A new organizational structure database: Examining structure through top management team compositions

Deskripsi

Studies using archival organizational structure data are not as prevalent as one might expect for such a critical strategy topic. We seek to facilitate more studies in this domain by introducing a novel, hand-collected dataset of top management team compositions of S&P 500 firms between 1993 and 2020. Alongside providing the original role titles, we use generative Artificial Intelligence (AI) to categorize executives' titles into 6 role groups and 12 hierarchical levels, enabling easier comparisons of structures across and within firms. Our findings not only align with prior research but also offer insights into industry-specific structural changes, functional distributions within organizations, and the evolution of executive roles. This work also highlights the potential of generative AI as a tool to empirically investigate key strategy questions.