Pivot-Linked Elicitation: A Unified Approach to Hierarchical Weight Elicitation and its Application to Best–Worst Methods

We study weight elicitation in Multiple Criteria Decision Analysis (MCDA) when decision criteria are organized hierarchically. We show that the conventional practice of eliciting weights separately at each level can lead to practical and conceptual limitations, including reliance on abstract upper-level judgments and the fragmentation of consistency across independent sub-models. To address these issues, we propose the PIvotLinked Elicitation (PILE) framework, which links groups through a small set of pivot criteria and integrates intra- and inter-group preference information into a single model. We instantiate PILE for best–worst methods, deriving nonlinear and linear PILE–Best-Worst Method (BWM) formulations, and illustrate the approach on two published use cases. The results demonstrate how PILE preserves the cognitive benefits of hierarchical structuring while enabling a more holistic and consistency-aware elicitation.