Factors impacting bus selection: Differences between the middle and later stages of COVID-19

Quansheng Yue · Zhongxiang Feng · Zhipeng Huang · Xiaobo Ruan

11 citations0/0 files storedMultimodal Transportation

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Transportation Planning and Optimization Urban Transport and Accessibility Transportation and Mobility Innovations

Abstract

As one of the most important modes of transportation, buses play an essential part in people's journeys. However, less has been known about whether and under what circumstances people will choose to travel by bus during the COVID-19 epidemic. Based on the theory of planned behaviour (TPB), the study examined how the impact of the different stages of COVID-19 (middle stage and later stage), the quality of public transport services and the fear of COVID-19 (FCV-19) are associated with individual choices. An online survey of 404 participants from Anhui Province, China was conducted. We collected data on demography information, together with related TPB constructs (behavioural intentions, self-reported bus use, attitudes, subjective norm, perceived behavioural control, fear of COVID-19 and bus passenger satisfaction). After verifying the scales and the basic TPB model, we established a structural equation model (SEM). Our analysis of the survey data yielded the following results: 1) In the middle stage of the COVID-19 epidemic, fear of COVID-19 was significantly related to the intention to take the bus, and passenger satisfaction was insignificantly related to travel by bus. 2) In the later stage of the COVID-19 epidemic, passenger satisfaction was significantly related to the decision to take the bus, and fear of COVID-19 was significantly related to the intention to travel by bus. These research results not only reveal the internal mechanism of passengers choosing to take the bus but also provide important information for future disaster emergency management. On this basis, some feasible suggestions are made to avoid the decrease of bus ridership and help the public transportation system recover from the crisis.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 11 citations exist upstream.

References

1981Evaluating Structural Equation Models with Unobservable Variables and Measurement Error 1999Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives 2014A new criterion for assessing discriminant validity in variance-based structural equation modeling 2018When to use and how to report the results of PLS-SEM 2011PLS-SEM: Indeed a Silver Bullet 2015A primer on partial least squares structural equation modeling (PLS-SEM)2009\nThe use of partial least squares path modeling in international marketing 2001Efficacy of the Theory of Planned Behaviour: A meta‐analytic review

Cited by

2025Enhancing public transit adoption through personalized incentives: a large-scale analysis leveraging adaptive stacking extreme gradient boosting in China 2024Joint Optimization of Speed and Holding Time Control for Bus Rapid Transit: A Multiobjective Approach 2024Flexible optimal bus‐schedule bridging for metro operation‐interruption

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.