Abstract
We describe an equilibrium model of peer-to-peer product sharing, or collaborative consumption, where individuals with varying usage levels make decisions about whether or not to own a homogenous product. Owners are able to generate income from renting their products to non-owners while non-owners are able to access these products through renting on as needed basis. We characterize equilibrium outcomes, including ownership and usage levels, consumer surplus, and social welfare. We compare each outcome in systems with and without collaborative consumption and examine the impact of various problem parameters. Our findings indicate that collaborative consumption can result in either lower or higher ownership and usage levels, with higher ownership and usage levels more likely when the cost of ownership is high. Our findings also indicate that consumers always benefit from collaborative consumption, with individuals who, in the absence of collaborative consumption, are indifferent between owning and not owning benefitting the most. We study both profit maximizing and social welfare maximizing platforms and compare equilibrium outcomes under both in terms of ownership, usage, and social welfare. We find that the difference in social welfare between the profit maximizing and social welfare maximizing platforms is relatively modest.
This chapter is based on the paper “Peer-to-Peer Product Sharing: Implications for Ownership, Usage and Social Welfare in the Sharing Economy”, Published Online: 16 May 2018 in Management Science, https://doi.org/10.1287/mnsc.2017.2970
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Notes
- 1.
The term sharing economy has been used to refer to businesses that enable the foregoing of ownership in favor of “on-demand” access. In several cases, this involves a single entity that owns the physical assets (e.g., Zipcar for short term car rentals). It also encompasses the peer-to-peer provisioning of services (e.g., Uber for transportation services, TaskRabbit for errands, and Postmates for small deliveries). For further discussion and additional examples, see Botsman and Rogers (2010), Malhotra and Van Alstyne (2014), Cusumano (2014), and Chase (2015).
- 2.
An article in the New York Times (2015) notes that “The average daytime speed of cars in Manhattan’s business districts has fallen to just under 8 miles per hour this year, from about 9.15 miles per hour in 2009. City officials say that car services like Uber and Lyft are partly to blame. So Mayor Bill de Blasio is proposing to cap their growth.” Note that, although the peer-to-peer product sharing we consider is different from the type of product sharing enabled by Uber (which requires the involvement of the owner as a service provider), the two share similarities in that they provide non-owners with access to a product without having to own it.
- 3.
A variety of pricing approaches are observed in practice. Some platforms allow owners to choose their own prices. Others (e.g., DriveMycar) determine the price. There are also cases where the approach is hybrid, with owners determining a minimum acceptable price but allowing the platform to adjust it higher (e.g., Turo), or with the platform suggesting a price (e.g., JustShareIt) but allowing owners to deviate. From conversations the authors had with several industry executives, there appears to be a push toward platform pricing, with several platforms investing in the development of sophisticated pricing engines to support owners.
- 4.
Under a servicization model, the firm can exert costly effort to improve certain characteristics of the product such as its energy efficiency during use or its durability. This could lower the corresponding operating costs, which in turn could result in higher usage. The phenomenon of higher efficiency leading to more usage is commonly referred to as the rebound effect. See Greening et al. [2000] for an overview and references. In our setting, the introduction of collaborative consumption can lead, under some conditions, to higher ownership because of the rental income owners derive from ownership.
- 5.
In a multi-server loss queueing system, customers arrive over time to receive service from a set of identical servers. A customer who does not find an available server upon arrival leaves the system without getting service. A customer who finds one or more available servers proceeds to receive service from one of these servers. Service takes a specified amount of time. Upon completion of service, the corresponding server becomes available. Both the interarrival and service times can be stochastic (see Cooper 1981, for additional details).
- 6.
For example, suppose the aggregate demand for renting per unit time is D(θ) = 1000 h and the aggregate supply for renting per unit time is S(θ) = 2000 h. If the average rental period is m = 5 h, then the arrival rate and the service capacity of the system are respectively λ(θ) = D(θ)∕m = 200 and μ(θ) = S(θ)∕m = 400 requests per unit time.
- 7.
An example of a not-for-profit platform is NeighborGoods, a peer-to-peer platform that facilitates the sharing of household goods. NeighborGoods allows owners to earn a rental fee but does not extract for itself a commission fee.
- 8.
This perhaps validates concerns expressed by the Singapore authorities that allowing peer-to-peer car sharing would increase car usage and road congestion and their initial decision to restrict peer-to-peer car rentals to evenings and weekends (Clifford Teo, CEO of iCarsclub, personal communication, 2015).
- 9.
Note that, in some cases, a platform could exert costly effort to reduce this cost. For example, when extra wear and tear is, in part, due to renters’ negligence, more effort could be invested in the vetting of would-be renters. Alternatively, the platform could provide more comprehensive insurance coverage or monitor more closely the usage behavior of a renter (such monitoring technology is already available for example in the case of cars).
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Benjaafar, S., Kong, G., Li, X., Courcoubetis, C. (2019). Peer-to-Peer Product Sharing. In: Hu, M. (eds) Sharing Economy. Springer Series in Supply Chain Management, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-030-01863-4_2
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