Cluster Analysis of Public Bike Sharing Systems for Categorization

• Main Authors: Tamás Mátrai, János Tóth
• Format: Article
• Language: English
• Published: MDPI AG 2020-07-01
• Series: Sustainability
• Subjects: public bike sharing; cluster analysis; categorization; data collection
• Online Access: https://www.mdpi.com/2071-1050/12/14/5501

The world population will reach 9.8 billion by 2050, with increased urbanization. Cycling is one of the fastest developing sustainable transport solutions. With the spread of public bike sharing (PBS) systems, it is very important to understand the differences between systems. This article focuses on the clustering of different bike sharing systems around the world. The lack of a comprehensive database about PBS systems in the world does not allow comparing or evaluating them. Therefore, the first step was to gather data about existing systems. The existing systems could be categorized by grouping criterions, and then typical models can be defined. Our assumption was that 90% of the systems could be classified into four clusters. We used clustering techniques and statistical analysis to create these clusters. However, our estimation proved to be too optimistic, therefore, we only used four distinct clusters (public, private, mixed, other) and the results were acceptable. The analysis of the different clusters and the identification of their common features is the next step of this line of research; however, some general characteristics of the proposed clusters are described. The result is a general method that could identify the type of a PBS system.