Imax-ai: an Explainable Artificial Intelligence Decision Support System for Innovation Maturity Analytics in Higher Education
Year: 2026
Type: article
Abstract: Innovation maturity models in higher education typically provide quantitative assessments without offering intelligent interpretive capabilities to support strategic decision-making. This study introduces IMAX-AI, an explainable artificial intelligence–driven decision-support artifact designed to extend the validated Innovation Maturity Index for Universities (IM-IU). Developed following a Design Science Research approach, IMAX-AI integrates psychometric validation, Random Forest–based feature weighting, and an explainable AI interpretive layer within a four-layer enterprise information systems architecture comprising data acquisition, quantitative maturity analytics, explainable intelligence, and governance-oriented visualization. The artifact was empirically demonstrated through its application in a public university located in Southern Brazil, illustrating its ability to identify multidimensional maturity profiles, detect structural asymmetries across institutional dimensions, and generate transparent, prioritized governance recommendations. By combining multidimensional maturity assessment with interpretable machine learning and intelligent decision support, IMAX-AI advances innovation maturity analytics beyond static benchmarking toward explainable, evidence-based governance for higher education institutions.
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7225231074