Reshaping Commercial Parking Space: A SEM–ANN Evaluation Based on Integrated IS Success and UTAUT2

The rapid expansion of intelligent technologies within urban commercial built environments has created an urgent need to understand how the quality attributes of infrastructure of smart parking space translate into sustained user behavioral engagement. This study proposes and empirically validates an integrated framework combining the Information Systems (IS) Success Model and the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) to examine continuance usage intention toward intelligent commercial parking space. Cross-sectional survey data from 610 users were analyzed using a hybrid structural equation modeling (SEM) and artificial neural network (ANN) methodology. Results confirm that information quality, service quality, and system quality differentially shape performance expectancy and effort expectancy, which in turn influence user satisfaction and continuance usage intention. Information quality emerged as the most consequential antecedent (normalized relative importance: 100% across both cognitive evaluation models), performance expectancy as the dominant cognitive mediator, and user satisfaction as the most proximal behavioral driver. The non-significant effect of system quality on effort expectancy is interpreted as reflecting a differentiated role of technical reliability in mature smart city environments. Findings provide theoretical contributions to IS success and technology acceptance scholarship in the intelligent built environment domain, and practical guidance for architects, facility managers, and urban planners.