| Despite the recent remarkable growth of air freight shipments, much of the existing literature on the geography of air transportation has paid more attention to passenger travel than freight shipments. The purpose of this dissertation is to elevate our understanding of spatial hierarchies and nodal connectivity by determining which specific variables most influence and shape the geographic distribution of air freight by metropolitan area using stepwise regression analysis.;The empirical results suggested a regression model of five independent variables is the most simple, effective, and parsimonious solution; 71.1% of the variation in the dependent variable was explained by the independent variables. The traffic shadow effect was the most important predictor in predicting the natural log of air freight, where small metropolitan areas within the traffic shadow of larger metropolitan areas tended to generate lower levels of freight. The model also suggested that other key predictors included per capita personal income, the transportation-shipping-logistics employment market share, the number of medical diagnostic establishments, and average high technology wages. Thus, metropolitan markets with more affluent people, diverse and efficient ground support systems, freight forwarders and other transportation services, an intense agglomeration of hospitals and medical universities, a highly skilled hi-tech workforce engaged in providing computer systems design and manufacturing generate high volumes of air freight. |
