Evidence map›Paper›PMID 35975184›Full record

ArticleJournal of air transport management2022

Recovery of Chinese low-cost carriers after the outbreak of COVID-19 pandemic.

Maozhu Liao, Chuntao Wu, Hongmeng Yan

Abstract read
In one paragraph

Article in Journal of air transport management, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Maozhu LiaoSauder School of Business, University of British Columbia, 2053 Main Mall, Vancouver, BC V6T 1Z2, Canada.
Chuntao WuSchool of Tourism, Sichuan University, No. 2 South Section, Yihuan Road, Chengdu, Sichuan, 610064, PR China.
Hongmeng YanSchool of Tourism, Sichuan University, No. 2 South Section, Yihuan Road, Chengdu, Sichuan, 610064, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study conducts a detailed analysis of the response of China's low-cost carriers (LCCs) to the threats posed by the pandemic from a route network perspective, aiming to explore the resilience of LCCs and Chinese airlines. Using geographic visualization and network analysis, we evaluate and compare the network connectivity of each Chinese LCC to see the change patterns, then elaborate on the network connection of Spring Airlines. The major results are: the LCC sector has not recovered, but some of them exceed the pre-pandemic levels in a less deregulated environment; different LCCs show different recovery patterns; Spring Airlines outperforms the other four LCCs in terms of network connectivity. The recovery process is supported by various external factors, such as the reduction of new confirmed COVID-19 local cases and international flights, the re-open of inter-provincial tour groups and tourism demand, the nationwide rebound activities promoted by the central government, and the supporting policies, especially new slot allocation processes issued by CAAC. The case study further indicates the effects of high-speed rail (HSR) and regional subsidy measures on the tactical actions of Springs in route planning. This paper serves as a referential case for the LCCs worldwide and has good application for the recovery of other LCCs in other countries. Moreover, the study conducted in this time window offers a chance to assess the development of Chinese airlines in a not fully deregulated aviation environment. It contributes to the debate on the theory of air network resilience.

Indexed as

ConnectivityCOVID-19Low-cost carriers (LCCs)ResilienceRoute network

Identifiers

PMID35975184
PMCPMC9372088

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.