https://eipublication.com/index.php/eijmrms/issue/feed 2025-08-18T07:03:34+00:00 Jenny Michel eieditor@eipublication.com Open Journal Systems <p><strong>Crossref doi - 10.55640/eijmrms</strong></p> <p><strong>Frequency: 12 issues per Year (Monthly)</strong></p> <p><strong>Areas Covered: Multidisciplinary</strong></p> <p><strong>Last Submission:- 25th of Every Month</strong></p> https://eipublication.com/index.php/eijmrms/article/view/3286 2025-08-18T07:03:34+00:00 Niyozova Umida Tulkin kizi niyozova@eipublication.com

<p>The article examines the features and challenges in the development of transport and information and communication infrastructure at the regional level. The influence of geography, economic resources, and government policy factors is analyzed. Specific statistical data, examples of successful cases, and recommendations for the coordinated development of two infrastructure areas for sustainable regional growth are provided.</p>

2025-08-17T00:00:00+00:00 Copyright (c) 2025 Niyozova Umida Tulkin kizi https://eipublication.com/index.php/eijmrms/article/view/3248 2025-07-31T21:04:19+00:00 Dr. Sofia Martinez sofia@eipublication.com Noura Al-Mansoori noura@eipublication.com

<p>The equitable and efficient allocation of scarce healthcare resources is a critical societal challenge, particularly evident during public health crises such as the COVID-19 pandemic. Traditional, ad-hoc rationing methods often lack transparency, consistency, and the capacity to systematically integrate complex ethical considerations. This article proposes an integrated framework for healthcare resource allocation that leverages advanced algorithmic mechanism design and matching theory. Drawing from established principles of efficiency (e.g., Pareto optimality, utilitarianism) and various facets of fairness (e.g., priority, non-discrimination, diversity, local justice), the framework employs algorithms such as bipartite matching and multi-attribute optimization to systematically distribute resources. Key results include enhanced transparency, optimized resource utilization, and the systematic integration of multiple, potentially competing, ethical values, all while maintaining computational feasibility and scalability. The discussion addresses the advantages over traditional methods, highlights the critical need for bias mitigation and public engagement in algorithmic design, and outlines limitations and areas for future research. The article concludes with policy implications, advocating for investment in research, clear ethical guidelines, robust data infrastructure, and interdisciplinary collaboration to ensure that algorithmic allocation systems are technically sound, ethically robust, and practically implementable for serving the collective good.</p>

2025-08-01T00:00:00+00:00 Copyright (c) 2025 Dr. Sofia Martinez, Noura Al-Mansoori