Transforming the Vocational Workforce: A Multi-Perspective Study on Fintech Adoption in Indonesia
DOI:
https://doi.org/10.12928/joves.v9i1.15082Keywords:
Fintech Adoption, Vocational Workface, Structural Equation, Modeling Digital Literacy, Technology Acceptance Indonesia, IFAMAbstract
The research fills a gap, in which we find that conventional technology adoption models such as TAM and UTAUT are not predicting vocational workers acceptance behaviour well (40-60%) and no prior work has extended these theories to be adapted generic model for skills worker. Methods: Sequential explanatory mixed-method design consisting of systematic literature review (301 studies), quantitative survey (n = 618 vocational workers in five Indonesian cities) and qualitative focus groups (n = 86). The model was also confirmed by means of Structural Equation Modeling (SEM) with the software AMOS 26.0. IFAM has a prediction accuracy of 84.5%, which is much higher than that in TAM (55%) and UTAUT (62%). Personal characteristics are found to be the strongest predictor of adoption (γ=0.684) with digital literacy emerging as its significant dimension (β=0.845). There is a significant mediator effect of User quality (β=0.745), and it has been cascading to the individual (β=0.682.), organizational (0.624)., process(β=0.594) and technology dimension((β=0.568). The model indicates acceptable validity indices (χ2/ df= 2.842, RMSEA =0.054; CFI =0.962; GFI = 0.924). to the best of our knowledge, his model is one of the only theoretically-based adoption model that has been empirically validated and included both vocational learning theories and technology acceptance models. The two-stage mediating process, synthesis of types of resistance and the hierarchical pathway effect are original theoretical contributions. The instructions in the VOCTECH-ADAPT model provide a well-defined path for implementers on how they should work when engaging with digital FI projects.
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