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Understanding the characteristics of air-traffic delays and disruptions is critical for developing ways to mitigate their significant economic and environmental impacts. Conventional delay-performance metrics reflect only the magnitude of incurred flight delays at airports; in this work, we show that it is also important to characterize the spatial distribution of delays across a network of airports. We analyze graph-supported signals, leveraging techniques from spectral theory and graph-signal processing to compute analytical and simulation-driven bounds for identifying outliers in spatial distribution. We then apply these methods to the case of airport-delay networks and demonstrate the applicability of our methods by analyzing U.S. airport delays from 2008 through 2017. We also perform an airline-specific analysis, deriving insights into the delay dynamics of individual airline subnetworks. Through our analysis, we highlight key differences in delay dynamics between different types of disruptions, ranging from nor’easters and hurricanes to airport outages. We also examine delay interactions between airline subnetworks and the system-wide network and compile an inventory of outlier days that could guide future aviation operations and research. In doing so, we demonstrate how our approach can provide operational insights in an air-transportation setting. Our analysis provides a complementary metric to conventional aviation-delay benchmarks and aids airlines, traffic-flow managers, and transportation-system planners in quantifying off-nominal system performance.
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Do Airports Boost Economic Development by Attracting Talent? An Empirical Investigation at the Subcounty Level
ObjectiveThe objectives of this study were to examine (1) the linkage from airports to regional talent distribution and (2) the effect of talent on regional economic development. MethodsUsing the data collected in Wisconsin at the municipal level, a subcounty level, in a region of the North Central United States from 1970 to 2010 and the American Community Survey 2006–2010 five‐year estimates, and random effects models and structural equation models, we employ descriptive and inferential statistics to examine the linkage from airports to talent to regional economic development. ResultsWe find that the farther a location is away from the airport, the lower its talent share tends to be, while greater passenger flow at the nearest airport increases a location's talent share. Given the quantity of passenger flow, a longer distance from the airport also reduces a location's talent share. The results furthermore suggest that economic development is impacted positively by passenger flow and talent share and negatively by distance to an airport. ConclusionOur results underscore the intermediate role of talent between airports and regional economic development; building the linkage from airports to talent within the context of regional economic development provides important insights for local policy making aimed at attracting talented migrants.
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- Award ID(s):
- 1541136
- PAR ID:
- 10034487
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Social Science Quarterly
- Volume:
- 99
- Issue:
- 1
- ISSN:
- 0038-4941
- Page Range / eLocation ID:
- p. 313-329
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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