Author
Abstract
The European Union’s Green Taxonomy is a pioneering classification system that facilitates sustainable investment and supports the achievement of key climate and energy targets. This paper introduces the innovative concept of “Warehouse 5.0,” a transformative paradigm for warehouse management that synergistically combines advanced artificial intelligence (AI) solutions with sustainable practices to meet the stringent criteria of the EU Green Taxonomy. Through an in-depth exploration of the taxonomy’s objectives, criteria, and requirements, this paper presents a comprehensive model for implementing Warehouse 5.0, explains the central role of AI in facilitating this transition, and provides concrete examples and implementation strategies. The six environmental goals of the EU’s Green Taxonomy serve as the foundation for the environmentally sustainable paradigm of Warehouse 5.0. Through the use of AI solutions, Warehouse 5.0 optimizes energy consumption, predicts and prevents equipment failure, ensures efficient water management, minimizes waste and promotes sustainable transportation and logistics. This paper shows how aligning Warehouse 5.0 with the EU Green Taxonomy can lead to significant long-term cost savings, improve a company’s reputation by adopting sustainable practices and contribute to a more environmentally conscious and resilient future. The implementation of this approach has yielded initial successes. The paper also highlights the criticality and challenges associated with implementing Warehouse 5.0. Implementing Warehouse 5.0 is critical for warehouses to meet the stringent criteria of the EU Green Taxonomy and promises significant environmental benefits, such as improved environmental performance, reduced greenhouse gas emissions, and the promotion of sustainable development.
Suggested Citation
Bernardo Nicoletti & Andrea Appolloni, 2025.
"Artificial Intelligence in Support of Warehousing 5.0 and the EU Green Taxonomy,"
Springer Proceedings in Business and Economics,,
Springer.
Handle:
RePEc:spr:prbchp:978-3-031-91686-1_9
DOI: 10.1007/978-3-031-91686-1_9
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