RESUMEN
• A resilience assessment framework for the GLSN across two dimensions, including static resilience and dynamic resilience. • Identification of overlapping community structure and key nodes with the clique percolation method. • A network disintegration method to consider the impact of traffic flow on system resilience assessment. • An innovative, knock-on effect simulation model with tailored, local weighted flow redistribution rules for dynamic resilience assessment. As a critical infrastructure system of modern society, the global liner shipping network (GLSN) has become increasingly complex and thus vulnerable to disruptions. This study proposes a resilience assessment framework for the GLSN across two dimensions, including static resilience and dynamic resilience. First, by leveraging high-frequency vessel movement data, the GLSN is constructed. Then, with the clique percolation method (CPM), overlapping community structures and key nodes can be identified. The static resilience assessment is initially conducted using simulation techniques, with nodes attacked through pre-designed scenarios. Then, a network disintegration method is employed to consider the impact of traffic flow on system resilience assessment, which separates the weighted GLSN into different layers for evaluation. The results show that both overlapping community structure and traffic flow significantly impact the resilience evaluation of the GLSN. Finally, to assess the dynamic resilience of the GLSN, we propose an innovative, knock-on effect simulation model with tailored, locally weighted flow redistribution rules. It provides a method for predicting the impacts of potential global disruptions (e.g., the COVID-19 pandemic) and critical maritime infrastructure failures (e.g., the Suez Canal obstruction) on the shipping network, which are of great concern not only to academia but also to industry. [ FROM AUTHOR]
RESUMEN
As a critical infrastructure system of modern society, the global liner shipping network (GLSN) has become increasingly complex and thus vulnerable to disruptions. This study proposes a resilience assessment framework for the GLSN across two dimensions, including static resilience and dynamic resilience. First, by leveraging high-frequency vessel movement data, the GLSN is constructed. Then, with the clique percolation method (CPM), overlapping community structures and key nodes can be identified. The static resilience assessment is initially conducted using simulation techniques, with nodes attacked through pre-designed scenarios. Then, a network disintegration method is employed to consider the impact of traffic flow on system resilience assessment, which separates the weighted GLSN into different layers for evaluation. The results show that both overlapping community structure and traffic flow significantly impact the resilience evaluation of the GLSN. Finally, to assess the dynamic resilience of the GLSN, we propose an innovative, knock-on effect simulation model with tailored, locally weighted flow redistribution rules. It provides a method for predicting the impacts of potential global disruptions (e.g., the COVID-19 pandemic) and critical maritime infrastructure failures (e.g., the Suez Canal obstruction) on the shipping network, which are of great concern not only to academia but also to industry.
RESUMEN
The recent experience of lockdowns during COVID-19 highlights the prolonged impact a pandemic could have on ports and the shipping industry. This paper uses port call data derived from the Automatic Identification System (AIS) reports from the world's 30 largest container ports to quantify both the immediate and longer-term impact of national COVID-19 lockdown policies on global shipping flows. The analysis uses the Difference-in-Difference (DID) and combined regression discontinuity design (RDD)-DID models to represent the effects of lockdown policies. The combination of RDD and DID models is particularly effective because it can mitigate time trends in the data, e.g., the Chinese New Year effect on Chinese ports. This study further examines the potential shock propagation effects, namely, how lockdown policy in one country (i.e., China) can affect the number of port calls in other countries. We categorize ports in other countries into a high-connectivity (with Chinese ports) group and a low-connectivity group, using a proposed connectivity index with China derived from individual vessel trajectories obtained from the AIS data. The results provide a clearly measurable picture of the kinds of trade shocks and consequent pattern changes in port calls over time caused by responses to lockdown policies of varying levels of stringency. We further document the existence of significant shock propagation effects. As the risk of pandemics rises in the twenty-first century, these results can be used by policy makers to assess the potential impact of different levels of lockdown policy on the maritime industry and trade flows more broadly. Maritime players can also use findings such as these to manage their capacity during lockdowns more effectively and to respond more flexibly to changing demand in seaborne transportation.
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This study investigates the key psychological factors that influence customer's intention to use cruise services post COVID-19. A theoretical model grounded on consumer and health-driven theories (i.e. perceived value, perceived trust and health belief model) is developed. A survey questionnaire is designed and administered to 376 Chinese consumers. The theoretical model was tested via structural equation modelling. Results reveal that the constructs of the health belief model (i.e. perceived benefits, perceived health threat, self-efficacy and cues to action) have a significant effect on customers' perceived value towards cruise services. Perceived value then has direct and indirect effects on customers' cruise intention through perceived trust. This study enhances academic research by justifying customers' intention to use cruise services via consumer and health-belief viewpoints and provides implications for cruise management and policy formulation.
RESUMEN
The cruise industry has suffered a huge loss due to the suspension of cruise operations during the COVID-19 pandemic. As the industry is preparing for recovery, there is an urgent need for research on cruise consumers' psychology, in particular, the factors influencing their intention to use cruise services after the pandemic. This study employs theories, namely, the health belief model, trust theory and attitude theory, to investigate consumers' use intention for cruise services after the pandemic. An online survey was administered to consumers in China's tourism industry, where 376 responses were received. Subsequently, this study employs structural equation modelling to test its theoretical model consisting of hypotheses. The results show that consumers' trust is directly influenced by health belief constructs including perceived safety threat, outcome expectation, self-efficacy and cues to action. Next, trust exerts a direct impact on consumers' attitude and intention to use cruise services. Moreover, this study finds full and partial mediation effects. The findings provide a series of recommendations for cruise operators and policymakers in terms of marketing strategies, service design, public communication and health measures.