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• W4382020373 abstract "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." @default.
• W4382020373 created "2023-06-27" @default.
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• W4382020373 date "2023-05-04" @default.
• W4382020373 modified "2023-10-05" @default.
• W4382020373 title "Investigating the Nonlinear Relationship between Takeout Order Demand and Built Environment under Different Periods of COVID-19" @default.
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• W4382020373 doi "https://doi.org/10.1155/2023/5248888" @default.
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