Abstract: Systems and methods are provided applicable to all choice scenarios where alternative competition is a function of alternative proximity along some attribute dimension. Discrete choice models can be developed which assign probabilities that a given decision-maker will choose different alternatives. Ordered Generalized Extreme Value (OGEV) and Hybrid-OGEV models are utilized to assess the probability that a given alternative is chosen based on its attributes and the parameter estimates of these attributes (obtained during model estimation). The attribute parameter estimates yield the relative importance of each attribute to a decision-maker. The attribute importance can differ by decision-maker such that different decision-makers can have different parameter estimates for the same attribute.