This past week the Annual Meeting of the Society for Risk Analysis took place in Charleston, SC. Dr. Francis and collaborators George Gray, John Carruthers, and Robert Lee presented a paper titled "Preferences related to urban sustainability under risk, uncertainty, and dynamics." The abstract is included here:
Numerous older cities in the US are experiencing a state of decline, due to shrinking populations, economic hardship, and many other factors. Large areas of these cities are comprised of contaminated and vacant land. We explore the decision context around land redevelopment approaches focused upon reducing risk, improving quality of life, and fostering sustainability. Characterizing the preferences and objectives of diverse stakeholders in a multi-attribute framework may improve decisions and planning. However, traditional decision analytic approaches tend to be ‘static’, and do not capture the temporal and spatial dynamics of this problem. We propose a framework that integrates stated and revealed preferences in a dynamic modeling environment designed to capture key attributes of urban sustainability identified by stakeholders. The utility of this model will be demonstrated through an observational experiment. Key attributes and preferences will be elicited from a population of stakeholders in a Web environment. After eliciting these preferences, the participants will then engage in a dynamic modeling exercise in which they are able to interactively explore land use decisions considering the complexities of urban dynamics; the numerous tradeoffs, risks, and uncertainties; the resource constraints; and so on. We call this model DMASE (for Dynamic/Multi-Attribute/Spatially-Explicit). Preferences over the key attributes will then be elicited again. We hypothesize that the key attributes and preferences will change appreciably based upon interaction with the DMASE model. Additionally, the model can be modified in an iterative fashion to capture the decision context and preferences of the participants in a more meaningful way. This work will lead to a decision support tool that will allow stakeholders and decision-makers in declining cities to make more informed decisions about changes in the complex urban environment.