Evidence map›Paper›PMID 33362434›Full record

ArticleInternational journal of consumer studies2021

Customers response to online food delivery services during COVID-19 outbreak using binary logistic regression.

Sangeeta Mehrolia, Subburaj Alagarsamy, Vijay Mallikraj Solaikutty

Abstract read
In one paragraph

Article in International journal of consumer studies, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

  1. Article
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  4. Investigating changes in travel behavior over time in response to the COVID-19 pandemic.Transportation research. Part F, Traffic psychology and behaviour · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
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  13. A Thematic Review on Using Food Delivery Services during the Pandemic: Insights for the Post-COVID-19 Era.International journal of environmental research and public health · 2022
    Review
  14. Review
  15. Article
  16. Article
  17. 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

3 authors.

Sangeeta MehroliaSchool of Business and Management Christ University Bangalore India.ORCID https://orcid.org/0000-0003-3162-4361
Subburaj AlagarsamySchool of Business and Management Christ University Bangalore India.ORCID https://orcid.org/0000-0003-1200-6381
Vijay Mallikraj SolaikuttyThe American College Madurai India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to empirically measure the distinctive characteristics of customers who did and did not order food through Online Food Delivery services (OFDs) during the COVID-19 outbreak in India. Data are collected from 462 OFDs customers. Binary logistic regression is used to examine the respondents' characteristics, such as age, patronage frequency before the lockdown, affective and instrumental beliefs, product involvement and the perceived threat, to examine the significant differences between the two categories of OFDs customers. The binary logistic regression concludes that respondents exhibiting high-perceived threat, less product involvement, less perceived benefit on OFDs and less frequency of online food orders are less likely to order food through OFDs. This study provides specific guidelines to create crisis management strategies.

Indexed as

binary logistic regressionCOVID‐19health belief modelonline food delivery servicespurchase decision

Identifiers

PMID33362434
PMCPMC7753470

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.