Learning in peer-to-peer markets: evidence from Airbnb
Contribuinte(s) |
Trindade, André Garcia de Oliveira Gorno, Leandro Caldieraro, Fabio |
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Data(s) |
06/06/2016
06/06/2016
30/03/2016
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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 | |
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 |