ABSTRACT
This chapter highlights key distinctions between the operations research and urban travel demand areas, given those early applications and methodological developments associated with discrete choice models occurred predominately in the urban travel demand area. In contrast to urban travel demand applications, aviation applications are characterized by relatively large volumes of revealed preference data that are used to produce demand forecasts that are a critical part of an airline's day-to-day operations. Data used to support an airline's day-to-day operations typically contain limited socio-economic and socio-demographic information. Accurately representing competition among alternatives is important to both urban travel demand and aviation studies. These developments, which represent major milestones in the advancement of discrete choice theory, include the nested logit, generalized nested logit, and Network Generalized Extreme Value models. The US is unique in that it is one of the few countries that collect a 10 percent ticket sample of passengers boarding domestic flights.
