A data-driven high-speed railway service quality optimisation model and its influencing factors for grouping research

High-speed railway service quality is a kind of experience and the degree of satisfaction of the experience when passengers consume passenger transport services, focusing on the process of service and the perceived satisfaction of passengers. This paper establishes the service quality evaluation index framework and system for high-speed railways by combining the concept of service quality for high-speed railways with the SERVQUAL model. The SERVQUAL evaluation model calculates the SQ score of each service factor to understand the change in service quality and combines the index weights and scores to calculate the recommendation degree of service quality optimisation of high-speed railways. The fsQCA method is introduced to construct the high-speed railway service quality influence model, and the data is obtained through a questionnaire to carry out a group analysis of the influence factors. The mean value of the evaluation score of high-speed railway service quality is -0.46, and the optimisation recommendation degree of the high-speed railway service quality optimisation indicators that need to be optimised is lower than -0.01. The coverage of the solutions in the group analysis is 0.872, which indicates that the five groupings are able to explain more than 87.2% of the high-speed railway service quality related cases in the sample. The data-driven service quality optimisation of high-speed railways needs to pay attention to the optimisation of basic service equipments and tools, and improve the dynamic response ability to better satisfy the needs of passengers in order to enhance their sense of access.