Current Status and Demand Patterns of Shared Bicycles in Jersey City

This paper, using New Jersey as a case study, examines the spatial allocation issues of shared bicycles. Utilizing data from New Jersey City for the months of January to July 2023 and employing Python scientific computing libraries, we conducted kernel density analysis to generate visualizations and analyze demand patterns in the selected New Jersey shared bicycle data. Three key findings emerged from our research, categorized as geographical demand, temporal trends, and cross-regional cycling. Regarding the geographical demand, it was evident that the demand for shared bicycles in the city center exceeded that at the city's outskirts, potentially linked to urban planning within the city. The temporal trends, showed a steady increase in bicycle rides to New York from January to July, with the peak demand occurring during the summer months. This aligns with existing research and common knowledge, as riders tend to prefer cycling in more comfortable weather conditions, which are prevalent in the summer. The phenomenon of cross-regional cycling is particularly intriguing, the destination points were often in New York. The significance of this phenomenon lies in the potential resource shortage within the shared bicycle system if a large number of bicycles are ridden in New Jersey but left in New York for extended periods. This issue could result in spatial allocation challenges and may also incur substantial costs for bicycle redistribution and management by the government. Therefore, this paper presents recommendations and suggestions for coordinating the allocation of shared bicycles between New Jersey and New York City.