Cycling promotes a healthier lifestyle and alleviates traffic congestion and air pollution. The present study focuses on the dockless bike sharing system in Dublin, Ireland and identifies the socio-economic and built environment factors that affect the dwell time. The origin- destination and timestamp databases obtained from Bleeper Bike are used to estimate the dwell time. The data is analysed using Uber H3 hexagonal zones, and non-spatial and spatial regression models (both spatial lag and spatial error models) are developed. The spatial error model was found to provide a better fit to dwell time. The study identified that key factors such as the presence of public transport stations and car ownership impact dwell time significantly.