Spatial Explanation and Planning for Resilience of Community-Based Small Businesses to Environmental Shocks

University Of Florida, Gainesville FL

Investigators

Abstract

The project aims to study how community-based small businesses (CSB) adapt to environmental shocks and promote economic growth in a changing climate, with research being completed through a spatially based planning lens. By bringing together knowledge and theories from socio-ecological systems, community economic development, and human behaviors, the research has the potential to generate valuable insights and methods for supporting CSB climate adaptation at various levels. While playing a vital role in creating vibrant communities, improving quality of life, and fostering workforce diversity, CSB are highly vulnerable to environmental shocks. The research and engagement activities lay the scientific foundation for creating more diverse and equitable environments and enabling local communities to develop strategies and policies for building resilience. Additionally, the project provides rich learning opportunities for students, business owners, practitioners, and policymakers. Community-based small businesses (CSB) must maintain and grow their customer base over time. However, their risk to environmental shocks has been underestimated when their location, land use, and infrastructure support are not carefully considered or well coordinated. The project aims to gain a quantitative, systematic, and generalized understanding of how specific characteristics of CSB locations and other spatial factors in their communities contribute to customer demand patterns and overall resilience. The research team leverages new and large datasets to develop a theory-guided framework that incorporates artificial intelligence to assist in spatial planning. This framework is designed to anticipate short-term resilience and evaluate long-term adaptation measures for CSB. While the initial focus is on coastal communities in the US Southeast affected by flooding, developed methods could be broadly applied to other natural disaster types and in other regions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.