Improving the quality of demand forecasts through cross nested logit: a stated choice case study of airport, airline and access mode choice

Airport choice models have been used extensively in recent years to determine the transport planning impacts of large metropolitan areas. However, these studies have typically focussed solely on airports within a given metropolitan area, at a time when passengers are increasingly willing to travel further to access airports. The present paper presents the findings of a study that uses broader, regional data from the East Coast of the United States collected through a stated choice based air travel survey. The study makes use of a Cross- Nested Logit (CNL) structure that allows for the joint representation of inter-alternative correlation along the three choice dimensions of airport, airline and access mode choice. The analysis shows not only significant gains in model fit when moving to this more advanced nesting structure, but the more appropriate cross-elasticity assumptions also lead to more intuitively correct substitution patterns in forecasting examples.