Factors affecting the perceived usefulness and intention to adopt artificial intelligence in manufacturing enterprises in the Southeast region of Vietnam

This study aims to explore “Factors affecting the perceived usefulness and intention to adopt artificial intelligence in manufacturing enterprises in the Southeast region of Vietnam.” Based on an integrated framework combining the Technology Acceptance Model (TAM) and the Technology–Organization–Environment (TOE) model, this study analyzes how organizational, technological, and environmental factors influence the adoption of artificial intelligence (AI). By employing a mixed-methods approach—comprising expert interviews and a quantitative survey of 435 manufacturing enterprises—the data were processed using SPSS 29.0 and AMOS 29.0 through several steps: reliability testing, Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM). The results reveal that five factors: government involvement (GI), perceived cost (PC), management support (MS), technical infrastructure (TI), and organizational culture (OC) positively influence perceived usefulness (PU). Meanwhile, competitive pressure (CP) and vendor partnership (VP) have a direct effect on the intention to adopt AI (AAI). Notably, perceived usefulness (PU) plays a significant mediating role and has a strong impact on the intention to adopt AI (AAI). These findings confirm the appropriateness of the TAM model in explaining AI acceptance behavior and provide managerial implications for business leaders and policymakers to promote AI adoption in manufacturing enterprises.

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Publication Details

Journal
Edelweiss Applied Science and Technology
Published
2025-06-11
DOI
https://doi.org/10.55214/25768484.v9i6.7973
Primary Topic
Digital Transformation in Industry
Type
article
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Factors affecting the perceived usefulness and intention to adopt artificial intelligence in manufacturing enterprises in the Southeast region of Vietnam

Pham Ngoc Khanh, Giao Thi Phuong Lan
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Edelweiss Applied Science and Technology
Digital Transformation in Industry
article

Factors affecting the perceived usefulness and intention to adopt artificial intelligence in manufacturing enterprises in the Southeast region of Vietnam

Pham Ngoc Khanh, Giao Thi Phuong Lan
article en

Abstract

This study aims to explore “Factors affecting the perceived usefulness and intention to adopt artificial intelligence in manufacturing enterprises in the Southeast region of Vietnam.” Based on an integrated framework combining the Technology Acceptance Model (TAM) and the Technology–Organization–Environment (TOE) model, this study analyzes how organizational, technological, and environmental factors influence the adoption of artificial intelligence (AI). By employing a mixed-methods approach—comprising expert interviews and a quantitative survey of 435 manufacturing enterprises—the data were processed using SPSS 29.0 and AMOS 29.0 through several steps: reliability testing, Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM). The results reveal that five factors: government involvement (GI), perceived cost (PC), management support (MS), technical infrastructure (TI), and organizational culture (OC) positively influence perceived usefulness (PU). Meanwhile, competitive pressure (CP) and vendor partnership (VP) have a direct effect on the intention to adopt AI (AAI). Notably, perceived usefulness (PU) plays a significant mediating role and has a strong impact on the intention to adopt AI (AAI). These findings confirm the appropriateness of the TAM model in explaining AI acceptance behavior and provide managerial implications for business leaders and policymakers to promote AI adoption in manufacturing enterprises.

Edelweiss Applied Science and TechnologyVol. 9(6)
Industrial University of Ho Chi Minh City (VN)
Partnerships for the goals
Openalex Percentile: Top 80%
Digital Transformation in Industry
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Factors affecting the perceived usefulness and intention to adopt artificial intelligence in manufacturing enterprises in the Southeast region of Vietnam — Pham Ngoc Khanh, Giao Thi Phuong Lan · Edelweiss Applied Science and Technology (2025) | TGRS Research Map | TGRS