An integrated bibliometric analysis of Benefit of the Doubt composite indicators for policy and decision analysis

The Benefit of the Doubt (BoD) is a non-parametric frontier model derived from Data Envelopment Analysis (DEA), used to construct composite indicators in various sectors of economic activity, with a particular focus on macroeconomic assessments. Based on documents published in the Web of Science from 1991 to 2025, we conduct a systematic bibliometric review on this topic, proposing future research directions derived from the bibliographic coverage of the most recurrent concepts, areas, and problems addressed in the current BoD literature. We identify core publication networks for non-parametric frontier composite indicators, highlighting trends, hot topics, and clusters of applications. As a result, we offer three different and comprehensive BoD research agendas based on a practical knowledge discovery exercise from expert knowledge and Large Language Models (LLM), highlighting attractive topics, theoretical contributions, concepts, methods, and potential applications. • Trace the evolution of BoD composite indicator research using systematic bibliometric analysis. • Identify six thematic clusters that characterize methodological development in BoD research. • Demonstrate convergence and divergence between expert-based and AI-generated research agendas. • Reveal methodological innovations that strengthen BoD indicator robustness and clarity. • Propose actionable research directions to advance BoD methods for policy and decision use.