A Bibliometric Analysis of Panic-Buying Behavior during a Pandemic: Insights from COVID-19 and Recommendations

Abstract

COVID-19 is the latest pandemic form and, as usual, it also opened gates for new avenues in consumer behavior research. Panic buying among consumers due to the current pandemic is the focus of this study. This study adopts a bibliometric approach to analyze the studies published in the last three years (2020–2022) (obviously, there is no research before 2020). Seventy-nine studies are included based on the Web of Science database. First, a general analysis is conducted to understand the current state of research by mapping countries, authors, publication outlets, citations, institutions, etc. It provides the association or linkage of the mentioned variables related to the mentioned studies. Second, insights and recommendations are provided based on specific keyword analysis and deep diving. The findings indicate that panic-buying behavior is a fact during COVID-19, especially in the first year, and specific factors were responsible for the same. In the second year, it ebbed substantially. This study provides recommendations for practitioners to deal with panic buying behaviors in future pandemics.

1. Introduction

Around March 2020, the COVID-19 outbreak officially turned into a pandemic. For over two years, we have seen many waves causing lockdowns and disruptions to everyday lives. However, during this pandemic, which is still wreaking havoc, consumer behavior changed drastically. Whatever the reasons (antecedents), it created panic in the consumer’s mind and led to typical buying behavior [1]. The purchase and stock of vast amounts of goods in anticipation of supply disruptions is called panic buying [2,3]. COVID-19 forced almost one in three consumers to purchase and create a good inventory of essentials that might last for an extended period [4]. This behavior created massive pressure on the supply chain, and economic woes escalated across the globe. Both the pandemic and the resultant panic-buying behavior negatively impacted the economies of many countries [5,6]. COVID-19 stands out as a pandemic as the impact is global and long-term. The spread of information and misinformation was fast, given the technological advancements in the last few years. Researchers across the domains started focusing on this panic buying behavior as early as the first half of 2020. Taking cues from the previous pandemics and the resultant panic-buying behaviors, many researchers tried to assess the antecedents, consequents, networks, and future behavioral patterns, to name a few [1,5,7,8].

Rationale of the Study

COVID-19 hit the world economy as the latest form of a pandemic. Nevertheless, of course, any pandemic gives rise to panic-buying behavior among the masses. The reasons might be a sense of severity, uncertainty, or a shortage of essential items [5,6]. Many studies over the last three years of COVID-19 have discussed various aspects of consumer panic-buying behavior. However, unfortunately, the studies have been primarily empirical. Therefore, this provided an opportunity to collate the notable works and assess the focal points of these studies. This study tries to provide an overview, review, and synthesis of significant literary works on the various aspects of panic buying during COVID-19. No bibliometric study on this domain has been attempted to date, and this study strives to fill this gap. The primary objective is divided into a few sub-objectives, provided below as the research questions related to panic buying during COVID-19.

RQ1: What are the general developments of publications in this field?

RQ2: What are the significant literary works that impacted this domain?

RQ3: What type of cooperation relationships exist among the existing literature?

RQ4: What are the trends and hot topics in the existing research?

RQ5: What are the critical insights based on the current literature?

The study is organized in the following manner. The following section explains the methodology adopted for the research. Section three provides the results that provide answers to RQ1:RQ3. It includes a general analysis, cooperation analysis, and keyword analysis. Finally, sections four and six provide significant findings and recommendations (RQ4 and RQ5).

2. Methodology

The primary aim of the bibliometric analysis is to collate and discuss the existing publications by mining the databases [6,9,10]. First, the database should be finalized to mine the articles per search terms. Second, the analysis approach has to be fixed. Finally, software packages, especially visualization and statistical packages, should be selected. This study uses a stage-wise methodology, shown in Figure 1, to address the research questions.

The study began with the planning phase. It included three aspects: finalizing the research questions and objectives, setting the inclusion criteria, and setting the search criteria. The next stage was about fixing the database(s). There were many databases available. However, two databases topped the chart based on various criteria: Scopus and Web of Science (WoS). Finally, the Web of Science core collection was chosen as the sole database as it only indexed high-quality publications.

Furthermore, the following criteria were used to include the literature in this article: studies related to panic buying behavior; studies related to COVID-19; documents limited to peer-reviewed journal articles and indexed conference outputs only; and studies published since 2020, as there is no prior literature on COVID-19. Then, an advanced search option was used, and ‘author keywords’ were used to search the articles. This was performed because the title option generated very few articles. Therefore, numerous combinations of author keywords were used, such as COVID-19, Covid-19, Coronavirus, Panic, Panic Buying, and Panic Buying Behavior, to name a few. More than one hundred and thirty articles were gathered using the database’s flexible/preliminary keyword combinations. One hundred and five articles were shortlisted based on the inclusion criteria and after removing duplicate publications. Twenty-two articles did not meet the quality standards, and four were removed after the manual screening [10]. Finally, seventy-nine articles were considered after fixing the keywords as given: (((AK = (COVID-19)) OR AK = (COVID-19)) AND ((AK = (panic buying)) OR AK = (Panic Buying))). Finally, it was finalized after using all the possible combinations with similar words as discussed above.

3. Bibliometric Analysis

A detailed bibliometric analysis of the selected articles was conducted in a structured manner.

The bibliometric analysis included three components: 1. General analysis, 2. Keywords analysis, and 3. Cooperation network [6,9]. It was followed by findings and recommendations. Finally, the study concluded with limitations and future directions. The VOSviewer v.1.6.18 software package was used for the analysis.

3.1. General Analysis

This section assesses the publications and citations over the pandemic’s last three years to understand the trends and research directions. Figure 2 shows that 2021 is the most productive year, and the answer is obvious. However, given the trend, 2022 might be the best year, especially in the citations. Figure 3 shows the top 10 research directions on panic-buying behavior during COVID-19. With 23 publications, the business domain leads the pack. It is followed by public environmental occupational health (11) and psychiatry (8).

After assessing the general trends of the publications and citations, a detailed analysis of the selected publications was conducted. Two tables (

Table 1. Total Publications (TP) of the top 10 countries, institutions, authors, and journals.

Rank	Country/Region	TP	Rank	Institution	TP	Rank	Author	TP	Rank	Journal	TP
1	USA	13	1	Northwest University South Africa	6	1	Yuen, K.F.	5	1	Journal of Retailing and Consumer Services	8
2	China	11	2	Nanyang Technological University	5	2	Wang, X.Q.	4	2	Frontiers in Public Health	6
3	Australia	10	3	Griffith University	4	3	Prentice, C.	3	3	Sustainability	5
4	South Africa	7	4	Islamic Azad University	4	4	Taylor, S.	3	4	Personality and Individual Differences	4
5	India	6	5	Jawaharlal Institute of Postgraduate Medical Education Research	3	5	Arafat, S.M.Y.	3	5	Frontiers in Psychiatry	3
6	Germany	6	6	Lincoln University	3	6	Wong, Y.D.	3	6	International Journal of Environmental Research and Public Health	3
7	Iran	5	7	University of British Columbia	3	7	Chen, T.	3	7	Frontiers in Psychology	2
8	Singapore	5	8	University of Canterbury	3	8	Cong, G.	3	8	International Journal of Consumer Studies	2
9	Canada	4	9	Qatar University	3	9	Ben Hassen, T.	3	9	International Journal of Emerging Markets	2
10	New Zealand	4	10	Chung Ang University	3	10	El Bilali, H.	3	10	Journal of Anxiety Disorders	2

and

Table 2. Total Citations (TC) of the top 10 countries, institutions, authors, and journals.

Rank	Country/Region	TC	Rank	Institution	TC	Rank	Author	TC	Rank	Journal	TC
1	South Africa	530	1	Northwest University South Africa	530	1	Dhir, A.	244	1	Journal Of Retailing and Consumer Services	505
2	Australia	521	2	Lut University	244	2	Farooq, A.	244	2	International Journal of Environmental Research and Public Health	194
3	China	491	3	University of Stavanger	244	3	Islam, N.	244	3	Journal of Service Management	138
4	USA	271	4	University of Turku	244	4	Laato, S.	244	4	Sustainability	137
5	Finland	266	5	University of Canterbury	223	5	Yuen, K.F.	201	5	Journal of Risk and Financial Management	108
6	Norway	244	6	Nanyang Technological University	201	6	Wang, X.Q.	186	6	Journal of Anxiety Disorders	97
7	New Zealand	225	7	Griffith University	168	7	Dyason, D.	160	7	International Journal of Consumer Studies	96
8	Singapore	201	8	University of New England	160	8	Fieger, P.	160	8	Frontiers in Psychology	64
9	Pakistan	193	9	Rajalakshmi School of Business	150	9	Prayag, G.	160	9	Frontiers in Public Health	57
10	India	191	10	Hefei University of Technology	150	10	Prentice, C.	152	10	Journal of Competitiveness	43

) were created to provide the top 10 publications and citations through four parameters: countries, institutions, authors, and journals [9]. The USA leads the publications (13), and South Africa leads the citations (530). Institution-wise, Northwest University, South Africa leads the publications (6) and citations (530). The Journal of Retailing and Consumer Services (JRCS) leads the list of journals with eight publications. The JRCS is also a clear winner regarding the number of citations (505). Author-wise, Dhir A, Farooq A, Islam N, and Laato S (244 each) lead the citations [5], and Yuen KF leads with five publications.

3.2. Keywords Analysis

After the general analysis of the shortlisted publications, VOS viewer was used to visualize the co-occurrence of keywords (author) in a study [9]. It was performed to assess the particular focus areas of the authors. A total of 255 keywords were used in the publications. Panic Buying was the top keyword (70), followed by COVID-19 (67). It was obvious as our selection criteria were based on these two terms. Other heavily used keywords were stockpiling, pandemic, COVID-19 pandemic, and consumer behavior. Figure 4 presents a visualization of the keywords along with the co-occurrences. COVID-19 is hidden by “panic buying” due to the similar numbers. All these 255 author keywords were grouped under 40 clusters.

3.3. Cooperation Network

After the general and keywords analyses, a network analysis (cooperation) was conducted based on three criteria: country/region, institution, and author. Table 1 and Table 2 already provided the top 10 listings for these criteria.

3.3.1. Country/Region

Figure 5a shows all the countries with a minimum of one document. Forty-one countries with six clusters were found. The USA, China, Australia, and South Africa cooperated the most. Out of the top five countries, China and Australia fall into the same cluster, proving a solid collaboration between these two countries. The other three countries collaborated with diverse geographically spread countries. The lower number of clusters showed strong cooperation between the mentioned countries. However, South Africa and the USA provided the maximum link strength showing their networking capabilities.

Figure 5b displays the cooperation network between the countries/regions based on a minimum of four document criteria. It was considered as the top 10 countries had a minimum of four publications (Table 1). However, 12 countries qualified for the requirements and were grouped under two clusters. Eight countries, led by the USA and China, were in one cluster, and the other four countries were grouped, led by Australia and South Africa. Only two clusters showed a strong collaboration between the top countries at a minimum of four publications. However, no specific geographic grouping was shown. China and the USA showed the maximum link strength, indicating their strong collaborations.

3.3.2. Institutions/Organizations

Furthermore, a cooperation analysis of the institutions was conducted. A visualization of the collaborative relationships is presented in Figure 6a,b. Figure 6a displays 150 institutions grouped under 10 clusters (minimum of one document). Again, 10 clusters for 150 institutions proved strong associations. The top 10 institutions have led strong collaborations with others. Northwest University leads the pack, followed by Nanyang Technological University, Griffith University, and Islamic Azad University. Northwest University had the maximum link strength too.

For a deeper understanding of the collaborations between the top 10 institutions, a collaborative network was assessed with a criterion of a minimum of three documents. An institution was considered to be one of the top 10 institutions if it had a minimum of three publications (Table 1). However, 12 institutions qualified for the requirements and were grouped under three clusters. Figure 6b shows that seven institutions, led by NTU and Griffith university, were in one cluster. The second group was led by Northwest University, and the third cluster grouped Islamic Azad University and Qatar University together. Only three clusters showed a strong collaboration between the top 12 institutions at a minimum of three publications. However, no specific geographic grouping was shown. NTU and Northwest university had the maximum link strength.

3.3.3. Authors

In this section, the collaboration network of the authors is assessed. Figure 7a presents a visualization of 269 authors grouped under 11 clusters (minimum of one document). Again, 11 clusters for 269 authors proved strong associations. The top five authors have led strong collaborations with others. Yuen KF, with five documents and 201 citations, had the maximum link strength.

Furthermore, a deep analysis of the collaboration between the top 10 authors was conducted, and a collaborative network was assessed with a criterion of a minimum of three documents. It was considered as the top 10 authors had a minimum of three publications (Table 1). However, 11 authors qualified for the criteria and were grouped under three clusters. Figure 7b shows that six authors were part of cluster 1. Three authors, led by Yuen KF, formed the second cluster, and the other two authors formed the third cluster. At a minimum of three publications, only three clusters showed a strong collaboration between the top 11 authors. Yuen KF, with five documents and 201 citations, had the maximum link strength.

4. Findings and Discussion

The COVID-19 pandemic is slowly coming to an end. However, it adversely impacted many domains in the last three years, especially consumer behavior. Panic-buying behavior was a significant and visible outcome in the last three years. This study conducted a bibliometric analysis of 79 quality outputs in the previous section. It provided specific insights, and a few research propositions were made. It was clear from the analysis that the current pandemic created panic among consumers, especially in the first year. By the second year, it ebbed with the introduction of medicines and vaccines [1,11]. The consumers were quite concerned about the availability of essential goods in the initial phase due to the COVID-19 breakdown in China and the country being the global supplier. Many countries handled it well with no shortages and open logistics channels. However, many countries suffered a lot as the governments needed to prepare [12]. Poor and underdeveloped counties suffered the most as the rich countries stockpiled the goods in advance. Developing countries, such as India, imposed strict lockdowns with doorstep delivery of essential goods for needy people. Hence, panic-buying behavior was there; however, it was mitigated by the end of the first year [1,12,13].

4.1. Preventive Measures

In continuation of previous insight, preventive measures, especially those imposed by the governments, significantly influenced panic-buying behavior. During the initial outbreak of COVID-19, many governments imposed strict lockdowns and shutdowns to prevent the spread. Although they ensured the availability of goods, it gave a wrong signal about the scarcity of items. It led to stockpiling and hoarding [1,8,14]. Alternately, global lockdowns also adversely impacted supply chains, causing panic among consumers [15,16]. It was the perception, not the reality, that caused panic among many consumers.

4.2. Social and Online Influence

Another prominent finding from the study implied that exposure to numerous online and social media platforms hugely swung consumer behavior, triggering panic [5,8]. In turn, information overload and the pandemic’s perceived severity caused panic-buying behavior [1,5,14,17]. Frequent exposure to social media posts during the lockdowns and isolations triggered panic. Online searches peaked, and the overload of information (primarily wrong) created panic in the consumer mindset [18]. The impact was enormous as social media reach and influence increased exponentially in the last decade. It created the perception of a scarcity of goods and the severity of the pandemic in the isolated populace, causing a chain reaction.

4.3. Peer Influence

Another trigger of panic-buying behavior was peer influence [1]. Human beings are highly social [19], and peer interactions influence all aspects of consumption decisions, including during the pandemic. Zeng et al. [19] highlighted the importance of family, friends, and nearby buyers’ influence on consumers during the pandemic. The spread of anxiety and panic is imminent within closely-knit groups under the pressures of the pandemic. Consumers seek cues from known persons and are quickly influenced by peer behavior. Lockdowns and isolations forced the populace to rely more heavily on communicating with family members and chatting with peer groups in search of more information [12,17,18], and they often mirrored their choices based on emotions and fear rather than logic.

4.4. The China Effect

Another prominent reason was the country of origin. The global supply chain was dependent on China. It was the source country for many economies [5,6,20]. The COVID-19 pandemic started in China and slowly spread to other countries. China adopted a zero-tolerance policy later, creating panic in other countries that were dependent on it for supplies. It was a chain reaction afterward, and the global consumers panicked and started hoarding and stockpiling due to the uncertain future of the supply chain. China suffered a lot, and major manufacturing companies based out of China were the global suppliers of essential goods. 2022 seems to be on a recovery path after three global waves, although the news of another wave is disturbing.

5. Implications

The fundamental objective of this study was to explore the latest research trends regarding panic buying during the COVID-19 crisis. This study has provided theoretical advancements, as it included almost all the major studies, both empirical and conceptual. In addition, a collection of knowledge resources in the given domain is provided so academia and practitioners can gain from this piece. Numerous conceptual, theoretical, and empirical opportunities are provided by this work for future researchers in the domain of consumerism and pandemics. New theories and models can be devised that can provide a solution to this problem in future pandemics. The studies included in this bibliometric analysis discussed various antecedents and consequents. Primary antecedents, such as a sense of severity, a sense of uncertainty, and a sense of scarcity, were outlined in these studies. Simultaneously, various mediators and moderators along with control variables were also provided, e.g., social media influence, addiction, religious values, and morality and ethics. The most significant consequence of panic buying is the nature of future consumption. It can be either panic consumption (that leads to chaos) or sustainable consumption (that provides stability).

Sustainable Consumption Is the Answer

“Sustainable Consumption and Production (known as SCP) is about doing more and better with less. It is also about decoupling economic growth from environmental degradation, increasing resource efficiency, and promoting sustainable lifestyles” [21]. The current pandemic made SCP more relevant than ever. Almost all the studies concluded that sustainable consumption answers pandemics and the resultant shutdowns and lockdowns. Digital transformation and sustainable consumption are two critical takeaways from pandemic-related research. It can work as an antidote to the panic buying disease. Sustainable consumption has several dimensions: social, political, economic, environmental, technological, and ethical. The present study also found it crucial to control panic buying-related chaos in society, especially in future scenarios.

6. Recommendations

Section 3 and Section 4 provided a detailed analysis of the data and discussed the significant findings. Based on the same, the author tried to give a few recommendations, mostly borne out of the implications of the critical studies. First, governments must be futuristic in their policy decisions and be able to pre-empt the fallouts of their choices [1]. The negative consequences might lead to the perceived scarcity and severity of the pandemic, which leads to panic-buying behavior [12]. Hence, they must plan for the minimum adverse consequences of their policy decisions in future pandemics. Second, governments must make effective economic policy decisions during the pandemic and plan accordingly for the next few years [6]. The economic impact of a pandemic usually is severe in the succeeding years. Hence, the decisions and actions must be ambidextrous. They should be focused on both the present and the future. Third, existing business models must be relooked at, given the complexities of a pandemic and the panic-buying behavior caused by it [1,6]. Marketers must be flexible, adaptive, and futuristic with on-the-spot solutions to handle sudden demand fluctuations. The current pandemic helped everyone understand it, and the same must be executed before the next one knocks on the door. Fourth, supply chains must be robust and adaptive on the demand side. Another critical factor was the reliance on a single source for significant supplies. It should be decentralized and spread across the geographic regions to handle better pandemic-induced panic-buying behaviors [6,12].

Furthermore, the influence of online and social media had a great effect on panic-buying behavior. The regulatory bodies (if not available, must be created) should effectively control fake news and rumors [1,5,14,17]. It might be difficult in democratic setups due to freedom of expression clauses. However, adequate mechanisms must be implemented, especially during a pandemic. COVID-19 has proven the negative influences of social media on the general public and panic behavior, and it must be regulated or curbed by the authorities. Sixth, the authorities should promote ethical behavior in the citizens. A sense of guilt can do wonders against stockpiling or hoarding, reducing the shortage of items and the panic in other consumers [1,8]. Seventh, technological upgrades are required across industries to meet future challenges. The current settings could not handle the COVID-19 crisis, hence they must be upgraded [6]. Online delivery mechanisms with shorter and better schedules should be encouraged globally to reduce the perception of scarcity and severity, reducing panic. Finally, prevention is better than cure. The current crisis has taught us a lot, and all stakeholders must learn to behave appropriately and responsibly during a pandemic.