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A multi-layer framework for modelling resilience in waterway-dependent supply chains using reliability theory : a case study of the West German canal system
Citation Link: https://doi.org/10.15480/882.17666
Publikationstyp
Doctoral Thesis
Date Issued
2026
Sprache
English
Author(s)
Gast, Johannes
Advisor
Referee
Title Granting Institution
Technische Universität Hamburg
Place of Title Granting Institution
Hamburg
Examination Date
2026-05-26
Institute
TORE-DOI
Citation
Technische Universität Hamburg (2026)
Background: Recent disruptions in waterway infrastructure highlight the vulnerabilities of waterway-dependent supply chains (SCs). Although substantial research in various disciplines exists, the effect of infrastructure availability on SC resilience (SCR) remains underexplored. This gap persists despite high-profile infrastructure failures, such as the 2021 Suez Canal blockage. Objective: This study develops a comprehensive SCR model for waterway-dependent SCs by integrating historical event data, infrastructure states, and dynamic time factors. The primary objective is to enable effective SC decision-making (SCDM) and the evaluation of mitigation strategies that preserve SC value during disruptions. Methods: This dissertation employs a mixed-method design to develop a multi-layer, multi-state SCR framework with four layers representing infrastructure, transportation, SCs, and industry. The approach integrates reliability theory to assess infrastructure availability, which informs an operations research model combining vehicle routing. Focusing on the West German canal system, the methods evaluate how availability affects cost, SC performance, and resilience strategies. Results: The results quantify the critical link between infrastructure state and SC performance, demonstrating how empirical transportation cost increases propagate through the supply chain. Key findings highlight the importance of infrastructure availability in facilitating effective risk mitigation, influenced by the warning times, availability, and SCR. The model further quantifies infrastructure disruption and mitigation effects on SCs' value and determines their viability. The analysis quantifies the system-wide cost of infrastructure disruption for the case study at approximately seven million EUR per day. Further, the model estimates the annual welfare utility of a single secondary lock chamber at one million EUR, demonstrating the scale of economic gains achievable through targeted resilience investments. In addition, the results reveal the novel 'shuttling effect': a cyclical phenomenon distinct from the 'ripple effect'. The shuttling effect arises from repeated, short-term capacity constraints in shared infrastructure. Conclusion: This research demonstrates that a deep understanding of infrastructure states is vital to strengthening SCR, particularly in waterway-dependent SCs. The resulting model provides actionable insights for SCDM and informs both private and public resilience enhancement strategies. Furthermore, the findings demonstrate that proactive SCDM can mitigate welfare loss more effectively than conventional reactive approaches by incorporating warning time, multimodal strategies, and considering the systemic risk of the 'shuttling effect'.
Subjects
supply chain resilience
inland waterway transport
reliability theory
multi-state networks
supply chain decision-making
availability assessment
DDC Class
388: Transportation
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Gast_Johannes_A-Multi-Layer-Framework-for-Modelling-Resilience-in-Waterway-Dependent-Supply-Chains.pdf
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