Inland waterways are complex socio-technical systems characterized by decentralized governance, dense dependency on limited collective resources, a highly interdependent network of transactional relationships, and susceptibility to both natural and manmade hazards and disruptions. The majority of the research in this field focuses on building robustness through hardening the infrastructure or optimizing recovery decisions based on economic concerns or minimizing recovery time. However, this type of research does not capture the human cognitive processes and collaboration at work during a disruption to a complex system with competing interest. Real-world recovery efforts are highly dependent upon human operators making un-modeled decisions in the context of a very specific and unique disrupted system states. Under these conditions situational awareness is too dynamic and emergent, and stakeholder interest too diverse to support optimization modeling or decision-making.

The current research represents a shift from resilience management efforts that assume centralized decision-making and resource control, to resilience management that emphasizes understanding the heuristics and human cognition dynamics governing the interaction between stakeholders in a decentralized context. While conceptual work exists discussing some of the topics that influence this dissertation (i.e., social capital, cognitive dimensions of resilience, technical-cognitive interactions), and while some of these concepts have been studied empirically in a community resilience context, there is little empirical research focusing on socio-technical systems such as inland waterway transportation systems. This research applies empirical methods to primary data and contributes to the field of resilience management of this particular class of socio-technical systems.