Year: 2026
Type: article
Study design: Observational Study
Abstract: The acceleration of Industry 4.0 has compelled enterprises to integrate automation, cyber-physical systems, and analytics into everyday operations. Despite rapid digitalization, the effectiveness of these initiatives depends largely on the human capacity to accept and collaborate with machines. This study applies the Technology Acceptance Model (TAM) to examine behavioral and organizational factors influencing automation adoption among 900 professionals across manufacturing, logistics, and service sectors. Using descriptive-correlational design and partial least squares structural equation modeling (PLS-SEM), the study investigates how perceived usefulness (PU) and perceived ease of use (PEOU) shape attitude (ATT) and behavioral intention (BI). Findings reveal that PU strongly predicts ATT and BI, while PEOU enhances PU and positive attitude toward technology. The proposed Human–Machine Synergy Framework situates these constructs within a socio-technical context, showing that automation readiness in enterprises arises when human competence and institutional scaffolding evolve together. The study enriches local Industry 4.0 scholarship and provides actionable guidance for managers, policymakers, and educators promoting inclusive digital transformation.
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7155051663
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