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{{Incubator}} [[Category:Incubator topics]]
{{Incubator}} [[Category:Incubator topics]][[Category:Destination Choice Models]]
=Multinomial logit=
=Multinomial logit=

Revision as of 19:30, 24 May 2017

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Multinomial logit

The most common implementation of destination choice is the multinomial logit (MNL) model. The following discussion assumes familiarity with the general formulation of MNL (provide a link). The destination choice problem is presented with reference to an individual decision-maker, however the model is equally applicable to aggregate, zone-based formulations, as discussed below.

Given a trip origin i, and decision-maker m, the utility of each destination j can be written as follows:


This function says that the utility of a destination depends on two

In a MNL model, destinations are characterized by their utility. Utility has two components: (i), a systematic or observed component, which depends on characteristics of the destination, the level of service between origin and destination, and/or the attributes of the traveler, and (ii) a random component, which represents unobserved characteristics of the destination. The mathematical formulation of the MNL model arises from the assumptions adopted to represent the random error term. Travelers are hypothesized to choose the destination that maximizes their utility. The utility of a destination is a function of multi-modal accessibilities and preferences, the attractiveness of the destination zone, person and household attributes, and other unknown, un-included attributes of the trip maker or the destination zone. The probability that trip m produced in zone i chooses destination zone j is given by the utility of zone j and the utility of all other possible destinations.

Gravity models as special case of MNL

Statistical theory=

=Equilibrium constraints / Shadow pricing

Accessibility variables, competing destinations, and agglomeration effects

Data driven models