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Motivating property owners to mitigate seismic risks for existing buildings is a major challenge for many earthquake-prone regions. This article identifies primary factors that may affect the adoption of seismic retrofit by owners of commercial and residential buildings, assesses the influence of economic, social, regulatory, and individual factors on retrofit implementation in three California cities, and discusses potential approaches to promoting seismic retrofits. Data for three retrofit programs are utilized to create predictive models for retrofit probability. The results suggest that retrofit probability for multifamily residential buildings may increase with building height, median housing value, educational attainment, and population density in the neighborhood, but may decrease with building age, building size, land value, and housing vacancy rate in the neighborhood. The retrofit decision for commercial buildings is strongly correlated with the number of stories and rooms, land value, vacancy rate, and population density, while the retrofit decision for residential buildings is highly associated with building age, number of rooms, land value, median housing value, median contract rent, and educational attainment. Overall, promoting seismic retrofits requires careful consideration of different motivators and impediments to owner’s retrofit actions for commercial and residential buildings, and for older, taller, larger buildings, which tend to be more vulnerable but are associated with higher retrofit costs. In addition, neighborhood characteristics including median housing value and vacancy rate may be strong indicators of the retrofit probability among building clusters.

This article presents the current state-of-practice with respect to quantifying the total cost to retrofit an existing building. In particular, we combine quantitative, qualitative, and heuristic data to provide a taxonomy for understanding the direct and indirect costs associated with seismic risk mitigation. Much of the literature to date has focused on estimating structural retrofit costs, the costs of retrofitting the structural elements of a building. In contrast, there is very little research or data on the remaining cost components of the total cost. We propose using structural cost as the foundation for approximating the remaining cost components and the total cost itself. To validate our findings, we compare the proposed approximations with actual cost estimates developed by engineering professionals.

This article presents a methodology for estimating seismic retrofit costs from historical data. In particular, historical retrofit-cost data from Federal Emergency Management Agency (FEMA) 156 is used to build a generalized linear model (GLM) to predict retrofit costs as a function of building characteristics. While not as accurate as an engineering professional’s estimate, this methodology is easy to apply to generate quick estimates and is especially useful for decision makers with large building portfolios. Moreover, the predictive modeling approach provides a measure of uncertainty in terms of prediction error. The article uses prediction error to compare different modeling choices, including the choice of distribution for costs. Finally, the proposed retrofit-cost model is implemented to estimate the cost to retrofit a portfolio of federal buildings. The application illustrates how the choice of distribution affects cost estimates.