Enhancing analytical methods of collective decision making

A common method of analysis when decisions have to be made by multiple stakeholders using multiple criteria is value tree analysis. Variations of this, such as the Public Value Forum (PVF), have been used especially in complex choices involving environmental issues [Keeney et al., MgtSci, 36, 9, 1990, pp. 1011-30]. Value tree analysis uses Multiattribute Utility Theory (MAUT) [Keeney and Raiffa, 1976] to evaluate a large number of alternatives. Decisionmakers decide the impact an alternative will have on each of many attributes and express how important each attribute is to them. The choice of attributes and the weights attached to them provide evidence of their values and preferences. The success of the PVF depends on the fact that individuals will understand each others' positions as they make explicit the tradeoffs among various attributes. However, participants in the PVF may have difficulty conveying in a precise way the information needed to calculate value scores and preference weights. Also, the language of MAUT lacks the flexibility to measure the degree to which a consensus of opinion can be reached. Fuzzy analysis [Zadeh, Info&Ctrl, 8, 1965, pp. 338-53] provides for uncertainty in scale responses which can be very common in a decisionmaker's choice of environment and flexibility of linguistic expression of preferences. The authors had a group of students decide whether to retain the present use of a cement facility or to adopt a modified use of the facility which involved the use of hazardous waste. Three stakeholder groups emerged from the student group--the community, the company, and the local officials. The attributes used by the participants were monetary impact, risk reduction, risk preference, health, and environmental quality. Using the fuzzy linguistic acceptability, the authors searched for the degree of acceptability each attribute had with each group and determined the lowest degree of acceptability around which a consensus could be obtained on an attribute, e.g., health. Also obtained for each attribute was a most desirable outcome, around which a consensus could be obtained. By examining the difference between the lowest consensus value and the most desirable outcome determined by a stakeholder group on a particular attribute, the authors identified where the greatest disagreement would arise. Thus, the outcome of the decision process is broadened from a single choice. Moreover, using joint analysis of the impact of each attribute and the most desirable outcome, one could assess that the most likely outcome of the decision process would be to reject the modified use of the facility. Strategic behavior could have been adopted by the students and there were limitations in the scope of study and the specifics of the scenario. However, the approach allows the inclusion of linguistic expressions difficult with the use of the traditional quantitative method of MAUT alone. One could expect to see that the complexity of a policy issue like this one is better handled, and its results better defended, with this inclusive, modified use of the PVF in which decisionmaking is enhanced by the use of fuzzy systems.