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

Autores/as

  • Camila Antuane Saavedra Mucha Universidad Peruana De Ciencias Aplicadas - (Pe), Perú
  • Jorge David Sanchez Torres Universidad Peruana De Ciencias Aplicadas - (Pe), Perú
  • Ariane Ledda Sandoval Pezo Universidad Peruana De Ciencias Aplicadas - (Pe), Perú
  • Maria Alejandra Santiago Tito Universidad Peruana De Ciencias Aplicadas - (Pe), Perú
  • Ariana Grace Vargas Ochoa Universidad Peruana De Ciencias Aplicadas - (Pe), Perú
  • Delia Mercedes Cerna Huarachi Universidad Peruana De Ciencias Aplicadas - (Pe), Perú

DOI:

https://doi.org/10.18687/LACCEI2025.1.1.764

Palabras clave:

Big Data, decision-making, automotive industry, batch processing, technologies.

Resumen

Abstract - 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. Keywords- Big Data, decision-making, automotive industry, batch processing, technologies.

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Publicado

2025-04-09

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Articles

Cómo citar

Saavedra Mucha, C. A., Sanchez Torres, J. D., Sandoval Pezo, A. L., Santiago Tito, M. A., Vargas Ochoa, A. G., & Cerna Huarachi, D. M. (2025). Big Data in operational decision making in the automotive industry in Asia period 2018 - 2023: literature review. LACCEI, 1(12). https://doi.org/10.18687/LACCEI2025.1.1.764

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