Natural Hazards

, Volume 84, Issue 2, pp 1219–1239 | Cite as

Developing a theoretical framework for integrated vulnerability of businesses to sea level rise

  • Jie Song
  • Zhong-Ren Peng
  • Liyuan Zhao
  • Chih-Hung Hsu
Original Paper


Sea level rise (SLR), as a likely outcome of climate change, threatens coastal communities through intensified storm surge, strong wind, flooding, and other extreme weather events. While social vulnerability to SLR is receiving overwhelming attention from research communities, studies on the business impacts of SLR are much less developed. In this study, an innovative framework of integrated business vulnerability is developed for environmental hazards (e.g., SLR) and is validated by a case study of Bay County, Florida. First, the model establishes a composite business vulnerability index (BVI) by incorporating business characteristics, infrastructure factors, and other indicators based on existing literature results. Second, it identifies impacted business indicators and how they will change with the projected SLR. To account for climate change uncertainty, floodplains are generated under three SLR levels (0, 0.2, and 0.9 m). Finally, this study uses a GIS-based methodology to combine physical and business vulnerabilities to investigate overall susceptibility and how this changes with SLR. Two important findings are identified. First, business vulnerability to flooding will be escalated substantially by SLR. Considerable amount of areas, businesses, and road networks would be exposed to highest flood risk zones due to SLR. Second, highest flood risk zones do not necessarily intersect with those areas of high BVI. The results can help local governments better allocate financial and manpower resources and assist hazard mitigation teams, urban planners, and city managers in steering business development away from high-risk regions due to SLR.


Business vulnerability index Sea level rise Coastal flooding Hurricane 



The authors thank the following colleagues—Dr. Jennifer L. Irish, Virginia Polytechnic Institute and State University; and Dr. James M. Kaihatu, Dr. Cecilia Giusti, and Dr. Francisco Olivera, Texas A&M University—for their help and invaluable suggestions on this study. We also thank the assistance of Mohammed M Gomma on collecting business data. We are grateful for the insightful comments offered by Xinyu Fu, Chao Liu, and Yujun Deng. In addition, we are highly appreciated for the comments from two anonymous reviewers who offered perceptive suggestions. The authors thank the US Census Bureau, the Florida Geographic Data Library, the Bay County Online, and the Bureau of Economic and Business Research for offering access to data. This paper was undertaken with support from the Florida Sea Grant, Grant No. R/GOM-RP-2, “A Parameterized Climate Change Projection Model for Hurricane Flooding, Wave Action, Economic Damages, and Population Dynamics.”


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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Jie Song
    • 1
  • Zhong-Ren Peng
    • 1
  • Liyuan Zhao
    • 2
  • Chih-Hung Hsu
    • 3
  1. 1.Department of Urban and Regional PlanningUniversity of FloridaGainesvilleUSA
  2. 2.School of Architecture and Urban PlanningHuaZhong University of Science and TechnologyWuhanPeople’s Republic of China
  3. 3.Zachry Department of Civil EngineeringTexas A&M UniversityCollege StationUSA

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