Date of Original Version
This paper describes a case study applying multi-criteria decision analysis (MCDA) to weight indicators for assessing the exposure and sensitivity of seaports to climate and extreme weather impacts. Researchers employed the analytic hierarchy method (AHP) of MCDA to generate weights for a subset of expert-selected indicators of seaport exposure and sensitivity to climate and extreme weather. The indicators were selected from the results of a survey of port-experts who ranked candidate indicators by magnitude of perceived correlation with the three components of vulnerability; exposure, sensitivity, and adaptive capacity. As those port-expert respondents found significantly stronger correlation between candidate indicators and the exposure and sensitivity of a port than with a port’s adaptive capacity, this AHP exercise did not include indicators of adaptive capacity. The weighted indicators were aggregated to generate composite indices of seaport exposure and sensitivity to climate and extreme weather for 22 major ports in the North East United States. Rank order generated by AHP-weighted aggregation was compared to a subjective expert-ranking of ports by expert-perceived vulnerability to climate and extreme weather. For the sample of 22 ports, the AHP-generated ranking matched three of the top four most vulnerable ports as assessed subjectively by port-experts. These results suggest that a composite index based on open data weighted via MCDA may eventually prove useful as a data-driven tool for identifying outliers in terms of relative seaport vulnerabilities, however, improvements in the standardized reporting and sharing of port data will be required before such an indicator-based assessment method can prove decision-relevant.
McIntosh, R.D., Becker, A. Applying MCDA to weight indicators of seaport vulnerability to climate and extreme weather impacts for U.S. North Atlantic ports. Environ Syst Decis (2020). https://doi.org/10.1007/s10669-020-09767-y
Available at: https://doi.org/10.1007/s10669-020-09767-y