A framework and case study for integrating household decision-making into post-earthquake recovery models

Abstract

Prior empirical research has demonstrated that the decisions of affected populations can significantly influence housing recovery outcomes following a natural hazard event. The current study seeks to develop an integrated post-earthquake recovery model that explicitly accounts for household decision-making. An empirical probabilistic utility-based decision model is developed using data from a survey of Los Angeles households. The results from a multinomial logistic regression showed that the time in residence, neighborhood evacuation level, physical damage to residence, duration of utility disruption and loss of access to the building, household income and earthquake insurance coverage had a statistically significant association with homeowners’ decisions. For renter decision-making, only physical damage to the residence and duration of utility disruption are found to be statistically significant. In addition to household decision-making, the integrated model incorporates probabilistic building performance assessment and a discrete-state stochastic process representation of post-earthquake housing recovery. The results from a case study incorporating three Los Angeles neighborhoods (Koreatown, East Hollywood and Lomita) show that the influence of household decision-making on occupancy-based recovery trajectories is amplified as the scale of damage increases.