摘要
从卖家、网站、外部环境、网上信任等方面构建信任度评价指标体系;将影响网上信任的因素作为输入,将信任度综合得分作为输出,然后,运用BP神经网络技术,从买家的角度,构建一个C2C电子商务信任度评价模型。从实验来看,训练样本和检验样本的平均误差率和标准差均较低,模型的稳定性较好。因此,以此构建的C2C电子商务信任模型有很重要的价值,可以对信任度进行较为准确有效的评估。
First, the authors build the indicators according to the seller, the website and the external environment. Meanwhile, the factors affecting online trust are treated as input, and the trust composite score are treated as the output value. Then, the authors ap- plied BP neural network technology to build a trust evaluation model for C2C e-commerce from the perspective of the buyers. According to the experiment, the standard deviation and the average error rate of the training samples and test samples are low. Also, the stability of the model is well. Therefore, this C2C e-commerce trust model has very important value and can be used to assess trust accurately and effectively.
出处
《图书情报工作》
CSSCI
北大核心
2012年第10期131-137,共7页
Library and Information Service
基金
华中师范大学中央高校基本科研业务费项目"电子商务信任度测评体系研究"(项目编号:CCNU09A04003)研究成果之一
