商品敘述：

Set in March 2018, the case follows ride-sharing company Uber as it develops and launches a new product called Express POOL. This product offers a reduced price to riders willing to carpool, walk a short distance to/from their pick-up and drop-off points, and wait a few minutes before being matched to a driver. Two weeks after the launch of Express POOL in six U.S. cities, Uber''s product managers discover that if riders are made to wait five minutes to be matched to a driver-rather than the standard two minutes-rider cancellation rates increase, but Uber''s costs per ride are reduced. Together with data scientists, engineers, and product operations specialists, the product managers must decide whether to keep rider wait times at two minutes or increase wait times to five minutes in the six newly launched cities. The decision is complicated by the fact that Uber''s data science team normally places a five-week moratorium on changes to any new product, to allow robust data to be collected on its performance. This case is paired with a supplementary dataset from Uber (courseware no. 619-702). In advance of the class discussion, students can analyze the data and draw their own conclusions about the trade-offs of maintaining the standard wait times or increasing them.

涵蓋領域：

Customer satisfaction;Data science;Innovation;Operations strategy;Predictive analytics;Product development;Software development and engineering;Strategy formulation

相關資料：

, (9-619-702), 0p, by Chiara Farronato, Alan MacCormack, Sarah Mehta;
, (9-620-034), 46p, by Chiara Farronato, Sarah Mehta;
, (9-620-702), 0p, by Chiara Farronato, Alan MacCormack, Sarah Mehta

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