Relationship between Panic Buying and Per Capita Income during COVID-19

Yoshizaki, Hugo Tsugunobu Yoshida; Brito, Irineu de; Hino, Celso Mitsuo; Aguiar, Larrisa Limongi; Pinheiro, Maria Clara Rodrigues

doi:10.3390/su12239968

Cited by 34 publications

(18 citation statements)

References 51 publications

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“…Additionally, consumers with higher household income are also expected to engage more in panic buying behavior because of their larger purchasing power which allows them to spend more on each shopping trip compared to consumers with lower household income limited by their lower purchasing power. This expectation is aligned with Yoshizaki’s finding that panic buying is more prevalent among the more affluent people, albeit panic buying does not grow linearly with income but follows a concave function with a diminishing slope [ 132 ]. However, this is not the case in this survey.…”

Section: Resultssupporting

confidence: 77%

The Determinants of Panic Buying during COVID-19

Chua

Yuen

Wang

et al. 2021

IJERPH

124

106

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The COVID-19 pandemic has seen an unmatched level of panic buying globally, a type of herd behavior whereby consumers buy an uncommonly huge amount of products because of a perception of scarcity. Drawing on the health belief model, perceived scarcity, and anticipated regret theories, this paper formulated a theoretical model that linked the determinants of panic buying and analyzed their interrelationships. Subsequently, data were collated from 508 consumers through an online survey questionnaire in Singapore that was conducted during the early stage of the pandemic, before the onset of the circuit breaker in April 2020. Next, an analysis of the results was done through structural equation modeling. It showed that the effect of the health belief model dimensions (i.e., perceived susceptibility, perceived severity, outcome expectation, cues to action, and self-efficacy) on panic buying is partially mediated by the consumers’ perceived scarcity of products. Furthermore, the effect of perceived scarcity on panic buying is partially mediated by consumers’ anticipation of regret. This paper expands on the current theoretical understanding of panic buying behavior, giving insights into the possible measures and solutions that policymakers and relevant stakeholders can uptake to manage panic buying in future a pandemic or health crisis.

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Section: Resultssupporting

confidence: 77%

The Determinants of Panic Buying during COVID-19

Chua

Yuen

Wang

et al. 2021

IJERPH

124

106

View full text Add to dashboard Cite

show abstract

“…This trend was partially driven by the media, which often showed pictures of empty shelves and warned of food shortages [84]. It also affected people from all income classes, including lower-income populations [85].…”

Section: Content Analysismentioning

confidence: 99%

Causal Impacts of Epidemics and Pandemics on Food Supply Chains: A Systematic Review

et al. 2021

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The epidemics and pandemics can severely affect food supply chains, including producers, retailers, wholesalers, and customers. To minimize their impacts, it is fundamental to implement effective policies that ensure continuity in the provision, affordability, and distribution of basic food items. This research identifies the main impacts of pandemics and epidemics on food supply chains and policies that can minimize these impacts. Based on a systematic literature review (SLR), 173 documents are analysed to propose a taxonomy of impacts on four supply chain links: demand-side, supply-side, logistics and infrastructure, and management and operation. The taxonomy presents the main impacts and respective mitigation policies. In addition, the literature review leads to the development of a comprehensive causal loop diagram (CLD) with the identification of main variables and their relationship with food supply chains. Finally, a specific research agenda is proposed by identifying the main research gaps. These findings provide a structured method for evaluating policies that ensure the functioning of food supply chains, particularly in disruptions such as epidemics and pandemics.

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“…Direct impacts include people infected by COVID-19, as they have to expend time and resources for their recovery. Indirect impacts arise from the changes in the operations, with the economies contracting themselves as a consequence of the pandemic; therefore, consumption, production, and thus the livelihoods of people are affected [8,34]. Human suffering rises [12] because, in most economies, supply could not respond to rising demands regarding health care services (hospitalization and intensive care units), key health care goods (oxygen and automatic respirators), and social aid (because with lockdowns, unemployment causes hunger and raises the incidence of poverty).…”

Section: A Humanitarian Logistics Framework For Pandemic Assessmentmentioning

confidence: 99%

Using Spatial Patterns of COVID-19 to Build a Framework for Economic Reactivation

et al. 2021

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In this article, we propose an application of humanitarian logistics theory to build a supportive framework for economic reactivation and pandemic management based on province vulnerability against COVID-19. The main research question is which factors are related to COVID-19 mortality between Peruvian provinces? We conduct a spatial regression analysis to explore which factors determine the differences in COVID-19 cumulative mortality rates for 189 Peruvian provinces up to December 2020. The most vulnerable provinces are characterized by having low outcomes of long-run poverty and high population density. Low poverty means high economic activity, which leads to more deaths due to COVID-19. There is a lack of supply in the set of relief goods defined as Pandemic Response and Recovery Supportive Goods and Services (PRRSGS). These goods must be delivered in order to mitigate the risk associated with COVID-19. A supportive framework for economic reactivation can be built based on regression results and a delivery strategy can be discussed according to the spatial patterns that we found for mortality rates.

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Relationship between Panic Buying and Per Capita Income during COVID-19

Cited by 34 publications

References 51 publications

The Determinants of Panic Buying during COVID-19

The Determinants of Panic Buying during COVID-19

Causal Impacts of Epidemics and Pandemics on Food Supply Chains: A Systematic Review

Using Spatial Patterns of COVID-19 to Build a Framework for Economic Reactivation

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