Predicting the drivers of behavioral intention to use mobile learning: A hybrid SEM-Neural Networks approach

作者：

Highlights：

• We examined the determinants of mobile learning using a hybrid SEM–ANN approach.

• TAM has significant influence on the intention to adopt.

• Psychological science constructs are non-significant with the intention to adopt.

• The moderating effect of age and gender are non-significant in this study.

• The model is able to explain 53.4% of the variance with effect size of 0.399.

摘要

•We examined the determinants of mobile learning using a hybrid SEM–ANN approach.•TAM has significant influence on the intention to adopt.•Psychological science constructs are non-significant with the intention to adopt.•The moderating effect of age and gender are non-significant in this study.•The model is able to explain 53.4% of the variance with effect size of 0.399.

论文关键词：Mobile learning (m-learning),Technology Acceptance Model (TAM),Structural Equation Modeling (SEM),Artificial Neural Networks (ANN),User behavior

论文评审过程：Available online 20 April 2014.

论文官网地址：https://doi.org/10.1016/j.chb.2014.03.052