Details of Research Outputs

The long term impact posed by climate change risk remains unclear and is subject to diverse interpretations from different maritime stakeholders. The inter-dynamics between climate change and ports can also significantly diversify in different geographical regions. Consequently, risk and cost data used to support climate adaptation is of high uncertainty and in many occasions, real data is often unavailable and incomplete. This paper presents a risk and cost evaluation methodology that can be applied to the analysis of port climate change adaptation measures in situations where data uncertainty is high. Risk and cost criteria are used in a decision-making model for the selection of climate adaptation measures. Information produced using a fuzzy-Bayesian risk analysis approach is utilized to evaluate risk reduction outcomes from the use of adaptation measures in ports. An evidential reasoning approach is then employed to synthesize the risk reduction data as inputs to the decision-making model. The results can assist policymakers in developing efficient adaptation measures that take into account the reduction in the likelihood of risks, their possible consequences, their timeframe, and costs incurred. A technical study across 14 major container ports in Greater China is presented to demonstrate the interaction between cost and risk analysis, and to highlight the applicability of the stated methodology in practice. The paper offers a useful analytical tool for assessing climate change risks to ports and selecting the most cost-effective adaptation measures in uncertain conditions. It can also be used to compare the practitioners’ perceptions of climate risks across different geographical regions, and to evaluate improvements after implementation of the selected adaptation measures with potential budgetary constraints. The methodology, together with the illustrative cases, provides important insights on how to develop efficient climate change adaptation measures in a supply chain context to improve the sustainability of development and enhance adaptation measures for ports, port cities, intermodal transport, supply chains, and urban and regional planning in general. © 2017 Elsevier Ltd