Abstract

This study examined the hypothesized structural relationships among Artificial Intelligence Adoption (AIA), Environmental Technologies (ET), Management Strategy (MS), and Environmental Sustainability (ES) in organizations involved in urban development and environmental management, with explicit relevance to Sustainable Development Goal 11 (SDG 11). Data were collected from 320 participant, and were analyzed through Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM). The results of the study showed that standardized factor loadings ranged from .819 to .862, Average Variance Extracted (AVE) from .695 to .721, and Composite Reliability from .901 to .912. The structural model showed excellent reported fit with the observed covariance structure (χ² = 138.426, df = 126, χ²/df = 1.099, p = 0.212, GFI = 0.958, NFI = 0.976, TLI = 0.991, CFI = 0.994, RMSEA = 0.016, RMR = 0.021). The results of the study showed that Artificial Intelligence Adoption (AIA) and Environmental Technologies (ET) had positive direct effect on Management Strategy (MS) (β = 0.468, p < 0.001 and 0.421, p < 0.001) respectively, while Management Strategy exerted positive effect direct on Environmental Sustainability (ES) (β = 0.493, p < 0.001). Artificial Intelligence Adoption (AIA) and Environmental Technologies had direct positive effect on Environmental Sustainability (ES) (β = 0.297, p < 0.001) and (0.276, p < 0.001) respectively. Management Strategy mediate the relationships between Artificial Intelligence Adoption (AIA) and Environmental Sustainability (ES) (β = 0.231, p < 0.001), and between Environmental Technologies (ET) and Environmental Sustainability (ES) (0.208, p < 0.001). The findings position Management Strategy as an organizational conversion mechanism linking technological capability with environmental sustainability outcomes relevant to sustainable urban environmental management (SDG 11).