Institute of Transportation, MOTC

     The core idea of Mobility as a Service (MaaS) emphasizes on using instead of owning and integrating a one-stop service platform which includes multiple modes services to meet travel demand of seamless and accessible mobility and to achieve the goal of reducing private vehicle usage. MaaS has become an emerging topic in the field of transportation worldwide recently and become one of main deployment projects of ITS policy in Taiwan as well. Since 2016, Kaohsiung City has begun to implement the urban MaaS demonstration project-MeNGo. A type of monthly pass bundling with multiple modes services launched in 2018. The sales of MeNGo monthly pass increased remarkably in the early period, however, have been stationary for a while. It is necessary to explore how to change MeNGo portfolio and to promote MeNGo effectively.

      This Study aim at demonstrating detailed customer segmentations of MeNGo monthly pass by using big data analytics and cluster analysis methods. Having collected IPASS e-ticket data provided by MeNGo operation companies, raw data formats and their availability are verified by establishing a  database process including data formatting, data cleansing and data testing. Meanwhile, multiple databases are also accessed to interpolate missing data and to correct data errors.

       As to customer segmentation, a total of 14 characteristic variables in three dimensions (ticket expense, travel behavior, travel distance) are determined based on international use cases. Then, K- Means is used as the cluster analysis method to verify several significant segments through statistical tests. Finally, these customer segments are named by customer’s behavior of using MeNGo monthly pass. As a result, MeNGo customers can be divided into four adult groups and five student groups according to their identifications and usage characteristics: (1) Suburban adult-customer, (2) Bus only adult-customer, (3) Commuter adult-customer, (4) Random adult-customer, (5) Suburban student- customer, (6) Bus only student-customer, (7) Short trip student-customer, (8) Commuter student- customer and (9) Random student-customer.

        Global MaaS use cases and local culture are referred to propose a target customer strategy map for increasing sales of MeNGo monthly pass. The bundling adjustment strategies should be implemented as the forward action, and the public transportation service quality improvements are backup strategies for MeNGo operators in the future.