The impact of paid social Q&amp;A on panic buying and digital hoarding at the stage of coexistence with COVID-19: The moderating role of sensitivity to pain of payment

Wang, Yajuan; Ding, Austin Shijun; Xu, Chonghuan

doi:10.1016/j.ijdrr.2022.103472

Cited by 11 publications

(2 citation statements)

References 87 publications

(104 reference statements)

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“…Most scholars only focus on the reasons for the panic buying of physical products and only a very few have realized the reasons for panic buying and digital hoarding of virtual products such as paid social Q&A during the COVID-19 pandemic. Wang et al [12] found through their study using the SOBC (Surprise, Opportunity, Belongingness, and Control) framework model that online paid Q&A can create emotional resonance among platform users, thereby stimulating their willingness to pay and ultimately lead to digital hoarding and panic-buying behavior. From the above research, it can be seen that the causes of triggering buying frenzies include social media, dissemination of harmful information, public-panic buying, supplier hoarding for profit, and conformity bias, among others.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Agent Evolutionary Game Analysis of Group Panic Buying in China during the COVID-19 Pandemic

et al. 2023

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With the global outbreak of COVID-19, the panic-buying incidents triggered by the variants of the Omicron strain have severely affected the normal social order. This paper considers the complex interest game and interactive relationship among multiple subjects in the mass-panic buying event caused by rumors and constructs a three-party evolution game model of local government, rumor-monger, and public. The strategy-selection process of each subject based on evolutionary game theory is studied, and the strategy selection of three game subjects in different situations and related influencing factors are analyzed. Taking the example of the montmorillonite powder panic buying caused by the XBB virus strain rumor in China, the evolutionary game model constructed in this study is simulated and analyzed. The study shows that the evolutionary process of the mass panic-buying event is characterized by six stages: the initial stage; the outbreak stage; the spread stage; the climax stage; the relief stage; and the recovery stage. There are four stable points in the evolutionary game of the three game subjects, namely (no intervention, no rumor, no panic buying), (no intervention, rumor, no panic buying), (intervention, no rumor, no panic buying), and (intervention, rumor, no panic buying). The strategy of government intervention will be adjusted according to the strategy selection of the public and the rumor-monger. Under the mechanism of reward and punishment of the higher-level government, increasing the punishment and reward intensity of the higher-level government will promote the local government to intervene in the rumor-mongering event faster, but increasing the reward intensity has a more significant impact on the intervention behavior of the local government than punishment, and increasing punishment intensity has a more significant impact on the non-rumor-mongering behavior of the rumor-monger than reward. The parameters of social risk-bearing cost, risk transmission coefficient, rumor-mongering income and cost, and public drug purchase cost have different degrees of influence on the evolutionary behavior of game subjects. Therefore, this study provides new ideas for effectively responding to mass panic buying events in the context of public emergencies.

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Section: Literature Reviewmentioning

confidence: 99%

Multi-Agent Evolutionary Game Analysis of Group Panic Buying in China during the COVID-19 Pandemic

et al. 2023

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“…However, the rapid spread of information through online networks also brings about various challenges. Privacy breaches, exposure to false information, and the propagation of harmful rumors are among the negative impacts associated with this phenomenon [1][2][3][4][5][6]. Therefore, it is crucial to deeply explore different forms of information spreading.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Information Spreading Model for One-Time Retweet Information in Complex Networks

Zhao,

Han,

Bao

et al. 2024

Entropy

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In the realm of online social networks, the spreading of information is influenced by a complex interplay of factors. To explore the dynamics of one-time retweet information spreading, we propose a Susceptible–Infected–Completed (SIC) multi-information spreading model. This model captures how multiple pieces of information interact in online social networks by introducing inhibiting and enhancement factors. The SIC model considers the completed state, where nodes cease to spread a particular piece of information after transmitting it. It also takes into account the impact of past and present information received from neighboring nodes, dynamically calculating the probability of nodes spreading each piece of information at any given moment. To analyze the dynamics of multiple information pieces in various scenarios, such as mutual enhancement, partial competition, complete competition, and coexistence of competition and enhancement, we conduct experiments on BA scale-free networks and the Twitter network. Our findings reveal that competing information decreases the likelihood of its spread while cooperating information amplifies the spreading of mutually beneficial content. Furthermore, the strength of the enhancement factor between different information pieces determines their spread when competition and cooperation coexist. These insights offer a fresh perspective for understanding the patterns of information propagation in multiple contexts.

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Panic consumption under public health emergencies: The mediating role of risk perception

Peng,

Hadžić,

Danner

et al. 2024

J Public Health (Berl.)

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Aim The primary objective of this study was to examine and explain the public panic consumption model based on the stimulus–organism–response theory, during the peak time period of the COVID-19 pandemic in China. Subject and methods The research data were collected through the questionnaires adapted for the purpose of this survey, which included a total of 408 participants (33% female) from the global population. The stepwise regression analysis has been conducted. Results The results have shown that both physical social networks and online social networks have a significant positive impact on infection risk perception, but the impact of physical social networks has proved to be a better predictor. Infection information obtained from physical social networks affects conformity buying and uncontrolled self-medication if the perceived risk perception is higher. When it comes to the impact of risk perception on conformity buying, health change has a significant negative regulatory effect. In the impact of risk perception on the uncontrolled self-medication, health change has no significant regulatory effect. Conclusions During the recent epidemic states, it is noticeable that public panic consumption has aggravated the difficulty of emergency management. Especially when it comes to the management of medical materials and medicines. In order to tackle this challenge in the future, the trigger mechanisms behind panic consumption are revealed.

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The impact of paid social Q&A on panic buying and digital hoarding at the stage of coexistence with COVID-19: The moderating role of sensitivity to pain of payment

Cited by 11 publications

References 87 publications

Multi-Agent Evolutionary Game Analysis of Group Panic Buying in China during the COVID-19 Pandemic

Multi-Agent Evolutionary Game Analysis of Group Panic Buying in China during the COVID-19 Pandemic

A Multi-Information Spreading Model for One-Time Retweet Information in Complex Networks

Panic consumption under public health emergencies: The mediating role of risk perception

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