Predicting trust in online advertising with an SEM-artificial neural network approach
作者：
Highlights：
• A nonlinear ADTRUST and Trust Building Model was integrated to predict trust.
• Age, gender, education and hours spent were incorporated as the control variables.
• A 10-fold cross-validated SEM-ANN analysis with the FFBP algorithm was applied.
• Reliability, website quality, willingness, reputation & hours spent are significant.
• 76.74% of the variance of trust in online advertising were explained by the model.
摘要
•A nonlinear ADTRUST and Trust Building Model was integrated to predict trust.•Age, gender, education and hours spent were incorporated as the control variables.•A 10-fold cross-validated SEM-ANN analysis with the FFBP algorithm was applied.•Reliability, website quality, willingness, reputation & hours spent are significant.•76.74% of the variance of trust in online advertising were explained by the model.
论文关键词：Consumer trust,Online advertising,Trust building model,ADTRUST,Artificial neural network
论文评审过程：Received 23 March 2020, Revised 21 May 2020, Accepted 4 August 2020, Available online 8 August 2020, Version of Record 10 October 2020.
论文官网地址：https://doi.org/10.1016/j.eswa.2020.113849
