A Qualitative Study to Explore Gaps Between Theory and Practice in Disaster Response Logistics Path Planning

In disaster response logistics, efficient transportation management is essential. For theoretical models to be effective, they must closely align with the practical challenges faced by responders navigating disrupted road networks. To that end, the aim of this study is to compare current logistics planning practices in disaster response organizations in the United States with assumptions found in the literature for online path planning under uncertainty. Data were collected from in-depth interviews with emergency responders across federal, state, private, and nonprofit organizations and coded to identify common planning practices. Findings were then compared to existing literature across several dimensions, including path-planning responsibility, network representation, planning goals, information sources, methods of discovering network status, and knowledge sharing. This study reveals several key differences between current practice and assumptions in online path planning models in literature. Most notably, current practices are unlikely to support models that require algorithms to assume immediate updates on road conditions, run within drivers’ vehicles, rely on knowledge of road status probabilities, or prioritize speed over reliability. Despite the availability of advanced online path planning models in literature, few are implemented in real-world settings due to these limitations. The study suggests that, for research advancements to be practical, practitioners must adopt formal information-sharing practices, while researchers should align models with the operational constraints and objectives of responders. These findings can help align research with practitioners’ needs, potentially improving logistics, expediting disaster response, and ultimately lessening the impact on affected communities.