Artificial Intelligence-Based Distribution Status of Sustainable Fashion Systems by Country : Comparative Case Studies of Stella McCartney, Patagonia, RE;CODE, and MUJI

The global fashion industry faces challenges from sustainability imperatives, market volatility, and digital transformation, making the management of complex logistics systems crucial. This study examined how leading sustainable fashion brands in Europe, the US, South Korea, and Japan utilize artificial intelligence (AI)-driven classification systems and quantum computing to improve efficiency, adaptability, and environmental responsibility in logistics. Grounded in the complex systems theory, this comparative case analysis examined the logistics frameworks of Stella McCartney (UK), Patagonia (US), RE;CODE (South Korea), and MUJI (Japan). Based on AI-enabled categorization, this study examined the dynamic feedback loops, decentralized decision-making structures, and systemic interdependencies that drive adaptive behaviors among these brands. Findings revealed distinct regional approaches shaped by national sustainability policies and digital governance models, highlighting the importance of complexity-aligned project methodologies in managing sustainable logistics. This study contributes to the growing discourse on AI and quantum computing as transformative tools for Industry 6.0, particularly regarding circular fashion and supply chain resilience.