Description
This study presents a comprehensive literature review examining the convergence of cybersecurity, ecommerce, supply chain management, and consumer engagement in the digital economy. Drawing on ten scholarly sources, this study explores key themes such as fraud detection using machine learning, cost behavior in e-commerce firms, the impact of Internet of Things (IoT) technologies in retail, and data science applications in cybersecurity. A central focus is the role of artificial intelligence (AI) and Genetic Algorithms (GA) in enhancing the accuracy of fraud detection systems, as well as the application of collaborative algorithms to identify fake reviews in online platforms. The research also analyzes how digital transformation influences cost structures, consumer trust, and cybersecurity resilience. Findings reveal that AI and machine learning are crucial in enhancing operational efficiency and safeguarding against emerging cyber threats. However, challenges such as data quality, model interpretability, and standardization persist. The study emphasizes the importance of adopting strategic, data-driven approaches and fostering interdisciplinary collaboration to address these issues. Implications for future research include the development of real-time fraud detection models, the ethical deployment of AI, and the enhancement of public-private cybersecurity partnerships. Ultimately, the research highlights the importance of intelligent systems and adaptive strategies in developing secure, efficient, and consumer-centric digital infrastructures in an increasingly interconnected world.
| Affiliation / University / Organization | Universidad Ana G. Méndez, Recinto de Gurabo |
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