@article {10.3844/jcssp.2023.988.997,
article_type = {journal},
title = {Artificial Intelligence Metamodel for Controlling and Structuring the Crisis Management Domain},
author = {Alheadary, Wael G.},
volume = {19},
number = {8},
year = {2023},
month = {Jul},
pages = {988-997},
doi = {10.3844/jcssp.2023.988.997},
url = {https://thescipub.com/abstract/jcssp.2023.988.997},
abstract = {Crisis management is the process through which a company deals with a significant and unpredictable incident threatening the company and its stakeholders. It aims to reduce the risk or impact of a crisis event and ensure the organization can continue to operate and prosper in the aftermath of the event. Various studies have been conducted on how to best manage and control the crisis management domain. However, the literature still lacks a descriptive metamodel applicable to solving the problems the domain practitioners may face. Therefore, this study adopted an Artificial Intelligence (AI) concept to control, structure, and manage the crisis management domain, based on design science research. The developed AI metamodel consists of 14 common concepts that can assist the domain practitioners to structure and manage the crisis management domain. Furthermore, the trancing technique was used to verify the effectiveness and applicability of the developed metamodel to the real-world problems of crisis management. The AI metamodel developed in this study can assist domain users in addressing crisis events and improvising decision-making processes. It incorporates real-time data from various sources to provide situational awareness for decision-makers and identifies relevant tactical plans to address crises.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}