Not All Micro, Small, and Medium Enterprises Are Equal: A UTAUT-Based Multi-Group Analysis of AI Marketing Tool Adoption in the Philippines
DOI:
https://doi.org/10.65687/bjbs.v2i1.8Keywords:
AI marketing tools, MSME adoption, UTAUT, multi-group analysis, digital marketingAbstract
This study investigates whether the determinants of AI marketing tool adoption, as theorized by the Unified Theory of Acceptance and Use of Technology (UTAUT), operate uniformly across the heterogeneous Philippine micro, small, and medium enterprise (MSME) sector or whether they are systematically conditioned by firm size and industry sector. Prior technology adoption research has largely treated MSMEs as a homogeneous analytical unit, producing aggregate parameter estimates that obscure structurally important differences within this sector. To address this theoretical and empirical gap, a quantitative cross-sectional survey was administered to 387 MSME owner-managers across Metro Manila, Philippines, from January to March 2025. Data were analyzed using partial least squares structural equation modeling (PLS-SEM) via SmartPLS 4.0, with measurement invariance established through the Measurement Invariance of Composite Models (MICOM) procedure prior to multi-group analysis (MGA). All five UTAUT structural paths were confirmed in the pooled model (R² = .587 for behavioral intention; R² = .483 for actual use). MGA revealed that firm size significantly moderates the adoption model: performance expectancy exerted substantially stronger influence among medium enterprises (β = .445) than micro enterprises (β = .198), while social influence showed the inverse pattern, significantly more salient among micro enterprises (β = .276) than medium enterprises (β = .098). Industry sector partially moderated the model, with service-based MSMEs demonstrating a significantly stronger effort expectancy effect than product-based counterparts (Δβ = .089, p = .041), reflecting the heightened ease-of-use sensitivity in service contexts where AI-powered customer interaction tools are most operationally demanding. These findings challenge the parameter invariance assumption embedded in prior UTAUT-based adoption research and establish that a segmented approach to MSME AI adoption support, differentiated by firm size and industry type, is both theoretically warranted and empirically necessary.
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