Big Data in operational decision making in the automotive industry in Asia period 2018 - 2023: literature review

Antuane Saavedra Mucha C.; David Sanchez Torres J.; Ledda Sandoval Pezo A.; Alejandra Santiago Tito M.; Grace Vargas Ochoa A.; Mercedes Cerna Huarachi D.; del Pilar Napa Alva R. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2025) · DOI: 10.18687/laccei2025.1.1.764

Resumen

The present article examines the influence of Big Data on operational decision-making in the Asian automotive industry from 2018 to 2023. In a context where digitalization has transformed business management, Big Data has become essential for real-time data processing, enhancing operational efficiency and responsiveness to market demands. This qualitative study, using the PRISMA methodology, focuses on analyzing the impact of technologies like batch processing, streaming processing, and NoSQL databases in decision-making across countries such as China, South Korea, and India. Through a comprehensive literature review, it highlights how these technologies have strengthened the industry's competitiveness in the region.

Instituciones: Universidad Peruana de Ciencias Aplicadas