Evolution and trends in business continuity prediction models

Purpose The study systematically investigates the evolution and scholarly trends in business continuity prediction models, providing a quantitative and structured mapping that highlights the models, networks and gaps in the literature. Design/methodology/approach A bibliometric analysis was conducted on 263 articles published between 1985 and 2024 and indexed in the Scopus database, using the search string “business continuity” OR “going concern” AND “model”. Data were processed through the combined use of Bibliometrix and VOSviewer, which enabled both quantitative analysis and visual representations of connections among authors, keywords, and thematic clusters. Findings The results show a nonlinear growth trend in publications, with significant peaks corresponding to global events and technological advances. The most influential journals belong to the management and auditing area, and the United States emerges as the most productive country. Guiral A. stands out as the most prolific author, while collaboration networks remain weak. The most frequent keywords are business continuity, risk assessment, supply chains and decision making, and the cluster analysis highlights three main research streams: data analysis, technological resilience and innovation. Research limitations/implications The study is limited to articles indexed in Scopus and to a specific search string. Practical implications The bibliometric approach offers practical applications, helping practitioners, researchers, and future model developers identify leading scholars, research clusters, or emerging topics in the field of business continuity. Originality/value This research provides a systematic and quantitative mapping of business continuity prediction models, outlining theoretical contributions and perspectives for future interdisciplinary studies.