Exploring the Spatially Heterogeneous Effects of the Built Environment on Bike-Sharing Usage during the COVID-19 Pandemic

Yang, Hongtai; Guo, Zishuo; Zhai, Gangyi; Yang, Linchuan; Huo, Jinghai

doi:10.1155/2022/7772401

Cited by 6 publications

(1 citation statement)

References 45 publications

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“…While survey data from a small sample can give operators an idea of how to develop, it does not provide direction for planning and managing spatial resources. Te built environment can respond to this need based on communityscale "5D" theory (5 types of built environment variables whose names start with D, including density, design, diversity, distance to the transit, and destination accessibility) [28,29]. Although the built environment factors are generally used to explain travel behavior [30,31], few scholars have discussed the impact of the built environment on takeout orders.…”

Section: Literature Reviewmentioning

confidence: 99%

Investigating the Nonlinear Relationship between Takeout Order Demand and Built Environment under Different Periods of COVID-19

Guo

Zhang

2023

Journal of Advanced Transportation

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The COVID-19 pandemic has hit the global restaurant business hard, especially dine-in. However, it has also provided opportunities for online dining, with takeout becoming a fulcrum for the economic resilience of the urban restaurant industry. Currently, research on the factors affecting takeout order demand under the pandemic has been inadequate. Therefore, this study uses multisource data from Nanjing to explore the changes in takeout order demand as the pandemic develops. And based on the Light gradient boosting machine (Light GBM) model, the nonlinear relationship between the built environment and order demand under different periods of pandemic is investigated, and the important factors affecting the demand are obtained. The results show that daily orders on average during COVID-19 decline by 25.6% than before COVID-19, while during the stabilization phase of the pandemic, they are 20.0% higher than before COVID-19. According to the relative importance ranking of factors in the model, land use diversity and road design influence takeout the most and the crucial influencing factors vary across pandemic periods. In the postpandemic era, special attention needs to be paid to the impact of the number of restaurants, colleges, offices, and main roads on takeout services. In addition, the thresholds of key built environment factors through partial dependency plots can enhance operators’ understanding of takeout services and provide suggestions for the spatial layout of takeout resources. While satisfying people’s dietary needs, the role of takeout in restoring the restaurant economy can be better utilized.

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Section: Literature Reviewmentioning

confidence: 99%

Investigating the Nonlinear Relationship between Takeout Order Demand and Built Environment under Different Periods of COVID-19

Guo

Zhang

2023

Journal of Advanced Transportation

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Impact Evaluation of COVID-19 on Transit Ridership: A Case Study of the Beijing Subway

Wang,

Guo,

Zou

et al. 2024

Urban Rail Transit

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A comprehensive understanding of the multifaceted ramifications of the coronavirus disease 2019 (COVID-19) on transit ridership is imperative for the optimization of judicious traffic management policies. The intricate influences of this pandemic exhibit a high degree of complexity, dynamically evolving across spatial and temporal dimensions. At present, a nuanced understanding remains elusive regarding whether disparate influencing factors govern inbound and outbound passenger flows. This study propels the discourse forward by introducing a methodological synthesis that integrates time series anomaly detection, impact inference, and spatiotemporal analysis. This amalgamation establishes an analytical framework instrumental in elucidating the spatiotemporal heterogeneity intrinsic to individual impact events, grounded in extensive time series data. The resulting framework facilitates a nuanced delineation, affording a more precise extraction of the COVID-19 impact on subway ridership. Empirical findings derived from the daily trip data of the Beijing subway in 2020 substantiate the existence of conspicuous spatiotemporal variability in the determinants influencing relative shifts in inbound and outbound ridership. Notably, stations situated in high-risk areas manifest a conspicuous absence of correlation with outbound trips, exhibiting a discernibly negative impact solely on inbound trips. Conversely, stations servicing residential and enterprise locales demonstrate resilience, evincing an absence of significant perturbation induced by the outbreak.

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Exploring year-to-year spatiotemporal changes in cycling patterns for bike-sharing system in the pre-, during and post-pandemic periods

Shi

Zhao

et al. 2023

Sustainable Cities and Society

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Exploring the Spatially Heterogeneous Effects of the Built Environment on Bike-Sharing Usage during the COVID-19 Pandemic

Cited by 6 publications

References 45 publications

Investigating the Nonlinear Relationship between Takeout Order Demand and Built Environment under Different Periods of COVID-19

Investigating the Nonlinear Relationship between Takeout Order Demand and Built Environment under Different Periods of COVID-19

Impact Evaluation of COVID-19 on Transit Ridership: A Case Study of the Beijing Subway

Exploring year-to-year spatiotemporal changes in cycling patterns for bike-sharing system in the pre-, during and post-pandemic periods

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