Relationship between Airport Efficiency and Surface Traffic

The focus of this paper is to identify and validate relationships between an airport efficiency metric and aggregate factors related to surface traffic movement. For validation, data from Dallas/Fort Worth (DFW) International airport is analyzed. Taxi time is used as the metric of efficiency with aggregate surface traffic count, taxi distance, and number of stops identified as large contributing factors to inefficiency. Simple linear and log-linear functional forms are used in regression to find the effect these factors have on taxi time, with variations of both models fitting the data with adjusted R values greater than 0.95. Predictive capability of the models was tested on an independent dataset. Linear models estimated 71% of the taxi times within one minute of the observed data while log-linear models estimated just fewer than 65% of the taxi times within one minute of the observed data. Estimates and prediction results indicate the need for testing alternate functional forms for the relationship between taxi time and the above mentioned factors of efficiency.