Here are a few of the data stories that caught my attention this week.
Uber’s dynamic pricing
Many passengers using the luxury car service Uber on New Year’s Eve suffered from sticker shock when they saw that a hefty surcharge had been added to their bills — a charge ranging from 3 to more than 6 times the regular cost of an Uber fare. Some patrons took to Twitter to complain about the pricing, and Uber responded with several blog posts and Quora answers, trying to explain the startup’s usage of “dynamic pricing.”
The idea, writes Uber engineer Dom Anthony Narducci, is that:
… when our utilization is approaching too high of levels to continue to provide low ETA’s and good dispatches, we raise prices to reduce demand and increase supply. On New Year’s Eve (and just after midnight), this system worked perfectly; demand was too high, so the price bumped up. Over and over and over and over again.
In other words, in order to maintain the service that Uber is known for — reliability — the company adjusted prices based on the supply and demand for transportation. And on New Year’s Eve, says Narducci, “As for how the prices got that high, at a super simplistic level, it was because things went right.”
TechCrunch contributor Semil Shah points to other examples of dynamic pricing, such as for airfares and hotels, and argues that we might see more of this in the future. “Starting now, consumers should also prepare to experience the underbelly of this phenomenon, a world where prices for goods and services that are in demand, either in quantity or at a certain time, aren’t the same price for each of us.”
But Reuters’ Felix Salmon argues that this sort of algorithmic and dynamic pricing might not work well for most customers. It isn’t simply that the prices for Uber car rides are high (they are always higher than a taxi anyway). He contends that the human brain really can’t — or perhaps doesn’t want to — handle this sort of complicated cost/benefit analysis for a decision like “should I take a cab or call Uber or just walk home.” As such, he calls Uber:
… a car service for computers, who always do their sums every time they have to make a calculation. Humans don’t work that way. And the way that Uber is currently priced, it’s always going to find itself in a cognitive zone of discomfort as far as its passengers are concerned.
Apache Hadoop reaches v1.0
The Apache Software Foundation announced that Apache Hadoop has reached v1.0, an indication that the big data tool has achieved a certain level of stability and enterprise-readiness.
V1.0 “reflects six years of development, production experience, extensive testing, and feedback from hundreds of knowledgeable users, data scientists, and systems engineers, bringing a highly stable, enterprise-ready release of the fastest-growing big data platform,” said the ASF in its announcement.
Proposed bill would repeal open access for federal-funded research
What’s the future for open data, open science, and open access in 2012? Hopefully, a bill introduced late last month isn’t a harbinger of what’s to come.
The Research Works Act (HR 3699) is a proposed piece of legislation that would repeal the open-access policy at the National Institutes of Health (NIH) and prohibit similar policies from being introduced at other federal agencies. HR 3699 has been referred to the Committee on Oversight and Government Reform.
The main section of the bill is quite short:
“No Federal agency may adopt, implement, maintain, continue, or otherwise engage in any policy, program, or other activity that
- causes, permits, or authorizes network dissemination of any private-sector research work without the prior consent of the publisher of such work; or
- requires that any actual or prospective author, or the employer of such an actual or prospective author, assent to network dissemination of a private-sector research work.”
The bill would prohibit the NIH and other federal agencies from requiring that grant recipients publish in open-access journals.
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