Gender Bias in Management Information Systems
In this post, Silvia Masiero and I reflect upon gender bias in the academic field of information systems.
In April 2020, the female co-author of this post submitted a panel proposal to a renowned conference in the field of information systems. The evaluations of the panel proposal were single-blind, that is, the reviewers were made aware of the identity of the submitting authors but not vice versa. Despite being an expert in her field along with her three female co-proponents, the proposal received a relatively poor evaluation of 3/7 in terms of the quality of presenters selected for the panel. Maybe it was just an unlucky coincidence, or…?
Gender bias is a systemic, unfair difference in the way individuals are treated due to their gender identification in a particular domain. A singular unpleasant or disappointing event does not constitute a bias — unless it can be shown to be outright discrimination—yet when such events accumulate and form a pattern we may be witnessing a biased treatment of a group of people.
Widely studied in the psychological literature, gender bias has inspired a large body of research on employment opportunities, career expectations, and progression across industries. In the academic profession, gender bias has been widely documented on dimensions such as research publications, peer review, research citations, publication quality perceptions, and tenure and hiring decisions. STEM disciplines have developed a rich body of evidence on gender bias, highlighting the subtle nature of the phenomenon that makes it difficult to detect and address.
The above-mentioned conference incident inspired us to conduct a literature review on how gender is addressed in information systems research, using the top journals of the field (commonly referred to as the Senior Scholars’ Basket of Journals) as a pool of data. Using relevant keywords (gender, gender bias, gender discrimination, gender inequality, male bias, stereotyping, sexism) we searched all Basket journals for all years, finding 312 papers including at least one of such words in the title, abstract, or keywords. We then independently coded all papers as “relevant” or “not relevant” to any form of research on gender, arriving at 86 papers categorized as relevant for our research out of 7,260 papers (1.2%) published in the journals.
There are three clusters of gender-related information systems research. The first cluster, comprising 55 papers, conceives gender as a variable to explain other phenomena, ranging from technology acceptance to its use and user attitudes towards technology. Attention for gender bias is present in the second cluster of 23 papers that engage with the treatment and representation of colleagues identifying as women in the IT profession. While not pertaining to the academic sector, these papers offer detail on gender imbalance in IT jobs: illuminating bias in organisational regimes, pay gaps and workforce composition. These papers also contemplate interventions taken in the IT industry to address the problem. In fact, Information Systems Journal has published a special issue dedicated to such interventions.
What about the eight remaining papers? These are those that engage gender imbalance — and in three cases, explicitly bias — in the academic field of information systems. Two papers note gender imbalances in the percentage of female authors in a top journal of the discipline, two do so for editorial boards, whereas one discusses the relationship between personal (including gender) and policy dimensions in the field. Three more studies engage biased dynamics in the field, with foci ranging from research to membership of the information systems academic community.
What should be done, then?
First, studies of instances of active gender discrimination — such as Gupta et al. (2019) — are a witness to the problem. They demonstrate active engagement with the problem and the willingness to deal with what it means in information systems research, but are still too few to provide a comprehensive picture of the situation in our field. We suggest, therefore, that more such studies, based on the lived experience of colleagues in the IS field, are needed.
Second, research on gender bias in other disciplines can be used as a source of ideas for research on our field. Research on gender bias in psychology and STEM offers, for instance, specific methodologies for studying gender that could also be adopted in information systems, too. Third and relatedly, the presence of active forums such as the Association of Information Systems Women’s Network (AISWN) and the activism of its members offer practical mechanisms to deal with problems, engaging the community in a meaningful dialogue about gender bias and its consequences.
Having reported the poor review to the organisers of the conference in 2020, the female author and her co-proponents were pleased to find that the organisers engaged their complaint and indeed, the very idea of “quality of presenters” was questioned in the conversation that ensued. We consider this a positive sign that IS scholars are capable and willing to take gender bias seriously. As our research on the problem proceeds, we consider research indivisible from an active look on the unfolding of bias, and from the importance of addressing it to ensure the collegial character of our discipline.
