Evidence map›Paper›PMID 35036314›Full record

ArticleCase studies on transport policy2022

The operation of labour charter flights during the COVID-19 pandemic in China.

Chuntao Wu, Hongmeng Yan, Wenjing Xue, Maozhu Liao

Open access · greenAbstract read
In one paragraph

Article in Case studies on transport policy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.3field-weighted citation impact, top 11% of its field
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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 2 institutions in 1 country.

Chuntao WuSchool of Tourism, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China.
Hongmeng YanSchool of Tourism, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China.
Wenjing XueSchool of Tourism, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China.
Maozhu LiaoSchool of Tourism, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China.
Sichuan University · CNSichuan Tourism University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

China was the first market badly hit by the COVID-19 pandemic. This paper explores how Chinese airlines started and involved in labour charter operations, and tanalyse the evolutionary patterns of the charter route network. Flying charter flights for migrant workers is a unique phenomenon in China, especially during the Wuhan lockdown period. The main results are three: (1) private airlines were more active in charter operations during the earlier period, (2) labour charter operation is a newly appeared aviation-government-industry cooperative business model, and (3) there was a spread, change and shift of both charter flows and charter passengers during the four-week period of the study. This case study not only produces useful insights about the important role of charter flights in China during the Covid-19 pandemic period, but also contributes to the theory and practice related to aviation resilience. Also, it contributes to the discussion about aviation policies in China, taking labour charter operation as a window time to predicate future airline dynamics in a more deregulated environment. The results can help airlines, and airports adjust routes, distribute capacity, and adjust layouts for Spring Festival labour transport in normal or post-pandemic times.

Indexed as

Charter flightsChinese airlinesCrisis responseThe COVID-19 pandemic

Identifiers

PMID35036314
PMCPMC8743854
OpenAlexW4206106080

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.