Identifying and assessing corporate employment variables that influence community resilience: A novel model

Erik Xavier Wood; Jon C. Lam; Monica Sanders

doi:10.5055/jem.0808

Authors

Erik Xavier Wood, MA https://orcid.org/0000-0003-0531-6314
Jon C. Lam, MBA
Monica Sanders, JD, LLM https://orcid.org/0000-0001-8970-7405

DOI:

https://doi.org/10.5055/jem.0808

Keywords:

community resilience, corporate social responsibility, disasters, emergency management

Abstract

Quantifying the concept of disaster resilience on a local level is becoming more critical as vulnerable communities face more frequent and intense disasters due to climate change. In the United States (US), corporations are often evaluated using social justice or environmental sustainability matrices for financial investment consideration. However, there are few tools available to measure a corporation’s contribution to disaster resilience on a local level. This study includes a focused literature review of employment variables that contribute to community resilience and a national survey that asked US emergency managers to rank the variables they believe have the greatest influence on individual resilience. A novel corporate community resilience model that ranks corporate contributions to disaster resilience in the communities where they operate was developed and then tested against data from five employment sectors from the same area. This model can be used by stakeholders to better understand how corporations can most efficiently contribute to county- and subcounty-level disaster resilience. The metrics used in this study are universal and translative, and thus, the development of this resilience model has global disaster resilience implications.

Author Biographies

Erik Xavier Wood, MA

Professor and Researcher, Georgetown University, Washington, DC

Jon C. Lam, MBA

CEO, Newbury Capital Management, South Pasadena, California

Monica Sanders, JD, LLM

Adjunct Professor of Law, Georgetown University Law Center; Founder, Undivide Project, Washington, DC

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