| Title | Probabilistic Modeling of Small Business Recovery after a Hurricane: A Case Study of 2017 Hurricane Harvey |
|---|---|
| ID_Doc | 70091 |
| Authors | Liang, D; Ewing, B; Cardella, E; Song, LG |
| Title | Probabilistic Modeling of Small Business Recovery after a Hurricane: A Case Study of 2017 Hurricane Harvey |
| Year | 2023 |
| Published | Natural Hazards Review, 24, 1 |
| Abstract | Economic resilience defines a community's ability to prevent, withstand, and quickly recover from major disruptions to its economic base. Instead of having repeated damage and need for outside assistance, resilient communities proactively protect themselves against hazards, build self-sufficiency, and become more sustainable over the long term. Within these communities, small businesses are an important driver of economic growth and employment. However, small businesses are extremely vulnerable to natural disasters: about 40-60 percent of them never reopen their doors after a disaster. To gain an insight into the vulnerability and resilience of small businesses, we collected firm-level data through an online survey of primary decision-makers of small businesses located in 2017 Hurricane Harvey impacted counties. The questions in the survey covered five broad categories: general business characteristics; finance impact; operation impact; built environment impact; and mitigation actions. The analysis shows a small variation in recovery time between industry groups. However, the contrast between firms that invested in resilience and firms that did not is significant. We then modeled the small business recovery as a stochastic process and used the survey data to select probability models and then estimate model parameters. If firms chose to invest in resilience, the mean and median times could be reduced by 57% and 8.5%, respectively. Using the baseline provided, a firm could estimate the length of recovery expected and prepare a business continuity plan accordingly. In a hurricane's aftermath, their performance can be benchmarked against that of their peers. The findings would serve as basis for public policies towards incentivizing prestorm mitigation and resilience-building actions. |
| https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29NH.1527-6996.0000602 |
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