Abstract
Recent years we have witnessed the rapid growth of social commerce in China, but many users are not willing to trust and use social commerce. So improving consumers’ trust and purchase intention has become a crucial factor in the success of social commerce. Business factors, environment factors and social factors including twelve secondary indexes build up a social commerce trust evaluation model. Questionnaires are handed out to collect twelve secondary indexes scores as input of BP neural network and composite score of trust as output. Model simulation shows that both training samples and test samples have low level of average error and standard deviation, which certify that the model has good stability and it is a good method for evaluating social commerce trust.
Cite
CITATION STYLE
Chen, L., & Wang, R. (2016). A Trust Evaluation Model for Social Commerce Based on BP Neural Network. Journal of Data Analysis and Information Processing, 04(04), 147–158. https://doi.org/10.4236/jdaip.2016.44013
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