Enhancing Coordination and Decision Making in Humanitarian Logistics Through Artificial Intelligence: A Grounded Theory Approach

Panagiotis Pantiris, Petros L. Pallis, Panos T. Chountalas () and Thomas K. Dasaklis
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Panagiotis Pantiris: School of Social Sciences, Hellenic Open University, 18 Aristotelous St., 26335 Patras, Greece
Petros L. Pallis: School of Social Sciences, Hellenic Open University, 18 Aristotelous St., 26335 Patras, Greece
Panos T. Chountalas: School of Social Sciences, Hellenic Open University, 18 Aristotelous St., 26335 Patras, Greece
Thomas K. Dasaklis: School of Social Sciences, Hellenic Open University, 18 Aristotelous St., 26335 Patras, Greece

Logistics, 2025, vol. 9, issue 3, 1-33

Abstract: Background: The adoption of artificial intelligence (AI) in humanitarian logistics is essential for improving coordination and decision making, especially in the challenging landscape of disaster-relief settings. However, the current literature offers limited empirical evidence with respect to the specific impact of AI on coordination and decision making for real-life humanitarian problems. Based on evidence from the humanitarian sector, this paper focuses on how AI could help humanitarian organizations collaborate better, streamline relief supply-chain operations and use resources more effectively. Methods: Twelve key themes influencing AI integration are identified by the study using a Grounded Theory (GT) approach based on interviews with experts from the humanitarian sector. These themes include data reliability, operational limitations, ethical considerations and cultural sensitivities, among others. Results: The findings suggest that AI improves forecasting, planning and inter-organizational coordination and is especially useful during the preparedness and mitigation stages of relief operations. Successful adoption, however, depends on adjusting tools to actual field conditions, building trust and training and striking a balance between algorithmic support and human expertise. Conclusions: The paper offers useful and practical advice for humanitarian organizations looking to use AI technologies in an ethical way while taking into account workforce capabilities, cross-agency cooperation and field-level realities.

Keywords: humanitarian logistics; artificial intelligence; decision making; coordination; disaster response; emergency management; resource optimization; supply chain operations; grounded theory (search for similar items in EconPapers)
JEL-codes: L8 L80 L81 L86 L87 L9 L90 L91 L92 L93 L98 L99 M1 M10 M11 M16 M19 R4 R40 R41 R49 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlogis:v:9:y:2025:i:3:p:113-:d:1721909

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