Examining the influence of women scientists on scientific impact and novelty: insights from top business journals

Women have historically encountered numerous barriers and biases that hinder their complete participation and acknowledgement in scientific research. In this study, we scrutinise the gender makeup of scientific teams publishing in top business journals based on a cross-sectional sample of 46,708 publications. Scientific impact is based on the citations, and novelty by using the NLP co-occurrence matrix to compute the cosine similarity between pairs of knowledge entities. Our findings reveal an inverse U-shaped relationship between the proportion of women scientists and scientific impact and a positive U-shaped association with novelty, significantly moderated by team size. These outcomes persist even after many controls and potentially relevant characteristics are taken into account. By delving into the divergent effects of female participation within teams, we not only reveal the nonlinear relationship between team gender composition and scientific discovery but also provide relevant advice for cross-gender collaborative researchers. Our evidence underscores the importance of a more detailed scholarly discussion of the role of women scientists in team performance, at least in business science research.