Leonard Edward Sely

Sustainable consumption has become a global priority, yet the factors that encourage people to adopt environmentally friendly purchasing behavior differ across cultures and technologies. This study explores how environmental knowledge, environmental attitude, and the perception of AI-driven personalization influence green purchasing intention and actual purchasing behavior among young consumers in Java, Indonesia. A survey of 517 university students was conducted, and the relationships among these factors were analyzed using structural equation modeling. The findings reveal that environmental knowledge strongly shapes environmental attitudes, which in turn enhance the intention and behavior to purchase green products. Perception of AI-driven personalization also strengthens green purchasing intention, although its direct effect on behavior is limited. These results suggest that digital platforms and marketers can promote sustainable consumption by combining environmental education with transparent and value-based AI personalization. The study contributes to understanding how psychological readiness and technological engagement together encourage greener consumption among youth in emerging economies.

Sustainable consumption is a global imperative, yet its behavioral drivers vary across cultural and technological contexts. This study examines how environmental knowledge (EK), environmental attitude (EAT), and perception of AI-driven personal-ization (PAI) shape green purchasing intention (GPI) and green purchasing behavior (GPB) among youth in Java, Indonesia. A cross-sectional survey of n = 517 university students (17–25 years) was analyzed using PLS-SEM (SmartPLS 4.0). The extended TPB model showed adequate measurement quality (e.g., SRMR = 0.074; HTMT < 0.90) and explanatory power (R²: EAT = 0.436; GPI = 0.373; GPB = 0.553; PAI = 0.077). Key structural paths were significant: EK → EAT (β = 0.661, p < 0.001); EAT → GPI (β = 0.445, p < 0.001); EAT → GPB (β = 0.366, p < 0.001); GPI → GPB (β = 0.444, p < 0.001); PAI → GPI (β = 0.136, p = 0.001), while PAI → GPB was not. Mediation tests (5,000 bootstraps) confirmed ro-bust indirect effects via EAT and GPI (e.g., EK → EAT → GPB; EAT → GPI → GPB; EK → EAT → GPI → GPB). Predictive assessment indicated Q² > 0 for endogenous constructs (EAT = 0.228; GPI = 0.220; GPB = 0.337), and PLSpredict favored the PLS-SEM model over a linear benchmark on 26 of 40 RMSE/MAE comparisons, evidencing out-of-sample utility. The findings suggest that strengthening knowledge to cultivate supportive at-titudes, coupled with transparent, value-aligned AI personalization, can elevate inten-tion and translate into greener purchases. Implications are offered for platform design, education, and policy in emerging markets.