A Socio-Technical Investigation of Human–AI Interaction in AI-enabled Decision Support Systems within Digital Supply Chains
Keywords:
human–AI interaction, decision support systems, digital supply chains; explainable, artificial intelligence, organizational adoptionAbstract
Digital supply chains increasingly rely on artificial intelligence to support planning, coordination, and risk mitigation decisions. While algorithmic accuracy has improved, organizational adoption continues to depend on how human decision makers interact with AI-enabled decision support systems. This study investigates human–AI interaction through a socio-technical lens, focusing on trust, interpretability, accountability, and organizational integration within digital supply chains. Drawing on empirical evidence and analytical modeling, the research demonstrates that effective human–AI collaboration enhances decision quality, resilience, and adaptive capacity. The findings contribute to information systems theory by clarifying how technical intelligence and social structures co-evolve in AI-driven supply chain environments.
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