Adoption of Technology-Based Training: Food Safety Among the Micro Scale Enterprises
Year: 2026
Type: conference-paper
Study design: Observational Study
Abstract: The escalating concern over food safety necessitates the effective adoption of advanced technological solutions, like blockchain-based traceability systems, which promise enhanced transparency and accountability across the supply chain. Despite this importance, food safety incidents persist, highlighting a gap in understanding the factors driving technology adoption, training effectiveness, and actual sustained use in this high-stakes domain. This study addresses this gap by utilizing the Unified Theory of Acceptance and Use of Technology (UTAUT) and Structural Equation Modeling (SEM) to investigate the factors influencing technology adoption in food safety management. A descriptive correlational research design was employed, using purposive sampling and a 4-point Likert scale questionnaire on a sample of 100 individuals in Micro scale enterprise, with data analyzed using JASP software. Key findings revealed significant counter-intuitive relationships with behavioral intention: performance expectancy had a significant negative effect, while effort expectancy had a significant positive effect, suggesting user skepticism towards oversimplified technologies and a preference for rigorous systems. Crucially, the model showed extremely low explanatory power for perceived quality of training and actual use, and behavioral intention did not significantly translate to actual use. These results imply that the standard UTAUT model is inadequate for this context, where intention fails to translate to action. The study strongly recommends refining the model by incorporating context-specific constructs like training content relevance and organizational sanctions/rewards for future research. Practical implications center on providing highly contextualized, hands-on training and investigating practical barriers to sustained usage beyond mere intention.
Institution: City of Malabon University
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7202287516