In China, auto sales rose sharply when Uber came to town. That should make you re-examine received wisdom about the sharing economy.
Considering its disruptive impact, the sharing economy makes suspiciously modest claims for itself, beginning with its very name. Companies such as Uber and Airbnb purport to provide platforms for sharing value from underutilized resources, such as cars that would otherwise be parked in a garage or empty guest rooms. But they also allow almost anyone to compete in industries (hospitality and transportation) that normally have a very high barrier to entry.
Consequently, societies are now debating whether the sharing economy is playing fair. Should these platforms be regarded–and regulated–the same as established players in their respective industries, or does their sharing-based business model grant them an exemption?
According to Brad Greenwood, professor of information systems and operations management at George Mason University School of Business, the public is still straining to come to grips with these complex questions. “People are casting the sharing economy as good or bad, either as a whole or citing individual companies. But that’s a horrifically unnuanced approach,” he says.
A sharper, less simplistic analysis would start by investigating the sharing economy’s foundational claim that all it’s doing is unlocking value from existing resources. Greenwood’s recent paper in Manufacturing & Service Operations Management (co-authored by Jing Gong of University of Virginia and Yiping Song of Fudan University) finds evidence contradicting the claim–at least as regards Uber. Greenwood’s research suggests that instead of merely putting dormant resources to good use, the sharing economy can incentivise people to act like entrepreneurs, investing in expensive equipment (in this case, new automobiles) needed to start up a business.
Greenwood and his collaborators used vehicle registration data from 14 major cities in China–the world’s largest market for new automobiles–to gauge the economic effects of Uber’s staged rollout spanning 2010-2015. In the three months following Uber’s introduction into a city district (or “prefecture-level city”, the Chinese government’s official term), new car registrations increased by an average of 11-12 percent within that district. Over the 12-month post-entry period, registrations kept on rising, apparently reflecting Uber’s network effects taking hold in the area.
Further, the researchers discovered that the post-Uber sales bump impacted mostly smaller, more fuel-efficient vehicles–the type that would appeal to an entrepreneurial Uber driver. As Greenwood observes, “People aren’t going out and buying a Chevy Silverado to drive for Uber. Fuel prices are your largest variable cost.” Also, the increased sales disproportionately derived from young and older adults, rather than buyers aged 35-44. This lines up with the notion that financially pressured age groups are more likely to drive for Uber.
All in all, Greenwood’s evidence bends away from the theory that ride-hailing apps cannibalize car sales by enabling the existing vehicle stock to absorb excess local demand. By extension, it possibly pokes holes in the claim that market disruption caused by the sharing economy is rooted in innovation, and not regulatory arbitrage.
Greenwood emphasizes that this is only one study with a limited timeframe. “It’s in China, and it starts with the short-term change in vehicle purchasing. So that’s kind of the scoping limitation of what we can say empirically.”
On the other hand, he references research by others indicating roughly similar economic effects at work in other contexts. “When Airbnb comes into a location, it actually drives down noise complaints, and the reason seems to be that more properties are unoccupied–they’re bought up by professional renters. This would also perhaps explain why Airbnb tends to drive up rents. Properties purchased for Airbnb are subtracted from the housing supply, which raises prices for tenants.”
Assuming some generalizability for his results, Greenwood sees a couple of ways in which they pertain to ongoing debates about the sharing economy. First, they may be germane to disputes over whether gig economy workers such as Uber drivers should be considered employees or independent contractors (the U.S. Department of Labor is taking a compromise position for now). “Employees bring IP and labor–that’s it,” Greenwood says. In Uber’s case, drivers are, in effect, investing in their own infrastructure which they own and operate, making the label “contractor” a potentially closer fit.
Second, Greenwood’s results could aid policymakers in levelling the playing field for incumbents and sharing-economy disruptors. To the extent that Uber drivers are seen to engage in regulatory arbitrage, the company’s invocation of innovation should lose potency as a charm against government oversight. “Policymakers should consider thoughtful changes to regulation of taxi and licensed livery services,” the paper states.
Understanding how ride-hailing apps impact auto purchases can also help policymakers start to weigh the pros and cons for public welfare. For example, in light of the unfavorable auto-loan terms available to low-income people, it is worth investigating whether driving for Uber is indeed a viable pathway out of economic distress.
What will the eventual effect of the sharing economy be on public welfare? “Anyone who says they know the answer to that question is either not thoughtful or is advocating a position,” Greenwood says.
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