Agent-based simulation model of panic buying behavior in urban public crisis events: A social network perspective

Fan, Ruguo; Yao, Qianyi; Chen, Rongkai; Qian, Rourou

doi:10.1016/j.scs.2023.105002

Cited by 9 publications

(1 citation statement)

References 115 publications

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“…Some other studies also look into disaster related social media content classification (Roy et al 2021) and behavior modeling (Sadri et al 2013(Sadri et al , 2014Fan et al 2023) . Although these studies observed spatial and temporal variation of user risk perception behavior, emphasizing on sentiment of the tweet contents in the case of a single hazard event, these solely focused on user behavior and ignored the efficiencies of transportation networks.…”

Section: Risk Perception and Crisis Communicationmentioning

confidence: 99%

Translating Risk Narratives in Socio-technical Systems into Infrastructure Utilization Metrics during Compounding Hazard Events

Kays,

Momin,

Muraleetharan

et al. 2024

Preprint

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Risk communication in times of disasters is complex, involving rapid and diverse communication in social networks (i.e., public and/or private agencies; residents) as well as limited mobilization capacity and operational constraints of physical infrastructure networks. Despite a growing literature on infrastructure interdependencies and co-dependent social-physical systems, an in-depth understanding of how risk communication in online social networks weighs into physical infrastructure networks during major disasters remains limited, let alone in compounding risk events. This study analyzes large-scale datasets of crisis mobility and activity-related social interactions and concerns available through social media (Twitter) for communities impacted by an ice storm in October 2020 in Oklahoma. Compounded by the COVID-19 pandemic, this aberrant ice storm caused significant traffic disruptions (among others) due to excessive ice accumulation. By using Twitter’s academic Application Programming Interface (API) that provides complete and unbiased data, geotagged tweets (~25.7K) were collected covering the entire state of Oklahoma. First, the study employes natural language processing techniques, such as topic modeling and Bidirectional Encoder Representations from Transformers (BERT) model to classify crisis narratives (e.g., tweets), and text quantification techniques to analyze them. Next, the geotagged quantified tweets are transformed into a weighting factor for the transportation infrastructure network by employing spatial analysis. Finally, using network analysis, this study develops an infrastructure risk map that integrates the co-located road network. The findings reveal that quantifying online social media content and communication patterns can highlight significant disruptions in critical infrastructure during compounding disaster events. By mapping the risks associated with road networks, the study provides emergency management agencies with valuable situational awareness, facilitating more efficient resource allocation and prioritization aimed at enhancing disaster response efforts.

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Section: Risk Perception and Crisis Communicationmentioning

confidence: 99%

Translating Risk Narratives in Socio-technical Systems into Infrastructure Utilization Metrics during Compounding Hazard Events

Kays,

Momin,

Muraleetharan

et al. 2024

Preprint

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Exploring the Coping Strategies of Bullying Targets in Organisations Through Abductive Reasoning: An Agent-Based Simulation Approach

Ho,

Campenni,

Manolchev

et al. 2024

J Bus Ethics

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Over recent decades, workplace bullying and other forms of ‘negative acts’ have become a phenomenon of global interest. Extant scholarship has recognized the negative effects, which escalating acts of verbal and physical aggression can have on individuals and the wider, ethical infrastructure of organisations. While previous studies have explored the antecedents of such negative acts and proposed various intervention and prevention strategies, there remains a critical need to examine the coping strategies employed by those targeted by bullying, particularly in instances where silence is the chosen response. In this pioneering study, we use primary data from two UK National Health Service trusts and agent-based social simulation, to determine whether it is possible to influence the coping strategies of bullying targets. Our findings suggest that perceived organisational support has a strong effect on changing bullying coping strategies, away from external (solicitors, Court of Law) and towards internal channels (colleagues, managers, etc.). We also find that TU membership can moderately influence a change in bullying coping strategies from doing nothing to taking actions. The article makes a conceptual contribution to the literature on coping strategies as a result of (un)ethical behaviour in organisations, offers methodological innovation and makes recommendations to organisational policymakers.

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How does the perception of informal green spaces in urban villages influence residents’ complaint Sentiments? a Machine learning analysis of Fuzhou City, China

Chen,

Yang,

et al. 2024

Ecological Indicators

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Agent-based simulation model of panic buying behavior in urban public crisis events: A social network perspective

Cited by 9 publications

References 115 publications

Translating Risk Narratives in Socio-technical Systems into Infrastructure Utilization Metrics during Compounding Hazard Events

Translating Risk Narratives in Socio-technical Systems into Infrastructure Utilization Metrics during Compounding Hazard Events

Exploring the Coping Strategies of Bullying Targets in Organisations Through Abductive Reasoning: An Agent-Based Simulation Approach

How does the perception of informal green spaces in urban villages influence residents’ complaint Sentiments? a Machine learning analysis of Fuzhou City, China

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