Applying voting rules to panel-based decision making in LCA

Background, aim, and scope  Cross-category weighting is one possible way to facilitate internal decision making when dealing with ambiguous impact assessment results, with simple additive weighting being a commonly used method. Yet, the question as to whether the methods applied today can, in fact, identify the most “environmentally friendly” alternative from a group perspective remains unanswered. The aim of this paper is to propose a new method for group decision making that ensures the effective identification of the most preferable alternative. Materials and methods  Common approaches to deduce a single set of weighting factors for application in a group decision situation (e.g., arithmetic mean, consensus) are discussed based on simple mathematics, empirical data, and thought experiments. After proposing an extended definition for “effectiveness” in group decision making, the paper recommends the use of social choice theory whose main focus is to identify the most preferable alternative based on individuals’ rankings of alternatives. The procedure is further supplemented by a Monte Carlo analysis to facilitate the assessment of the result’s robustness. Results  The general feasibility of the method is demonstrated. It generates a complete ranking of alternatives, which does not contain cardinal single scores. In terms of effectiveness, the mathematical structure of the procedure ensures the eligibility for compromise of the group decision proposal. The sensitivity analysis supports the decision makers in understanding the robustness of the proposed group ranking. Discussion  The method is based upon an extended definition of effectiveness which acknowledges the eligibility for compromise as the core requirement in group decision contexts. It is shown that multi-attribute decision-making (MADM) methods in use in life cycle assessment (LCA) today do not necessarily meet this requirement because of their mathematical structure. Further research should focus on empirical proof that the generated group results are indeed more eligible for compromise than results generated by current methods that utilize an averaged group weighting set. This is closely related to the question considering under which mathematical constraints it is even possible to generate an essentially different result. Conclusions  The paper describes a new multi-attribute group decision support system (MGDSS) for the identification of the most preferable alternative(s) for use in panel-based LCA studies. The main novelty is that it refrains from deducing a single set of weighting factors which is supposed to represent the panel as a whole. Instead, it applies voting rules that stem from social choice theory. Because of its mathematical structure, the procedure is deemed superior to common approaches in terms of its effectiveness. Recommendations and perspectives  The described method may be recommended for use in internal, panel-based LCA studies. In addition, the basic approach of the method—the combination of MADM methods with social choice theory—can be recommended for use in all those situations where multi-attribute decisions are to be made in a group context.