Predicting m-commerce adoption determinants: A neural network approach

► Predictors of m-commerce adoption were examined in this research. ► The UTAUT model was extended by incorporating perceived value, trust, perceived enjoyment and personal innovativeness. ► Neural network was developed to examine the research model. ► Results showed that neural network can offer be...

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Veröffentlicht in:	Expert systems with applications Jg. 40; H. 2; S. 523 - 530
1. Verfasser:	Chong, Alain Yee-Loong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier Ltd 01.02.2013 Elsevier
Schlagworte:	Applied sciences Biological and medical sciences China Computer science; control theory; systems Computer systems and distributed systems. User interface Consumer behaviour Decision theory. Utility theory Decisions Determinants Exact sciences and technology Fundamental and applied biological sciences. Psychology Linear inference, regression M-commerce Mathematical models Mathematics Neural network Neural networks Nonlinearity Operational research and scientific management Operational research. Management science Probability and statistics Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Regression Regression analysis Sciences and techniques of general use Social interactions. Communication. Group processes Social psychology Software Statistics Technology adoption UTAUT Technology adoption Neural network UTAUT M-commerce Consumer behaviour Acceptance Information system Modeling Innovation Linear prediction Confidence Technology Network analysis Technology transfer Electronic trade Value analysis Social perception Regression analysis User profile Non linear model Unified theory Chinese Explosives Non linear effect Mobile computing
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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