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

Computers in Human Behavior

Volumn 36, Issue , 2014, Pages 198-213

  Tan, Garry Wei Han ^a   Ooi, Keng Boon ^b   Leong, Lai Ying ^a   Lin, Binshan ^c  

^a UNIVERSITI TUNKU ABDUL RAHMAN   (Malaysia)

^b Linton University College   (Malaysia)

^c LOUISIANA STATE UNIVERSITY   (United States)

Author keywords

Artificial Neural Networks (ANN); Mobile learning (m learning); Structural Equation Modeling (SEM); Technology Acceptance Model (TAM); User behavior

Indexed keywords

INFORMATION TECHNOLOGY; NEURAL NETWORKS; SURVEYS; BACKPROPAGATION; E-LEARNING; ECONOMIC AND SOCIAL EFFECTS; SENSITIVITY ANALYSIS;

ACADEMIC QUALIFICATION; EDUCATIONAL INSTITUTIONS; M-LEARNING; MULTI LAYER PERCEPTRON; PERSONAL INNOVATIVENESS; STRUCTURAL EQUATION MODELING; TECHNOLOGY ACCEPTANCE MODEL; USER BEHAVIORS; FEED-FORWARD BACK PROPAGATION;

BEHAVIORAL RESEARCH;

EID: 84899428011     PISSN: 07475632     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chb.2014.03.052     Document Type: Article

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