Intelligent Systems for Sustainable Digital Ecosystems in Fast-Food Services: Shaping Generation Z Consumption Behaviors and Environmental Outcomes

Abstract

Digital transformation in the fast-food industry has fostered the development of sustainable and adaptive digital ecosystems, particularly among Generation Z consumers. This systematic literature review synthesizes 30 rigorously selected peer-reviewed articles from six major academic databases to examine how intelligent systems—artificial intelligence, machine learning, and advanced analytics—support sustainable growth in quick-service restaurants. The thematic analysis identified measurable impacts: intelligent systems increased average order values by 15–25%, reduced customer service response times by 40–60%, and decreased food waste by 15–25% through supply chain optimization. Generation Z consumers also demonstrated 30–40% higher repeat purchase frequencies when exposed to personalized recommendations and sustainability transparency features. The findings indicate that AI-driven personalization, automation, and supply chain optimization can simultaneously enhance operational efficiency, enable hyper-personalized customer experiences, and promote sustainable consumption behaviors. However, implementation challenges—including data privacy concerns, algorithmic bias risks, and greenwashing vulnerabilities—require robust governance frameworks. This review advances understanding of how emerging technologies align profit objectives with environmental responsibility, while offering practical implications for restaurant operators, technology providers, and policymakers.

Keywords

Digital ecosystem; Fast-food industry; Generation Z; sustainability; Machine learning