Learning in peer-to-peer markets: evidence from Airbnb


Autoria(s): Wu, Edson An An
Contribuinte(s)

Trindade, André Garcia de Oliveira

Gorno, Leandro

Caldieraro, Fabio

Data(s)

06/06/2016

06/06/2016

30/03/2016

Resumo

Peer-to-peer markets are highly uncertain environments due to the constant presence of shocks. As a consequence, sellers have to constantly adjust to these shocks. Dynamic Pricing is hard, especially for non-professional sellers. We study it in an accommodation rental marketplace, Airbnb. With scraped data from its website, we: 1) describe pricing patterns consistent with learning; 2) estimate a demand model and use it to simulate a dynamic pricing model. We simulate it under three scenarios: a) with learning; b) without learning; c) with full information. We have found that information is an important feature concerning rental markets. Furthermore, we have found that learning is important for hosts to improve their profits.

Identificador

http://hdl.handle.net/10438/16568

Idioma(s)

en_US

Palavras-Chave #Learning #Peer-to-peer markets #Airbnb #Arquitetura não-hierárquica (Rede de computador) #Anúncios - Indústria de hospitalidade - Inovações tecnológicas #Empresas novas
Tipo

Dissertation