Analyzing Commute Mode Choice Using the LCNL Model in the Post-Covid-19 Era
Evidence from China
Bibliographic Data
| ID | 15469722 |
|---|---|
| Authors | Siliang Luan (0000-0002-0529-3821, Jilin University), Qingfang Yang (0000-0002-4603-1887, Jilin University), Zhongtai Jiang (0000-0003-4911-1935, Jilin University, corresponding author), Huxing Zhou (0000-0002-5979-3741, Jilin University), Fanyun Meng (0000-0003-4689-6095, Jilin University) |
| Year | 2022 |
| Volume | 19 |
| Issue | 9 |
| Pages | 5076-5076 |
| Publication date | 2022-04-21 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph19095076 |
| PMID | 35564471 |
| OpenAlex | W4224253078 |
| Language | EN |
| Citations received | 1 |
| References cited | 54 |
The purpose of this paper is to gain an insight into commuting and travel mode choices in the post-COVID-19 era. The surveys are divided into two waves in Qingdao, China: the first-wave questionnaires were collected under the background of a three-month zero growth of cases; the second wave was implemented after the new confirmed cases of COVID-19. The latent class nested logit (LCNL) model is applied to capture heterogeneous characteristics among the various classes. The results indicate that age, income, household composition, and the frequency of use of travel modes are latent factors that impact users' attitudes toward mass transit and the private car nests when undergoing the shock of the COVID-19 pandemic. Individuals' trepidation regarding health risks began to fade, but this is still a vital consideration in terms of mode choice and the purchase of vehicles. Moreover, economic reinvigoration, the increase in car ownership, and an increase in the desire to purchase a car may result in great challenges for urban traffic networks
2019-20 coronavirus outbreak · China · Coronavirus disease 2019 (COVID-19 · Geography · Mode (computer interface · Outbreak · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · Computer Science · Economic and Environmental Valuation · Medicine · Psychology · Transportation Planning and Optimization · Urban Transport and Accessibility · Internal Medicine · Virology
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| Unique citing works | 1 |
|---|---|
| Citations per year | 0,5 |
| Citation span | 2024 - 2024 (1) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 1 |