Implementation of artificial intelligence project, quality internal and external supply chain integration, responsiveness for operational performance in manufacturing

Tarigan, Zeplin Jiwa Husada and Maer, Maria Natalia Damayanti and Malelak, Mariana Ing and Basana, Sautma Ronni and Siagian, Hotlan and Nasir, Zarul Azhar bin (2025) Implementation of artificial intelligence project, quality internal and external supply chain integration, responsiveness for operational performance in manufacturing. [UNSPECIFIED]

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Abstract

This paper analyzes the effect of Artificial Intelligence (AI) implementation projects on the operational performance of manufacturing companies in Indonesia, considering the mediating role of quality internal integration, quality external integration, and supply chain responsiveness. This study uses a quantitative research approach, utilizing a survey method, with 109 manufacturing companies in Java and Bali that have adopted AI technology in their production processes. Data processing was carried out using the Partial Least Squares (PLS) approach. The results indicate that the AI implementation project has a significant impact on both internal quality integration and external quality integration but does not directly affect supply chain responsiveness or operational performance. Quality internal integration is proven to be a key variable that significantly affects quality external integration, supply chain responsiveness, and operational performance. Meanwhile, quality external integration has a significant effect on supply chain responsiveness but not on operational performance directly. Additionally, supply chain responsiveness has been proven to positively contribute to improving operational performance. The conceptual model developed in this study successfully demonstrates a multi-layered influence path from AI implementation project to operational performance through quality integration and supply chain responsiveness. This study highlights the importance of synergy between AI technology and internal and externally integrated quality management systems in achieving operational excellence in the manufacturing sector. These findings expand the theoretical understanding of the strategic role of AI in the context of supply chain and operational quality.

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