Exploring board gender diversity: a co-word analysis and conceptual framework of themes and trends in literature

Purpose This study employs co-word analysis to map thematic patterns in board gender diversity (BGD) research and reveal how themes interconnect and evolve. Design/methodology/approach A total of 1,015 peer-reviewed articles from Web of Science were analyzed using co-word analysis. In lieu of a full-text review, a computational approach is adopted, whereby metadata (keywords, titles, abstracts) is analyzed using Python-based tools. This process facilitates the detection of term co-occurrences and the visualization of thematic clusters. Thematic clusters are captured through pattern recognition, thereby offering an in-depth look at field development. Findings Five thematic clusters were identified: corporate performance and governance; policy and regulation; diversity and inclusion; sustainability and corporate responsibility; and methodology and research approaches. Performance terms frequently co-occur with contextual moderators and institutional factors, reflecting recognition that diversity effects operate through complex, contingent mechanisms. Research limitations/implications Reliance on single-database metadata and absence of full-text analysis are key limitations. Future research should integrate multiple databases and mixed-methods approaches, focusing on contingency and complexity. Practical implications Policymakers should move beyond numerical quotas to foster inclusive board cultures. Practitioners should recognize that diversity benefits require strategic integration of diverse voices. Originality/value This study provides the first large-scale mapping of BGD scholarship’s conceptual architecture through keyword co-occurrence. In contradistinction to citation-based bibliometrics, this methodology unveils the manner in which researchers frame investigations and the ways in which themes converge, thereby identifying opportunities for future inquiry.