The optimal multistage solutions suggest not to saturate any available station and to allocate a lower number of bikes compared to the case of constant capacity (see Table 12 ). Comparing Tables 14 and 15 , we observe that the optimal number of bikes to assign to each bike-station in the multistage setting are approximately 60 −80% of what we obtained in the two-stage setting for the case of Uniform, Normal and Log-normal distributions, while approximately 97.5% in the case of the Exponential distribution (in total 203 instead of 208). The results can be again justified by the fact the multistage model allows us for more flexibility having more stages and consequently more recourse decisions: Instead of assigning a large and costly (in terms of procurement cost) number of bikes at the beginning of the service, uncertain demand can be satisfied through renting and redirecting bikes over the day, and finally transshipping them over the night, without incurring in the risk of paying larger stock-out costs. The same considerations apply to the total costs of the multistage model, which is 50 −70% of the two-stage one for the former distributions, while higher for the Exponential one.