NSF-JST: Advanced Data and Methods to Improve Hazard Resilience for Underrepresented Groups: Minority- and Women-Owned Small and Mid-Sized Businesses

North Dakota State University Fargo, Fargo ND

Investigators

Abstract

This project supports a binational effort (US-Japan) to advance small- and medium-sized enterprise (SME) resilience, both conceptually and empirically, focusing mainly on minority- and women-owned enterprises. These businesses face challenging and complex recovery in the aftermath of disasters, exacerbated by supply chain disruptions and limitations on access to capital. This project aims for theoretical advancement in dynamic economic resilience and methodological innovation for observational data gathering and analysis. It deepens our understanding of the determinants of SME resilience and their propagation throughout a recovery path. The results facilitate identification of best practices and provide government agencies with tools to mitigate disproportionate consequences of natural disasters borne by underrepresented groups. To this end, the project targets several interrelated research questions and explores if: 1) accelerating the pace of resilience investments is more effective at reducing overall losses than simply reducing the duration of recovery; 2) resilience and recovery differ between women- and minority-owned SMEs and SMEs more broadly; 3) women- and minority-owned SMEs face unique social, cultural and public-sector challenges in resilience and recovery; and 4) characteristics of disasters (e.g., property damage, production input disruptions, critical infrastructure disruptions) affect an SME’s ability to implement dynamic resilience tactics. It also examines the effectiveness and equity of those tactics in various contexts (e.g., labor shortage, infrastructure disruptions, supply-chain disruptions), among others. The project extends microeconomic production theory to dynamic economic resilience and connects these theoretical advances to multi-area data collection efforts. Novel data analysis techniques are applied, such as econometric and sequential decision-making models. The application to SMEs owned and operated by underrepresented groups is expected to improve equity, social justice, and capacity-building in the disbursement of disaster assistance. 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.