Air transportation by metropolitan area: Different measures of airport activity yields.

详细信息   

• 作者：McCarthy ; Michael Brian.
• 学历：M.A.
• 年：2010
• 导师：Debbage, Keith G.,eadvisorWalcott, Susan M.ecommittee memberLiu, Zhi-Junecommittee member
• 毕业院校：The University of North Carolina
• Department：College of Arts & Sciences: Geography
• ISBN：9781109773828
• CBH：1476226
• Country：USA
• 语种：English
• FileSize：2443478
• Pages：100

文摘

Airports and the airline industry are key components of the national economy, in part, because air transportation shapes the spatial hierarchy of metropolitan economies. However, it is less well understood how various measures of airport activity might affect or correlate to economic, geographic, and social characteristics of a given metropolitan area. Consequently, this paper analyzes how conventional indicators of airport activity (i.e., enplanements per capita, flight departures per capita, and market originations per capita) might vary spatially and whether the same set of predictor variables are responsible for this variance. Using data from the Bureau of Transportation Statistics, Department of Labor, and the Census Bureau, the regression models for the airport activity variables indicate that the traffic shadow effect and per capita income are the only two predictor variables common in the three models. Conversely, airline-hub status was only significant in the enplanements per capita and the flight departures per capita models. Mega-regions (e.g., New York City, Washington D.C.) underperform on all three measures of airport activity despite their dominance in absolute terms, while tourist destinations (e.g., Las Vegas, Honolulu) tend to over-perform. The overall contribution of this paper is to highlight how different measures of metropolitan area airport activity might yield different spatial and predictive outcomes. Finding answers to this set of questions is crucial to better understand which airport activity measure best captures the geography of the United States air transportation market and which metropolitan area characteristics are key predictor variables in this determination.