Artificial Intelligence and Blockchain as Enablers of Resilient and Sustainable Multimodal Transport Chains: Evidence from a Multi-Actor Qualitative Study

This research analyses how the joint integration of artificial intelligence and blockchain can contribute to the resilience and sustainability of multimodal transport chains. We adopt an interpretivist and constructivist stance in order to understand the modalities of appropriation, negotiation, and deployment of AI–blockchain mechanisms at the port–rail–road interfaces. The data come from 29 semi-structured interviews conducted with four categories of actors involved in multimodal corridors: digital-solution start-ups, transport–logistics SMEs, industrial shippers, and infrastructure managers. The thematic analysis, conducted through an abductive approach, highlights that the expected effects of AI and blockchain do not manifest directly on sustainability, but mainly pass through four mediating organizational mechanisms. First, shared logistics visibility appears as the decisive entry point. Inter-organizational coordination, supported by augmented governance mechanisms, conditions the translation of visibility into joint decisions. Third, distributed trust is built around shared evidence. Transactional automation unfolds gradually, with an ambivalence between efficiency gains and risks of rigidity in crisis situations. These mechanisms jointly fuel resilience as well as sustainability. The study proposes an integrated conceptual model and opens the way to a confirmatory phase by suggesting avenues for operationalizing the constructs.