likely designed with independent work in mind. With increasing numbers of employees engaged in interdependent jobs, managers need to find new ways to evaluate individual contributions and rely on multiple sources when determining rewards.

How much progress towards equity have we made? 

Since 1960 the gap has narrowed, although it has hovered around 80 percent for several decades. Despite continuing inequities, women are more likely to graduate from high school, graduate from college and earn master’s degrees. They earn half of all doctorates. In MBA programs, women represent 47 percent of those receiving graduate business degrees from U.S. business schools (in 2020)—a significant increase from less than 5 percent in 1970.

Furthermore, women have gained control over reproduction with the dissemination of a birth control pill, and age at first marriage has continued to rise along with the percentage of women who prioritize career success. These factors are interrelated: investment in education—and interest in career advancement—becomes more attractive for women who have more control over family planning.

While there is much progress in educational attainment, the pay gap is largest in the highest-paid jobs that demand overwork, which economist Claudia Goldin calls “greedy jobs.” Jobs that are highly compensated, such as finance or corporate law, pay disproportionately more on a per-hour basis when they require more time (more than 40 hours a week) and offer less flexibility. A gender pay gap is sustained in these jobs because women are more likely to choose a more flexible path that does not have such high rewards for overwork. Goldin, who recently won the Nobel Prize, calls this issue the “last chapter” in the converging economic roles of men and women.

I have a forthcoming case with economist Peter Debaere about Goldin’s work, which uses protagonists from both of our books, “To America and Back Again” (English for: “Naar jouw Amerika en terug”), and “The Rise of Corporate Feminism,” to illustrate certain historical trends in women’s labor force participation.

Important to note is that even though women in the highest-paid work face the highest wage gap penalties, in general women remain overrepresented in the lowest-paying occupations. And occupations with greater proportions of women tend to pay less even when controlling for educational and skill requirements. Occupational gender segregation intersects with race and ethnicity. As of 2019, white men were overrepresented in jobs with the highest pay (e.g., physician, chief executive, financial investment, pilot, architect) and women (white, Black and Latina), as well as Black and Latino men, were overrepresented in jobs with the lowest pay (e.g., food service, childcare, cashier). So while the gender wage gap is lower among those with less education, occupational segregation remains high in those jobs.

What practical policies or actions are most effective in closing the gender wage gap?

It is difficult to declare one specific remedy for the gender wage gap. Recommendations usually target change at the individual or organizational level while governments are also forwarding interventions. For individuals, there has been much emphasis on women’s propensity (or lack thereof) to negotiate their starting salaries, particularly with the publication and dissemination of “Women Don’t Ask,” a groundbreaking book from 2003.

Recent research using MBA data from management professors Laura Kray, Jessica Kennedy and Margaret Lee suggests that actually women do ask, and the wage gap for this population is no longer an individual-level phenomenon. Instead, organizations and governments should advance solutions, and there is promise in at least two remedies: banning salary history and promoting pay transparency.

Given the historic lack of pay transparency in the private sector, companies are increasingly opting to perform audits to try to ensure pay equity regardless of gender or race. And states are adopting laws to ban an employer’s questions about a candidate’s previous salary, which has been shown to improve salary outcomes for women and underrepresented minorities. Under consideration at the federal level is the Paycheck Fairness Act, which would expand coverage for equal pay and also ban salary history considerations and promote pay transparency.

The University of Virginia Darden School of Business prepares responsible global leaders through unparalleled transformational learning experiences. Darden’s graduate degree programs (MBA, MSBA and Ph.D.) and Executive Education & Lifelong Learning programs offered by the Darden School Foundation set the stage for a lifetime of career advancement and impact. Darden’s top-ranked faculty, renowned for teaching excellence, inspires and shapes modern business leadership worldwide through research, thought leadership and business publishing. Darden has Grounds in Charlottesville, Virginia, and the Washington, D.C., area and a global community that includes 18,000 alumni in 90 countries. Darden was established in 1955 at the University of Virginia, a top public university founded by Thomas Jefferson in 1819 in Charlottesville, Virginia.

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Molly Mitchell Associate Director of Content Marketing and Social Media Darden School of Business University of Virginia [email protected]

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Research: Gender Pay Gaps Shrink When Companies Are Required to Disclose Them

• Morten Bennedsen,
• Elena Simintzi,
• Margarita Tsoutsoura,
• Daniel Wolfenzon

Results from a study of Danish companies.

Government-mandated reporting of gender pay discrepancies has been a subject of much debate in the last 5-10 years. Those arguing for this legislation argue that it will help to address the persistent gender wage gap. Opponents insist that not only is that unlikely; it will also increase companies’ administrative burden and decrease profits. Until recently there has been no strong evidence to support either side. However, researchers have just conducted the first empirical study on the impact of mandatory wage transparency. That study’s results suggest that disclosing disparities in gender pay does in fact narrow the gender wage gap. The results showed that from 2003 to 2008, the gender pay gap at mandatory reporting firms shrank 7%, from 18.9% to 17.5%, while the gap at control firms stayed steady at 18.9%. This improvement came without a negative effect on firms’ net income.

Government-mandated reporting of gender pay discrepancies has been a subject of much debate in the last 5-10 years. Those arguing for legislation to require such reporting say that it will help to address the persistent gender wage gap. Opponents insist that not only is that unlikely; it will also increase companies’ administrative burden and decrease profits. Until recently there has been no strong evidence to support either side.

• MB Morten Bennedsen is André and Rosalie Hoffmann Chaired Professor at INSEAD and Niels Bohr Professor at University of Copenhagen and the Center for Economic and Policy Research.
• ES Elena Simintzi is an assistant professor of finance at the University of North Carolina Kenan-Flagler Business School and the Center for Economic and Policy Research.
• MT Margarita Tsoutsoura is an associate professor of finance at Cornell University and the National Bureau for Economic Research.
• DW Daniel Wolfenzon is Stefan H. Robock Professor of Finance and Economics at Columbia Business School and the National Bureau for Economic Research.

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Gender in the Economy - Areas of Research

Areas of research.

The Study Group will emphasize a number of central topics regarding Gender in the Economy. These include:

1. Victimization, Vulnerability, and Violence against Women . One of the basic differences between men and women is men’s often monopoly on violence. Topics include domestic violence; how women’s geographic mobility is hindered and its economic consequences; patriarchy historically considered; greater financial security as a means to reduce victimization and violence; bargaining in households; harassment and violence in the workplace.

2. Household Finance Issues . Household finance is an expansive subject area in developing and developed nations. The topics include the role of mobile money; bargaining in households; financial literacy of women; access to bank accounts and credit; women’s empowerment as flowing from financial security; the impact of women’s property rights for financial investment decisions; control over money in household bargaining and marital dissolution.

3. Women’s Wellbeing and Children’s Health . Women now live a lot longer than do men in most parts of the world. They didn’t always, and in some parts of the world today, they still do not. Topics here include maternal mortality, contraception, abortion (particularly sex selective), and AIDS. Access to family planning services cuts across all nations and time periods. Changes in health risks due to women’s increased economic roles and more risky behaviors are also important.

4. Women and Education across the World . An irony in the study of gender differences is the remarkable increase in women’s levels of higher education at the same time that gender differences in earnings and employment remain substantial. Still, many of the world’s women struggle to obtain minimal levels of education. This expansive subject area includes returns to education, reasons for barriers to girl’s education in some nations, how gender gaps in the labor market are responding to relative skill levels, and college majors of women and men.

5. U-Shaped Female Labor Force Function across Economic Development and History. It is well known that across a host of nations, market (paid) employment of women traces out a U-shape. But nations often get stuck at the lower level due to persistent social norms, traditions, stigmas, and other ways in which women are limited in their ability to grate out of the home and into the world of paid employment. Topics include barriers to labor force participation and employment, paid versus unpaid labor, self-employment, social norms, structural change.

6. Gender Earnings Gaps . The gap between men’s and women’s earnings exists across the income distribution and the education distribution. But the gap is generally far greater for higher earners and for those with more education. Yet, the economic hardship is generally greater at the bottom. Topics include the role of time controllability and compensating differentials; discrimination in pay in a host of circumstances; women’s bargaining skills; how the gender gap feeds into women’s vulnerability; how firm-level and political leadership impact these gaps; feedback mechanisms between household’s decisions and the labor market.

7. Women-Centered Policies, Child-Centered Policies, and Missing Fathers . Much of the world (even developing nations) has embraced paid parental leave. Early education in enabling women’s work and benefitting children is an important topic throughout the world. Interdependencies between these two policies and their political economy are important to study. Topics include parental leave policy, especially programs that incentivize fathers to use them; firm-level policies, especially in developed countries. In developing countries, possible topics include how migration and decline in multi-generational living arrangements affect childcare and women’s work and the rise of market-based childcare services.

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Twenty years of gender equality research: A scoping review based on a new semantic indicator

Paola belingheri.

1 Dipartimento di Ingegneria dell’Energia, dei Sistemi, del Territorio e delle Costruzioni, Università degli Studi di Pisa, Largo L. Lazzarino, Pisa, Italy

Filippo Chiarello

Andrea fronzetti colladon.

2 Department of Engineering, University of Perugia, Perugia, Italy

3 Department of Management, Kozminski University, Warsaw, Poland

Paola Rovelli

4 Faculty of Economics and Management, Centre for Family Business Management, Free University of Bozen-Bolzano, Bozen-Bolzano, Italy

Associated Data

All relevant data are within the manuscript and its supporting information files. The only exception is the text of the abstracts (over 15,000) that we have downloaded from Scopus. These abstracts can be retrieved from Scopus, but we do not have permission to redistribute them.

Gender equality is a major problem that places women at a disadvantage thereby stymieing economic growth and societal advancement. In the last two decades, extensive research has been conducted on gender related issues, studying both their antecedents and consequences. However, existing literature reviews fail to provide a comprehensive and clear picture of what has been studied so far, which could guide scholars in their future research. Our paper offers a scoping review of a large portion of the research that has been published over the last 22 years, on gender equality and related issues, with a specific focus on business and economics studies. Combining innovative methods drawn from both network analysis and text mining, we provide a synthesis of 15,465 scientific articles. We identify 27 main research topics, we measure their relevance from a semantic point of view and the relationships among them, highlighting the importance of each topic in the overall gender discourse. We find that prominent research topics mostly relate to women in the workforce–e.g., concerning compensation, role, education, decision-making and career progression. However, some of them are losing momentum, and some other research trends–for example related to female entrepreneurship, leadership and participation in the board of directors–are on the rise. Besides introducing a novel methodology to review broad literature streams, our paper offers a map of the main gender-research trends and presents the most popular and the emerging themes, as well as their intersections, outlining important avenues for future research.

Introduction

The persistent gender inequalities that currently exist across the developed and developing world are receiving increasing attention from economists, policymakers, and the general public [e.g., 1 – 3 ]. Economic studies have indicated that women’s education and entry into the workforce contributes to social and economic well-being [e.g., 4 , 5 ], while their exclusion from the labor market and from managerial positions has an impact on overall labor productivity and income per capita [ 6 , 7 ]. The United Nations selected gender equality, with an emphasis on female education, as part of the Millennium Development Goals [ 8 ], and gender equality at-large as one of the 17 Sustainable Development Goals (SDGs) to be achieved by 2030 [ 9 ]. These latter objectives involve not only developing nations, but rather all countries, to achieve economic, social and environmental well-being.

As is the case with many SDGs, gender equality is still far from being achieved and persists across education, access to opportunities, or presence in decision-making positions [ 7 , 10 , 11 ]. As we enter the last decade for the SDGs’ implementation, and while we are battling a global health pandemic, effective and efficient action becomes paramount to reach this ambitious goal.

Scholars have dedicated a massive effort towards understanding gender equality, its determinants, its consequences for women and society, and the appropriate actions and policies to advance women’s equality. Many topics have been covered, ranging from women’s education and human capital [ 12 , 13 ] and their role in society [e.g., 14 , 15 ], to their appointment in firms’ top ranked positions [e.g., 16 , 17 ] and performance implications [e.g., 18 , 19 ]. Despite some attempts, extant literature reviews provide a narrow view on these issues, restricted to specific topics–e.g., female students’ presence in STEM fields [ 20 ], educational gender inequality [ 5 ], the gender pay gap [ 21 ], the glass ceiling effect [ 22 ], leadership [ 23 ], entrepreneurship [ 24 ], women’s presence on the board of directors [ 25 , 26 ], diversity management [ 27 ], gender stereotypes in advertisement [ 28 ], or specific professions [ 29 ]. A comprehensive view on gender-related research, taking stock of key findings and under-studied topics is thus lacking.

Extant literature has also highlighted that gender issues, and their economic and social ramifications, are complex topics that involve a large number of possible antecedents and outcomes [ 7 ]. Indeed, gender equality actions are most effective when implemented in unison with other SDGs (e.g., with SDG 8, see [ 30 ]) in a synergetic perspective [ 10 ]. Many bodies of literature (e.g., business, economics, development studies, sociology and psychology) approach the problem of achieving gender equality from different perspectives–often addressing specific and narrow aspects. This sometimes leads to a lack of clarity about how different issues, circumstances, and solutions may be related in precipitating or mitigating gender inequality or its effects. As the number of papers grows at an increasing pace, this issue is exacerbated and there is a need to step back and survey the body of gender equality literature as a whole. There is also a need to examine synergies between different topics and approaches, as well as gaps in our understanding of how different problems and solutions work together. Considering the important topic of women’s economic and social empowerment, this paper aims to fill this gap by answering the following research question: what are the most relevant findings in the literature on gender equality and how do they relate to each other ?

To do so, we conduct a scoping review [ 31 ], providing a synthesis of 15,465 articles dealing with gender equity related issues published in the last twenty-two years, covering both the periods of the MDGs and the SDGs (i.e., 2000 to mid 2021) in all the journals indexed in the Academic Journal Guide’s 2018 ranking of business and economics journals. Given the huge amount of research conducted on the topic, we adopt an innovative methodology, which relies on social network analysis and text mining. These techniques are increasingly adopted when surveying large bodies of text. Recently, they were applied to perform analysis of online gender communication differences [ 32 ] and gender behaviors in online technology communities [ 33 ], to identify and classify sexual harassment instances in academia [ 34 ], and to evaluate the gender inclusivity of disaster management policies [ 35 ].

Applied to the title, abstracts and keywords of the articles in our sample, this methodology allows us to identify a set of 27 recurrent topics within which we automatically classify the papers. Introducing additional novelty, by means of the Semantic Brand Score (SBS) indicator [ 36 ] and the SBS BI app [ 37 ], we assess the importance of each topic in the overall gender equality discourse and its relationships with the other topics, as well as trends over time, with a more accurate description than that offered by traditional literature reviews relying solely on the number of papers presented in each topic.

This methodology, applied to gender equality research spanning the past twenty-two years, enables two key contributions. First, we extract the main message that each document is conveying and how this is connected to other themes in literature, providing a rich picture of the topics that are at the center of the discourse, as well as of the emerging topics. Second, by examining the semantic relationship between topics and how tightly their discourses are linked, we can identify the key relationships and connections between different topics. This semi-automatic methodology is also highly reproducible with minimum effort.

This literature review is organized as follows. In the next section, we present how we selected relevant papers and how we analyzed them through text mining and social network analysis. We then illustrate the importance of 27 selected research topics, measured by means of the SBS indicator. In the results section, we present an overview of the literature based on the SBS results–followed by an in-depth narrative analysis of the top 10 topics (i.e., those with the highest SBS) and their connections. Subsequently, we highlight a series of under-studied connections between the topics where there is potential for future research. Through this analysis, we build a map of the main gender-research trends in the last twenty-two years–presenting the most popular themes. We conclude by highlighting key areas on which research should focused in the future.

Our aim is to map a broad topic, gender equality research, that has been approached through a host of different angles and through different disciplines. Scoping reviews are the most appropriate as they provide the freedom to map different themes and identify literature gaps, thereby guiding the recommendation of new research agendas [ 38 ].

Several practical approaches have been proposed to identify and assess the underlying topics of a specific field using big data [ 39 – 41 ], but many of them fail without proper paper retrieval and text preprocessing. This is specifically true for a research field such as the gender-related one, which comprises the work of scholars from different backgrounds. In this section, we illustrate a novel approach for the analysis of scientific (gender-related) papers that relies on methods and tools of social network analysis and text mining. Our procedure has four main steps: (1) data collection, (2) text preprocessing, (3) keywords extraction and classification, and (4) evaluation of semantic importance and image.

Data collection

In this study, we analyze 22 years of literature on gender-related research. Following established practice for scoping reviews [ 42 ], our data collection consisted of two main steps, which we summarize here below.

Firstly, we retrieved from the Scopus database all the articles written in English that contained the term “gender” in their title, abstract or keywords and were published in a journal listed in the Academic Journal Guide 2018 ranking of the Chartered Association of Business Schools (CABS) ( https://charteredabs.org/wp-content/uploads/2018/03/AJG2018-Methodology.pdf ), considering the time period from Jan 2000 to May 2021. We used this information considering that abstracts, titles and keywords represent the most informative part of a paper, while using the full-text would increase the signal-to-noise ratio for information extraction. Indeed, these textual elements already demonstrated to be reliable sources of information for the task of domain lexicon extraction [ 43 , 44 ]. We chose Scopus as source of literature because of its popularity, its update rate, and because it offers an API to ease the querying process. Indeed, while it does not allow to retrieve the full text of scientific articles, the Scopus API offers access to titles, abstracts, citation information and metadata for all its indexed scholarly journals. Moreover, we decided to focus on the journals listed in the AJG 2018 ranking because we were interested in reviewing business and economics related gender studies only. The AJG is indeed widely used by universities and business schools as a reference point for journal and research rigor and quality. This first step, executed in June 2021, returned more than 55,000 papers.

In the second step–because a look at the papers showed very sparse results, many of which were not in line with the topic of this literature review (e.g., papers dealing with health care or medical issues, where the word gender indicates the gender of the patients)–we applied further inclusion criteria to make the sample more focused on the topic of this literature review (i.e., women’s gender equality issues). Specifically, we only retained those papers mentioning, in their title and/or abstract, both gender-related keywords (e.g., daughter, female, mother) and keywords referring to bias and equality issues (e.g., equality, bias, diversity, inclusion). After text pre-processing (see next section), keywords were first identified from a frequency-weighted list of words found in the titles, abstracts and keywords in the initial list of papers, extracted through text mining (following the same approach as [ 43 ]). They were selected by two of the co-authors independently, following respectively a bottom up and a top-down approach. The bottom-up approach consisted of examining the words found in the frequency-weighted list and classifying those related to gender and equality. The top-down approach consisted in searching in the word list for notable gender and equality-related words. Table 1 reports the sets of keywords we considered, together with some examples of words that were used to search for their presence in the dataset (a full list is provided in the S1 Text ). At end of this second step, we obtained a final sample of 15,465 relevant papers.

Text processing and keyword extraction

Text preprocessing aims at structuring text into a form that can be analyzed by statistical models. In the present section, we describe the preprocessing steps we applied to paper titles and abstracts, which, as explained below, partially follow a standard text preprocessing pipeline [ 45 ]. These activities have been performed using the R package udpipe [ 46 ].

The first step is n-gram extraction (i.e., a sequence of words from a given text sample) to identify which n-grams are important in the analysis, since domain-specific lexicons are often composed by bi-grams and tri-grams [ 47 ]. Multi-word extraction is usually implemented with statistics and linguistic rules, thus using the statistical properties of n-grams or machine learning approaches [ 48 ]. However, for the present paper, we used Scopus metadata in order to have a more effective and efficient n-grams collection approach [ 49 ]. We used the keywords of each paper in order to tag n-grams with their associated keywords automatically. Using this greedy approach, it was possible to collect all the keywords listed by the authors of the papers. From this list, we extracted only keywords composed by two, three and four words, we removed all the acronyms and rare keywords (i.e., appearing in less than 1% of papers), and we clustered keywords showing a high orthographic similarity–measured using a Levenshtein distance [ 50 ] lower than 2, considering these groups of keywords as representing same concepts, but expressed with different spelling. After tagging the n-grams in the abstracts, we followed a common data preparation pipeline that consists of the following steps: (i) tokenization, that splits the text into tokens (i.e., single words and previously tagged multi-words); (ii) removal of stop-words (i.e. those words that add little meaning to the text, usually being very common and short functional words–such as “and”, “or”, or “of”); (iii) parts-of-speech tagging, that is providing information concerning the morphological role of a word and its morphosyntactic context (e.g., if the token is a determiner, the next token is a noun or an adjective with very high confidence, [ 51 ]); and (iv) lemmatization, which consists in substituting each word with its dictionary form (or lemma). The output of the latter step allows grouping together the inflected forms of a word. For example, the verbs “am”, “are”, and “is” have the shared lemma “be”, or the nouns “cat” and “cats” both share the lemma “cat”. We preferred lemmatization over stemming [ 52 ] in order to obtain more interpretable results.

In addition, we identified a further set of keywords (with respect to those listed in the “keywords” field) by applying a series of automatic words unification and removal steps, as suggested in past research [ 53 , 54 ]. We removed: sparse terms (i.e., occurring in less than 0.1% of all documents), common terms (i.e., occurring in more than 10% of all documents) and retained only nouns and adjectives. It is relevant to notice that no document was lost due to these steps. We then used the TF-IDF function [ 55 ] to produce a new list of keywords. We additionally tested other approaches for the identification and clustering of keywords–such as TextRank [ 56 ] or Latent Dirichlet Allocation [ 57 ]–without obtaining more informative results.

Classification of research topics

To guide the literature analysis, two experts met regularly to examine the sample of collected papers and to identify the main topics and trends in gender research. Initially, they conducted brainstorming sessions on the topics they expected to find, due to their knowledge of the literature. This led to an initial list of topics. Subsequently, the experts worked independently, also supported by the keywords in paper titles and abstracts extracted with the procedure described above.

Considering all this information, each expert identified and clustered relevant keywords into topics. At the end of the process, the two assignments were compared and exhibited a 92% agreement. Another meeting was held to discuss discordant cases and reach a consensus. This resulted in a list of 27 topics, briefly introduced in Table 2 and subsequently detailed in the following sections.

Evaluation of semantic importance

Working on the lemmatized corpus of the 15,465 papers included in our sample, we proceeded with the evaluation of semantic importance trends for each topic and with the analysis of their connections and prevalent textual associations. To this aim, we used the Semantic Brand Score indicator [ 36 ], calculated through the SBS BI webapp [ 37 ] that also produced a brand image report for each topic. For this study we relied on the computing resources of the ENEA/CRESCO infrastructure [ 58 ].

The Semantic Brand Score (SBS) is a measure of semantic importance that combines methods of social network analysis and text mining. It is usually applied for the analysis of (big) textual data to evaluate the importance of one or more brands, names, words, or sets of keywords [ 36 ]. Indeed, the concept of “brand” is intended in a flexible way and goes beyond products or commercial brands. In this study, we evaluate the SBS time-trends of the keywords defining the research topics discussed in the previous section. Semantic importance comprises the three dimensions of topic prevalence, diversity and connectivity. Prevalence measures how frequently a research topic is used in the discourse. The more a topic is mentioned by scientific articles, the more the research community will be aware of it, with possible increase of future studies; this construct is partly related to that of brand awareness [ 59 ]. This effect is even stronger, considering that we are analyzing the title, abstract and keywords of the papers, i.e. the parts that have the highest visibility. A very important characteristic of the SBS is that it considers the relationships among words in a text. Topic importance is not just a matter of how frequently a topic is mentioned, but also of the associations a topic has in the text. Specifically, texts are transformed into networks of co-occurring words, and relationships are studied through social network analysis [ 60 ]. This step is necessary to calculate the other two dimensions of our semantic importance indicator. Accordingly, a social network of words is generated for each time period considered in the analysis–i.e., a graph made of n nodes (words) and E edges weighted by co-occurrence frequency, with W being the set of edge weights. The keywords representing each topic were clustered into single nodes.

The construct of diversity relates to that of brand image [ 59 ], in the sense that it considers the richness and distinctiveness of textual (topic) associations. Considering the above-mentioned networks, we calculated diversity using the distinctiveness centrality metric–as in the formula presented by Fronzetti Colladon and Naldi [ 61 ].

Lastly, connectivity was measured as the weighted betweenness centrality [ 62 , 63 ] of each research topic node. We used the formula presented by Wasserman and Faust [ 60 ]. The dimension of connectivity represents the “brokerage power” of each research topic–i.e., how much it can serve as a bridge to connect other terms (and ultimately topics) in the discourse [ 36 ].

The SBS is the final composite indicator obtained by summing the standardized scores of prevalence, diversity and connectivity. Standardization was carried out considering all the words in the corpus, for each specific timeframe.

This methodology, applied to a large and heterogeneous body of text, enables to automatically identify two important sets of information that add value to the literature review. Firstly, the relevance of each topic in literature is measured through a composite indicator of semantic importance, rather than simply looking at word frequencies. This provides a much richer picture of the topics that are at the center of the discourse, as well as of the topics that are emerging in the literature. Secondly, it enables to examine the extent of the semantic relationship between topics, looking at how tightly their discourses are linked. In a field such as gender equality, where many topics are closely linked to each other and present overlaps in issues and solutions, this methodology offers a novel perspective with respect to traditional literature reviews. In addition, it ensures reproducibility over time and the possibility to semi-automatically update the analysis, as new papers become available.

Overview of main topics

In terms of descriptive textual statistics, our corpus is made of 15,465 text documents, consisting of a total of 2,685,893 lemmatized tokens (words) and 32,279 types. As a result, the type-token ratio is 1.2%. The number of hapaxes is 12,141, with a hapax-token ratio of 37.61%.

Fig 1 shows the list of 27 topics by decreasing SBS. The most researched topic is compensation , exceeding all others in prevalence, diversity, and connectivity. This means it is not only mentioned more often than other topics, but it is also connected to a greater number of other topics and is central to the discourse on gender equality. The next four topics are, in order of SBS, role , education , decision-making , and career progression . These topics, except for education , all concern women in the workforce. Between these first five topics and the following ones there is a clear drop in SBS scores. In particular, the topics that follow have a lower connectivity than the first five. They are hiring , performance , behavior , organization , and human capital . Again, except for behavior and human capital , the other three topics are purely related to women in the workforce. After another drop-off, the following topics deal prevalently with women in society. This trend highlights that research on gender in business journals has so far mainly paid attention to the conditions that women experience in business contexts, while also devoting some attention to women in society.

Fig 2 shows the SBS time series of the top 10 topics. While there has been a general increase in the number of Scopus-indexed publications in the last decade, we notice that some SBS trends remain steady, or even decrease. In particular, we observe that the main topic of the last twenty-two years, compensation , is losing momentum. Since 2016, it has been surpassed by decision-making , education and role , which may indicate that literature is increasingly attempting to identify root causes of compensation inequalities. Moreover, in the last two years, the topics of hiring , performance , and organization are experiencing the largest importance increase.

Fig 3 shows the SBS time trends of the remaining 17 topics (i.e., those not in the top 10). As we can see from the graph, there are some that maintain a steady trend–such as reputation , management , networks and governance , which also seem to have little importance. More relevant topics with average stationary trends (except for the last two years) are culture , family , and parenting . The feminine topic is among the most important here, and one of those that exhibit the larger variations over time (similarly to leadership ). On the other hand, the are some topics that, even if not among the most important, show increasing SBS trends; therefore, they could be considered as emerging topics and could become popular in the near future. These are entrepreneurship , leadership , board of directors , and sustainability . These emerging topics are also interesting to anticipate future trends in gender equality research that are conducive to overall equality in society.

In addition to the SBS score of the different topics, the network of terms they are associated to enables to gauge the extent to which their images (textual associations) overlap or differ ( Fig 4 ).

There is a central cluster of topics with high similarity, which are all connected with women in the workforce. The cluster includes topics such as organization , decision-making , performance , hiring , human capital , education and compensation . In addition, the topic of well-being is found within this cluster, suggesting that women’s equality in the workforce is associated to well-being considerations. The emerging topics of entrepreneurship and leadership are also closely connected with each other, possibly implying that leadership is a much-researched quality in female entrepreneurship. Topics that are relatively more distant include personality , politics , feminine , empowerment , management , board of directors , reputation , governance , parenting , masculine and network .

The following sections describe the top 10 topics and their main associations in literature (see Table 3 ), while providing a brief overview of the emerging topics.

Compensation

The topic of compensation is related to the topics of role , hiring , education and career progression , however, also sees a very high association with the words gap and inequality . Indeed, a well-known debate in degrowth economics centers around whether and how to adequately compensate women for their childbearing, childrearing, caregiver and household work [e.g., 30 ].

Even in paid work, women continue being offered lower compensations than their male counterparts who have the same job or cover the same role [ 64 – 67 ]. This severe inequality has been widely studied by scholars over the last twenty-two years. Dealing with this topic, some specific roles have been addressed. Specifically, research highlighted differences in compensation between female and male CEOs [e.g., 68 ], top executives [e.g., 69 ], and boards’ directors [e.g., 70 ]. Scholars investigated the determinants of these gaps, such as the gender composition of the board [e.g., 71 – 73 ] or women’s individual characteristics [e.g., 71 , 74 ].

Among these individual characteristics, education plays a relevant role [ 75 ]. Education is indeed presented as the solution for women, not only to achieve top executive roles, but also to reduce wage inequality [e.g., 76 , 77 ]. Past research has highlighted education influences on gender wage gaps, specifically referring to gender differences in skills [e.g., 78 ], college majors [e.g., 79 ], and college selectivity [e.g., 80 ].

Finally, the wage gap issue is strictly interrelated with hiring –e.g., looking at whether being a mother affects hiring and compensation [e.g., 65 , 81 ] or relating compensation to unemployment [e.g., 82 ]–and career progression –for instance looking at meritocracy [ 83 , 84 ] or the characteristics of the boss for whom women work [e.g., 85 ].

The roles covered by women have been deeply investigated. Scholars have focused on the role of women in their families and the society as a whole [e.g., 14 , 15 ], and, more widely, in business contexts [e.g., 18 , 81 ]. Indeed, despite still lagging behind their male counterparts [e.g., 86 , 87 ], in the last decade there has been an increase in top ranked positions achieved by women [e.g., 88 , 89 ]. Following this phenomenon, scholars have posed greater attention towards the presence of women in the board of directors [e.g., 16 , 18 , 90 , 91 ], given the increasing pressure to appoint female directors that firms, especially listed ones, have experienced. Other scholars have focused on the presence of women covering the role of CEO [e.g., 17 , 92 ] or being part of the top management team [e.g., 93 ]. Irrespectively of the level of analysis, all these studies tried to uncover the antecedents of women’s presence among top managers [e.g., 92 , 94 ] and the consequences of having a them involved in the firm’s decision-making –e.g., on performance [e.g., 19 , 95 , 96 ], risk [e.g., 97 , 98 ], and corporate social responsibility [e.g., 99 , 100 ].

Besides studying the difficulties and discriminations faced by women in getting a job [ 81 , 101 ], and, more specifically in the hiring , appointment, or career progression to these apical roles [e.g., 70 , 83 ], the majority of research of women’s roles dealt with compensation issues. Specifically, scholars highlight the pay-gap that still exists between women and men, both in general [e.g., 64 , 65 ], as well as referring to boards’ directors [e.g., 70 , 102 ], CEOs and executives [e.g., 69 , 103 , 104 ].

Finally, other scholars focused on the behavior of women when dealing with business. In this sense, particular attention has been paid to leadership and entrepreneurial behaviors. The former quite overlaps with dealing with the roles mentioned above, but also includes aspects such as leaders being stereotyped as masculine [e.g., 105 ], the need for greater exposure to female leaders to reduce biases [e.g., 106 ], or female leaders acting as queen bees [e.g., 107 ]. Regarding entrepreneurship , scholars mainly investigated women’s entrepreneurial entry [e.g., 108 , 109 ], differences between female and male entrepreneurs in the evaluations and funding received from investors [e.g., 110 , 111 ], and their performance gap [e.g., 112 , 113 ].

Education has long been recognized as key to social advancement and economic stability [ 114 ], for job progression and also a barrier to gender equality, especially in STEM-related fields. Research on education and gender equality is mostly linked with the topics of compensation , human capital , career progression , hiring , parenting and decision-making .

Education contributes to a higher human capital [ 115 ] and constitutes an investment on the part of women towards their future. In this context, literature points to the gender gap in educational attainment, and the consequences for women from a social, economic, personal and professional standpoint. Women are found to have less access to formal education and information, especially in emerging countries, which in turn may cause them to lose social and economic opportunities [e.g., 12 , 116 – 119 ]. Education in local and rural communities is also paramount to communicate the benefits of female empowerment , contributing to overall societal well-being [e.g., 120 ].

Once women access education, the image they have of the world and their place in society (i.e., habitus) affects their education performance [ 13 ] and is passed on to their children. These situations reinforce gender stereotypes, which become self-fulfilling prophecies that may negatively affect female students’ performance by lowering their confidence and heightening their anxiety [ 121 , 122 ]. Besides formal education, also the information that women are exposed to on a daily basis contributes to their human capital . Digital inequalities, for instance, stems from men spending more time online and acquiring higher digital skills than women [ 123 ].

Education is also a factor that should boost employability of candidates and thus hiring , career progression and compensation , however the relationship between these factors is not straightforward [ 115 ]. First, educational choices ( decision-making ) are influenced by variables such as self-efficacy and the presence of barriers, irrespectively of the career opportunities they offer, especially in STEM [ 124 ]. This brings additional difficulties to women’s enrollment and persistence in scientific and technical fields of study due to stereotypes and biases [ 125 , 126 ]. Moreover, access to education does not automatically translate into job opportunities for women and minority groups [ 127 , 128 ] or into female access to managerial positions [ 129 ].

Finally, parenting is reported as an antecedent of education [e.g., 130 ], with much of the literature focusing on the role of parents’ education on the opportunities afforded to children to enroll in education [ 131 – 134 ] and the role of parenting in their offspring’s perception of study fields and attitudes towards learning [ 135 – 138 ]. Parental education is also a predictor of the other related topics, namely human capital and compensation [ 139 ].

Decision-making

This literature mainly points to the fact that women are thought to make decisions differently than men. Women have indeed different priorities, such as they care more about people’s well-being, working with people or helping others, rather than maximizing their personal (or their firm’s) gain [ 140 ]. In other words, women typically present more communal than agentic behaviors, which are instead more frequent among men [ 141 ]. These different attitude, behavior and preferences in turn affect the decisions they make [e.g., 142 ] and the decision-making of the firm in which they work [e.g., 143 ].

At the individual level, gender affects, for instance, career aspirations [e.g., 144 ] and choices [e.g., 142 , 145 ], or the decision of creating a venture [e.g., 108 , 109 , 146 ]. Moreover, in everyday life, women and men make different decisions regarding partners [e.g., 147 ], childcare [e.g., 148 ], education [e.g., 149 ], attention to the environment [e.g., 150 ] and politics [e.g., 151 ].

At the firm level, scholars highlighted, for example, how the presence of women in the board affects corporate decisions [e.g., 152 , 153 ], that female CEOs are more conservative in accounting decisions [e.g., 154 ], or that female CFOs tend to make more conservative decisions regarding the firm’s financial reporting [e.g., 155 ]. Nevertheless, firm level research also investigated decisions that, influenced by gender bias, affect women, such as those pertaining hiring [e.g., 156 , 157 ], compensation [e.g., 73 , 158 ], or the empowerment of women once appointed [ 159 ].

Career progression

Once women have entered the workforce, the key aspect to achieve gender equality becomes career progression , including efforts toward overcoming the glass ceiling. Indeed, according to the SBS analysis, career progression is highly related to words such as work, social issues and equality. The topic with which it has the highest semantic overlap is role , followed by decision-making , hiring , education , compensation , leadership , human capital , and family .

Career progression implies an advancement in the hierarchical ladder of the firm, assigning managerial roles to women. Coherently, much of the literature has focused on identifying rationales for a greater female participation in the top management team and board of directors [e.g., 95 ] as well as the best criteria to ensure that the decision-makers promote the most valuable employees irrespectively of their individual characteristics, such as gender [e.g., 84 ]. The link between career progression , role and compensation is often provided in practice by performance appraisal exercises, frequently rooted in a culture of meritocracy that guides bonuses, salary increases and promotions. However, performance appraisals can actually mask gender-biased decisions where women are held to higher standards than their male colleagues [e.g., 83 , 84 , 95 , 160 , 161 ]. Women often have less opportunities to gain leadership experience and are less visible than their male colleagues, which constitute barriers to career advancement [e.g., 162 ]. Therefore, transparency and accountability, together with procedures that discourage discretionary choices, are paramount to achieve a fair career progression [e.g., 84 ], together with the relaxation of strict job boundaries in favor of cross-functional and self-directed tasks [e.g., 163 ].

In addition, a series of stereotypes about the type of leadership characteristics that are required for top management positions, which fit better with typical male and agentic attributes, are another key barrier to career advancement for women [e.g., 92 , 160 ].

Hiring is the entrance gateway for women into the workforce. Therefore, it is related to other workforce topics such as compensation , role , career progression , decision-making , human capital , performance , organization and education .

A first stream of literature focuses on the process leading up to candidates’ job applications, demonstrating that bias exists before positions are even opened, and it is perpetuated both by men and women through networking and gatekeeping practices [e.g., 164 , 165 ].

The hiring process itself is also subject to biases [ 166 ], for example gender-congruity bias that leads to men being preferred candidates in male-dominated sectors [e.g., 167 ], women being hired in positions with higher risk of failure [e.g., 168 ] and limited transparency and accountability afforded by written processes and procedures [e.g., 164 ] that all contribute to ascriptive inequality. In addition, providing incentives for evaluators to hire women may actually work to this end; however, this is not the case when supporting female candidates endangers higher-ranking male ones [ 169 ].

Another interesting perspective, instead, looks at top management teams’ composition and the effects on hiring practices, indicating that firms with more women in top management are less likely to lay off staff [e.g., 152 ].

Performance

Several scholars posed their attention towards women’s performance, its consequences [e.g., 170 , 171 ] and the implications of having women in decision-making positions [e.g., 18 , 19 ].

At the individual level, research focused on differences in educational and academic performance between women and men, especially referring to the gender gap in STEM fields [e.g., 171 ]. The presence of stereotype threats–that is the expectation that the members of a social group (e.g., women) “must deal with the possibility of being judged or treated stereotypically, or of doing something that would confirm the stereotype” [ 172 ]–affects women’s interested in STEM [e.g., 173 ], as well as their cognitive ability tests, penalizing them [e.g., 174 ]. A stronger gender identification enhances this gap [e.g., 175 ], whereas mentoring and role models can be used as solutions to this problem [e.g., 121 ]. Despite the negative effect of stereotype threats on girls’ performance [ 176 ], female and male students perform equally in mathematics and related subjects [e.g., 177 ]. Moreover, while individuals’ performance at school and university generally affects their achievements and the field in which they end up working, evidence reveals that performance in math or other scientific subjects does not explain why fewer women enter STEM working fields; rather this gap depends on other aspects, such as culture, past working experiences, or self-efficacy [e.g., 170 ]. Finally, scholars have highlighted the penalization that women face for their positive performance, for instance when they succeed in traditionally male areas [e.g., 178 ]. This penalization is explained by the violation of gender-stereotypic prescriptions [e.g., 179 , 180 ], that is having women well performing in agentic areas, which are typical associated to men. Performance penalization can thus be overcome by clearly conveying communal characteristics and behaviors [ 178 ].

Evidence has been provided on how the involvement of women in boards of directors and decision-making positions affects firms’ performance. Nevertheless, results are mixed, with some studies showing positive effects on financial [ 19 , 181 , 182 ] and corporate social performance [ 99 , 182 , 183 ]. Other studies maintain a negative association [e.g., 18 ], and other again mixed [e.g., 184 ] or non-significant association [e.g., 185 ]. Also with respect to the presence of a female CEO, mixed results emerged so far, with some researches demonstrating a positive effect on firm’s performance [e.g., 96 , 186 ], while other obtaining only a limited evidence of this relationship [e.g., 103 ] or a negative one [e.g., 187 ].

Finally, some studies have investigated whether and how women’s performance affects their hiring [e.g., 101 ] and career progression [e.g., 83 , 160 ]. For instance, academic performance leads to different returns in hiring for women and men. Specifically, high-achieving men are called back significantly more often than high-achieving women, which are penalized when they have a major in mathematics; this result depends on employers’ gendered standards for applicants [e.g., 101 ]. Once appointed, performance ratings are more strongly related to promotions for women than men, and promoted women typically show higher past performance ratings than those of promoted men. This suggesting that women are subject to stricter standards for promotion [e.g., 160 ].

Behavioral aspects related to gender follow two main streams of literature. The first examines female personality and behavior in the workplace, and their alignment with cultural expectations or stereotypes [e.g., 188 ] as well as their impacts on equality. There is a common bias that depicts women as less agentic than males. Certain characteristics, such as those more congruent with male behaviors–e.g., self-promotion [e.g., 189 ], negotiation skills [e.g., 190 ] and general agentic behavior [e.g., 191 ]–, are less accepted in women. However, characteristics such as individualism in women have been found to promote greater gender equality in society [ 192 ]. In addition, behaviors such as display of emotions [e.g., 193 ], which are stereotypically female, work against women’s acceptance in the workplace, requiring women to carefully moderate their behavior to avoid exclusion. A counter-intuitive result is that women and minorities, which are more marginalized in the workplace, tend to be better problem-solvers in innovation competitions due to their different knowledge bases [ 194 ].

The other side of the coin is examined in a parallel literature stream on behavior towards women in the workplace. As a result of biases, prejudices and stereotypes, women may experience adverse behavior from their colleagues, such as incivility and harassment, which undermine their well-being [e.g., 195 , 196 ]. Biases that go beyond gender, such as for overweight people, are also more strongly applied to women [ 197 ].

Organization

The role of women and gender bias in organizations has been studied from different perspectives, which mirror those presented in detail in the following sections. Specifically, most research highlighted the stereotypical view of leaders [e.g., 105 ] and the roles played by women within firms, for instance referring to presence in the board of directors [e.g., 18 , 90 , 91 ], appointment as CEOs [e.g., 16 ], or top executives [e.g., 93 ].

Scholars have investigated antecedents and consequences of the presence of women in these apical roles. On the one side they looked at hiring and career progression [e.g., 83 , 92 , 160 , 168 , 198 ], finding women typically disadvantaged with respect to their male counterparts. On the other side, they studied women’s leadership styles and influence on the firm’s decision-making [e.g., 152 , 154 , 155 , 199 ], with implications for performance [e.g., 18 , 19 , 96 ].

Human capital

Human capital is a transverse topic that touches upon many different aspects of female gender equality. As such, it has the most associations with other topics, starting with education as mentioned above, with career-related topics such as role , decision-making , hiring , career progression , performance , compensation , leadership and organization . Another topic with which there is a close connection is behavior . In general, human capital is approached both from the education standpoint but also from the perspective of social capital.

The behavioral aspect in human capital comprises research related to gender differences for example in cultural and religious beliefs that influence women’s attitudes and perceptions towards STEM subjects [ 142 , 200 – 202 ], towards employment [ 203 ] or towards environmental issues [ 150 , 204 ]. These cultural differences also emerge in the context of globalization which may accelerate gender equality in the workforce [ 205 , 206 ]. Gender differences also appear in behaviors such as motivation [ 207 ], and in negotiation [ 190 ], and have repercussions on women’s decision-making related to their careers. The so-called gender equality paradox sees women in countries with lower gender equality more likely to pursue studies and careers in STEM fields, whereas the gap in STEM enrollment widens as countries achieve greater equality in society [ 171 ].

Career progression is modeled by literature as a choice-process where personal preferences, culture and decision-making affect the chosen path and the outcomes. Some literature highlights how women tend to self-select into different professions than men, often due to stereotypes rather than actual ability to perform in these professions [ 142 , 144 ]. These stereotypes also affect the perceptions of female performance or the amount of human capital required to equal male performance [ 110 , 193 , 208 ], particularly for mothers [ 81 ]. It is therefore often assumed that women are better suited to less visible and less leadership -oriented roles [ 209 ]. Women also express differing preferences towards work-family balance, which affect whether and how they pursue human capital gains [ 210 ], and ultimately their career progression and salary .

On the other hand, men are often unaware of gendered processes and behaviors that they carry forward in their interactions and decision-making [ 211 , 212 ]. Therefore, initiatives aimed at increasing managers’ human capital –by raising awareness of gender disparities in their organizations and engaging them in diversity promotion–are essential steps to counter gender bias and segregation [ 213 ].

Emerging topics: Leadership and entrepreneurship

Among the emerging topics, the most pervasive one is women reaching leadership positions in the workforce and in society. This is still a rare occurrence for two main types of factors, on the one hand, bias and discrimination make it harder for women to access leadership positions [e.g., 214 – 216 ], on the other hand, the competitive nature and high pressure associated with leadership positions, coupled with the lack of women currently represented, reduce women’s desire to achieve them [e.g., 209 , 217 ]. Women are more effective leaders when they have access to education, resources and a diverse environment with representation [e.g., 218 , 219 ].

One sector where there is potential for women to carve out a leadership role is entrepreneurship . Although at the start of the millennium the discourse on entrepreneurship was found to be “discriminatory, gender-biased, ethnocentrically determined and ideologically controlled” [ 220 ], an increasing body of literature is studying how to stimulate female entrepreneurship as an alternative pathway to wealth, leadership and empowerment [e.g., 221 ]. Many barriers exist for women to access entrepreneurship, including the institutional and legal environment, social and cultural factors, access to knowledge and resources, and individual behavior [e.g., 222 , 223 ]. Education has been found to raise women’s entrepreneurial intentions [e.g., 224 ], although this effect is smaller than for men [e.g., 109 ]. In addition, increasing self-efficacy and risk-taking behavior constitute important success factors [e.g., 225 ].

Finally, the topic of sustainability is worth mentioning, as it is the primary objective of the SDGs and is closely associated with societal well-being. As society grapples with the effects of climate change and increasing depletion of natural resources, a narrative has emerged on women and their greater link to the environment [ 226 ]. Studies in developed countries have found some support for women leaders’ attention to sustainability issues in firms [e.g., 227 – 229 ], and smaller resource consumption by women [ 230 ]. At the same time, women will likely be more affected by the consequences of climate change [e.g., 230 ] but often lack the decision-making power to influence local decision-making on resource management and environmental policies [e.g., 231 ].

Research gaps and conclusions

Research on gender equality has advanced rapidly in the past decades, with a steady increase in publications, both in mainstream topics related to women in education and the workforce, and in emerging topics. Through a novel approach combining methods of text mining and social network analysis, we examined a comprehensive body of literature comprising 15,465 papers published between 2000 and mid 2021 on topics related to gender equality. We identified a set of 27 topics addressed by the literature and examined their connections.

At the highest level of abstraction, it is worth noting that papers abound on the identification of issues related to gender inequalities and imbalances in the workforce and in society. Literature has thoroughly examined the (unconscious) biases, barriers, stereotypes, and discriminatory behaviors that women are facing as a result of their gender. Instead, there are much fewer papers that discuss or demonstrate effective solutions to overcome gender bias [e.g., 121 , 143 , 145 , 163 , 194 , 213 , 232 ]. This is partly due to the relative ease in studying the status quo, as opposed to studying changes in the status quo. However, we observed a shift in the more recent years towards solution seeking in this domain, which we strongly encourage future researchers to focus on. In the future, we may focus on collecting and mapping pro-active contributions to gender studies, using additional Natural Language Processing techniques, able to measure the sentiment of scientific papers [ 43 ].

All of the mainstream topics identified in our literature review are closely related, and there is a wealth of insights looking at the intersection between issues such as education and career progression or human capital and role . However, emerging topics are worthy of being furtherly explored. It would be interesting to see more work on the topic of female entrepreneurship , exploring aspects such as education , personality , governance , management and leadership . For instance, how can education support female entrepreneurship? How can self-efficacy and risk-taking behaviors be taught or enhanced? What are the differences in managerial and governance styles of female entrepreneurs? Which personality traits are associated with successful entrepreneurs? Which traits are preferred by venture capitalists and funding bodies?

The emerging topic of sustainability also deserves further attention, as our society struggles with climate change and its consequences. It would be interesting to see more research on the intersection between sustainability and entrepreneurship , looking at how female entrepreneurs are tackling sustainability issues, examining both their business models and their company governance . In addition, scholars are suggested to dig deeper into the relationship between family values and behaviors.

Moreover, it would be relevant to understand how women’s networks (social capital), or the composition and structure of social networks involving both women and men, enable them to increase their remuneration and reach top corporate positions, participate in key decision-making bodies, and have a voice in communities. Furthermore, the achievement of gender equality might significantly change firm networks and ecosystems, with important implications for their performance and survival.

Similarly, research at the nexus of (corporate) governance , career progression , compensation and female empowerment could yield useful insights–for example discussing how enterprises, institutions and countries are managed and the impact for women and other minorities. Are there specific governance structures that favor diversity and inclusion?

Lastly, we foresee an emerging stream of research pertaining how the spread of the COVID-19 pandemic challenged women, especially in the workforce, by making gender biases more evident.

For our analysis, we considered a set of 15,465 articles downloaded from the Scopus database (which is the largest abstract and citation database of peer-reviewed literature). As we were interested in reviewing business and economics related gender studies, we only considered those papers published in journals listed in the Academic Journal Guide (AJG) 2018 ranking of the Chartered Association of Business Schools (CABS). All the journals listed in this ranking are also indexed by Scopus. Therefore, looking at a single database (i.e., Scopus) should not be considered a limitation of our study. However, future research could consider different databases and inclusion criteria.

With our literature review, we offer researchers a comprehensive map of major gender-related research trends over the past twenty-two years. This can serve as a lens to look to the future, contributing to the achievement of SDG5. Researchers may use our study as a starting point to identify key themes addressed in the literature. In addition, our methodological approach–based on the use of the Semantic Brand Score and its webapp–could support scholars interested in reviewing other areas of research.

Supporting information

Acknowledgments.

The computing resources and the related technical support used for this work have been provided by CRESCO/ENEAGRID High Performance Computing infrastructure and its staff. CRESCO/ENEAGRID High Performance Computing infrastructure is funded by ENEA, the Italian National Agency for New Technologies, Energy and Sustainable Economic Development and by Italian and European research programmes (see http://www.cresco.enea.it/english for information).

Funding Statement

P.B and F.C.: Grant of the Department of Energy, Systems, Territory and Construction of the University of Pisa (DESTEC) for the project “Measuring Gender Bias with Semantic Analysis: The Development of an Assessment Tool and its Application in the European Space Industry. P.B., F.C., A.F.C., P.R.: Grant of the Italian Association of Management Engineering (AiIG), “Misure di sostegno ai soci giovani AiIG” 2020, for the project “Gender Equality Through Data Intelligence (GEDI)”. F.C.: EU project ASSETs+ Project (Alliance for Strategic Skills addressing Emerging Technologies in Defence) EAC/A03/2018 - Erasmus+ programme, Sector Skills Alliances, Lot 3: Sector Skills Alliance for implementing a new strategic approach (Blueprint) to sectoral cooperation on skills G.A. NUMBER: 612678-EPP-1-2019-1-IT-EPPKA2-SSA-B.

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Here’s How Bad Workplace Gender Bias Has Become

Gender bias continues to sprout in the workplace—both in explicit and covert ways.

A new survey of over 1,000 women by The Muse job board revealed that 41 percent of women have felt discriminated against based on their gender during a job interview, and 42 percent said they have encountered gender-biased or inappropriate questions during a job interview.

The report also showed that:

• Over 1 in 3 (38 percent) of women have hesitated to apply for a job due to perceived gender bias.
• 2 out of 3 think women in their industry have a hard time getting promoted.
• 55 percent do not feel there’s enough female representation in the leadership at their organization.
• 79 percent of women said they are more likely to seek out companies that have equal representation of women in managerial/leadership positions when looking for a new job.

While the findings are troubling, 63 percent of respondents did say they felt supported as a woman at work.

“We have made incredible progress over the past few years toward increasing gender equity in the workplace, but as the results of this survey reveal, there’s still so much more progress needed—particularly in the hiring and job interview process,” said Heather Tenuto, CEO of The Muse.

SHRM Online collected additional news on gender bias in the workplace.

New Report Finds 30 Different Biases Impact Women at Work

Gender bias and discrimination have held women back in the workplace for generations, but new research indicates gender-based judgments barely scratch the surface of ways professional women are criticized throughout their careers. Researchers identified 30 characteristics that women say were used against them in the workplace, including age, attractiveness and body size.

Gender Discrimination in Tech Industry Worsening

A 2023 report by tech career marketplace Dice revealed the percentage of tech professionals who said they experienced gender discrimination rose from 21 percent in 2021 to 26 percent in 2022.

To reduce discrimination, HR professionals should consider incorporating procedures to assess hiring processes and salaries, asking for feedback from the workforce via surveys and enlisting a third-party consultant to further identify opportunities for improvement.

( SHRM Online )

The Groups Hit Hardest by the Gender Pay Gap

While progress has been made toward eliminating the gender pay gap, some groups of women fare worse than others, according to an annual report. Overall, women in the U.S. earn 83 cents for every dollar a man earns. But women of color, mothers, women working remotely and women leaders are earning less than that. Here’s how employers can contribute to a more equitable workplace and keep their top female talent.

5 Ways to Reduce Gender Inequality at Work

​Research has shown that societal biases toward women have contributed to gender salary disparities in the U.S. Generation Z women have lower pay expectations than men have when entering the workforce, according to a recent report by career app Handshake. Handshake researchers explained that the difference in pay expectations “highlights the long-standing issue of gender pay disparity: Women's salary expectations are lower from the start, potentially reflecting historical pay gaps.”

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As artificial intelligence technology continues to develop, the demand for workers with the ability to work alongside and manage AI systems will increase. This means that workers who are not able to adapt and learn these new skills will be left behind in the job market.

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Regions & Countries

Gender pay gap in u.s. has remained stable in recent years, but is narrower among young workers.

About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of The Pew Charitable Trusts .

Louisiana's gender pay gap ranks fifth among United States, according to recent study

A study on the gender pay gap reveals which states ranked at the top for providing unequal wages between males and females.

Research found that in Louisiana there is a difference of $14,048 dollars between what men and women earn, according to a news release. The study, conducted by Journo Research, analyzed U.S. Census data and looked at the average annual full-time work earnings in every state for both males and females to determine which states are paying women less than men.

Across all states, the average male annual wage for a full-time worker was $61,661.60, compared to the average yearly wage for a full-time working female of $50,314.66, meaning that nationally, men were found to be paid $11,346.84 more a year on average – or 20.27% more a year.

In 2022, Louisiana women who were full-time wage and salary workers had median weekly earnings of $822, or 77.3% of the $1,064 median weekly earnings of their male counterparts, the U.S. Bureau of Labor Statistics reported. In conjunction with this, in 2021, Business.org — an organization providing tools and data for small businesses — released a report that shows Louisiana was one of the worst states for wage equality. 

Louisiana ranks fifth on that list. Coming in first place is New Hampshire, where the annual wage gap is $18,044. Utah was second, with a disparity of $17,528 in annual wages between genders.

Third place went to North Dakota, where the wage gap annually was $14,082. In North Dakota, the average annual wage for a male working full-time was found to be $61,786, compared to the average of that of a female also working full-time of only $47,704.

With a gender pay disparity of $14,053, Virginia was fourth on the list. Women working full-time in Virginia were found to earn $56,498, compared to men, who were seen to earn $70,551 annually, on average, according to the study.

Efforts to address Louisiana's wage gap in recent years have been proposed but fallen short. In 2013, the state passed the Louisiana Equal Pay for Women Act, which required state agencies to pay women employees the same as a male employee doing the same work. The law, only applied to state employees and did not impact private businesses.

“The study's findings shine a light on the existence of major gender pay gaps throughout the United States and, hopefully, can be used as a catalyst to bring the issue to a wider audience, where the issue can continue to be addressed,” said a spokesperson for Journo Research. The study underscores the need for targeted strategies, such as salary transparency, and subsidizing childcare, and discussions to address these discrepancies and promote greater wage equality nationwide.”

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April 5, 2024

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People who work from home are less likely to get pay rises and promotions, finds research

by Tony Trueman, British Sociological Association

People who work from home all or part of the time are less likely to get pay rises and promotions, the first post-COVID research project into the WFH phenomenon has found.

A survey of 937 UK managers found that they were 11% less likely to give a promotion to staff who worked entirely from home than to those who were completely office-based.

Hybrid workers—those working partly in the office and partly at home—were on average 7% less likely to be promoted.

Managers were 9% less likely to give a pay rise to staff working entirely from home than to those who were completely office-based, and 7% less likely to give one to hybrid workers.

The research found a gender gap : managers were 15% less likely to promote men who worked entirely from home than those who were completely office-based, and 10% less likely to give a pay increase. The figures for women were 7% and 8%, respectively.

Agnieszka Kasperska, Professor Anna Matysiak and Dr. Ewa Cukrowska-Torzewska, all from the University of Warsaw, carried out the research, the first study since the lockdowns began in the UK on how working from home affects careers.

They presented 937 managers employed in various businesses and industries within the UK with two profiles of hypothetical full-time staff members who worked either five days at the office a week, five days at home, or three days at the office and two at home. The managers then chose which one they were likely to promote, and also which one they would give a pay rise to.

Agnieszka Kasperska told the British Sociological Association's online annual conference 5 April, 2024 that "the recent COVID-19 pandemic has triggered a substantial shift towards working from home, potentially influencing employers' attitudes and companies' readiness to manage remote employees.

"However, our findings indicate that individuals working from home still encounter career penalties, irrespective of the widespread adoption of this mode of work.

"Both male and female remote workers experience career penalties, but they are substantially larger for men."

They found that in organizations with very demanding work cultures, the managers were around 30% less likely to promote and 19% less likely to give a pay rise to men who worked entirely from home than to men who worked solely in the office. The figures for women were 15% and 19%, respectively. In organizations with more supportive environments, no penalty to staff for flexible working was found.

"In more supportive organizations, so where there is less pressure and long working days and where family-friendly policies exist, we don't find such negative consequences of remote work," she said.

The profiles given to managers also included different characteristics such as gender, age, experience in the sector, skill level and family situation. The raw data were adjusted to remove the influence of these from the final results so that the effects of working from home could be studied in isolation.

Provided by British Sociological Association

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