Grey clustering of the variations in the back-to-front airplane boarding method considering COVID-19 flying restrictions

• Published in: Grey systems Vol. 12; no. 1; pp. 25 - 59
• Main Authors: Delcea, Camelia, Cotfas, Liviu-Adrian, Milne, R. John, Xie, Naiming, Mierzwiak, Rafał
• Format: Journal Article
• Language: English
• Published: Bingley Emerald Publishing Limited 03.01.2022; Emerald Group Publishing Limited
• Subjects: Air travel; Airline industry; Airline operations; Airport terminals; Airports; Alliances; Boarding; Business metrics; Clustering; Coronaviruses; COVID-19; COVID-19 diagnostic tests; Epidemics; Masks; Medical supplies; Methods; Pandemics; Passenger comfort; Passengers; Severe acute respiratory syndrome coronavirus 2; Social distancing; System theory; Travel; Viral diseases; COVID-19; Airplane boarding; Agent-based modelling; Social distancing; Grey clustering; Back-to-front; Grey analysis; One-door boarding
• ISSN: 2043-9377; 2043-9385
• DOI: 10.1108/GS-11-2020-0142

PurposeThe airline industry has been significantly hit by the occurrence of the new coronavirus SARS-CoV-2, facing one of its worst crises in history. In this context, the present paper analyses one of the well-known boarding methods used in practice by the airlines before and during the coronavirus outbreak, namely back-to-front and suggests which variations of this method to use when three passenger boarding groups are considered and a jet bridge connects the airport terminal with the airplane.Design/methodology/approachBased on the importance accorded by the airlines to operational performance, health risks, and passengers' comfort, the variations in three passenger groups back-to-front boarding are divided into three clusters using the grey clustering approach offered by the grey systems theory.FindingsHaving the clusters based on the selected metrics and considering the social distance among the passengers, airlines can better understand how the variations in back-to-front perform in the new conditions imposed by the novel coronavirus and choose the boarding approach that better fits its policy and goals.Originality/valueThe paper combines the advantages offered by grey clustering and agent-based modelling for offering to determine which are the best configurations that offer a reduced boarding time, while accounting for reduced passengers' health risk, measured through three indicators: aisle risk, seat risk and type-3 seat interferences and for an increased comfort for the passengers manifested through a continuous walking flow while boarding.