Analysis of Customer Satisfaction in Tourism Services Based on the Kano Model

Understanding customer needs is of great significance to enhance service quality and competitive advantage. However, for the tourism industry, it still unclear how mine improvement strategies from tourist-generated online reviews. This paper aims develop a data-driven approach conduct fine-grained dimension analysis satisfaction with services. First, this uses Latent Dirichlet Allocation explore key dimensions tourist Next, based on Chinese sentiment dictionary, tourists’ emotional attitudes towards each can be identified. Then, backpropagation neural network used measure complex relationship between orientations different their satisfaction. Finally, according improved Kano model, multi-dimensional attribute classification realized support strategic improvement. The proposed method empirically verified through real review dataset. results exhibit theoretical practical implications our method.