Identifying and understanding factors that influence the demand of ridesourcing market is essential for online hailing systems to improve the quality of service. This paper proposes a two-level growth model (GM) to identify the potential multi-level factors that may affect online ride-hailing service demand. By using the massive datasets from Didi Chuxing, Inc., including both Didi Express and Didi Taxi services, the order number fluctuations at different urban circle zones after the implementation of restrictions on ridesourcing in Shanghai, 2016 were analyzed, to assess the competition and mutual complementarities between Express and Taxi, the two major services provided by Didi Chuxing. The relative market share of Express was estimated to reveal the possible related spatial and temporal factors, which further demonstrates significant positive associations between ridesourcing demand and built environment factors, such as commercial/residential land use, public transport accessibility, as well as weather conditions. Metro service availability and rainy weather were found correlated with a relatively higher market share of Express service. Additionally, compared to the regular road transit service, the metro system was found to have a stronger correlation with the ridesourcing demand. Findings of this study may provide guidelines for urban planning and traffic operations, which in turn assists to achieve high-quality ridesourcing service for travellers.