Abstract: It is difficult for the existing research methods to describe the nonlinear relationship and influence path among the users’ multiple perception constructs during the product usage. This may lead that the user perception model is not real and accurate enough. Therefore, a new method combining structural equation model (SEM) with artificial neural network (ANN) is proposed for user perception modeling. Firstly, based on the results of SEM analysis, main factors that influence user perception and the causal relationship between user perception constructs are identified; Then, the result of SEM analysis is converted to the topology of the ANN model, so that a structured artificial neural network model for user perception is established, in order to get the connection weights between the network nodes the BP (back propagation) algorithm is used to train the model; Finally, the validity of the proposed method is demonstrated by a case study of smart phone user perception modeling, the results show that the SEM-ANN model with good goodness of fit and interpretability can more accurately and quantitatively express the relationship between user perception constructs and the factors that influence user perception constructs.

Key words: product design; user perception; user experience; structural equation model; BP neural network; smart phone