ArticleTransportation research record2023
Will We Fly Again? Modeling Air Travel Demand in light of COVID-19 through a London Case Study.
Article in Transportation research record, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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.
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Who cites it
8 citing papers in PubMed.
- Explaining US travel behavior with perceived threat of pandemic, consumer sentiment, and economic policy uncertainty.Transport policy · 2023Article
- Systematic review of passenger demand forecasting in aviation industry.Multimedia tools and applications · 2023Article
- Impact of perceptions and attitudes on air travel choices in the post-COVID-19 era: A cross-national analysis of stated preference data.Travel behaviour & society · 2023Article
- COVID-19 pandemic and air transportation: Summary of Recent Research, Policy Consideration and Future Research Directions.Transportation research interdisciplinary perspectives · 2022Article
- Air travel choice, online meeting and passenger heterogeneity - An international study on travellers' preference during a pandemic.Transportation research. Part A, Policy and practice · 2022Article
- Applications of discrete choice experiments in COVID-19 research: Disparity in survey qualities between health and transport fields.Journal of choice modelling · 2022Article
- ANN-Based traffic volume prediction models in response to COVID-19 imposed measures.Sustainable cities and society · 2022Article
- Exploring the relationship between the COVID-19 pandemic and changes in travel behaviour: A qualitative study.Transportation research interdisciplinary perspectives · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The COVID-19 pandemic and associated travel restrictions have created an unprecedented challenge for the air transport industry, which before the pandemic was facing almost the exact opposite set of problems. Instead of the growing demand and need for capacity expansion warring against environmental concerns, the sector is now facing a slump in demand and the continuing uncertainty about the impacts of the pandemic on people's willingness to fly. To shed light on consumer attitudes toward air travel during and post the pandemic, this study presents an analysis that draws on recently collected survey data (April-July 2020), including both revealed and stated preference components, of 388 respondents who traveled from one of the six London, U.K., airports in 2019. Several travel scenarios considering the circumstances and attitudes related to COVID-19 are explored. The data is analyzed using a hybrid choice model to integrate latent constructs related to attitudinal characteristics. The analysis confirms the impact of consumers' health concerns on their willingness to travel, as a function of travel characteristics, that is, cost and number of transfers. It also provides insights into preference heterogeneity as a function of sociodemographic characteristics. However, no significant effects are observed concerning perceptions of safety arising from wearing a mask, or concerns over the necessity to quarantine. Results also suggest that some respondents may perceive virtual substitutes for business travel, for example video calls and similar software, as only a temporary measure, and seek to return to traveling as soon as it is possible to do so safely.
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Registered trials
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.