Abstract
One of the major differences between markets that follow a “sharing economy” paradigm and traditional two-sided markets is that the supply side in the sharing economy often includes individual nonprofessional decision makers, in addition to firms and professional agents. Using a data set of prices and availability of listings on Airbnb, we find that there exist substantial differences in the operational and financial performance of professional and nonprofessional hosts. In particular, properties managed by professional hosts earn 16.9% more in daily revenue, have 15.5% higher occupancy rates, and are 13.6% less likely to exit the market compared with properties owned by nonprofessional hosts, while controlling for property and market characteristics. We demonstrate that these performance differences between professionals and nonprofessionals can be partly explained by pricing inefficiencies. Specifically, we provide empirical evidence that nonprofessional hosts are less likely to offer different rates across stay dates based on the underlying demand patterns, such as those created by major holidays and conventions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Airbnb will soon be booking more rooms than the world’s largest hotel chains. Quartz. January 20, 2015.
- 2.
Airbnb in the city. New York State Office of General Attorney. October, 2014.
- 3.
We restrict our attention to properties offered as entire apartments or houses and exclude those properties where the hosts also reside, so that we focus on a relatively homogeneous group of hosts with similar levels of mobility.
- 4.
“Airbnb, New York State Spar Over Legality Of Rentals.” NPR. October 16, 2014.
- 5.
In Sect. 20.5, we focus on the subset of hosts who make their properties available more than four days per week (50% of the time). Because of the high availability of their properties, it is less likely that these hosts will cancel availability for other reasons. We do not find any qualitative differences in our results by focusing on this subsample.
- 6.
Ideally, we would like to use a fixed-effect model to control for a listing’s specific characteristics. However, since our independent variable of interest (i.e., whether a property is managed by a professional or a nonprofessional host) is time-invariant, including fixed effects in our model would absorb the effect of the variable of interest.
- 7.
We did not find a significant effect of average rating due to its lack of variation. Moreover, average rating is missing when there is no review available, which will limit the number of observations when included. Therefore, we decide to drop average rating in our analyses.
References
Anderson C, Xie X (2011) A choice-based dynamic programming approach for setting opaque prices. Prod Oper Manag 21(3):590–605
Armstrong M (2006) Competition in two-sided markets. RAND J Econ 37(3):668–691
Benjaafar S, Kong G, Li X, Courcoubetis C (2015) Modeling and analysis of collaborative consumption in peer-to-peer car sharing. Working paper, University of Minnesota
Bitran G, Caldentey R (2003) An overview of pricing models for revenue management. Manuf Serv Oper Manag 5(3):203–229
Bodea T, Ferguson M, Garrow L (2009) Choice-based revenue management: data from a major hotel chain. Manuf Serv Oper Manag 11(2):356–361
Buell RW, Kim T, Tsay CJ (2015) Creating reciprocal value through operational transparency. Harvard Business School Technology & Operations Mgt Unit working paper (14–115)
Cachon GP, Daniels KM, Lobel R (2015) The role of surge pricing on a service platform with self-scheduling capacity. Working paper
Cullen Z, Farronato C (2014) Outsourcing tasks online: matching supply and demand on peer-to-peer internet platforms. Working paper
David PA (1985) Clio and the economics of qwerty. Am Econ Rev 75:332–337
DellaVigna S (2009) Psychology and economics: evidence from the field. J Econ Lit 47(2):315–372
DellaVigna S, Pollet JM (2009) Investor inattention and Friday earnings announcements. J Financ 64(2):709–749
Edelman BG, Luca M, Svirsky D (2015) Racial discrimination in the sharing economy: evidence from a field experiment. Harvard Business School NOM Unit working paper (16–069)
Eisenmann T, Parker G, Van Alstyne MW (2006) Strategies for two-sided markets. Harv Bus Rev 84(10):92
Ellison G, Fudenberg D (2003) Knife-edge or plateau: when do market models tip? Q J Econ 118:1249–1278
Farrell J, Saloner G (1985) Standardization, compatibility, and innovation. RAND J Econ 16:70–83
Fradkin A (2014) Search frictions and the design of online marketplaces. NBER working paper
Frei F, Morriss A (2012) Uncommon service. Harvard Business Review Press, Boston
Gallego G, Van Ryzin G (1994) Optimal dynamic pricing of inventories with stochastic demand over finite horizons. Manag Sci 40(8):999–1020
Girotra K, Netessine S (2014) The risk-driven business model: four questions that will define your company. Harvard Business Press, Boston
Gurvich I, Lariviere M, Moreno A (2015) Operations in the on-demand economy: staffing services with self-scheduling capacity. Working paper, Northwestern University
Horton JJ, Zeckhauser RJ (2016) Owning, using and renting: some simple economics of the “sharing economy.” Technical report, National Bureau of Economic Research
Huang T, Allon G, Bassamboo A (2013) Bounded rationality in service systems. Manuf Serv Oper Manag 15(2):263–279
Jerath K, Netessine S, Veeraraghavan SK (2010) Revenue management with strategic customers: last-minute selling and opaque selling. Manag Sci 56(3):430–448
Kabra A, Belavina E, Girotra K (2015) Bike-share systems: accessibility and availability. Chicago Booth Research Paper (15-04)
Katz ML, Shapiro C (1985) Network externalities, competition, and compatibility. Am Econ Rev 75:424–440
Lederman R, Olivares M, Ryzin GV (2014) Identifying competitors in markets with fixed product offerings. Columbia Business School research paper no. 14-10
List JA (2003) Does market experience eliminate market anomalies? Q J Econ 118(1):41–72
List JA (2004) Neoclassical theory versus prospect theory: evidence from the marketplace. Econometrica 72(2):615–625
Malmendier U, Tate G (2008) Who makes acquisitions? CEO overconfidence and the market’s reaction. J Financ Econ 89(1):20–43
Mayer C (2001) Loss aversion and seller behavior: evidence from the housing market. Q J Econ 116:1233–1260
Netessine S, Shumsky RA (2005) Revenue management games: horizontal and vertical competition. Manag Sci 51(5):813–831
Parker GG, Van Alstyne MW (2005) Two-sided network effects: a theory of information product design. Manag Sci 51(10):1494–1504
Parker G, Van Alstyne M, Choudary S (2016) Platform revolution. W. W. Norton & Company, New York
Rosenbaum PR (2002) Observational studies. Springer, New York
Su X (2007) Intertemporal pricing with strategic customer behavior. Manag Sci 53(5):726–741
Su X (2008) Bounded rationality in newsvendor models. Manuf Serv Oper Manag 10(4):566–589
Talluri KT, Van Ryzin GJ (2006) The theory and practice of revenue management, vol 68. Springer, New York
Zervas G, Proserpio D, Byers J (2014) The rise of the sharing economy: estimating the impact of Airbnb on the hotel industry. Boston U School of Management research paper (2013-16)
Zhao W, Zheng YS (2000) Optimal dynamic pricing for perishable assets with nonhomogeneous demand. Manag Sci 46(3):375–388
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Li, J., Moreno, A., Zhang, D.J. (2019). Agent Pricing in the Sharing Economy: Evidence from Airbnb. 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_20
Download citation
DOI: https://doi.org/10.1007/978-3-030-01863-4_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-01862-7
Online ISBN: 978-3-030-01863-4
eBook Packages: Business and ManagementBusiness and Management (R0)