A novel approach to study the relationship between Customer Satisfaction and service performances

The incremental efforts needed to study the relationship between Customer Satisfaction and service performances deserve more attention. This paper pays attention to Product KQIs (Key Quality Indicators), and proposes a novel approach for this study. By developing special processes to normalize data, select training samples, and determine the network model, Artificial Neural Network (ANN) is applied to the system successfully. Compared with other similar methods, the approach provides the variable weights of the Product KQIs, which can more effectively reflect their relative influences on Customer Satisfaction. The feasibility of our approach is validated through a service system based on OSS (Operational Support System) and BSS (Business Support System) architecture, which runs in the experimental environment of our campus network.