Compiled Global Dataset on Digital Business Model Research

This dataset provides a comprehensive collection of bibliometric and projection modeling data centered on the study of digital business models. The bibliometric coverage spans the years 2020–2024, consisting of 469 peer-reviewed documents retrieved from Scopus. These works were authored by 1,351 contributors and published across 332 sources, selected through rigorous inclusion criteria: relevance to the research domain, full-year coverage, peer-reviewed status, and accessibility for analysis.The bibliometric file, available in CSV format, contains rich metadata including author names, titles, publication years, EID, source information, citation counts, document types, DOIs, open access status, affiliations, identifiers, funding details, and complete reference lists. Complementary PNG visualizations are provided, featuring thematic maps, trend topics, and a research flowchart. The analysis was conducted using Microsoft Excel for summary statistics and annual publication counts, alongside R Biblioshiny for thematic mapping and topic trend identification.For the modeling component, annual publication growth is projected from 2025–2034 using a logistic growth model (S-curve) implemented in Python. Outputs include both CSV tables and PNG charts that depict historical trends and forward-looking projections. The design enables an informed understanding of research trajectories, offering insights into growth dynamics and potential saturation patterns within the field.