The article explores how different models can better predict seasonal recreation demand by considering error correlation and demand substitution. By comparing nested logit and mixed logit models, researchers found that mixed logit models can offer more flexibility in capturing correlation patterns across sites and choice occasions. This flexibility can lead to a wider range of price elasticities being allowed in the models.