Panic buying or preparedness? The effect of information, anxiety and resilience on stockpiling by Muslim consumers during the COVID-19 pandemic

Claire Eloise Sherman (College of Business, Zayed University, Abu Dhabi, United Arab Emirates)
Damien Arthur (College of Business, Zayed University, Abu Dhabi, United Arab Emirates)
Justin Thomas (College of Natural and Health Sciences, Zayed University, Abu Dhabi, United Arab Emirates)

Journal of Islamic Marketing

ISSN: 1759-0833

Article publication date: 26 February 2021

Issue publication date: 13 May 2021

1587

Abstract

Purpose

The purpose of this study is to examine the causes of consumer stockpiling by Muslim consumers during the coronavirus (COVID-19) pandemic. Specifically, this paper examines exposure to COVID-19 information and its relationship with panic buying directly, indirectly through anxiety and as moderated by resilience.

Design/methodology/approach

In the early stages of the COVID-19 pandemic, this study surveys 1,006 Muslims from a sample of 1,392 UAE citizens and residents about their exposure to COVID-19 information, anxiety, resilience and panic buying.

Findings

Greater exposure to COVID-19 information had a direct effect on panic buying yet a much weaker indirect effect through increased anxiety. This mediating effect is only significant at moderate to high levels of resilience, suggesting panic buying is a particular coping response of resilient individuals who experience anxiety after greater exposure to COVID-19 information. Anxiety was found to increase panic buying above that directly related to COVID-19 information exposure.

Social implications

Findings provide some guidance for policymakers where a nuanced approach to building and directing resilience and in directing information flows are needed to curtail panic buying within their Muslim populations.

Originality/value

While the phenomenon of consumer stockpiling is referred to as panic buying, the findings suggest that anxiety plays a smaller role in the process than preparedness prompted by crisis-related information exposure. Furthermore, this is the first study to date to specifically examine COVID-19 related panic buying among a Muslim population.

Keywords

Citation

Sherman, C.E., Arthur, D. and Thomas, J. (2021), "Panic buying or preparedness? The effect of information, anxiety and resilience on stockpiling by Muslim consumers during the COVID-19 pandemic", Journal of Islamic Marketing, Vol. 12 No. 3, pp. 479-497. https://doi.org/10.1108/JIMA-09-2020-0309

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited


1. Introduction

The coronavirus (COVID-19) pandemic is having a significant impact on health and psychological well-being. On January 4th, 2021, 12 months since the World Health Organization (2021) reported on the first cluster of cases, over 1.8 million deaths and 83 million infections had been reported globally. Alongside this rising mortality and morbidity, the early stages of the pandemic were also associated with an increase in so-called “panic buying”.

While the term “panic buying” has been frequently used in the news media to explain pandemic-related stock-outs, it is less frequently used in academic research (Yuen et al., 2020). This is most likely due to doubts surrounding whether increased consumption during a disaster is actually driven by panic. In their review of citizen disaster response, Helsloot and Ruitenberg (2004) argue that most individuals respond to disasters in a rather rational way. Along this line of reasoning, Kulemeka (2010) argues that disaster shopping is not so much driven by panic associated with an imminent threat, but by being organized and preparing for the perceived threat and potential stock-outs through the stockpiling of essentials. In support of this, a recent study of panic buying during the COVID-19 pandemic found conscientiousness to be related to toilet paper stockpiling (Garbe et al., 2020). However, the threat of disaster generally leads to increased anxiety (Yuen et al., 2020) and one coping response may be to make purchases that are perceived as safeguarding oneself and family. Specifically, through the purchase of utilitarian goods, individuals may be reducing anxiety by increasing their sense of control (Chen et al., 2017). The term panic buying becomes a potential misnomer/oversimplification if we acknowledge that both anxiety and reasoned preparedness are candidate explanations for consumer stockpiling during a pandemic. In this study, for convenience, we retain the term “panic buying,” restricting its meaning to the increased purchasing of essential goods due to a widespread threat.

Panic buying was not often seen during previous infectious disease outbreaks such as the SARS, MERS and Ebola virus epidemics (Sim et al., 2020). A possible explanation for the surge in panic buying during the COVID-19 pandemic is the highly contagious nature of the virus and the global increase in digital connectivity and social media consumption (Depoux et al., 2020). In this study, we examine exposure to COVID-19 information and its relationship with panic buying directly, indirectly through anxiety and as moderated by resilience. Furthermore, while one research study has investigated the impact of COVID-19 on generalized anxiety in a majority Muslim sample (89.4%) (Islam et al., 2020), no study to date has specifically examined COVID-19 related panic buying by Muslims. This study fills this gap, by examining how the aforementioned factors are operationalized among Muslim citizens and residents of the United Arab Emirates (UAE).

We first begin by detailing the context of COVID-19 and, in particular, its development and impact within the UAE during the early stages of the pandemic. This is followed by an examination of panic buying from the perspective of the Muslim consumer. Next, the development of three hypotheses, underpinned by the theory of planned behavior and the conservation of resources theory, result in a moderated mediation model that explains panic buying. A test of this model then provides an indication of the strength of both direct and indirect paths and the moderating role of resilience to provide some clarity on whether UAE Muslims are driven to panic buy due to increased anxiety or reasoned preparedness and the role that resilience plays. By understanding the nuance in what drives panic buying, it is hoped that attempts to control excessive panic buying can be better informed and, in particular, in relation to Muslim communities. Theoretically, we also hope to test the relevance of anxiety-based versus more rational theories of behavior and to illuminate the potentially detrimental role of resilience in the case of panic buying.

2. Panic buying during the early stages of the COVID-19 pandemic

To contain the spread of COVID-19, the strategies recommended by the World Health Organization and the majority of governments around the world (including the UAE) are social distancing and hand and respiratory hygiene. As the pandemic took hold, messages of the importance of engaging in good hygiene behaviors saturated media around the world and increased the demand for sanitizers, soaps, masks and gloves (Banerjee, 2020). The first reports of panic buying came from Asia in early February and were related to the consumer stockpiling of masks (Jankowicz, 2020). This was of particular concern for health authorities as there were fears it would lead to insufficient supply for health-care professionals to safely perform their duties. Hence, in the early days of the pandemic, many countries actively encouraged their citizens not to purchase masks to ensure ample supply for those most at risk (e.g. UAE and USA) (Khaleej Times, 2020; Cramer and Sheikh, 2020).

By early March, incidents of panic buying of other hygiene products such as hand sanitizer and toilet paper had been reported in Australia, Hong Kong, Italy, UK, USA, Singapore and others (Jankowicz, 2020). By mid-March supermarket sales in many countries around the world were substantially higher than the previous year, with the greatest increase in staples (e.g. canned goods, pasta and rice) and non-food household supplies (e.g. soap and toilet paper) (IRI, 2020; O’Connell et al., 2020). While the increased consumption of masks, gloves and hand sanitizer appeared rational given they helped perform the recommended preventative behaviors, at face value the mass purchasing of staples and non-food household supplies appeared to be driven by panic. While COVID-19 related anxiety undoubtedly influenced such purchasing behavior, it too had some rational underpinnings. The need to stay at home and rumors of stockouts increased perceptions of limited time scarcity of household supplies. In addition, stockouts and images of empty supermarket shelves and videos of patrons fighting over supplies in both traditional and social media increased perceptions of limited quantity scarcity (Islam et al., 2021). With little risk of wastage (most stockpiled essentials do not or take a long time to spoil), herd behavior kicked-in creating a self-fulfilling cycle of panic buying, stockouts, publicity and social media sharing, leading to more panic buying, etc (Naeem, 2021).

Coupled with the distribution challenges that movement restrictions created, panic buying increasingly disrupted supply chains and stockout situations were exacerbated. As this prevented individuals in vulnerable groups from accessing essential items (Yuen et al., 2020), retailers and governments urged the public to be considerate of others by refraining from stockpiling. In the United Arab Emirates, for example, a country that imports 80-90% of its food supplies (Fischbach, 2018), supermarket chains reassured consumers there was no need to panic buy as they had enough stock (Sasseendran and Chaudhary, 2020) and the Attorney-General asked the public to stop sharing panic buying videos as it was creating unnecessary panic and could be considered a cyber-crime (Sebugwaawo, 2020). Despite such pleas for constraint, in the early days of the pandemic, panic buying substantially increased household spending on essential items. For example, there was a 32.5% increase in grocery spending in March 2020, compared to March 2019 across the US (Trading Economics, 2020).

3. Panic buying and the Muslim consumer

While the entire world is grappling with the same universal threat of a deadly and contagious virus there are still contextual differences that change the way that individuals, communities and societies might respond to this threat. The different beliefs and practices unique to various communities may dictate the extent to which they are protected or exposed to both the virus itself and the secondary social, economic and environmental impacts. For Muslims, one difference is in applying teachings from the Quran and Ahadith to the challenges of the COVID-19 pandemic. Panic buying or stockpiling might be judged differently depending on the nature of the buying process, whether there is sufficient supply and to whom the duty of buying the goods is perceived to benefit.

Panic buying during the COVID-19 pandemic has entailed both hoarding and competing in the amassing of worldly goods, both of which are prohibited under Islamic teachings. In one of the Quranic verses, Allah SWT says “Al haaku mut takathur” (Al-Quran Verse 102) which may condemn the practice of panic buying as diverting. Panic buying may also be seen as an injustice to others who then find the shelves empty and so there is a duty to others that may be neglected. This is exemplified in another verse:

Give the relatives their (due) right, as well as the needy and the traveler, but do not squander wastefully. Indeed the wasteful are brothers of satans and Satan is ungrateful to his Lord (Quran 17:26-27).

While an argument against panic buying, there is a hint within this verse that may drive a Muslim to undertake panic buying, where it mentions giving relatives their due right and any visitors or guests. For instance, if the intention is to provide for a family or to be sure there is enough in the cupboards to receive guests generously then this verse might convince a Muslim that it is necessary to stockpile. Similarly, in a verse speaking about the beautiful qualities of His beloved servants, God says, “And those who, when they spend, are neither wasteful nor stingy, but choose a middle course between that.” (Quran 25:67). In this way, a Muslim that is simply storing extra food and not wasting excess food, yet is still able to provide for guests when they arrive, will feel they are on the right path. Finally, while many Muslims might turn closer to God during times of crisis such as the COVID-19 pandemic, they are also specifically taught preparedness in the Hadith; “Trust in Allah, but tie your camel” (Sunan al-Tirmidhī 2517) which specifically encourages Muslims to prepare. As can be seen, the application of these teachings may depend on Muslims’ risk perceptions and intentions surrounding panic buying which may dictate their behavior during the COVID-19 pandemic.

4. Development of hypotheses

Research has shown that both the type and the amount of information can influence the perceived risk of any event, situation or behavior. While news and health information can help to provide a more accurate description of a situation and its risks (Fischhoff et al., 2017), in the case of a pandemic, information is likely to heighten perceived risk (Taha et al., 2014). For instance, messages focusing on the need to stay at home and avoid public places and news of supermarket shortages and supply chain disruptions all portray risks. As exposure to such messages increases perceived risk, exposed individuals are more likely to take defensive action such as stockpiling essential goods to avoid potential stock-outs or in anticipation of consuming more at home and avoiding trips to the supermarket. The theory of planned behavior (Ajzen, 1991) can explain such actions. When exposed to COVID-19 information, individuals consider the impact on the supply of household resources and develop intentions to purchase more in preparedness. In addition, individuals further consider their ability to perform the action of purchasing. Given heightened perceptions of limited time and limited quantity scarcity (Islam et al., 2021), it is likely individuals would form intentions to purchase quickly otherwise they may lose control of the situation and their ability to perform the desired action. Two recently published studies investigating COVID-19 consequences have used the theory of planned behavior to frame their investigations of intentions to adopt epidemic prevention strategies (Ahmad et al., 2020) and grocery shopping behaviors (Li et al., 2020), providing evidence that the public has generally engaged in planned coping responses.

During the COVID-19 pandemic the number of media articles mentioning “stockpiling” peaked in early March (Loxton et al., 2020) and “panic buying” was the focus of at least 214 online media reports by the 22nd of May 2020 (Arafat et al., 2020b). In addition to such specific content, the amount of general COVID-19 information consumed would also increase perceptions of risk and drive coping responses. News consumption during the early stages of the pandemic increased dramatically. For example, in early March article views from major US news publishers increased by 60%. Furthermore, while coronavirus articles represented only about 1% of all the articles published during this period, they represented more than 13% of views (Guaglione, 2020). No other story saturated media in 2020 like the COVID-19 pandemic. It is likely that such excessive information exposure increased intentions to prepare which manifest in stockpiling as a form of protection motivation and problem-focused coping response:

H1.

Exposure to COVID-19 information will positively influence panic buying behavior.

Moreover, enhancing the likelihood of panic buying behavior, increased information consumption during the COVID-19 pandemic and the subsequent perceived threats within this information are likely to increase anxiety (Garfin et al., 2020). Anxiety is an emotion based on the appraisal of a threat that involves cognitive responses, such as worry and tension, and is often characterized by physiological symptoms, such as increased heart rate and jitteriness (Spielberger, 1972, p. 246). This negative state of being can induce both adaptive and maladaptive behaviors as a means to cope with or remove this tension or worry. When this negative state is heightened there may be a greater impetus to use coping behaviors. By its nature, information related to COVID-19 is overwhelmingly negative such as information on the prevalence and risk of death, economic downturn, loss of jobs, social isolation and scarcity of food and other essentials. Thus, the more an individual is exposed to these negative cues, the more anxiety, worry and distress they experience, as was found with increased exposure to media stories relating to the 2014 Ebola outbreak (Thompson et al., 2017) and an early COVID-19 study linking increased media exposure (hours consumed per day) and generalized anxiety (Yao, 2020).

While not all panic purchases are health-focused, the act of purchasing can improve mental health by reducing pandemic-related anxiety. In this way, panic buying may be used as mood-repair or a form of gaining control in the context of heightened anxiety and uncertainty, with a similar effect found during other disasters such as hurricanes (Kemp et al., 2014). Thus, the more an individual is exposed to information about the pandemic the more they will experience heightened anxiety due to the increased perceived threat. The mediating role of anxiety in affecting panic buying can be explained by the conservation of resources theory which suggests that an actual loss or threat of resource loss, will induce stress and motivate attempts by the affected individual to conserve or regain these resources (Hobfoll, 1989). Necessities such as food and sanitary items are an object form of resource and regular access to them could be seen as a loss. Furthermore, contracting COVID-19 poses a loss in health or even life potentially and so could be considered a loss in one’s condition or state. While there are several factors that have been found to offset this actual or threat of loss (such as social support, a prior reserve of resources and even optimism), one of the most effective ways to reduce the stress is to regain the resources or preemptively gain more resources in anticipation of the loss (Hobfoll and Schumm, 2011). In this way, exposure to more COVID-19 information is likely to fuel panic buying, as it is one of several pertinent coping responses able to alleviate the anxiety produced by the threat. Nevertheless, it is feasible that not all panic buying results from this information-induced anxiety but is the result of planned behavior preparing for the imminent threat. Therefore, it is expected that the relationship between information exposure and panic buying will be partially, not fully, mediated by anxiety:

H2.

Anxiety will partially mediate the relationship between COVID-19 information exposure and panic buying behavior.

As the discussion above suggests, there are several factors that may intervene in directing the coping response taken by an individual when faced with the stress of losing resources. These factors such as dispositional optimism, flexibility, prior experience in regaining resources and social support, are all factors that promote resilience (Chen and Bonanno, 2020). Resilience is a dispositional style or form of interaction with an environmental stressor that allows someone to better face adversity by adapting more positively (Fletcher and Sarker, 2013). Defined as an event in someone’s life that normally involves adjustment difficulties, it is clear that for a huge number of people around the world, COVID-19 has been a source of adversity. From smaller adversities such as wearing a mask to significant adversities such as losing one’s job or even loved ones, there have been many opportunities for individuals to test their resilience. Importantly, being resilient does not mean one would not necessarily feel anxiety, it means you are able to adapt quickly, take action to resolve a loss of control or even see the initial adversity in a more positive light. Resilience can have very positive effects in spite of negative events. Indeed, a recent study found resilience moderates the indirect effect of COVID-19-related stress on depressive symptoms (Havnen et al., 2020). Importantly, it is not that the individual does not feel stress but that being more resilient directs the individual away from downstream negative consequences such as depression in this case.

Unlike depressive symptoms, the action of spending may not necessarily be perceived as a maladaptive response to the stress caused by the perceived risk of stock shortages or supermarket visits, at least not at the individual level. Indeed, a series of studies on the link between stress and consumer spending suggest that after experiencing stress consumers may undertake spending on necessities specifically to gain greater control over a newly uncontrollable environment (Durante and Laran, 2016), a potential manifestation of resilience. Interestingly, this is different from spending on non-necessities which increased for people who believed they could not restore control and maybe more akin to a form of mood repair for less resilient individuals.

These findings might easily be applied to the case of panic buying, where being exposed to more COVID-19 information would still increase anxiety levels in those who are more resilient. However, as resilient people are more optimistic in their ability to cope with anxiety, resilience should moderate the degree to which anxiety motivates them to engage in coping behaviors that regain their sense of control such as spending more on necessities. Hence, upon feeling anxiety, individuals high in resilience might be more likely to engage in significant stockpiling, as stockpiling necessities is perceived as a relevant, adaptive response taken to reduce the anxiety specific to COVID-19 threats:

H3.

Resilience will moderate the indirect effect of COVID-19 information exposure on panic buying by increasing the effect of anxiety on panic buying behavior.

5. Methodology

The context for this study was the UAE during the early stages of the COVID-19 pandemic. The UAE recorded its first case of COVID-19 on January 29th, 2020, however, community transmission remained well contained until mid-March (NCEMA, 2020). As cases began to rise, reports of panic buying began to circulate on social media. On March 15, the Abu Dhabi Crown Prince reassured the nation that the country could infinitely supply everyone with all required food and medicine (Duncan and Dutton, 2020) and government announcements denouncing rumors of product unavailability followed (Sasseendran and Chaudhary, 2020). Arafat et al. (2020a) argue that such statements limit panic buying as they reduce the perceived fear of scarcity. On March 23, the government announced a nationwide night-time curfew and a daytime stay at home order with exceptions for essential purposes that would begin on March 26. Such government announcements of internal movement restrictions during the COVID-19 pandemic were found to be a strong predictor of consumer panic in the short term (7–10 days) in a 52-country study (Keane and Neal, 2021). For example, consumer spending in New Zealand peaked on March 23, the day their lockdown was announced and three days prior to the lockdown being implemented (Hall et al., 2020). Based on our observation of news and social media, we believe the lockdown announcement and other announcements in the same week relating to the suspension of passenger flights and the closure of malls and non-essential retailers, coincided with a peak in consumer stockpiling in the UAE and that it slowly diminished as the country gradually reopened throughout April, May and June. Google Trends (2020) provides some indirect evidence of this as the search term “panic buying” peaked in the UAE on March 23 and dissipated throughout April-June. This timing is also relatively well aligned to the experience of other countries that were on a similar pandemic trajectory. For example, Prentice et al. (2020) found Twitter posts on panic buying originating from Queensland, Australia, peaked in late March to early April.

Ideally, data collection would have begun on March 23 or earlier, however, as questionnaire development and ethical approval took time, the survey went live on April 8 and ran through to May 5. In total, 1,392 UAE citizens and residents completed the survey during this period. Participants were recruited via UAE media and the email networks of the National Program for Happiness and Well-being and received no financial reward for their involvement. As indicated in Table 1, across the entire sample 1,006 (72.3%) of the respondents were Muslim, while Christians made up the majority (15.3%) of the remaining 386 participants. In total, 82.8% of the overall sample and 84.7% of the Muslim sample were female. While not representative of the broader UAE population, it was seen as an advantage as UAE women are more commonly responsible for household shopping, particularly in patriarchal Emirati families (De Bel Air et al., 2018) and Lins and Aquino (2020) found differences in the rate of COVID-19 related panic buying between men and women. Ages ranged from 18 to 73, but were youthfully skewed, with 40.6% of the overall sample and 54.0% of the Muslim sample between 18 and 24 years of age. While not representative of the nation, the UAE does have a relatively youthful population with 34% under 25 years of age (Oxford Business Group, 2016). UAE nationals made up 61.6% of the overall sample and 78.6% of the Muslim sample. As the UAE is comprised mainly of expatriate workers (De Bel Air, 2015), Emiratis were overrepresented in the sample. That said, the ethnic profile of the overall sample was diverse, comprising 66 nationalities.

To measure COVID-19 information exposure participants were asked to rate how much information about COVID-19 they had obtained on a scale ranging from (1) “none” to (4) “a lot” from each of the following sources: newspapers, television, social media, government agencies and family or friends. Responses from the five categories were summed to create an overall COVID-19 information exposure score ranging from 5 to 20.

The 7-item Generalized Anxiety Disorder scale (GAD-7) was chosen to measure anxiety as it has been used in other investigations examining COVID-19 information and anxiety (Huang and Zhao, 2020; Islam et al., 2020; Yao, 2020). The GAD-7 is highly correlated with state anxiety (Doi et al., 2018) and provides an excellent continuous anxiety measure with good validity and reliability (Spitzer et al., 2006). The GAD-7 asks respondents, “Over the last two weeks, how often have you been bothered by the following problems?” All items such as “feeling nervous, anxious or on edge,” are scored on a four-point scale and then summed to create an anxiety score ranging from 0–21. The scale demonstrated a high degree of internal consistency (α = 0.935).

The six-item brief resilience scale (BRS) was used to measure the trait of resilience (Smith et al., 2008). The Likert scale consists of items such as, “I tend to bounce back quickly after hard times” measured on five points. After reversing negatively worded items the scale is summed to create a resilience score ranging from 6 to 30. The scale demonstrated an acceptable level of internal consistency (α = 0.703). The validity of both the GAD-7 and BRS were also examined via a confirmatory factor analysis. While there were some method effects with the three reverse coded items in the BRS scale, when accounted for, the model demonstrated excellent fit on all measures (CFA: χ2 = 355.10, df = 61, p =0.000, TLI = 0.962, CFI = 0.971, IFI = 0.971, RMSEA = 0.059), aside from the chi-square p-value being significant. However, with such a large sample size the chi-square p-value is not a good determinant of model fit because it is much more likely to be overestimated (Iacobucci, 2010).

To assess panic buying, respondents were asked to “indicate the degree to which you have increased your purchasing of the following items in recent weeks because of the COVID-19 pandemic.” The phrase “in recent weeks” was included as peak panic buying in the UAE occurred around two weeks prior to the launch of the survey. Respondents indicated their level of panic buying on a five-point scale across nine product categories: tinned food, water, hand sanitizer, toilet roll, dried food, bread, pharmaceuticals, batteries and fuel. While Garbe et al.’s (2020) study focused solely on toilet paper consumption, it was determined that a score based on multiple product categories would be a more valid measure of panic buying. After conducting exploratory factor analysis, batteries and fuel were removed from the scale as purchases did not substantially increase during the lockdown. At face value, this made sense, as the curfew and stay-at-home order discouraged driving and unlike with a natural disaster (e.g. a hurricane), power outages were not anticipated. The remaining seven items could all be purchased from supermarkets and/or pharmacies which was important as they remained open during the lockdown and had most likely prepared to the best of their ability for a surge in consumer stockpiling (Kostev and Lauterbach, 2020). The scale items demonstrated a high degree of internal consistency (α = 0.860), so were summed to create a panic buying score ranging from 7 to 35.

Moreover, the focal variables of the model also included the covariate of education level, a single-item ordinal measure asking for the participant’s highest qualification across five categories. Education level was controlled for as it is related to information processing and has been found to be negatively correlated with anxiety during the COVID-19 pandemic (Lei et al., 2020). Similarly, as Garbe et al. (2020) found that people who are more threatened by COVID-19 stockpile more toilet paper, we included pre-existing health conditions as a second covariate in the model. This was measured with a dichotomous item where respondents simply indicated whether they did (1) or did not (0) have a pre-existing health condition. The final covariate was place belonging and was controlled for as the feeling of kinship and trust in others could help reduce anxiety and panic related to COVID-19 (Arafat, 2020a). Place belonging was measured on a four-point scale for the single-item, “How strongly do you feel you belong to your immediate neighborhood?” as it has been used in previous studies (Piscopo et al., 2017).

Participants chose to complete the survey in either English (72.1%) or Arabic (27.9%). All measures were translated and back-translated by two bilingual psychologists with the exception of GAD-7, which was already available in both languages.

6. Results and findings

Before examining the three hypotheses with our Muslim sample, initial data was examined for any differences between the retained Muslim sample and other participants, in terms of media exposure types and the level of panic buying for various product categories (Table 2). A breakdown of the products stockpiled revealed that our Muslim sample increased their purchasing of five of the seven product categories by significantly more than other participants. The exceptions were toilet paper and pharmaceuticals where no significant difference was found. Furthermore, an analysis of the information source of COVID-19 information found our Muslim sample gained significantly less information from traditional media such as newspapers and TV and significantly more from social media and family and friends, as well as the UAE Government. While this provides an idea of the sample characteristics, any comparison between faiths should be made with caution as, four faiths each represented more than 10% of the non-Muslim sample and so this sub-sample had considerable diversity within itself.

For the main analysis, all hypotheses were tested within a second stage moderated mediation model using PROCESS macro (Hayes, 2018; model 14; see Figure 1 and Table 3). The model predicts a small but significant amount of the variance in both anxiety (R2 = 0.051, F(3, 1006) = 13.89, p =0.000) and panic buying (R2 = 0.14, F(7, 1006) = 22.15, p =0.000). While this leaves a large amount of variance unexplained this might be expected as there are many other factors that may influence anxiety and to a lesser extent panic buying. In anticipation, the covariates of education (βA = −0.19, p =0.00; βPB = −0.09, p =0.02), pre-existing health condition (βA = 0.26, p =0.00; βPB = 0.12, p =0.19) and belonging (βA = −0.10, p =0.00; βPB = −0.11, p =0.00) were included to control for confounds particularly relevant to information processing and COVID-19-related anxiety. All the hypothesized direct and indirect estimates were significant at p =0.05 and their bootstrap confidence intervals did not include zero (Table 4).

As hypothesized, greater COVID-19 information exposure was associated with increased panic buying (H1: β = 0.26, p =0.000, 95% CI*: 0.195 to 0.324), while moderate, this was the largest effect observed within the model. COVID-19 information exposure also increased anxiety as expected (β = 0.08, p =0.021, 95% CI*: 0.013 to 0.146), although it was a small effect and anxiety had a direct positive association with panic buying (β = 0.17, p =0.000, 95% CI*: 0.109 to 0.238). Confirmation of both these paths provided the possibility of a significant mediation effect and inspection of the conditional indirect effects revealed the significant positive effect of information exposure on panic buying through an increase in anxiety (H2: conditional indirect effects = 0.008, 0.014, 0.019; 95% CI*s: 0.000 to 0.020, 0.002 to 0.028, 0.003 to 0.040), confirming our second hypothesis. This significant result suggests that, while small, there is a mediation effect whereby the direct effect of COVID-19 information exposure on panic buying decreases after accounting for the mediation effect of anxiety (ΔR2 = 0.005, p =0.027).

Resilience played a moderating role in affecting panic buying demonstrated by both a significant interaction effect with anxiety (H3: IntAxR = 0.07, p =0.027, CI*: 0.008 to 0.129) and a significant index of moderated mediation (H36: Index = 0.0054; CI*: 0.0001 to 0.0141). To understand this moderating effect the relationship was graphed based on interpolations at the mean and ± 1 SD (Figure 2) and further by inspecting the Johnson-Neyman significance region, which indicates at what levels of the moderator the mediating effect is significant (Figure 3). As can be seen, at low levels of resilience the mediating effect of anxiety is not significant, yet becomes significant at moderate to high levels of resilience, with an increasing effect size. This suggests that as information-induced anxiety increases so too does panic buying for more resilient individuals.

7. Discussion

The amount of pandemic-related information individuals are exposed to is clearly associated with greater panic buying. This is largely a direct effect that is not due to COVID-19 information inducing greater anxiety. Hence, while it is referred to as panic buying, anxiety plays a smaller role in consumer stockpiling than planned rational preparedness prompted by increased COVID-19 information exposure. This suggests that the prevailing theory that guides panic buying is planned behavior (Ajzen, 1991), where the increased exposure to scarcity messages that emphasize limited quantity and limited time availability (Islam et al., 2021) brings forward consumer actions on their regular intentions to purchase the staples and non-food household supplies. It is this bringing forward of the purchasing actions of many individuals that create the intensified cycle of panic buying and it is clear that increased COVID-19 information is an instigator of what is quite a reasoned phenomenon at the individual level.

While it might be tempting to disregard the small and relatively low-powered mediation effect of anxiety on the relationship between information exposure on panic buying, this effect may still be important when considering the dynamics of the panic buying phenomenon. For instance, it is possible that initial panic buying is first carried out by those who experience greater anxiety as they take in information about the unfolding pandemic. As increased information about lockdowns and disruption to daily lives is received some individuals sense a loss in their regular condition and, in the case of necessities, a loss of access and so their anxiety increases due to a perceived lack of control which again heightens motivations to purchase, to purchase more and to purchase quickly (Hobfoll, 1989). While it may be small, this initial bout of stockpiling has the potential to create a snowball effect whereby the shelves are more bare than usual. In turn, news of this visible shortage filters to those in the larger, less anxious population who are then prompted by this information to be pragmatic “panic buyers.” In this way, the small effect may induce enough of a tipping point to create the larger effect of widespread stockpiling, which has been found to influence social conventions once the minority reaches 25–27% (Centola et al., 2018). This information spread effect may also explain why, while lower in anxiety, Muslims who feel a greater sense of belonging to their community, are more likely to panic buy outside of the influence of anxiety; they are better connected and receiving more information via social media, as well as family and friends.

Despite this small information-anxiety relationship, results suggest that anxiety alone may still fuel panic buying outside of any association with increased information exposure. In this way, panic buying may still be considered a form of mood repair or regaining of control for anxiety induced in other ways, such as for those with pre-existing health conditions. There is a multitude of factors that may induce anxiety during a pandemic, that could lead to stockpiling as a form of coping. In fact, a recent meta-analysis estimated that 31.9% of the general population had experienced anxiety during the pandemic (Salari et al., 2020). What is perhaps more interesting is that the effects of anxiety on panic buying are amplified by an individual’s resilience. This indicates that when anxiety is felt, it is those who are resilient who are more likely to undertake panic buying. While this may initially seem counter-intuitive, it makes sense when an individual views panic buying as an adaptive coping behavior because those who are resilient are more likely to take greater steps to reduce their anxiety or to positively adapt to the situation (Fletcher and Sarker, 2013). For Muslims, this positive view of panic buying may stem from teachings of preparedness and familial responsibilities, where their intention is to avoid a resource loss for themselves and family. While panic buying is understood as a negative societal phenomenon, that it stems from a positive adaptation to adversity at the individual level is important as it helps to determine where to focus efforts. For instance, while attempts have been made to enhance individuals’ resilience during COVID-19, it might, for example, be more beneficial to focus efforts on enhancing community resilience or social cohesion (Chen and Bonanno, 2020). Understanding this is important for those trying to control panic buying as it means that strategies other than encouraging personal resilience may need to be used for those who are particularly high in anxiety. Indeed, efforts to increase resilience may have the opposite effect for well-intended policymakers when considering panic buying.

Alternately, the focus of policy could be on making people believe that panic buying is a maladaptive coping response and directing them to reduce their anxiety through other means. In particular, reducing the likelihood or severity of the threats, such as providing reassurances that the country has a well-developed supply chain or food security plans in place, or that delivery services will be enhanced by supermarkets ensuring the continual access to goods may reduce the initial perception of the threat to an individual’s resources. Applying the conservation of resources theory might mean instilling a greater sense of individual and community control over the situation, which may be important for whether people feel they even need to act to shore up resources in the first place (Hobfoll and Schumm, 2002).

8. Implications

There are many actions that governments and retailers have taken to limit panic buying with much of the focus on enforcing purchase quotas and assuring people that supplies are not in danger, as well as providing more general advice on how to manage anxiety and mental health issues. Furthermore, there have been recommendations from health authorities for individuals to avoid consuming excessive amounts of COVID-19 information when they are feeling overwhelmed with anxiety (e.g. World Health Organization, 2020). While this advice is important, these results suggest the focus should expand beyond encouraging people to reduce information intake to avoid mental health repercussions. It may also be important to advise people to reduce their information exposure so that they do not seemingly rationally overcompensate with their behaviors. Media literacy is always important to promote but may be particularly important at times of crisis to help people understand how the information they consume is influencing their beliefs and actions, which extend beyond effects on mental health. Indeed, the type of information flow within the UAE Muslim community may be important to consider where greater word-of-mouth or sharing through social networks may mean more susceptibility to alarmist information that may not have the same vetting process as more official sources. While less formal avenues such as family and friends or social media shares may fit this description, it is encouraging that Muslims in the UAE are likely to source COVID-19 information from the Government. This finding provides hope for governments who wish to find a stronger foothold in disseminating proactive and reactive information to those who may more often receive ill-advised or sensationalist information through non-regulated forms of media. To facilitate this, official information would be better structured in less traditional media formats and specifically produced to be passed along community networks.

In addition to limiting negative information exposure, society would benefit from efforts to redirect high levels of resilience which amplify the effect of information-induced anxiety. This may not center on reducing the amount of information exposure but on other initiatives such as providing information and education on other adaptive, prosocial coping behaviors and encouraging the use of other resources such as community support or even reminding people of the sufficiency of their existing resources or their regular resourcing habits. Specifically, pandemic preparedness plans in Muslim communities may look to integrate scriptural prohibitions against hoarding to help reduce such socially maladaptive behaviors, while simultaneously reinforcing Islamic teachings on equality of humanity and brotherhood (Arham, 2010). Islamic scholars could be consulted on health messaging in such contexts, to tap into core Islamic values resonant with desired behaviors.

That a greater sense of belonging is associated with reduced anxiety within the Muslim population is beneficial, yet further understanding may be needed to ensure that this belongingness does not simultaneously fuel panic buying directly but reduces the need for it by framing these networks as a resource. Moreover, focusing on those who experience anxiety, policymakers may also need to focus more specifically on those who are not just anxious but also resilient. The first step would be determining who these people are, which may be difficult, as it is unlikely they exhibit many outward signs. However, if particular pockets of society that are high in resilience could be identified it would enable a focused effort to redirect resilience in these targeted populations away from hoarding resources. Furthermore, identifying geographically based populations that are more resilient could help in directing where to secure supply chains. This may have the dual benefit of suppressing panic buying in particularly prone areas and avoiding further panic buying media coverage that might enable the spread to even non-anxious or low resilience populations.

9. Limitations and suggestions for future research

This study has a number of limitations. First, as noted, the sample was one of convenience and as a result, overrepresents women and youth. As such, care should be taken when making generalizations to the broader Muslim market. Given that significant differences in stockpiling and information sources between Muslim and the eliminated participants were found, future studies should use random sampling techniques in both groups and conduct a more detailed comparison of their consumer stockpiling responses to disasters. Another limitation of this study is that the survey went live two weeks after the peak in COVID-19 related panic buying in the UAE. While the panic buying measure asked respondents to reflect on purchases made in recent weeks, it would have been preferable to have collected data on panic buying behavior during its peak. Third, to obtain the time-sensitive data in a rapid fashion, the study relied upon self-report measures and in the case of panic buying and COVID-19 information exposure, new measures that have not been rigorously validated. As with any cross-sectional mediation analysis, it is possible that the directionality of the relationships does not hold. While theoretical arguments were made it is possible anxiety influenced panic buying but also increased the consumption of COVID-19 information, which, in turn, increased anxiety. Future studies should examine these relationships in a controlled or longitudinal setting to enhance the potential for causal inferences to be made. Finally, as this study found that only a proportion of panic buying is related to anxiety, we suggest that future studies investigate preparedness and other variables that may influence consumer stockpiling in anticipation of a disaster, in particular, the level of religiosity and whether this precedes certain adaptive behaviors. After a more thorough understanding of the construct is developed, a new more accurate name should be proposed that better encapsulates the phenomenon and does not itself give rise to panic when used in the media.

Figures

Model of moderated mediation on panic buying

Figure 1.

Model of moderated mediation on panic buying

The interaction effect of anxiety and resilience on panic buying

Figure 2.

The interaction effect of anxiety and resilience on panic buying

Johnson-Neyman plot of the mediation effect of anxiety at levels of resilience (standardized)

Figure 3.

Johnson-Neyman plot of the mediation effect of anxiety at levels of resilience (standardized)

Total and Muslim sample demographics

Total Muslim Total Muslim
Freq (%) Freq (%)   Freq (%) Freq (%)
Female 1,152 82.8 852 84.7 National 857 61.6 791 78.6
Male 240 17.2 154 15.3 Expatriate 535 38.4 215 21.3
Muslim 1,006 72.3 N/A N/A 18–24 565 40.6 543 54.0
Christian 221 15.9 N/A N/A 25–39 478 34.3 296 29.4
Hindu 46 3.3 N/A N/A 40–54 296 21.3 146 14.5
Other 119 8.5 N/A N/A 55+ 53 3.8 21 2.1
<High school 6 0.4 4 0.4 City 641 46.0 502 49.9
High school 404 29.0 382 38.0 Suburb 563 40.4 395 39.2
Bachelors 648 46.6 437 43.4 Town-village 163 11.7 92 9.1
Masters 246 17.7 134 13.3 Farm 25 1.8 17 1.7
Doctorate 88 6.3 49 4.9      

Mann-Whitney U tests of differences in panic buying product categories and COVID-19 information sources between the Muslim and eliminated samples

Dependent variable Religion N Mean SD SE W p
Product categories 
Tinned food Muslim 1,006 2.46 1.288 0.041 173,500 0.001
  Other 386 2.23 1.338 0.068    
Water Muslim 1,006 3.31 1.459 0.046 166,061 <0.001
  Other 386 2.93 1.501 0.076    
Sanitary Muslim 1,006 3.64 1.254 0.040 172,761 0.001
  Other 386 3.38 1.341 0.068    
Toilet rolls Muslim 1,006 2.47 1.301 0.041 184,576 0.139
  Other 386 2.37 1.354 0.069    
Dried foods Muslim 1,006 3.09 1.371 0.043 177,009 0.009
  Other 386 2.88 1.353 0.069    
Bread Muslim 1,006 3.02 1.387 0.044 152,620 <0.001
  Other 386 2.50 1.278 0.065    
Pharmacy Muslim 1,006 2.37 1.317 0.042 182,718 0.077
  Other 386 2.23 1.294 0.066    
COVID-19 info source 
Newspaper Muslim 1,006 1.65 1.032 0.033 263,968 <0.001
  Other 386 2.43 1.219 0.062    
TV Muslim 1,006 2.47 1.188 0.037 208,941 0.023
  Other 386 2.64 1.216 0.062    
Social media Muslim 1,006 3.50 0.879 0.028 146,103 <0.001
  Other 386 3.11 0.981 0.050    
Family and friends Muslim 1,006 3.02 1.009 0.032 149,905 <0.001
  Other 386 2.64 0.919 0.047    
Government Muslim 1,006 3.26 0.994 0.031 154,350 <0.001
  Other 386 2.95 0.964 0.049    

Means, standard deviations and correlation coefficients of modeled variables*

Variable Mean SD 2 3 4 5 6 7
1 Info exposure 8.997 2.131 0.09a −0.11a 0.29a 0.06b −0.19a −0.06b
2 Anxiety 8.689 6.694 −0.43a 0.21a −0.10a −0.15a 0.09a
3 Resilience 19.302 4.459 −0.14a 0.04b 0.16a 0.00b
4 Panic buy score 20.36 6.933 0.10a −0.15a 0.03b
5 Belonging 1.958 1.003 0.05b 0.02b
6 Education level 1.843 0.836 0.16a
7 Pre-existing health 0.116 0.321
Notes:
a

p < 0.01,

b

not significant, anxiety = GAD-7, resilience = BRS.

*All variables were tested using Pearson’s correlation coefficient, except education and pre-existing health using Spearman’s rho

Regression results for the moderated mediation model

Model variables R R2 MSE F(4, 1001) p
Anxiety 0.2249 0.0506 42.71 13.89 0.000
β SE (HC3) t p CI (95%)
Const. 0.49 0.099 4.90 0.000 [0.2913, 0.6796]
Info exposure 0.08 0.034 2.32 0.021 [0.0131, 0.1459]
Pre-exist 0.39 0.099 3.88 0.000 [0.1984, 0.5789]
Education −0.19 0.038 −4.97 0.000 [−0.2630, −0.1137]
Belonging −0.10 0.033 −2.95 0.003 [−0.1597, −0.0323]
R R2 MSE F(7, 998) p
Panic buy 0.38 0.141 0.86 22.152 0.000
β SE (HC3) t p CI (95%)
Const. 0.02 0.090 0.22 0.823 [−0.1509, 0.1936]
Info exposure 0.26 0.033 7.79 0.000 [0.1950, 3240]
Anxiety (A) 0.17 0.034 5.12 0.000 [0.1086, 0.2380]
Resilience (R) −0.03 0.035 −0.72 0.473 [−0.921, 0.0436]
A x R 0.07 0.031 2.21 0.027 [0.0082, 0.1286]
Pre-Exist 0.12 0.091 1.30 0.193 [−0.0582, 0.2953]
Education −0.09 0.035 −2.47 0.014 [−0.1542, −0.0179]
Belonging 0.11 0.031 3.47 0.001 [0.0492, 0.1672]

References

Ajzen, I. (1991), “The theory of planned behavior”, Organizational Behavior and Human Decision Processes, Vol. 50 No. 2, pp. 199-211.

Ahmad, A., Iram, K. and Jabeen, G. (2020), “Perception-based influence factors of intention to adopt COVID-19 epidemic prevention in China”, Environmental Research, Vol. 190.

Arafat, S.M.Y., Kar, S.K. and Kabir, R. (2020a), “Possible controlling measures of panic buying during COVID-19”, International Journal of Mental Health and Addiction, Vol. 289.

Arafat, S.M.Y., Kar, S.K., Menon, V., Kaliamoorthy, C., Mukherjee, S., Alradie-Mohamed, A., Sharma, P., Marthoenis, M. and Kabir, R. (2020b), “Panic buying: an insight from the content analysis of media reports during T COVID-19 pandemic”, Neurology, Psychiatry and Brain Research, Vol. 37, pp. 100-103.

Arham, M. (2010), “Islamic perspectives on marketing”, Journal of Islamic Marketing, Vol. 1 No. 2, pp. 149-164.

Banerjee, D. (2020), “The other side of COVID-19: impact on obsessive compulsive disorder (OCD) and hoarding”, Psychiatry Research, Vol. 288 No. 6, pp. 1-2.

Centola, D., Becker, J., Brackbill, D. and Baronchelli, A. (2018), “Experimental evidence for tipping points in social convention”, Science, Vol. 360 No. 6393, pp. 1116-1119.

Chen, S. and Bonanno, G.A. (2020), “Psychological adjustment during the global outbreak of COVID-19: a resilience perspective”, Psychological Trauma: Theory, Research, Practice, and Policy, Vol. 12, pp. S51-S54.

Chen, C.Y., Lee, L. and Yap, A.J. (2017), “Control deprivation motivates acquisition of utilitarian products”, Journal of Consumer Research, Vol. 43 No. 6, pp. 1031-1047.

Cramer, M. and Sheikh, K. (2020), “Surgeon general urges the public to stop buying face masks”, The New York Times, February 29, available at: www.nytimes.com/2020/02/29/health/coronavirus-n95-face-masks.html (accessed 29 September 2020).

De Bel Air, F. (2015), “Demography, migration, and the labour market in the UAE”, Explanatory Note No. 7/2015, Gulf Labour Market and Migration programme of the Migration Policy Center and the Gulf Research Center, available at: https://cadmus.eui.eu/bitstream/handle/1814/36375/GLMM_ExpNote_07_2015.pdf (accessed 29 September 2020).

De Bel Air, F., Safar, J. and Destrehan, B. (2018), “Marriage and family in the Gulf today: storms over a patriarchal institution?”, Arabian Humanities, Vol. 10.

Depoux, A., Martin, S., Karafillakis, E., Preet, R., Wilder-Smith, A. and Larson, H. (2020), “The pandemic of social media panic travels faster than the COVID-19 outbreak”, Journal of Travel Medicine, Vol. 27 No. 3, pp. 1-2.

Doi, S., Ito, M., Takebayashi, Y., Muramatssu, K. and Horikoshi, M. (2018), “Factorial validity and invariance of the 7-item generalized anxiety disorder scale (GAD-7) among populations with and without self-reported psychiatric diagnostic status”, Frontiers in Psychology, Vol. 9 No. 9, pp. 1-6.

Duncan, G. and Dutton, J. (2020), “Coronavirus: we are prepared to face any challenge, says Sheikh Mohamed bin Zayed”, The National, March 16, available at: www.thenational.ae/uae/coronavirus-we-are-prepared-to-face-any-challenge-says-sheikh-mohamed-bin-zayed-1.993463 (accessed 29 September 2020).

Durante, K.M. and Laran, J. (2016), “The effect of stress on consumer saving and spending”, Journal of Marketing Research, Vol. 53 No. 5, pp. 814-828.

Fischbach, T. (2018), “Advancing food security in the UAE”, Mohammed Bin Rashid school of government policy paper, available at: www.mbrsg.ae/getattachment/859ddec7-f5ed-48dd-99dd-4e1b8f326112/Advancing-food-security-in-the-UAE.aspx (accessed 29 September 2020).

Fischhoff, B., Wong-Parodi, G., Garfin, D.R., Holman, E.A. and Silver, R.C. (2017), “Public understanding of ebola risks: mastering an unfamiliar threat”, Risk Analysis, Vol. 38 No. 1, pp. 71-83.

Fletcher, D. and Sarker, M. (2013), “Psychological resilience: a review and critique of definitions, concepts, and theory”, European Psychologist, Vol. 18 No. 1, pp. 12-23.

Garbe, L., Rau, R. and Toppe, T. (2020), “Influence of perceived threat of COVID-19 and HEXACO personality traits on toilet paper stockpiling”, PLoS One, Vol. 15 No. 6, pp. 1-12.

Garfin, D.R., Silver, R.C. and Holman, E.A. (2020), “The novel coronavirus (COVID-19) outbreak: amplification of public health consequences by media exposure”, Health Psychology, Vol. 39 No. 5, pp. 355-357.

Google Trends (2020), “Exploring what the world is searching”, available at: https://trends.google.com/ (accessed 29 September 2020).

Guaglione, S. (2020), “Traffic increases 60% to publishers' sites amid coronavirus”, Publishers Daily, 17 March, available at: www.mediapost.com/publications/article/348611/traffic-increases-60-to-publishers-sites-amid-co.html (accessed 29 September 2020).

Hall, M.C., Prayag, G., Fieger, P. and Dyason, D. (2020), “Beyond panic buying: consumption displacement and COVID-19”, Journal of Service Management, Vol. 32 No. 1, pp. 113-128.

Hayes, A.F. (2018), Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach, 2nd Ed., Guilford Press, New York, NY.

Havnen, A., Anyan, F., Hjemdal, O., Solem, S., Gurigard Riksfjord, M. and Hagen, K. (2020), “Resilience moderates negative outcome from stress during the COVID-19 pandemic: a moderated-mediation approach”, International Journal of Environmental Research and Public Health, Vol. 17 No. 18, pp. 6461-6478.

Helsloot, I. and Ruitenberg, A. (2004), “Citizen response to disasters: a survey of literature and some practical implications”, Journal of Contingencies and Crisis Management, Vol. 12 No. 3, pp. 98-111.

Hobfoll, S.E. (1989), “Conservation of resources: a new attempt at conceptualizing stress”, American Psychologist, Vol. 44 No. 3, pp. 513-524.

Hobfoll, S.E. and Schumm, J.A. (2002), “Conservation of resources theory: application to public health promotion”, in DiClemente, R.J., Crosby, R.A. and Kegler, M.C. (Eds), Emerging Theories in Health Promotion Practice and Research, John Wiley and Sons, New York, NY, pp. 131-156.

Huang, Y. and Zhao, N. (2020), “Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 outbreak in China: a web-based cross-sectional survey”, Psychiatry Research, Vol. 288 No. 6, pp. 1-6.

IRI (2020), “COVID-19 impact: consumer spending tracker for measured channels. Information resources inc”, available at: www.iriworldwide.com/IRI/media/Library/2020-04-30-IRI-BCG-COVID-Global-Consumer-Spend-Tracker.pdf (accessed 29 September 2020).

Islam, M.S., Ferdous, M.Z. and Potenza, M.N. (2020), “Panic and generalized anxiety during the COVID-19 pandemic among Bangladeshi people: an online pilot survey early in the outbreak”, Journal of Affective Disorders, Vol. 276 No. 1, pp. 30-37.

Islam, M.S., Pitafi, A.H., Arya, V., Wang, Y., Akhtar, N., Mubarik, S. and Xiaobei, L. (2021), “Panic buying in the COVID-19 pandemic: a multi-country examination”, Journal of Retailing and Consumer Services, Vol. 59.

Jankowicz, M. (2020), “The coronavirus outbreak has prompted people around the world to panic buy toilet paper. Here’s why”, Business Insider, available at: www.businessinsider.com/coronavirus-panic-buying-toilet-paper-stockpiling-photos-2020-3?r=US&IR=T (accessed 10 March).

Keane, M. and Neal, T. (2021), “Consumer panic in the COVID-19 pandemic”, Journal of Econometrics, Vol. 220 No. 1, pp. 86-105.

Kemp, E., Kennett‐Hensel, P.A. and Williams, K.H. (2014), “The calm before the storm: examining emotion regulation consumption in the face of an impending disaster”, Psychology and Marketing, Vol. 31 No. 11, pp. 933-945.

Khaleej Times (2020), “You DON'T need masks to stay safe from coronavirus: UAE ministry”, available at: www.khaleejtimes.com/photos/nation/you-dont-need-masks-to-stay-safe-from-coronavirus-uae-ministry (accessed 29 September 2020).

Kostev, K. and Lauterbach, S. (2020), “Panic buying or good adherence? Increased pharmacy purchases of drugs from wholesalers in the last week prior to Covid-19 lockdown”, Journal of Psychiatric Research, Vol. 130, pp. 19-21.

Kulemeka, O. (2010), “US consumers and disaster: observing ‘panic buying’ during the winter storm and hurricane seasons”, in Campbell, M.C., Inman, J. and Pieters, R. (Eds), NA – Advances in Consumer Research, Vol. 37, Association for Consumer Research, Duluth, MN, pp. 837-838.

Lei, L., Huang, X., Zhang, S., Yang, J., Yang, L. and Xu, M. (2020), “Comparison of prevalence and associated factors of anxiety and depression among people affected by versus people unaffected by quarantine during the COVID-19 epidemic in southwestern China”, Medical Science Monitor, Vol. 26, pp. 1-12.

Li, J., Hallsworth, A.G. and Coca-Stefaniak, J.A. (2020), “Changing grocery shopping behaviors among Chinese consumers at the outset of the COVID-19 outbreak”, Journal of Economic and Social Geography, Vol. 111 No. 3, pp. 574-583.

Lins, S. and Aquino, S. (2020), “Development and initial psychometric properties of a panic buying scale during COVID-19 pandemic”, Heliyon, Vol. 6 No. 9.

Loxton, M., Truskett, R., Scarf, R., Sindone, L., Baldry, G. and Zhao, Y. (2020), “Consumer behaviour during crises: preliminary research on how coronavirus has manifested consumer panic buying, herd mentality, changing discretionary spending and the role of the media in influencing behaviour”, Journal of Risk and Financial Management, Vol. 13 No. 8, pp. 1-21.

Naeem, M. (2021), “Do social media platforms develop consumer panic buying during the fear of covid-19 pandemic”, Journal of Retailing and Consumer Services, Vol. 58.

NCEMA (2020), “UAE coronavirus (COVID-19) updates”, UAE National Emergency Crisis and Disaster Management Authority, available at: https://covid19.ncema.gov.ae/en (accessed 29 September 2020).

O’Connell, M., De Paula, A. and Smith, K. (2020), “Preparing for a pandemic: spending dynamics and panic buying during the COVID-19 first wave”, Center for Economic Policy Research Discussion Paper, available at: https://repec.cepr.org/repec/cpr/ceprdp/DP15371.pdf (accessed 4 January 2021).

Oxford Business Group (2016), “The report; Dubai 2016”, available at: https://oxfordbusinessgroup.com/analysis/young-heart-meeting-needs-region’s-growing-youth-population (accessed 29 September 2020).

Piscopo, A., Siebes, R. and Hardman, L. (2017), “Predicting sense of community and participation by applying machine learning to open government data”, Policy and Internet, Vol. 9 No. 1, pp. 55-75.

Prentice, C., Chen, J. and Stantic, B. (2020), “Timed intervention in COVID-19 and panic buying”, Journal of Retailing and Consumer Services, Vol. 57.

Salari, N., Hosseinian-Far, A., Jalali, R., Vaisi-Raygani, A., Rasoulpoor, S., Mohammadi, M., Rasoulpoor, S. and Khaledi-Paveh, B. (2020), “Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: a systematic review and meta-analysis”, Global Health, Vol. 16 No. 57.

Sasseendran, S. and Chaudhary, S.B. (2020), “UAE retailers allay fears about stock depletion, say no need to panic buy”, Gulf News, 17 March, available at: https://gulfnews.com/uae/uae-retailers-allay-fears-about-stock-depletion-say-no-need-to-panic-buy-1.70428460

Sebugwaawo, I. (2020), “Coronavirus: don't share videos of panic buying in bulk”, Khaleej Times, 16 March, available at: www.khaleejtimes.com/coronavirus-outbreak/coronavirus-dont-share-videos-of-panic-buying-in-bulk (accessed 29 September 2020).

Sim, K., Chua, H.C., Vieta, E. and Fernandez, G. (2020), “The anatomy of panic buying related to the current COVID-19 pandemic”, Psychiatry Research, Vol. 288 No. 6, p. 1.

Smith, B.W., Dalen, J., Wiggins, K., Tooley, E., Christopher, P. and Bernard, J. (2008), “The brief resilience scale: assessing the ability to bounce back”, International Journal of Behavioral Medicine, Vol. 15 No. 3, pp. 194-200.

Spielberger, C.D. (Ed.), (1972), Anxiety: Current Trends in Theory and Research, Academic Press, Oxford.

Spitzer, R.L., Kroenke, K., Williams, J.B.W. and Löwe, B. (2006), “A brief measure for assessing generalized anxiety disorder: the GAD-7”, Archives of Internal Medicine, Vol. 166 No. 10, pp. 1092-1097.

Taha, S.A., Matheson, K. and Anisman, H. (2014), “H1N1 was not all that scary: uncertainty and stressor appraisals predict anxiety related to a coming viral threat”, Stress and Health, Vol. 30 No. 2, pp. 149-157.

Thompson, R.R., Garfin, D.R., Holman, E.A. and Silver, R.C. (2017), “Distress, worry, and functioning following a global health crisis: a national study of Americans’ responses to Ebola”, Clinical Psychological Science, Vol. 5 No. 3, pp. 513-521.

Trading Economics (2020), “U.S. Retail sales 1992-2020 data”, available at: https://tradingeconomics.com/united-states/retail-sales (accessed 29 September 2020).

World Health Organization (2021), “WHO coronavirus disease (COVID-19) dashboard”, available at: https://covid19.who.int (accessed 4 January 2021).

World Health Organization (2020), “Looking after our mental health”, available at: www.who.int/campaigns/connecting-the-world-to-combat-coronavirus/healthyathome/healthyathome–-mental-health (accessed 29 September 2020).

Yao, H. (2020), “The more exposure to media information about COVID-19, the more distressed you will feel”, Brain, Behavior, and Immunity, Vol. 87, pp. 167-169.

Yuen, K.F., Wang, X., Ma, F. and Li, K.X. (2020), “The psychological causes of panic buying following a health crisis”, International Journal of Environmental Research and Public Health, Vol. 17 No. 10, pp. 1-14.

Corresponding author

Claire Eloise Sherman can be contacted at: claire.sherman@zu.ac.ae

Related articles