Integration of Text Mining, Railqual, Kano Model, and Kansei Engineering for Train Service Excellence

Customer satisfaction is insufficient. It applies to all service industries including train services. Apart from weather conditions and safety issues, the challenges faced by train services are improving passenger comfort, sense of well-being, and emotional satisfaction. How to understand and satisfy the customer emotional needs is critical. Conventional methods such as survey and interview sometimes bring shortcomings. Hence, this study proposes the integrated approach of text mining, Railqual, Kano model, and Kansei Engineering (KE) in train services. Text mining is inserted in the KE methodology to refine the more representative Kansei words and service attributes experienced. The finding shows that there were 8 final Kansei words, namely, clean, extraordinary, comfortable, spacious, modern, friendly, cool, and cheap. Related to critical train service attributes, there were 3 items i.e., comfortable temperature in train, politeness of staff, and good quality meals served in train. Surely, the continuous scheduled air conditioner maintenance, training “dealing with people” for staff, and food supplier evaluation should be prioritized.