Research on the Inﬂuencing Factors of Panic Buying Under Public Health Emergencies –

. The COVID-19 outbreak in early 2020 not only had a signiﬁcant impact on China at the macro level, but also triggered changes in public psychology and irrational behavior at the individual level, one of the typical features of which was the panic buying behavior exhibited by residents during the outbreak. Based on Perceived Risk theory, emotion infection theory and information processing theory, this paper investigates the inﬂuence of herd mentality on panic buying behavior and the mediating role of Perceived Risk and information over-load, and validates the model by collecting data from 326 residents through a questionnaire. The results show that herding mentality, Perceived Risk, and information overload all have positive e ﬀ ects on panic buying; Perceived Risk and information overload partially mediate the e ﬀ ect between herding mentality and panic buying, and information overload carries more mediating e ﬀ ects. These results suggest that higher levels of herding, Perceived Risk, and information overload can intensify individuals’ panic buying and cause further irrational buying behavior. In response to the ﬁndings, this paper also proposes counter-measures to deal with panic buying from three aspects: individuals, media, and government


Introduction
The sudden outbreak of the COVID-19 epidemic in early 2020 had a great impact on politics and economy, as well as on the psychology and lives of individuals. The panic buying of "Chinese medicine Shuanghuanglian Oral Liquid", masks, and household goods that occurred during the outbreak also received widespread attention. Panic buying is similar to "snapping up" behavior, and is actually a manifestation of irrational consumption behavior, which usually occurs during public health emergencies. Such irrational behavior not only causes social panic, leading to market shortage and market regulation mechanism failure, but also tends to waste resources due to excessive hoarding, which further increases the burden of social epidemic prevention materials [1].
From the academic perspective, panic buying has received immense attention in various scholarly disciplines, such as consumer psychology [2], marketing [3], and economics [4]. During the COVID-19 outbreak, many scholars have also observed from the perspective of perceived risk [5][6][7][8][9], threat-related uncertainty [4,10], stress-relieving coping behaviors, social impacts [11], and the technological impact of social media [12][13][14]. To cope with these factors, panic buying may serve as a fear-limiting, anxious coping mechanism to face the unknown [15]. Nevertheless, there is still ambiguity in the operationalization and determinants of variables during the global pandemic that the current research framework is trying to explore.
In order to further investigate the influencing factors of panic buying behavior and then form effective management countermeasures and experiences, this study conducted data collection in the form of a questionnaire and conducted an empirical study based on this data to provide reference for the management and prediction of residents' consumption behavior in the event of future public health emergencies based on the experience of this epidemic. Meanwhile, to make up for the limitations and shortcomings of existing studies.

Herd Mentality and Panic Buying
Panic buying is actually built on the stress, anxiety, and overbuying that consumers experience during emergencies or uncertain times [9]. Panic buying is characterized by short-term contradictions between supply and demand in the market when there is an extreme shortage of goods, a surge in demand, and high product prices in the local market in the short term, and is characterized by group and suddenness, short duration, based on a specific situation, and rumors accompanied by speculation.
Many scholars have studied the causes of panic buying from the perspective of social psychology, and through the combing and analysis of literature, it is found that there are two main categories of factors influencing panic buying. First, external causes. For example, the influence of those around them, exaggerated and misleading media information; The second is the internal cause. Examples include an individual's fear of resource scarcity, a feeling of losing control of the environment, and inner fears and insecurities [11].
Panic buying is considered to be a "mass panic" behavior, which can be explained by the theory of emotional infection, which refers to exaggerated or excessive fear spread through "infection". Fear, individuals unconsciously imitate the expressions and behaviors of those they directly interact with in conversations, resulting in group activity [16]. When friends, relatives, or other people they do not know buy a lot of certain products, consumers may feel nervous, anxious, or even panic, and in order to cope with the panic buying of others, individuals tend to buy like crazy, which is also a manifestation of the "herd effect". The anxiety, panic and other negative emotions generated by the herd mentality will affect consumers' perceptions and increase their level of Perceived Risk, enhancing their Perceived Risks of the outside world. Therefore, the following hypothesis is proposed. Hypothesis 1. Herd mentality positively influences panic buying, the higher the level of herd mentality, the more likely consumers are to make panic purchases.
Hypothesis 2. Herd mentality positively influences Perceived Risk, the higher the level of herd mentality, the higher the level of perceived risk.

The Mediating Role of Perceived Risk
Perceived Risk theory suggests that when individuals perceive external risks, they proactively take various actions to reduce their risks. In fact, investigations undertaken by Clemens et al (2020) and Herman et al(2020) have shown the positive impact of perceived pandemic risk on consumers' product selection, and thus, their panic consumption will influenced by perceived risk [17,18].
Individuals experience insecurity and uncertainty when they perceive high levels of risk, when they prefer to bring certainty by controlling things around them, and buying as many items as possible to meet basic needs is a shortcut to cope with insecurity. Therefore, the present study, defines perceived risk as an individual's perception of exposure to potential uncertainties and health hazards amidst the COVID-19 pandemic [9]. In summary, this paper proposes the following hypothesis.
Hypothesis 3. Perceived Risk has a positive effect on panic buying, and the higher the level of consumers' Perceived Risk, the more inclined they are to make panic buying.
Perceived Risk is a subjective feeling and perception, which is influenced by psychological, social and even cultural factors. When consumers perceive risk and their tolerance is not able to cope with it, they perceive a high degree of uncertainty and risk in making decisions based on the information they obtain alone, so they reduce this risk by various means, such as aligning themselves with the behavior of others, i.e., developing herd mentality and herding behavior. In the study of perceived risk in online shopping, the mediating variable between website factors, product factors, consumer factors, and purchase intention is perceived risk. Accordingly, the following hypothesis is proposed in this paper.
Hypothesis 4. Perceived Risk plays a mediating role in herd mentality and panic buying.

The Mediating Role of Information Overload
Social media is an important channel for information delivery and crisis management tools when a crisis event occurs, and is highly responsive and widely distributed. However, compared to traditional media, social media is also very prone to overload, redundancy, and a wide variety of sources of information, which can cause information overload and lead to maladaptive cognitive, emotional, and behavioral consequences.
In addition to disseminating actual information, social media can also create exaggerated and misleading information, which has also which provokes stockpiling practices during the COVID-19 pandemic [19].
Based on information processing theory, when the amount of information exceeds the individual's cognitive processing capacity, it affects the efficiency of information processing and thus affects the individual's decision making, motivation, and attitude, triggering a series of negative emotions such as anxiety and anger, and the individual's perceived information overload is positively correlated with anxiety, depressive symptoms, and trait anger. Information redundancy and disinformation can make individuals' anxiety levels rise significantly in the course of media information [20]. Excessive attention to negative news reports can lead to the spread of fear and negative emotions, and media dissemination of news about shortages of essential goods further reinforces panic buying behavior [13]. In summary, we propose the following hypothesis.
Hypothesis 5. Information overload positively affects panic buying. The higher the level of information overload, the more consumers tend to make panic buying.
Hypothesis 6. Herd mentality can positively influence the level of information overload, the higher the level of consumer's herd mentality, the higher the level of information overload.
Information processing theory also suggests that individuals may feel anxious when they find that there is no way to find the desired information accurately and quickly. Information overload also acts on specific information behaviors by affecting individuals' attitudes, beliefs, and emotions, among others [21]. In addition, individuals use available health information to relate it to real or fictitious symptoms, resulting in negative emotions such as false self-diagnosis, exaggerated symptoms, and fears. Individuals, in turn, tend to reduce panic and anxiety by following the behavior of others, or reduce internal discomfort by consuming or purchasing. Accordingly, this paper proposes the hypothesis.
Hypothesis 7. Perceptual information overload plays a mediating role in herd mentality and panic buying.
Integrating the above analysis, this paper constructs the theoretical model as shown in figure 1.

Questionnaire Design
We used a questionnaire to test the hypotheses of the research model. The questionnaire was divided into two parts; the first part included six potential variables and the second part was basic personal information. In this paper, the questionnaire design was carried out according to the following steps. Firstly, the initial questionnaire scale was made on the basis of collecting relevant research literature at home and abroad. Since measurements of panic buying remain limited to date [22], the measurement of panic buying will integrate the research of Cham TH et al [9], Catherine Prentice et al [17], BentallI et al [23]; The herd psychological problem project originated from Jin Xiaotong [18]; The perceived risk problem project originated from Xi Juzhe [15]; and the information overload question item was derived from Chen Qiong [12]. Secondly, for the original measurement scale, this paper invited professionals to modify the wording of some questionnaire items while maintaining the original meaning; Thirdly, in order to ensure the validity of the questionnaire, small-scale tests were conducted on campus and interviews were conducted before the questionnaire was distributed on a large scale. The questionnaire was modified based on the results of the test and interview, and the final questionnaire was formed. For scale questions, all questions were evaluated on a Likert 5-point scale (1 was strongly disagreed, 5 was strongly agreed).
This questionnaire is based on the questionnaire star platform, and a 29-question questionnaire was designed using a questionnaire, which was collected from January 13 to April 20, 2022. In the questionnaire, respondents were asked to recall their real home status and purchases during the severe epidemic closure and control period to complete the questionnaire. In this study, the following two criteria were set for the screening of the questionnaire data to exclude the data that did not meet the criteria: firstly, the data that were filled out for less than the average time were excluded; secondly, test questions were set in the questionnaire to check whether the subjects were serious in checking and answering the questions,

Research Method
Compared with the traditional regression method, the structural equation model (SEM) is based on theoretical analysis to construct a preset model diagram and verify. Its advantage is to analyze the multi-causal relationship, so this method is selected to explore the influencing factors, effects and paths of residents' panic purchasing under public health emergencies. The measurement equation is as follows: The structural equations are as follows: Where x and y represent vectors of endogenous (information overload, perceived risk and panic buying) and exogenous (herd mentality) measurement variables, respectively; land x and land y represent the factor load matrix of the observed variables to the latent variables ξ and η , respectively; δ and ε represent the measurement error terms x and y , respectively; η and ξ represent endogenous (information overload, perceived risk and panic buying) and exogenous (herd psychology) latent variables, respectively. B is the relationship between endogenous latent variables; Γ is the influence of exogenous latent variables on endogenous latent variables; θ is the structural residual term.

Reliability and Validity Analysis
Amos 25.0 was used for data testing in this study. Validated factor analysis was performed to test the measurement model and reliability was measured by the loading reliability (CR) and the Cronbach's alpha value of the Cronbach's coefficient. The results are shown in table 5, where the CR values for all variables were greater than the recommended value of 0.7 and the Cronbach's alpha values for all variables were greater than the critical value of 0.7, indicating that the sample data had high internal consistency and good reliability. Validity is generally divided into convergent validity and discriminant validity. The average variance extracted (AVE) is usually used to test the convergent validity and discriminant validity of each latent variable. Convergent validity measures the degree of correlation between different question items of the same dimension. The AVE values of the constructs involved in this study are shown in table 2 . The AVE values of the study constructs ranged from 0.54 to 0.74, which were all greater than the minimum criterion of 0.5, indicating that the study constructs had good convergent validity.
Discriminant validity refers to the degree of variation between different conceptual question items, and when the square root of the AVE value of this variable is greater than the correlation coefficient between it and other latent variables, then the measurement model has good discriminant validity. The square root of the AVE values of each variable in this study and the correlation coefficients between this variable and other variable are shown in table 3 . The value on the diagonal line is the square root of the AVE value of each variable, and the correlation coefficient between each variable and other variables is shown at the bottom left of the diagonal line.
As can be seen from table 3 , the square root of the AVE value of each study construct is significantly greater than the correlation coefficient between it and the other latent variables, which indicates good discriminant validity among the study constructs.

Hypothesis Test
The  From the test results in table 5 , it can be seen that all hypotheses of this study passed the significance test. Specifically: residents' herding mentality has a positive influence on information overload, perceived risk and panic buying, so hypotheses H6, H2 and H1 are all valid; information overload and perceived risk have a significant positive influence on public panic buying behavior, so hypotheses H3 and H5 are all valid. In addition, mediating Overload. Note 2: "*", "**", and "***" mean significant at the level of 5%, 1%, and 0.1%, respectively.
effects suggest that information overload has the greatest impact on the public's panic buying behavior, with perceived risk ranking second.

Research Conclusions and Theoretical Contributions
This paper takes 326 residents as the research sample, constructs a path model of the influence of herd mentality on panic buying behavior, and analyzes it empirically, and finally draws the following conclusions and insights. Firstly, herd mentality directly and positively influences residents' panic buying behavior. In the case of environmental threats or external risks, individuals with stronger imitation ability, i.e., the stronger the herd mentality, are able to complete the reserve of possible scarce resources earlier, reduce the uncertainty of future environmental changes, enhance the sense of control over themselves as well as the environment, and the degree of perceived risk can help them understand the surrounding dangers earlier. Therefore, the higher the degree of herd mentality of individuals, the higher the degree of perceived risk, and the more likely they are to make panic purchases in the face of public health events.
Secondly, perceived risk and information overload play a mediating role in herd effect and panic purchasing, and information overload carries more mediating roles. This may be due to the fact that most of the information about the outbreak was disseminated through the Internet, which contains many news of varying authenticity. In addition, verbal transmission by friends, relatives, and other people also had a great influence on individuals, and these massive amounts of information further deepened individuals' fears. In this fearful mood, it is easy to be influenced by the emotions or behaviors of people around them, so when people around them appear to buy and hoard collectively, in order to alleviate this negative emotion, individuals tend to imitate others behaviors and reduce the uncertainty caused by fear through panic buying.
Finally, this study makes theoretical contributions from two aspects. On the one hand, it defines the constituent dimensions of panic buying and designs a measurement scale. In the current research on panic buying, the focus is mainly on extended discussions and case studies of the concept of panic buying, and there is a lack of quantitative research on the panic buying behavior of residents in public health events. Therefore, this study innovatively combines the existing research results to propose a panic buying measurement scale, which provides a specific measurement idea for subsequent panic buying research. On the other hand, the path model of the effect of herding psychology on panic buying is constructed and tested empirically. In this study, the three components of herding psychology, perceived risk and information overload are considered in a framework, and the path model of herding psychology on panic buying is constructed to systematically explain the influence of herding psychology on panic buying behavior.

Practical Implications
First of all, the public should remain rational, disbelieve rumors and not spread them, and adjust their emotions appropriately. Do not deliberately suppress or avoid negative emotions, which are easily counterproductive, but take the initiative to accept and adjust negative emotions.Besides, they should receive information from official channels and avoid believing and spreading false information. Furthermore, it is important to properly regulate one's own emotions and avoid dwelling on negative emotions to reduce the impact of the epidemic on one's life.
Second, the media should release accurate information, clarify rumors in a timely manner, and guide the public to communicate correctly. Fundamentally, panic consumption due to perceptions of market supply shortage has been the result of media communication, or rather, miscommunication [12,15,17]. Official media should disclose information quickly, accurately, and in a timely manner to clarify facts and reduce panic buying. Untimely and inappropriate information exchange is likely to make the public have negative associations. Strengthening information exchange can reduce public panic and avoid the generation of panic buying behavior.
Finally, the government should play the function of market organization and do a good job of monitoring public opinion. Faced with the epidemic the government should represent the interests of all parties, remain neutral, use social intermediary organizations such as industry associations to provide micro information about the industry, manage market order and protect public rights and interests, and effectively prevent panic buying. In addition, public opinion monitoring should be done. Do a good job of capturing, researching and reporting information on the fast-growing, heavily forwarded and continuously spreading content, filtering misinformation in real time, and making information public and clarifying through multiple channels.

Research Limitations and Prospects
There are still research shortcomings in this paper. Firstly, less consideration is given to individual traits and other factors. In this study, we mainly investigated individuals from the perspective of demographic variables, but ignored the influence of factors such as individual personality traits and personality characteristics in panic buying, which can be differentiated for different groups in the future. Secondly, recall bias was not considered. Respondents filled out the questionnaire questions in the form of recall, but with the passage of time, individuals' perceptions of their state and emotions during the quarantine period of the epidemic at that time would be weakened to some extent. In addition, since the vaccine has been developed and administered nationwide, the epidemic has been largely alleviated, and individuals' true perceptions of the epidemic will be diluted or even forgotten, which further increases the error of the questionnaire and causes the experimental research results to be contingent. Third, the change in individual perceptions over time was not considered. This study is a static questionnaire survey to collect data, and less consideration is given to portraying the process of Perceived Risk changes. The public's Perceived Risks tend to vary depending on the changes in their perceptions of the evolution of emergencies, so it is necessary to introduce the time factor into the quantitative study of perceived risks.