Pub1-Fusion analysis package: data, scripts, and figures for the systematic and bibliometric review of digital signals in business forecasting

Open analysis archive accompanying the manuscript When digital signals predict business outcomes: a hybrid systematic and bibliometric review of two decades of evidence (Cuervo & Marques, 2026; under review at International Journal of Information Management).

This archive contains: (i) the deduplicated 1,007-record bibliometric corpus from Scopus and Web of Science; (ii) the SLR coding sheet for the 20 quality-assessed studies, with signal type (S1–S4), KPI family (K1–K5), effect magnitudes, MMAT 2018 scores and quality tiers; (iii) the PRISMA 2020 flow counts in structured form; (iv) the VOSviewer network map and edge files used to produce the bibliometric figures; (v) the Python scripts that produced each figure and table; and (vi) the rendered figures in TIFF format.

The general analytical pipeline that ingested, deduplicated, screened, extracted and clustered these data is implemented in the open-source proportione-prisma toolkit, released separately under MIT licence (DOI: 10.5281/zenodo.19883809). This archive is a study-specific companion to that toolkit.