A hybrid SEM and ANN approach to predict the individual cloud computing adoption based on the UTAUT2

The Impact of Cloud Computing Adoption on Firm Performance Among SMEs in Palestine

“…Besides, the study's SEM finding shows that facilitating states, e.g., compatibility with the current system, ICT knowledge, and technology infrastructure, is the most significant determinant of CCA in Palestine, supporting that of earlier works (Alkhater et al, 2018;Tella et al, 2020;Song, 2022). Thus, SME owners/managers must pay the heaviest attention to building those facilitating states to get the highest advantage of CCA.…”

“…Another quantitative study by Skafi et al (2020) confirms that poor infrastructure negatively affects CCA among SMEs. Meanwhile, scholar Song (2022) finds FCLT as a significant predictor of CCA in ANN method but insignificant determinant in SEM. These mixed results make it attractive for scholars to conduct deeper research.…”

“…This study uses a machine learning method, i.e., Artificial Neural Network (ANN) to complement SEM in data analysis. ANN delivers greater accuracy than SEM Song, 2022). The usage of ANN method helps scholars to estimate the significance of the variables (Shahzad et al, 2020), and to verify and complete the SEM outcomes (Alhasnawi et al, 2023;Mustafa et al, 2023;).…”

“…Thus, to solve these shortcomings, scholars (Mustafa et al, 2023;Alhasnawi et al, 2023) use machine learning method, e.g., artificial neural networks (ANN) as the next phase of examination involving sole concealed tier. Methodically, unlike earlier publications employing a single-phase SEM (Gui et al, 2021;Lutfi, 2022;Shetty and Panda, 2022) which cannot predict the complexities influencing multidimensional decisionmakings, or using a single-phase ANN method (Shahzad et al, 2020), this study uses the integrated SEM-ANN, following the recommendation from Alhasnawi et al (2023) and Song (2022). Due to its deep learning capacity, the use of ANN construction using at least two hidden tiers may produce more accurate non-linear relations in the framework (Kalinić et al, 2021).…”

“…To answer the above research questions, this study uses a two-phase systematic method through combining SEM and machine learning framework that many academicians recommend for assessing technology adoption behaviors (Mustafa et al, 2023;Hamdan et al, 2022b;Song, 2022). The potency in SEM's path examination is used to answer QS1 and QS2, whereas the machine learning approach responds to QS3.…”