Business & IT

Peer-reviewed scientific journal · Czech Technical University in Prague

ISSN 1805-3777 (print)
ISSN 2570-7434 (online)

Business & IT · Vol. XIII(2) · 2023

Automotive Manufacturing Firms and Their Usage of Machine Learning to Drive Efficiency in Asia

Zikri Mohhamad Kuraishi

Journal
Business & IT, Vol. XIII(2), pp. 65–73
Year
2023
DOI
https://doi.org/10.14311/bit.2023.02.07

Abstract

Objective - Rapid innovation and globalization have generated large opportunities, and also choices in the marketplace for firms and customers. Naturally, competitive pressures have led to production and internationalization, leading to a significant increase in products. The post tries to identify the need for legitimate time business intelligence that contained supply chain analytics. Design/methodology/approach - The paper offers argument and analysis of the advantages, and also hurdles in BI. Outcomes - The newspaper concentrates on the importance of revisiting the conventional BI concept, which fuses and consolidates information of a business, to assist service oriented businesses and also search for retention and customer loyalty. Enhancing effectiveness and productivity of supply chain analytics dealing with a BI tactic is essential to a company's opportunity to reach the competitive advantage. Originality/value - This newspaper furthers understanding of the issues that involve the use of BI products in supply chains.

Keywords

Manufacturing, Automotive Industry, Profitability, Efficiency

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How to cite (APA)

Zikri Mohhamad Kuraishi (2023). Automotive Manufacturing Firms and Their Usage of Machine Learning to Drive Efficiency in Asia. Business & IT, Vol. XIII(2), pp. 65–73. https://doi.org/10.14311/bit.2023.02.07

Editorial information: Business & IT, ISSN 2570-7434, Creative Commons licence CC BY 4.0, published by CTU in Prague, 2023. https://bit.fsv.cvut.cz/