This technical report provides an extended validation of the Explainability Solution Space (ESS) through cross-domain evaluation. While initial validation focused on employee attrition prediction, this study introduces a heterogeneous intelligent urban resource allocation system to demonstrate the generality and domain-independence of the ESS framework. The second case study integrates tabular, temporal, and geospatial data under multi-stakeholder governance conditions. Explicit quantitative positioning of representative XAI families is provided for both contexts. Results confirm that ESS rankings are not domain-specific but adapt systematically to governance roles, risk profiles, and stakeholder configurations. The findings reinforce ESS as a generalizable operational decision-support instrument for explainable AI strategy design across socio-technical systems.
@article{arxiv.2603.01235,
title = {Extended Empirical Validation of the Explainability Solution Space},
author = {Antoni Mestre and Manoli Albert and Miriam Gil and Vicente Pelechano},
journal= {arXiv preprint arXiv:2603.01235},
year = {2026}
}