Predicting Increase in Demand for Public Buses in University Students Daily Life Needs: Case Study Based on a City in Japan

Abstract

Accessibility and economic sustainability of public bus services (PBS) have been in a continuous decline in Japan’s countryside. Rural cities also suffer from population transformation toward industrial centers experiencing rapid economic growth. In the present study, we reviewed the current demand status of PBS in Kitami, a rural city in Japan that hosts a national university. The investigation was performed by examining students’ daily lives using a survey to collect data representing a portion of the population. The objective was to predict the change in demand rate for PBS concerning the necessities of everyday life from the perspective of university students as potential users of PBS. Intuitively, decision-makers at every level display a distinct prejudice toward alternatives that intend to change the long-lasting status quo, hence in the question sequence, a two-step verification probe was used to reveal a person’s actual perceived opinion. Accordingly, the respondents’ initial demand rate for PBS was around 60%; however, this score increased to 71% in the secondary confirmation. Afterward, using machine learning-based prediction methods, we could predict this demand at over 90% of F-measure, with the most reliable and stable prediction method reaching 80% by other daily life indicators’ weight. Finally, we supplied thorough evidence for our approach’s usability by collecting and processing the data’s right set regarding this study’s objective. This method’s highlighted outcomes would help to reduce the local governments’ and relevant initiatives’ adaptability time to demands and improve decision-making flexibility.