Resident recovery priorities for activities and services after a hypothetical hurricane: Insights from metropolitan survey data

This study investigates the recovery priorities of residents in metropolitan areas for restoring electric power utility and transportation infrastructure impacted by hurricanes.

Utilizing a survey distributed across four major U.S. cities—Houston, New York City, Washington D.C., and Miami—the research poses hypothetical hurricanes to explore how demographics, socio- economic features, work characteristics, and access to alternative power source(s) influence individual preferences for restoration to recover disrupted activities and services. Through the application of rank-ordered logit models, including latent class and recursive partitioning techniques, the study identifies distinct preference patterns across various groups. The latent class rank-ordered logit model reveals three distinct groups with varied recovery priorities. For instance, younger residents with flexible work options and access to alternative power sources prioritize employment and banking services for their community, while older working-age residents without children at home focus on food and health services.

These insights highlight the importance of recognizing such heterogeneity in restoration and recovery planning. On the other hand, the recursive partitioning approach effectively captures broad trends, such as prioritization of essential services like health and food, but shows limitations in revealing more detailed preference differences.

The study advocates for a more tailored approach to disaster restoration and recovery that not only prioritizes technical and infrastructural restoration but also aligns with the specific needs and preferences of the affected populations. By aligning recovery efforts more closely with resident preferences, policymakers and emergency managers can enhance the efficacy and perception of post-disaster recovery efforts, ultimately leading to more resilient urban communities.