Probabilistic Modeling of Small Business Recovery after a Hurricane: A Case Study of 2017 Hurricane Harvey
Publication: Natural Hazards Review
Volume 24, Issue 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.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions. As survey responses could reveal the identity of businesses who participated in the study, information on their finances, operations, and impacts can only be made available, upon request, for reuse in aggregated forms. Survey instrument and statistical models that do not contain confidential information on individual businesses are available from the corresponding author upon reasonable request.
Acknowledgments
This material is based upon work supported by the National Institute of Standards and Technology (under Award # 70NANB19H061) and Center for Risk-Based Community Resilience Planning) and Economic Development Administration (under Project # 08-79-05280) of US Department of Commerce. Any opinions, findings, and conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsors.
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Natural Hazards Review
Volume 24 • Issue 1 • February 2023
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This work is made available under the terms of the Creative Commons Attribution 4.0 International license, https://creativecommons.org/licenses/by/4.0/.
History
Received: Nov 2, 2021
Accepted: Aug 14, 2022
Published online: Dec 1, 2022
Published in print: Feb 1, 2023
Discussion open until: May 1, 2023
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