This paper outlines the application of non-additive measures and Choquet integral in the construction of a composite indicator to assess the performance of international climate think tanks and evaluate their influence in shaping climate policies and raising awareness among the general public. The composite index consists of 15 carefully selected indicators according to the feedback provided by Experts within the field and structured into three main pillars: Activities, Publications and Dissemination. In order to compare Think Tanks of different size and hence to measure their efficiency, the standardized ranking is also computed dividing the Think Tank outcome in each criterion by the number of its researchers. The application of fuzzy measures and Choquet integral, allowing taking into account potential interactions existing among criteria, increases substantially the model capability both in eliciting effectively Experts’ preferences and in aggregating indicators. Moreover, we present a novel technique for the aggregation of Experts’ preferences where Decision Makers’ weights have been set proportionally to their consistency in evaluating the specific questionnaire.

This paper outlines the application of non-additive measures and Choquet integral in the construction of a composite indicator to assess the performance of international climate think tanks and evaluate their influence in shaping climate policies and raising awareness among the general public. The composite index consists of 15 carefully selected indicators according to the feedback provided by Experts within the field and structured into three main pillars: Activities, Publications and Dissemination. In order to compare Think Tanks of different size and hence to measure their efficiency, the standardized ranking is also computed dividing the Think Tank outcome in each criterion by the number of its researchers. The application of fuzzy measures and Choquet integral, allowing taking into account potential interactions existing among criteria, increases substantially the model capability both in eliciting effectively Experts’ preferences and in aggregating indicators. Moreover, we present a novel technique for the aggregation of Experts’ preferences where Decision Makers’ weights have been set proportionally to their consistency in evaluating the specific questionnaire.