Consumer responses towards essential purchases during COVID-19 pan-India lockdown.

Gopal R Patil, Rutuja Dhore, B K Bhavathrathan, Digvijay S Pawar, Prasanta Sahu, Asim Mulani

Open access · greenAbstract read

In one paragraph

Article in Research in transportation business & management, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it

0cells of the map it votes in

2citing papers in PubMed

5.6field-weighted citation impact, top 4% of its field

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

2 citing papers in PubMed, 21 citations in OpenAlex.

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Article
COVID-19 effects on urban driving, walking, and transit usage trends: Evidence from Indian metropolitan cities.Cities (London, England) · 2022
Article

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 at 4 institutions in 1 country.

Gopal R PatilDepartment of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India.

Rutuja DhoreDepartment of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India.

B K BhavathrathanDepartment of Civil Engineering, Indian Institute of Technology Palakkad, Kozhippara P. O, Palakkad 678557, Kerala, India.

Digvijay S PawarDepartment of Civil Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy District 502285, Telangana, India.

Prasanta SahuDepartment of Civil Engineering, Birla Institute of Technology and Science Pilani, Hyderabad 500078, Telangana, India.

Asim MulaniDepartment of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India.

Indian Institute of Technology Bombay · INBirla Institute of Technology and Science - Hyderabad Campus · INIndian Institute of Technology Hyderabad · INIndian Institute of Technology Palakkad · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Humanity experienced one of the worst crises in recent history due to the COVID-19 pandemic. The spread of the disease and the lockdown announced by the government of India created an emergency, disrupting the supply of essential commodities and creating panic and anxiety among the people. This paper aims at capturing the behavior of consumers purchasing essential commodities before and during the lockdown using an online questionnaire. Responses from 730 households covering 20 states in India were used. The data analysis revealed that consumers made a lesser number of trips during lockdown but purchased excess commodities considering the future uncertainties. The local family grocery stores, called

Indexed as

Consumer responseCOVID-19Essential commoditiesFactor analysisIndia

Identifiers

PMID38013949

DOI10.1016/j.rtbm.2021.100768

PMCPMC9173572

OpenAlexW4200031718

What OpenQuestion holds

Textmetadata

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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.