Cloud computing adoption in education-oriented SMES: From technological conditions to readiness

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Type of the article: Research Article

Abstract
Cloud computing has become an important infrastructure for digital transformation, yet its adoption remains uneven among education-oriented small and medium-sized enterprises (SMEs), particularly in developing countries. This study examines how technological factors influence cloud computing adoption among education-oriented SMEs, with particular emphasis on the mediating role of organizational technology readiness. A structured online questionnaire survey was conducted with 117 legally registered education-oriented SMEs in Vietnam, including private training centers, EdTech firms, private schools, corporate training providers, and other private education service providers. These firms were selected because they directly provide educational or training services and represent key private-sector users or prospective users of cloud-based solutions. Data were collected from August to October 2025 from one designated key informant in each firm and analyzed using partial least squares structural equation modeling (PLS-SEM). The model explains 59.2% of the variance in organizational technology readiness and 57.5% of the variance in cloud computing adoption. Experience with technology positively affects readiness (β = 0.300, t = 4.236, p < 0.001) and adoption (β = 0.366, t = 5.040, p < 0.001), whereas perceived privacy and security risk negatively affect readiness (β = –0.407, t = 7.342, p < 0.001) and adoption (β = –0.318, t = 4.999, p < 0.001). Technology compatibility and technology knowledge influence adoption indirectly through organizational technology readiness. The findings indicate that readiness is a key organizational mechanism through which technological conditions are translated into cloud adoption decisions in education-oriented SMEs.

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    • Figure 1. Proposed research model
    • Figure 2. Measurement model assessment
    • Table 1. Sample and respondent profile
    • Table 2. Outer loadings, construct reliability, and convergent validity
    • Table 3. Discriminant validity (HTMT criterion)
    • Table 4. VIF, R2, Q2, and SRMR
    • Table 5. Path coefficients, effect sizes, and hypotheses testing
    • Table 6. Mediation effects of technology readiness
    • Data curation
      Chinh Thu Vu
    • Formal Analysis
      Chinh Thu Vu, Huong Thi Lan Le
    • Resources
      Chinh Thu Vu
    • Software
      Chinh Thu Vu
    • Validation
      Chinh Thu Vu, Hai Ninh Nguyen
    • Visualization
      Chinh Thu Vu
    • Writing – original draft
      Chinh Thu Vu, Huong Thi Lan Le, Hai Ninh Nguyen
    • Writing – review & editing
      Chinh Thu Vu, Huong Thi Lan Le, Hai Ninh Nguyen
    • Conceptualization
      Huong Thi Lan Le, Hai Ninh Nguyen
    • Methodology
      Huong Thi Lan Le, Hai Ninh Nguyen
    • Project administration
      Huong Thi Lan Le, Hai Ninh Nguyen
    • Supervision
      Huong Thi Lan Le, Hai Ninh Nguyen