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Authors
Abstract(s)
The contemporary financial services sector is undergoing a profound digital transformation,
yet the success of Online Financial Services (OFS) is fundamentally contingent on
user acceptance. Adoption remains uneven, hindered by complex perceptual barriers,
including security concerns and gaps in financial literacy. Traditional adoption literature,
often reliant on aggregate models like the Technology Acceptance Model (TAM),
frequently commits the average user fallacy, obscuring the distinct perceptual profiles
that exist within the population. Furthermore, the precise nature of the ”Digital Divide”
remains contested, whether it is a generational barrier (Age) or a socio-economic one
(Education and Income). This dissertation addresses these gaps through a quantitative,
descriptive-analytic study. Employing a cross-sectional survey (N = 225), this research
integrates theories of TAM, UTAUT, and Diffusion of Innovations (DOI) with the critical,
domain-specific constructs of Perceived Risk and Trust. The analysis is conducted in three
phases: (1) a correlational analysis to map the perceptual structure, (2) non-parametric
group comparisons to examine demographic divides, and (3) a ”person-centric” hierarchical
cluster analysis to identify latent user profiles. The results yield three key findings.
First, Perceived Risk is found to be statistically ”decoupled” from the core ”Adoption
Core” (Usefulness, Ease of Use), suggesting it operates as a separate, latent factor for existing
users. Second, the analysis confirms the existence of two distinct divides: a ”Grey
Digital Divide,” where Age primarily impacts Perceived Ease of Use (PEOU), and a more
powerful ”Literacy Divide,” where Education and Income significantly predict Perceived
Usefulness (PU) and Facilitating Conditions. Third, the cluster analysis challenges the
”average user” model, identifying three distinct profiles: ”Favorable with Friction” (High
PU, but Low PEOU and High Risk), ”Pragmatic Skeptics” (High PEOU, but Low PU
and Low Trust), and ”Ease-Oriented & Autonomous” (classic utility-focused users). The
study’s primary contribution is the indication that membership in these profiles is significantly
predicted by Education, not by Age. This suggests the most significant barrier
to inclusive digital finance is shifting from a generational gap to a digital and financial
literacy gap. These findings imply that financial institutions should consider abandoning
a ”one-size-fits-all” strategy and instead deploy targeted design, trust-building, and
value-proposition interventions tailored to these distinct, education-driven user segments.
Description
Keywords
Fintech Technology Acceptance Model (TAM) Perceived Risk Trust Cluster Analysis