Disaster Assistance Winners and Losers
Do Small Businesses Benefit
Bibliographic Data
| ID | 21476767 |
|---|---|
| Authors | Maria Watson (0000-0002-6392-5081, Twitter (United States), corresponding author) |
| Year | 2022 |
| Volume | 88 |
| Issue | 3 |
| Pages | 305-318 |
| Publication date | 2022-07-03 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of the American Planning Association (JOURNAL) |
| Journal identifiers | ISSN: 0194-4363 • E-ISSN: 1939-0130 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/01944363.2021.1980086 |
| OpenAlex | W4200234520 |
| Language | EN |
| Citations received | 4 |
| References cited | 41 |
Problem, research strategy, and findings Disaster assistance in the United States has faced criticism for widening the unequal impacts of disasters, but little is known about whether and how this phenomenon applies to businesses. Small businesses make up most businesses in the United States, but they are particularly vulnerable to hazards given their relative lack of capital. Because recovery assistance to businesses is primarily loan based, this lack of capital can create conflicts in how aid is perceived and allocated. Assistance providers must balance aiding the most severely damaged businesses and lending to those that will be able to repay; for small business, the threat of additional debt can make even low-interest loans seem risky. With this research I attempted to better understand how these competing factors play out in recovery through regression analyses of approved loan amounts and loan utilization decisions in Galveston (TX) after Hurricane Ike. I found that businesses with higher repayment ability such as larger businesses, older businesses, and corporations were approved for high loan amounts. Smaller businesses, businesses with higher damage, and businesses with longer loan terms were less likely to use the loans in their recovery, despite being approved. These findings suggest that businesses with the resources to recover were more likely to be the ones benefiting from additional disaster assistance.Takeaway for practice These findings suggest that planners may need to create their own recovery programs specifically targeting subgroups of businesses that are important to their communities. Although important to many economic development initiatives, very small businesses, entrepreneurs, and sole proprietors may not benefit from federal assistance, particularly if they were severely damaged
Business · Collateral · Debt · Loan · Small business · Disaster Management and Resilience · Disaster Response and Management · Infrastructure Resilience and Vulnerability Analysis · Finance
Commercial Building Recovery Methodology for Use in Community Resilience Modeling
Assessing Catchment Vulnerability of Community-Based Small Businesses to Coastal Hazards
An evaluation of disaster preparedness policy
Benchmarking Plans for Community-Based Small Business Resilience across Gulf Coast Counties
Social justice implications of US managed retreat buyout programs
Disaster and Recovery
Mapping social vulnerability to enhance housing and neighborhood resilience
Social vulnerability and short-term disaster assistance in the United States
Importance of Households in Business Disaster Recovery
Why Latino Vendor Markets Matter
Businesses and Disasters
Social Vulnerability to Disasters
Measuring social equity in flood recovery funding
Predicting long-term business recovery from disaster
Mitigation Planning
Community Businesses as Social Units in Post-Disaster Recovery
The Role of SBA Loans in Small Business Survival after Disaster Events
Earthquake Recovery
Rebounding from disruptive events
A Comparison of the Bicoastal Disasters of 1989
Hurricane Andrew
Building Community Resiliency
Small Business in the Face of Crisis
The Evolution and Structure of Natural Hazard Policies
Vulnerability of community businesses to environmental disasters
Winners and losers
Damages Done
| Unique citing works | 4 |
|---|---|
| Citations per year | 1,33 |
| Citation span | 2023 - 2026 (4) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 4 |