Timed intervention in COVID-19 and panic buying
Open accessAbstract
In view of 2020 outbreak of the pandemic COVID-19, the paper examines the relationship between government measures for combating the pandemic and their side effects. Panic buying is identified as one such side effect. Among various models and measures undertaken by government to manage the pandemic, timed-intervention policy is commonly practiced by most countries. This paper examines the timing effect between government measures and panic buying. Three studies were undertaken to understand the timing effect and identify a connection between timed measures and consumer behaviours. Semantic analysis, secondary data search, and big data analytics were deployed to address the research aim. Although claiming a causal relationship is cautioned, the findings reveal a connection between timing of government measures and panic buying. These findings are discussed with the support of real-life evidence. Implications for researchers and practitioners conclude this paper.
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In both the US and Australia, panic buying peaked in March 2020.
“In both countries panic buying peaked in March (Keane and Neal, 2020; Loxton et al., 2020; Prentice et al., 2020).”
From Why did all the toilet paper disappear? Distinguishing between panic buying and hoarding during COVID-19 (2021) · cites this paper as Prentice et al., 2020
The Discussion reports that panic buying in Australia peaked in late March and early April, so the claim is supported for Australia but narrows the reported peak to March. The paper's analysis concerns Australia; the cited passages do not establish when panic buying peaked in the US. (LLM, conf=0.88)
Experimental — accuracy not yet measuredThe announcement of public health measures such as social distancing and lockdowns seem to coincide with surges of panic buying.
“Because the announcement of public health measures such as social distancing and lockdowns seem to coincide with surges of panic buying (Keane and Neal, 2020; Prentice et al., 2020), public health bodies could work more closely with retailers and their relevant supply chains to increase product stocks during disasters.”
From Why did all the toilet paper disappear? Distinguishing between panic buying and hoarding during COVID-19 (2021) · cites this paper as Prentice et al., 2020
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Cites
Dynamic Graph CNN for Learning on Point Clouds
Wang, Y., Sun, Y., Liu, Z., Sarma, S. E., Bronstein, M. M., & Solomon, J. M. (2019) · ACM Transactions on Graphics · doi:10.1145/3326362 · Cited by 7,199 · see citing works
VADER: a parsimonious rule-based model for sentiment analysis of social media text
Hutto, C., & Gilbert, E. (2014) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v8i1.14550 · Cited by 6,087 · see citing works
Supply disruption management under consumer panic buying and social learning effects
Zheng, R., Shou, B., & Yang, J. (2020) · Omega · doi:10.1016/j.omega.2020.102238 · Cited by 192 · see citing works
Becken, S., Stantić, B., Chen, J., Alaei, A., & Connolly, R. M. (2017) · Journal of Environmental Management · doi:10.1016/j.jenvman.2017.07.007 · Cited by 110 · see citing works
Self-citationThe Seroprevalence of Pandemic Influenza H1N1 (2009) Virus in China
Xu, C., Bai, T., Iuliano, A. D., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0017919 · Cited by 48 · see citing works
Flagged first, then by citations
Research works printed but not linked: 3
- Australian Associated Press NSW coronavirus cases spike to 171 Retrieved from https://www.centralwesterndaily.com.au/story/6679581/nsw-coronavirus-cases-spike-to-171/?cs=12215 2020
- Bin M. Cheung P. Crisostomi E. Ferraro P. Myant C. Parisini T. Shorten R. On Fast Multi-Shot Epidemic Interventions for Post Lock-Down Mitigation: Implications for Simple Covid-19 Models 2020 arXiv preprint arXiv:2003.09930 · arXiv
- Ozili P.K. Arun T. Spillover of COVID-19: impact on the global economy. Available at: SSRN 3562570 2020
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Bentall, R. P., Lloyd, A., Bennett, K., McKay, R., Mason, L., Murphy, J., McBride, O., Hartman, T. K., Gibson-Miller, J., Levita, L., et al. (2021) · PLOS ONE · doi:10.1371/journal.pone.0246339 · Cited by 138 · see citing works
David, J., Visvalingam, S., & Norberg, M. M. (2021) · Psychiatry Research · doi:10.1016/j.psychres.2021.114062 · Cited by 54 · see citing works
- Authors
- Prentice, C., Chen, J., & Stantic, B.
- Affiliations
- Griffith University (AU)
- Corresponding author
- Prentice, Catherine
- Venue
- Journal of Retailing and Consumer Services
- Publisher
- Elsevier BV
- Published
- 2020-11
- Volume
- 57
- Pages
- 102203
- ISSN
- 0969-6989 (ISSN-L)
- PMC
- PMC7414736
- OpenAlex
- W3047782976
- Cited by
- 230
- References
- 5
- Citations by year
- 2026: 8 · 2025: 11 · 2024: 26 · 2023: 38 · 2022: 65 · 2021: 70 · 2020: 12
- FWCI
- 39.33
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Retailing and Consumer Services (publishedVersion)
- PubMed Central (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Griffith Research Online (submittedVersion, cc-by-nc-nd)
- Funders
- Inspector General Emergency Management Queensland, Australia
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › COVID-19 Pandemic Impacts
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Social Sciences › Sociology and Political Science › COVID-19 Prevention and Impact
- Keywords
- COVID-19 pandemic, panic buying, government pandemic measures, timing effects, consumer behavior, retail demand
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