Scenarios for a post-COVID-19 world airline network

Author:

Ye Jiachen1,Ji Peng123ORCID,Barthelemy Marc45

Affiliation:

1. Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University 1 , Shanghai 200433, People’s Republic of China

2. Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education 2 , Shanghai 200433, People’s Republic of China

3. MOE Frontiers Center for Brain Science, Fudan University 3 , Shanghai 200433, People’s Republic of China

4. Institut de Physique Théorique, Université Paris Saclay, CEA, CNRS 4 , F-91191 Gif-sur-Yvette, France

5. Centre d’Analyse et de Mathématique Sociales, (CNRS/EHESS), 54 5 , Boulevard Raspail, 75006 Paris, France

Abstract

The airline industry was severely hit by the COVID-19 crisis with an average demand decrease of about 64 % (IATA, April 2020), which triggered already several bankruptcies of airline companies all over the world. While the robustness of the world airline network (WAN) was mostly studied as a homogeneous network, we introduce a new tool for analyzing the impact of a company failure: the “airline company network” where two airlines are connected if they share at least one route segment. Using this tool, we observe that the failure of companies well connected with others has the largest impact on the connectivity of the WAN. We then explore how the global demand reduction affects airlines differently and provide an analysis of different scenarios if it stays low and does not come back to its pre-crisis level. Using traffic data from the Official Aviation Guide and simple assumptions about customer’s airline choice strategies, we find that the local effective demand can be much lower than the average one, especially for companies that are not monopolistic and share their segments with larger companies. Even if the average demand comes back to 60 % of the total capacity, we find that between 46 % and 59 % of the companies could experience a reduction of more than 50 % of their traffic, depending on the type of competitive advantage that drives customer’s airline choice. These results highlight how the complex competitive structure of the WAN weakens its robustness when facing such a large crisis.

Funder

China 2030 Major projects

National Natural Science Foundation of China

Shanghai Municipal Science and Technology Major Project

Paris 2030

Publisher

AIP Publishing

Subject

Applied Mathematics,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics

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