From a modeling perspective, there are several key points of interest. First, the presence of less-than-daily frequencies
may influence the construct of the underlying choice set considered by customers. That is, if customers are aware of an airline’s
schedule, they would not pay to exclude a city that had no flights for their desired departure and return dates. We
investigate this question in detail in the results section. We model the choice of destination exclusion conditional on a particular
package selection using a multidimensional binary logit model that assumes that destination choice exclusion probabilities
(conditional on a particular package selection) are independent of other destinations in the choice set, i.e., each
destination is independently or ‘‘sequentially’’ examined by the customer who decides whether to chose that destination
or not. This model is presented in the next section.