More Empirical Analyses Needed to Examine the Impact of the Sharing Economy

The sharing economy has been attracting much attention. The usual practice in the conventional rental services market has been for owners to rent out their assets entirely. Today, however, they can utilize their assets at certain times and earn income at other times by renting them out on a short term basis. For instance, Airbnb, a U.S.-based online accommodation marketplace operator that connects room and home lenders and renters, and Uber Technologies Inc., another U.S.-based online transportation network company that provides services using owner-driven cars, have been growing rapidly.

Meanwhile, full-fledged efforts to analyze the sharing economy—whether theoretically or empirically—have just begun in the past couple of years. In this article, I would like to introduce some of the early attempts.

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"Peer-to-peer (P2P)," rather than the "sharing economy," is the term used in economics. P2P originally emerged as a term referring to a type of networking architecture in which workstations communicate with one another on an equal footing. In the context of this article, it means connecting individuals for transactions.

Such an arena for personal asset utilization business is called a "P2P rental marketplace" or "P2P platform." This can be defined as a type of two-sided market, exemplified by credit card payment processing services that provide a platform for transactions between various shops and buyers. The larger the number of participants there are on both sides (i.e., shops and credit card holders), the greater are the benefits. The presence of such network externalities is one reason behind the explosive development of P2P.

Rental markets are nothing new. Up until recently, however, the scope of rental service providers has been limited to businesses. What are the background factors that have enabled individuals to provide such services?

To begin with, in the case where individuals rent out their unused homes and cars, both supply and demand for such rental services occur at a specific time and space. Matching such supply and demand is extremely difficult and involves exorbitant search costs.

Usually, individuals do not have sufficient financial resources to foot the bill for the search costs. They also lack various other management resources needed to provide rental services, including hard resources such as marketing and payment systems as well as soft resources such as trust and reputation.

Thus, the sharing of durable goods and property among individuals was typically limited to cases in which owners rented out their rarely used expensive assets, such as a vacation home, to their acquaintances or relatives on a long-term basis and free of charge.

However, things are quite different today as search and monitoring costs have been lowered dramatically as a result of the development of information and communications technology (ICT) and, most importantly, the penetration of smartphones equipped with Internet connection, global positioning system (GPS) technology, and a high-definition camera. For instance, the GPS capabilities of smartphones, with which both drivers and passengers can check the actual distance travelled, are playing a critical role in Uber's business model, and so are high-definition cameras that provide precise information on the features and quality of vacant rooms available for rent on Airbnb.

Furthermore, the problem of insufficient resources has been largely addressed. Platform operators provide physical resources by taking advantage of economies of scale (as exemplified by credit card companies' payment systems), while reputations, evaluations, and recommendations—widely seen in electronic commerce sites such as the one operated by eBay Inc.—together serve as a mechanism for keeping players better informed of the reputation of those on the other side of transactions. All of this works to prevent players on both sides of the transactions from engaging in opportunistic behavior (e.g., seeking self-interest by deceiving or preying on the weakness of others). Needless to say, we need to keep in mind that, as shown in recent research findings, P2P evaluation tends to produce overrated grades because disappointed users do not bother to evaluate.

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In what follows, I would like to consider challenges for P2P rental markets by looking at their impact from the following two perspectives: 1) impact on employment and 2) impact on the relevant existing industries.

In a 2015 paper, Princeton University Professor Alan Krueger et al. identified the characteristics of Uber's driver-partners based on a web survey conducted in 2014 to which a total of 601 driver-partners from 20 market areas in the United States responded. The survey found that Uber's driver-partners are younger, highly educated, and more likely to identify their race as white, compared to average taxi drivers and chauffeurs in the United States. Most of them had a job prior to partnering with Uber, and many have continued in their jobs after partnering with Uber.

Uber driver-partners work fewer hours per week, with roughly half of them working 15 hours or less per week, whereas 35% of taxi drivers and chauffeurs work 50 hours or more (see Table). Notably, Uber driver-partners' earnings per hour are fairly stable regardless of the number of hours worked and higher than those for taxi drivers and chauffeurs.

As such, Uber offers fairly flexible work opportunities, allowing driver-partners to earn a decent amount of money efficiently by using spare time while continuing without compromising their primary job. Such flexibility, together with its driver-partner rating system and sharing of driver-partners' reputations with potential customers, are the factors that attract relatively competent individuals.

Although it is disputable whether Uber's driver-partners can be defined as workers, the fact that Uber enables driver-partners to work in a self-controlled manner deserves attention.

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From the viewpoint of regulating P2P rental markets, it is important to identify their impact on the relevant existing industries. In a 2015 paper, Boston University Assistant Professor Georgios Zervas et al. analyzed the impact of Airbnb on the short-term accommodation market and conventional hotels in the state of Texas.

They found that a 10% increase in the size of the Airbnb market translates into a 0.39% decrease in conventional hotel revenue. In certain municipalities where the number of Airbnb listings has grown rapidly, such as the capital city of Austin, conventional hotel revenue has dropped by 8% to 10%. The entry of Airbnb has also resulted in a slight decrease in hotel room occupancy rates and a significant decrease in room charges. Thus, conventional hotel users also benefit from the entry of Airbnb. Zervas et al. showed that Airbnb's ability to respond flexibly to seasonal fluctuations in demand has been particularly effective in suppressing the surge in conventional hotel room charges during peak demand periods.

Another notable point is that Airbnb's impact varies across different types of hotels. Typically, amenities provided by Airbnb properties are limited compared to those available at conventional hotels. Thus, hotels in the high-end market segment—i.e., high grade hotels, large-scale chain hotels, and those capable of accommodating business needs such as holding major conferences—are found to be less vulnerable to the impact of Airbnb. This means that conventional hotels should be able to compete, differentiate their services, and secure their positions in the market, instead of simply waiting to be defeated and ousted from the market by the new breed of players.

When a new breed of competitors enters the market, the most likely reaction of incumbent players is to rush to protect themselves by putting up vehement opposition and/or lobbying for overly burdensome regulations under the name of protecting consumers. Such is the case not only in Japan but also in the United States and Europe. In the United States, however, different states have different sets of laws and regulations, resulting in varying degrees of Airbnb penetration across states which effectively provide testing grounds for trials and errors. In Japan, we should utilize national strategic special zones as testing grounds for such new business models and relevant regulations to explore the optimal level of regulatory control.

>> Original text in Japanese

* Translated by RIETI.