摘要
本文在相关理论分析的基础上,从客户因素、互联网银行因素和社会因素等方面构建包括28个影响互联网银行接受度的指标体系,对我国的小微企业主、商业银行高管和个人客户发放调查问卷。利用人工神经网络模型对有效的1136组数据进行实证检验。结果表明,影响客户接受互联网银行的因素中账户安全是客户考虑的最重要因素,相对重要性为最高的18%;其次是客户对互联网银行优势的了解程度,相对重要性占16%;客户对互联网银行借款人风险的考量也是影响其是否接受互联网银行的重要因素,相对重要性占比为14%;客户对民间征信的态度也占了相对重要性的12%。而手机功能、辅助功能、制度、操作等指标相对不那么重要。各指标的作用方向表明,互联网银行的产品和服务越是安全、优势越明显、风险越低、征信越完全、风险偏好越高,那么客户就越倾向于接受互联网银行。相比之下,手机功能、辅助功能、制度、操作等指标的相对重要性较低。
This paper studies 28 indicators affecting the acceptance of Internet Banking in China including customer preference,Internet Banking factors,social factors and others. Questionnaires were handed out to small and micro entrepreneurs,commercial bank executives and bank customers.An Artificial Neural Network Model was performed on data comprising of more than 1136 groups.The results show that the attitude towards account security,understanding the advantages of Internet Banking,the evaluation of borrower＇s risk and the customer＇s attitude towards the credit information system are relatively important factors affecting the acceptance of Internet Banking. The impact direction of each indicator shows that customers are more likely to accept Internet Banking if it had better security,more advantages,lower Internet Banking customer risk and a more developed credit information and surveillance system. In contrast,indicators for mobile phone applications,auxiliary functions,systems and operations are of relatively less importance.
出处
《南京社会科学》
CSSCI
北大核心
2018年第2期27-35,共9页
Nanjing Journal of Social Sciences
关键词
互联网银行
客户接受度
人工神经网络
internet banking
customer acceptance
artificial neural network
