Network science approach for identifying disruptive elements of an airline

Abdelghany, 2004, A model for projecting flight delays during irregular operation conditions, J. Air Transport. Manag., 10, 385, 10.1016/j.jairtraman.2004.06.008 AhmadBeygi, 2008, Analysis of the potential for delay propagation in passenger airline networks, J. Air Transport. Manag., 14, 221, 10.1016/j.jairtraman.2008.04.010 Alderighi, 2007, Assessment of new hub-and-spoke and point-to-point airline network configurations, Transport Rev., 27, 529, 10.1080/01441640701322552 Barnhart, 2014, Modeling passenger travel and delays in the national air transportation system, Oper. Res., 62, 580, 10.1287/opre.2014.1268 Baruah, 2019, Comparison of the airline networks of India with ANI based on network parameters, 74 Brandes, 2013, What is network science?, Netw. Sci., 1, 1, 10.1017/nws.2013.2 Brueckner, 2021, Airline mitigation of propagated delays via schedule buffers: theory and empirics, Transp. Res. E: Logistra, 150 (C) Brueckner, 2022, Airline delay propagation: a simple method for measuring its extent and determinants, Transport. Res. B, 162 (Aug.), 55, 10.1016/j.trb.2022.05.003 Clark, 2018, Resilience of the U.S. National airspace system airport network, IEEE Trans. Intell. Transport. Syst., 19, 3785, 10.1109/TITS.2017.2784391 Cong, 2016, Empirical analysis of airport network and critical airports, Chin. J. Aeronaut., 29, 512, 10.1016/j.cja.2016.01.010 Couto, 2015, Structural properties of the Brazilian air transportation network, An Acad. Bras Ciências, 87, 1653, 10.1590/0001-3765201520140155 Cumelles, 2021, Cascading failures in airport networks, J. Air Transport. Manag., 92 Du, 2018, Delay causality network in air transport systems, Transp. Res. E: Logistra, 118, 466, 10.1016/j.tre.2018.08.014 Du, 2017, Identifying vital edges in Chinese air route network via memetic algorithm, Chin. J. Aeronaut., 30, 330, 10.1016/j.cja.2016.12.001 Gershkoff, 2016, Shaping the future of airline disruption management (IROPS) Giannikas, 2022, A data-driven method to assess the causes and impact of delay propagation in air transportation systems, Transport. Res. C Emerg. Technol., 143 Gopalakrishnan, 2017, A comparative analysis of models for predicting delays in air traffic networks Gui, 2020, Flight delay prediction based on aviation big data and machine learning, IEEE Trans. Veh. Technol., 69, 140, 10.1109/TVT.2019.2954094 Hong, 2016, Structural properties of the Chinese air transportation multilayer network, Chaos, Solit. Fractals, 86, 28, 10.1016/j.chaos.2016.01.027 Hossain, 2017, A complex network approach towards modeling and analysis of the Australian Airport Network, J. Air Transport. Manag., 60, 1 Janić, 2005, Modeling the large scale disruptions of an airline network, J. Transport. Eng., 131, 249, 10.1061/(ASCE)0733-947X(2005)131:4(249) Jia, 2014, An exploratory analysis on the evolution of the US airport network, Phys. A: Stat. Mech. Appl., 413, 266, 10.1016/j.physa.2014.06.067 Jiang, 2017, The transition point of the Chinese multilayer air transportation networks, Int. J. Mod. Phys. B, 31, 10.1142/S0217979217501867 Jiang, 2017, Evolution trends of the network structure of Spring Airlines in China: a temporal and spatial analysis, J. Air Transport. Manag., 60, 18, 10.1016/j.jairtraman.2016.12.009 Jiang, 2019, Identifying critical nodes’ group in complex networks, Phys. A: Stat. Mech. Appl., 514, 121 Jin, 2019, Study on structural characteristics of China's passenger airline network based on network motifs analysis, Sustainability, 11, 2484, 10.3390/su11092484 Kivelä, 2014, Multilayer networks, J. Complex Netw., 2, 203, 10.1093/comnet/cnu016 Li, 2018, Evidential identification of influential nodes in network of networks, Chaos, Solit. Fractals, 117, 283, 10.1016/j.chaos.2018.04.033 Liu, 2008, Estimation of arrival flight delay and delay propagation in a busy hub-airport, Vol. 4, 500 Lordan, 2017, Analyzing the multilevel structure of the European airport network, Chin. J. Aeronaut., 30, 554, 10.1016/j.cja.2017.01.013 Lordan, 2019, Core and critical cities of global region airport networks, Phys. A: Stat. Mech. Appl., 513, 724, 10.1016/j.physa.2018.08.123 Lordan, 2014, Study of the topology and robustness of airline route networks from the complex network approach: a survey and research agenda, J. Transport Geogr., 37, 112, 10.1016/j.jtrangeo.2014.04.015 Lordan, 2015, Robustness of airline alliance route networks, Commun. Nonlinear Sci. Numer. Simul., 22, 587, 10.1016/j.cnsns.2014.07.019 Newman, 2018 Olariaga, 2018, Influence of the liberalization of the air transport industry on configuration of the traffic in the airport network, 43 Reggiani, 2010, Connectivity and concentration in airline networks: a complexity analysis of Lufthansa's network, Eur. J. Inf. Syst., 19, 449, 10.1057/ejis.2010.11 Sathanur, 2019, Identification of critical airports from the perspective of delay and disruption propagation in air travel networks, 19469105 Song, 2017, Analysis of the air transport network characteristics of major airports, Asian J. Shipp. Logist., 33, 117, 10.1016/j.ajsl.2017.09.002 Thiagarajan, 2017, A machine learning approach for prediction of on-time performance of flights, 1 Walker, 2017, Coda digest Wandelt, 2019, Evolution of domestic airport networks: a review and comparative analysis, Transp. Build., 7, 1 Wang, 2003, Flight connections and their impacts on delay propagation, vol. 1, pp. 5.B.4-5.1-9 Wang, 2017, The structure and dynamics of the multilayer air transport system, 1 Wang, 2019, Measuring the resilience of an airport network, Chin. J. Aeronaut., 32, 2694, 10.1016/j.cja.2019.08.023 Wehmuth, 2018, A multilayer and time-varying structural analysis of the Brazilian air transportation network, 57 Wong, 2012, A survival model for flight delay propagation, J. Air Transport. Manag., 23, 5, 10.1016/j.jairtraman.2012.01.016 Wu, 2019, An improved SVM model for flight delay prediction, 1 Xu, 2005, Estimation of delay propagation in the national aviation system using Bayesian networks Yang, 2019, Empirical structural analysis on Chinese airline network, 2757