WEICOM: A Similarity-Based Method for Weight Compromise

This paper introduces WEIghts COMpromise (WEICOM), a novel aggregation method designed to derive a consensus weight vector in Multi-Criteria Decision Analysis (MCDA) involving multiple expert inputs. WEICOM aims to maximize the average similarity, measured by the Weights Similarity Coefficient 2 (WSC2), between the aggregated vector and a set of initial weight vectors, ensuring a balanced representation of all expert preferences. The method is applied to a real-world case study, assessing energy-related sustainability indicators in agri-food systems. The study evaluates the energy performance of countries based on six key criteria, including CO 2 emissions, on-farm energy use, and waste disposal. In addition, a simulation study is conducted to assess the robustness of WEICOM under varying numbers of criteria and experts, comparing its performance with tradition aggregation methods such as mean, median, and maximin. Results from both empirical and simulation-based analyses demonstra that WEICOM consistently outperforms conventional aggregation techniques, offering a more stable and transparent solution for integrating expert judgments in complex decision-making contexts. This approach provides valuable insights for applications in sustainability assessments, participatory decision-making, and environmental policy evaluations.