Net and configurational effects of determinants on cloud computing adoption by SMEs under cloud promotion policy using PLS-SEM and fsQCA

卷:8

Article

关键词: QUALITATIVE COMPARATIVE-ANALYSIS;    AUTONOMOUS VEHICLES;    EMPIRICAL-ANALYSIS;    COMPLEXITY THEORY;    ENTERPRISES SMES;    SUCCESS FACTORS;    SAAS ADOPTION;    INTENTION;    PERSPECTIVE;    INNOVATION;   

DOI  :  10.1016/j.jik.2023.100388

来源: SCIE

【 摘 要 】

A deeper understanding of cloud computing is required to accelerate its adoption and leverage its cost, performance, reliability, and security. However, information about the combined effect of factors influencing cloud computing adoption using traditional statistical methods is limited. Based on a literature review of firms' adoption of cloud computing, we identified 12 determinants to explore how antecedent factors influence cloud computing adoption by small and medium-sized enterprises (SMEs). We used symmetric and asymmetric techniques to analyze data from 203 Chinese SMEs. The partial least squares structural equation modeling (PLS-SEM) assessed the net impact of each antecedent, and the fuzzy-set qualitative comparative analysis (fsQCA) provided a supplementary analysis by highlighting the configurations of the causal conditions associated with cloud computing adoption. The PLS-SEM results show that security concerns, top management support, IT competence, competitive pressure, trading partner pressure, and provider support influence SMEs' decisions to adopt cloud computing. Interestingly, fsQCA provides a deeper understanding of the complex causality that PLS-SEM does not capture. That is, fsQCA revealed seven configurations resulting in high-level cloud computing adoption and eight causal paths leading to the negation of cloud computing adoption. These findings indicate that several conditions with no significant influence in PLS-SEM were adequate when combined with other conditions in the configurations. The results of the complementary analysis provide theoretical and practical insights.& COPY; 2023 The Author(s). Published by Elsevier Espana, S.L.U. on behalf of Journal of Innovation & Knowledge. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)