AI Brand Visibility Instrument (ABVI): Indicator Data and Analysis Code

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Authors: Dmitrij Żatuchin
Cited by: 0

Abstract

This dataset contains the indicator matrix and reproducible analysis code supporting the paper "AI Brand Intelligence as a Measurement Instrument: Factorial Validity of Multi-Method Corporate Visibility Assessment" (submitted to Information & Management). The deposit includes: indicator_matrix.json — 12×11 indicator matrix covering 12 brands across 5 industries (SaaS, consulting, e-commerce, fintech, healthtech). Indicators are drawn from two source studies: LLM reputation sourcing (S2, n=1,311 responses) and category ownership mapping (S5, n=3,750 responses). analysis.ipynb — Jupyter notebook implementing the full psychometric validation pipeline: descriptive statistics, Bartlett and KMO tests, PCA with Varimax rotation, EFA with Oblimin rotation, AVE and composite reliability, Fornell-Larcker discriminant validity, and visualizations (biplot, loading heatmap, scree plot). All data is derived from commercially available AI systems (GPT, Gemini, Perplexity). No human participants were involved.

Fields of Study & Subjects

Corporate Identity and Reputation Digital Marketing and Social Media Consumer Behavior in Brand Consumption and Identification

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
27 February 2026
Language
EN
Document type
Dataset