{"id":{"repo_id":"unm","oai_identifier":"oai:digitalrepository.unm.edu:geog_etds-1016"},"canonical_url":"https://search.dev.ndltd.org/etd/unm/oai:digitalrepository.unm.edu:geog_etds-1016","repository":{"repo_id":"unm","name":"University of New Mexico","base_url":"https://digitalrepository.unm.edu/do/oai/"},"display":{"title":"The Effect of Airport Delays on the Evolution of the U.S. Air Travel Network","abstract":"An investigation is made into the question of how U.S. airlines respond to airport-based delays at domestic airports using data from the FAAs On-Time Performance database and aircraft inventories for major U.S. Airlines. Three delay mitigation techniques are studied: increasing aircraft size, rerouting transit passengers, and decreasing schedule peaking. Regression analysis is used to determine where significant relationships exist between study variables and the overall level of flight delay for all airlines at each airport they serve. T-Tests indicate schedule peaking is more likely to be increased at airports with higher levels of delay, but that no specific airline undertakes this strategically, and that airlines are not more likely to make changes at airports where they are more dominant. However no airlines were found to make any changes at airports where there are no competing airlines.'","abstract_html":"An investigation is made into the question of how U.S. airlines respond to airport-based delays at domestic airports using data from the FAAs On-Time Performance database and aircraft inventories for major U.S. Airlines. Three delay mitigation techniques are studied: increasing aircraft size, rerouting transit passengers, and decreasing schedule peaking. Regression analysis is used to determine where significant relationships exist between study variables and the overall level of flight delay for all airlines at each airport they serve. T-Tests indicate schedule peaking is more likely to be increased at airports with higher levels of delay, but that no specific airline undertakes this strategically, and that airlines are not more likely to make changes at airports where they are more dominant. However no airlines were found to make any changes at airports where there are no competing airlines.'","abstract_has_math":false,"creators":["Cox, Eric"],"institution":null,"degree_name":"Geography","degree_level":"Masters","degree_discipline":"Geography","degree_department":null,"school":null,"contributors":["Hadjilambrinos, Constantine","Benedict, Karl","Freundschuh, Scott"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-07-11T07:00:00Z","date_published":"2013-07-11T07:00:00Z","updated_at":"2026-07-24T05:27:31Z","subjects":["Air Travel","Network","Airport Delays"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalrepository.unm.edu/geog_etds/17"],"render_values":[{"text":"https://digitalrepository.unm.edu/geog_etds/17","href":"https://digitalrepository.unm.edu/geog_etds/17","code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/1928/23174","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hadjilambrinos, Constantine","Benedict, Karl","Freundschuh, Scott"]},{"key":"dc:creator","label":"Author","values":["Cox, Eric"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Geography"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters","Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Geography"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Air Travel","Network","Airport Delays"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/1928/23174","https://digitalrepository.unm.edu/geog_etds/17"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["An investigation is made into the question of how U.S. airlines respond to airport-based delays at domestic airports using data from the FAAs On-Time Performance database and aircraft inventories for major U.S. Airlines. Three delay mitigation techniques are studied: increasing aircraft size, rerouting transit passengers, and decreasing schedule peaking. Regression analysis is used to determine where significant relationships exist between study variables and the overall level of flight delay for all airlines at each airport they serve. T-Tests indicate schedule peaking is more likely to be increased at airports with higher levels of delay, but that no specific airline undertakes this strategically, and that airlines are not more likely to make changes at airports where they are more dominant. However no airlines were found to make any changes at airports where there are no competing airlines.'"]},{"key":"dc:title","label":"Title","values":["The Effect of Airport Delays on the Evolution of the U.S. Air Travel Network"]}]}],"canonical_facts":{"dc:contributor":["Hadjilambrinos, Constantine","Benedict, Karl","Freundschuh, Scott"],"dc:creator":["Cox, Eric"],"dc:description.abstract":["An investigation is made into the question of how U.S. airlines respond to airport-based delays at domestic airports using data from the FAAs On-Time Performance database and aircraft inventories for major U.S. Airlines. Three delay mitigation techniques are studied: increasing aircraft size, rerouting transit passengers, and decreasing schedule peaking. Regression analysis is used to determine where significant relationships exist between study variables and the overall level of flight delay for all airlines at each airport they serve. T-Tests indicate schedule peaking is more likely to be increased at airports with higher levels of delay, but that no specific airline undertakes this strategically, and that airlines are not more likely to make changes at airports where they are more dominant. However no airlines were found to make any changes at airports where there are no competing airlines.'"],"dc:identifier":["http://hdl.handle.net/1928/23174","https://digitalrepository.unm.edu/geog_etds/17"],"dc:language":["English"],"dc:subject":["Air Travel","Network","Airport Delays"],"dc:title":["The Effect of Airport Delays on the Evolution of the U.S. Air Travel Network"],"thesis:degree_discipline":["Geography"],"thesis:degree_level":["Masters","Thesis"],"thesis:degree_name":["Geography"]},"updated_at":"2026-07-24T05:27:31Z"}