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Sustainable Information System for Enhancing Virtual Company Resilience Through Machine Learning in Smart City Socio-Economic Scenarios

Authors :
Lipianina-Honcharenko Khrystyna
Komar Myroslav
Melnyk Nazar
Komarnytsky Roman
Source :
ECONOMICS, Vol 12, Iss 2, Pp 69-96 (2024)
Publication Year :
2024
Publisher :
Sciendo, 2024.

Abstract

This paper introduces an innovative framework for the management of virtual companies in smart urban environments, with an emphasis on socio-economic resilience facilitated by Sustainable Information Systems. The system aims to equip virtual enterprises in smart cities with tools for robust operations amid socio-economic challenges. Its effectiveness is evidenced by improvements in investment risk assessment, business process simulation, and HR project management, enhancing efficiency and foresight. A key feature is predictive analytics for crisis demand forecasting, enabling swift market adjustments and strategic inventory management. It also helps identify alternative clients and suppliers, ensuring business continuity. Integrating machine learning and augmented reality, the system supports automation and strategic decision-making, significantly benefiting the e-commerce sector by addressing fluctuating demand, supply chain issues, and market adaptations during crises. The Sustainable Information System for Virtual Company Management in Smart Cities offers crucial support for e-businesses facing these socio-economic challenges, facilitating their navigation through turbulent times. Its meticulously designed architecture and functionalities make it a powerful instrument for assisting virtual companies in crisis conditions, fostering their sustainable growth within the socio-economic framework of smart urban settings. Comparative studies with existing models underscore this system’s superior efficiency and holistic approach, highlighting its contribution to enhancing the operational efficiency of virtual companies by 95%, reducing the time needed for critical activities like investment risk analysis and business process simulation, and bolstering the socio-economic resilience of smart cities against crises

Details

Language :
English
ISSN :
23035013
Volume :
12
Issue :
2
Database :
Directory of Open Access Journals
Journal :
ECONOMICS
Publication Type :
Academic Journal
Accession number :
edsdoj.0938873a6bed4a979e44605e9f5ec632
Document Type :
article
Full Text :
https://doi.org/10.2478/eoik-2024-0022