Evidence map›Paper›PMID 35474715›Full record

ArticleTransportation research. Part D, Transport and environment2022

Investigating factors influencing takeout shopping demand under COVID-19: Generalized additive mixed models.

Fan Zhang, Yanjie Ji, Huitao Lv, Xinwei Ma, Chenchen Kuai, Wenhao Li

Abstract read
In one paragraph

Article in Transportation research. Part D, Transport and environment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Fan ZhangSchool of Transportation, Southeast University, Dongnandaxue Road 2, Nanjing, Jiangsu, China.
Yanjie JiSchool of Transportation, Southeast University, Dongnandaxue Road 2, Nanjing, Jiangsu, China.
Huitao LvSchool of Transportation, Southeast University, Dongnandaxue Road 2, Nanjing, Jiangsu, China.
Xinwei MaSchool of Civil and Transportation Engineering, Hebei University of Technology, Tianjin, China.
Chenchen KuaiSchool of Transportation, Southeast University, Dongnandaxue Road 2, Nanjing, Jiangsu, China.
Wenhao LiSchool of Transportation, Southeast University, Dongnandaxue Road 2, Nanjing, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic severely hampered the freedom of shopping travel while increasing individuals' interest in takeout. Although many studies have examined takeout shopping, the available literature provides insufficient evidence on the factors influencing takeout shopping demand under the COVID-19. In this study, generalized additive mixed models were developed based on sampling data of takeout orders in Nanjing before, during, and post the pandemic to measure the associations between takeout shopping demand and neighborhood characteristics at the business circle scale. The results show that population density, house prices, road density, and catering all have a significant impact on takeout shopping demand, while the roles of land use (residential and company indexes) before and post the pandemic are opposite. Besides, the factors influencing the recovery of the demand before and after the pandemic were analyzed. These findings provide important insights into the development of the takeout industry in the post-pandemic era.

Indexed as

Built environmentBusiness circleCOVID-19Generalized additive mixed modelTakeout shopping demand

Identifiers

PMID35474715
PMCPMC9023357

What OpenQuestion holds

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Registered trials

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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.