基于SEM和神经网络的移动社交电商用户隐私信息披露意愿研究

Research on the Prediction of Privacy Information Disclosure Intention of Mobile Social Ecommerce Users

在移动社交电商情境中,用户的交互方式发生改变,个人隐私信息安全问题凸显,上述变化将会对用户的隐私信息披露意愿产生重要影响。为了探究移动社交电商用户隐私信息披露意愿的影响因素,本文基于S-O-R理论建立结构方程模型,旨在探究影响用户隐私信息披露意愿的影响因素及其作用机理。结果表明隐私政策有效性、隐私设置有效性、信息交互、情感交互等因素均正向显著影响用户隐私信息披露意愿。在此基础上,基于平台特征和用户感知收益构建了GA-BP神经网络预测模型,并针对不同预测结果提出具体应对措施。最终,文章从隐私信息安全保障和平台个性化服务等方面提出促进移动社交电商平台可持续发展的建议。

In the mobile social e-commerce context,the user's interaction mode has changed,and the security of personal privacy and information has come to the fore,and these changes will have an important impact on the user's willingness to disclose private information.In order to explore the influencing factors of users'willingness to disclose private information in the mobile social e-commerce context,this paper establishes a structural equation model based on the S-O-R theory,which includes eight variables:effectiveness of privacy policy,effectiveness of privacy settings,information interaction,emotional interaction,personalization,privacy concerns,perceived benefits,and willingness to disclose private information,with the aim of exploring the influencing factors and their role in influencing users'willingness to disclose private information.The results show that:(1)the effectiveness of privacy policy,the effectiveness of privacy settings,information interaction,emotional interaction,and personalization all positively and significantly affect users'willingness to disclose private information;(2)the effectiveness of privacy policy,the effectiveness of privacy settings,and emotional interaction all negatively and significantly affect privacy concerns;and the effectiveness of privacy settings,information interaction,emotional interaction,and personalization all positively and significantly affect perceived benefits.On this basis,this paper constructs a GA-BP neural network based on platform characteristics and user perception,and proposes specific countermeasures for different prediction results.Ultimately,this paper puts forward feasible suggestions to enhance users'willingness to disclose private information in four aspects:increasing the platform's privacy protection,improving the platform's personalized service construction,reducing the risk of privacy leakage,and reasonably applying the disclosure willingness prediction model.