A formal model for consensus and negotiation in environmental management.
Environmental management decisions typically lie at the interface of science and public policy. Consequently, these decisions involve a number of stakeholders with competing agendas and vested interests in the ultimate decision. In such cases, it is appropriate to adopt formal methods for consensus building to ensure transparent and repeatable decisions. In this paper, we use an environmental management case study to demonstrate the utility of a mathematical consensus convergence model in aggregating values (or weights) across groups. Consensus models are applicable when all parties agree to negotiate in order to resolve conflict. The advantage of this method is that it does not require that all members of the group reach agreement, often an impossible task in group decision making. Instead, it uses philosophical foundations in consensus building to aggregate group members' values in a way that guarantees convergence towards a single consensual value that summarizes the group position. We highlight current problems with ad hoc consensus and negotiation methods, provide justification for the adoption of formal consensus convergence models and compare the consensus convergence model with currently used methods for aggregating values across a group in a decision making context. The model provides a simple and transparent decision support tool for group decision making that is straightforward to implement.
Regan
Helen M
HM
Biology Department, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-4614, USA. hregan@sciences.sdsu.edu
Colyvan
Mark
M
Markovchick-Nicholls
Lisa
L
D003142:Communication; D032921:Consensus; D003247:Conservation of Natural Resources / Q000331:legislation & jurisprudence; D003661:Decision Support Techniques; D004781:Environmental Exposure / Q000517:prevention & control*; D004782:Environmental Health; D006801:Humans; D008954:Models, Biological; D017008:Negotiating; D018570:Risk Assessment; D012308:Risk Management / Q000379:methods*