Empirical identification of the chief digital officer role: A latent Dirichlet allocation approach

Abstract

This study examines the global demand for Chief Digital Officers (CDOs) to determine a universal CDO archetype in terms of competencies and tasks. It uses Bayesian statistics and Latent Dirichlet Allocation (LDA) topic modeling to measure multiple dimensions in a sample of 518 job postings for CDO positions. Findings show the hybrid nature of newly appointed CDOs, who feature a mixture of both business administration and technological skills. Further, the study highlights the pivotal role of CDOs in terms of strategic change in companies. The study has three major contributions. First, it showcases the value of LDA in job profiling research. Second, it bridges the existing knowledge gaps in CDO literature with empirical evidence from a global dataset and identifies a core CDO profile based on data extracted through LDA. Third, it illustrates the current market requirements for CDO positions, which is useful to both companies and candidates. © 2022 Elsevier Inc.