Logistics Flow Optimization for Advanced Management of the Crisis Situation

Analytical method to improve the decision-making criteria approach in managing digital social channels

This study explores the decision-making process involved in managing digital communities in the digital social channel ecosystem, specifically in the context of antagonistic digital communication and harmful content dissemination. The rise of digital communities in social media has changed the way people interact with each other, form communities, and participate in social activities. However, these interactions can also lead to conflicts, and the dissemination of harmful content can pose a risk to users' information security. This research proposes a method to mitigate these issues and optimize efficacy while minimizing potential hazards. The proposed method is based on the analysis of the information situation in the management of digital communities under conditions of complete uncertainty, antagonistic behaviour, and partial uncertainty. The study examines the decision-making process involved in antagonistic interaction among users of digital social channels. The methods proposed in this research were implemented to prevent the adverse consequences of community conflicts and the dissemination of potential risks to the security of users' information through prompt and efficacious decision-making. The proposed strategy optimizes efficacy through the implementation of the Wald criteria while minimizing potential hazards by adhering to the Savage criteria. Additionally, the Hurwitz criteria, which presents a balanced approach incorporating both the maximum and minimum criteria, was also employed. The methods were tested within the online community present on the social media platform, Facebook social networks, and the results demonstrate that the suggested technique improves the effectiveness and validity of managers' decisions in digital communities. The study also highlights the use of social networks and the virtual sphere as tools for hybrid warfare on the internet, which can be effective. Effective community management is necessary to mitigate the negative effects of online interactions, and the proposed method offers a valuable tool for managers to make informed decisions and prevent adverse consequences.

What Can COVID-19 Teach Us about Using AI in Pandemics?

The COVID-19 pandemic put significant strain on societies and their resources, with the healthcare system and workers being particularly affected. Artificial Intelligence (AI) offers the unique possibility of improving the response to a pandemic as it emerges and evolves. Here, we utilize the WHO framework of a pandemic evolution to analyze the various AI applications. Specifically, we analyzed AI from the perspective of all five domains of the WHO pandemic response. To effectively review the current scattered literature, we organized a sample of relevant literature from various professional and popular resources. The article concludes with a consideration of AI’s weaknesses as key factors affecting AI in future pandemic preparedness and response.