The Relationship between Drivers of Artificial Intelligence and Willingness to Adopt Artificial Intelligence among Manufacturing Industries in Johor

Authors

  • Nor Kamariah Kamaruddin

Keywords:

Drivers , Artificial Intelligence

Abstract

Nowadays, the manufacturing industry’s adoption of artificial intelligence is still delayed and difficult. Due to the need of deep learning and the difficulty in understanding it, thus many nations including Malaysia are still having trouble in adopting artificial intelligence. Encourage public-private sector cooperation to advance the use of AI in industry by offering awards, money, and regulatory assistance are just a few ways that governments may encourage the adoption of AI and it may foster knowledge sharing, speed up the transfer of technology, and reduce barriers to AI adoption. The purpose of this research was to determine the relationship between Drivers of AI and willingness to adopt artificial intelligence among manufacturing industries in Johor. The study focuses on a population of 500 manufacturing industries located in Johor. To ensure a representative sample, the researcher employed the Krejcie and Morgan table, determining that a sample size of 217. This study used a quantitative method to collect data using questionnaires via Google Form. The data was analyzed using Statistical Package for the Social Sciences (SPSS) software version 27. The findings showed all the drivers of AI include AI technology advantage (r=0.431), supply chain collaboration(r=0.431) and environmental uncertainty(r=0.262) have a significant relationship between willingness to adopt AI.  This study aims to enhance awareness within the manufacturing industry regarding strategies for bolstering their competitive advantage through the adoption of Artificial Intelligence.

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Published

25-06-2024

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Article

How to Cite

Nor Kamariah Kamaruddin. (2024). The Relationship between Drivers of Artificial Intelligence and Willingness to Adopt Artificial Intelligence among Manufacturing Industries in Johor. Research in Management of Technology and Business, 5(1), 812-825. https://penerbit.uthm.edu.my/periodicals/index.php/rmtb/article/view/16109