Building a Values-Informed Mental Model for New Orleans Climate Risk Management

Douglas L. Bessette, Lauren A. Mayer, Bryan Cwik, Martin Vezér, Klaus Keller, Robert J. Lempert, Nancy Tuana

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Individuals use values to frame their beliefs and simplify their understanding when confronted with complex and uncertain situations. The high complexity and deep uncertainty involved in climate risk management (CRM) lead to individuals’ values likely being coupled to and contributing to their understanding of specific climate risk factors and management strategies. Most mental model approaches, however, which are commonly used to inform our understanding of people's beliefs, ignore values. In response, we developed a “Values-informed Mental Model” research approach, or ViMM, to elicit individuals’ values alongside their beliefs and determine which values people use to understand and assess specific climate risk factors and CRM strategies. Our results show that participants consistently used one of three values to frame their understanding of risk factors and CRM strategies in New Orleans: (1) fostering a healthy economy, wealth, and job creation, (2) protecting and promoting healthy ecosystems and biodiversity, and (3) preserving New Orleans’ unique culture, traditions, and historically significant neighborhoods. While the first value frame is common in analyses of CRM strategies, the latter two are often ignored, despite their mirroring commonly accepted pillars of sustainability. Other values like distributive justice and fairness were prioritized differently depending on the risk factor or strategy being discussed. These results suggest that the ViMM method could be a critical first step in CRM decision-support processes and may encourage adoption of CRM strategies more in line with stakeholders’ values.

Original languageEnglish (US)
Pages (from-to)1993-2004
Number of pages12
JournalRisk Analysis
Issue number10
StatePublished - Oct 2017

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Physiology (medical)

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