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Uber ‘stumbling upon’ behavioural economics

Uber’s head of economic research, Keith Chen, told NPR’s Shankar Vedantam during an episode of The Hidden Brain podcast that users of the service are willing to accept surge pricing increases of as much as 9.9 times if their smartphone’s battery is close to flat.

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This simple revelation last week created a bit of a media storm, even though Uber were at pains to reassure that they weren’t using this data to set their pricing. Uber have taken classical economic theory of supply and demand to a higher level than any other B2C business I can think of. This has been much to the consternation of many, even though time-based discriminatory pricing has been well established amongst transport providers for many years. What is interesting about this revelation however, is how it interacts with behavioural economics. In the classical model, battery life would never have been a factor that would be considered in pricing, but in behavioural economics it makes absolute sense that the potential anxiety of being left stranded without a working smartphone and no ride home would impact on the demand side of the equation.

Uber apparently didn’t set out to capture the “battery level” data, it just came with the data stream, and someone at Uber thought it might be interesting to explore that data. From this curiosity came insight. Curiosity and exploration is as important in data science as the science bit.

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