Understanding generative AI effects on sustainable consumption outcomes: A complementary analytical approach
Behzad Foroughi · Technology in Society · 2026
Research on generative AI (GenAI) in marketing has largely emphasized adoption and engagement outcomes, with limited evidence on how GenAI-assisted shopping shapes sustainable consumption across economic, social, and environmental dimensions. Addressing this gap, this study draws on Affordance Actualization Theory and service-dominant logic to link GenAI affordances to perceived empowerment and value co-creation, and subsequently to sustainable consumption outcomes, while examining the moderating roles of promotion focus and prevention focus. Survey data from 386 GenAI users in Vietnam were analyzed using “partial least squares structural equation modeling” (PLS-SEM) and complemented with “artificial neural network” (ANN) analysis. The results show that understandability, personalization, and anthropomorphism positively influence perceived empowerment and value co-creation, whereas accuracy and currency show selective effects and timeliness is not significant. Perceived empowerment and value co-creation positively predict economic and environmental sustainable consumption, but neither mechanism predicts social sustainable consumption. Regulatory focus shows selective moderation, strengthening some sustainability links and weakening others. ANN results reinforce the dominant roles of personalization and understandability. The study advances understanding of how GenAI features translate into sustainability-relevant consumer outcomes and offers actionable implications for retailers, GenAI designers, and policy actors seeking to encourage responsible consumption through GenAI-enabled shopping.