Validation of Measurement Constructs for Trust, Autonomy, Resilience, and Innovation in Edge Intelligence Systems

Abstract

The objective of this study was to validate a measurement instrument designed to assess key organizational and system-level constructs trust, autonomy, resilience, and innovation within edge intelligence ecosystems. While these constructs are frequently examined in technology management and intelligent systems research, few studies have rigorously tested their measurement properties in the context of distributed, edge-centric infrastructures, where system architectures, operational workflows, and decision-making practices differ significantly from traditional cloud-centric models. A quantitative, cross-sectional research approach was employed, collecting data from 50 participants, including researchers, system architects, and edge computing practitioners. The instrument’s psychometric properties were evaluated using factor loadings, composite reliability (CR), average variance extracted (AVE), and the Heterotrait–Monotrait Ratio (HTMT). Findings revealed strong convergent validity, with factor loadings ranging from acceptable to excellent, CR values exceeding 0.87, and AVE values above the 0.50 threshold. Discriminant validity was supported through HTMT ratios below 0.85, indicating that the constructs are empirically distinct. The validated instrument offers a reliable framework for assessing organizational and technological factors that influence the effectiveness, trustworthiness, and innovation potential of edge intelligence deployments. This study contributes to the advancement of intelligent and autonomous edge systems by enabling robust measurement and analysis of critical success factors, supporting secure, resilient, and future-oriented edge computing applications. The results indicate that the instrument is psychometrically sound and suitable for broader application in edge intelligence research.