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Application of BP neural network in evaluating e-business performance for service industry

机译:BP神经网络在服务业电子商务绩效评估中的应用

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摘要

The BP neural network model has a convergence and self-adaptability. Based on BP neural network algorithms, we establish the prediction system of e-business performance for Chinese service industry. According to our former studies, the e-business performance is measured by process performance of customer relationship management, financial performance and competitive performance. In this BP neural network model, the inputs in this study are the data of e-business performance measured by a five-point Likert scale, and the expected outputs of training neural network come from cluster analysis. Then, we take 14 indicators of e-business performance as inputs, and the level of e-business performance as outputs. The results show that the evaluation system is reliable and accurate; it can be used for evaluating enterprise performance effectively.
机译:BP神经网络模型具有收敛性和自适应性。基于BP神经网络算法,建立了中国服务业电子商务绩效预测系统。根据我们以前的研究,电子商务绩效是通过客户关系管理流程绩效,财务绩效和竞争绩效来衡量的。在这个BP神经网络模型中,本研究的输入是通过五点李克特量表测得的电子商务绩效数据,而训练神经网络的预期输出则来自聚类分析。然后,我们以14个电子商务绩效指标作为输入,并以电子商务绩效水平作为输出。结果表明,该评价系统是可靠,准确的。它可用于有效评估企业绩效。

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