The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry

Zervas, Georgios; Proserpio, Davide Μ.; Byers, John W.

doi:10.2139/ssrn.2366898

Cited by 45 publications

(17 citation statements)

References 32 publications

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“…Actualmente, el incremento en el uso de dispositivos móviles ha permitido obtener datos suficientes en otros ámbitos y extender este tipo de estudios también a ciudades de menor tamaño -entre 50 y 100 mil habitantes- (Morstatter et al, 2013;Leontidou et al, 2007;Lansley y Longley, 2016). También, el auge de otras redes sociales -como pueden ser Foursquare, Google Places o Pinterest-, ha permitido ampliar los temas de estudio (Martí, Serrano-Estrada y Nolasco-Cirugeda, 2017;De Vries et al, 2013;Byers, Proserpio y Zervas, 2016;Béjar et al, 2016; García-Palomares, Gutierrez y Mínguez, 2015).…”

Section: Los Datos Generados En Redes Sociales Como Fuente Para El Esunclassified

Los datos geolocalizados de las redes sociales en el estudio de cuestiones urbanas complejas: cinco temas, cinco redes

Ciriquián¹,

Nolasco‐Cirugeda²,

Serrano-Estrada³

2019

ACE: Architecture, City and Environment

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Geolocated data generated by social networks allow various kinds of urban-related issues to be addressed, broadening knowledge on the different dynamics that occur in the city. This study has a twofold objective: (1) to identify which data variables from five well known social networks-Foursquare, Instagram, Twitter, Google Places and Airbnb-offer potential insights on the study of specific urban phenomena; and, (2) to delve into five exemplary urban topics that can be tackled by analysing the data from these social networks. Methodology Social media are analysed and specific urban issues that can be assessed through their data variables are identified. Specifically, five themes that encompass several research issues are identified through the combination of different data variables. Conclusions Data generated in social networks used for urban study purposes provide a valuable opportunity to address issues such as: [1] the use and preference for certain activities and places; [2] the image and perception of urban spaces; [3] spatiotemporal patterns of people presence and urban space-use; [4] supply and demand of economic activity; and, [5] identification of areas of concentration and specialization in the city. Originality This up to date and easily accessible information provides a thorough picture of complex issues in relation to urban dynamics that, until recently, were not easily measurable and quantifiable. Thus, the interpretation of these data broadens knowledge on city dynamics that can be useful for decision-making processes in the planning and design of the city.

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Section: Los Datos Generados En Redes Sociales Como Fuente Para El Esunclassified

Los datos geolocalizados de las redes sociales en el estudio de cuestiones urbanas complejas: cinco temas, cinco redes

Ciriquián¹,

Nolasco‐Cirugeda²,

Serrano-Estrada³

2019

ACE: Architecture, City and Environment

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“…In addition to increasing the efficiency of the market, successful multisided platforms create and rely on network externalities which benefit both buyers, through lower fees and increased match quality, and sellers, through increased market size (Armstrong, 2006;Rochet & Tirole, 2004). As a result, in markets where platforms emerge, incumbent firms often face increased competition, or even displacement, while platform participants correspondingly benefit from increases in market efficiency (Byers, Proserpio, & Zervas, 2013;Chakravorti & Roson, 2005;Parker & Alstyne, 2005;Seamans & Zhu, 2014;Tucker & Zhang, 2010).…”

Section: Digital Multisided Platformsmentioning

confidence: 99%

Digital Multisided Platforms and Women's Health: An Empirical Analysis of Peer-to-Peer Lending

2019

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“…Website registration and listings are completely free of charge. Airbnb derives revenue from both guests and hosts for this service: guests pay a 9-12% service fee for each reservation they make, depending on the length of their stay, and hosts pay a 3% service fee to cover the cost of processing payments (Zervas et al, 2016).…”

Section: The Airbnb Casementioning

confidence: 99%

“…To reinforce this behaviour, Airbnb has built an online reputation system that enables and encourages participants to rate and review each completed stay. Guests use star ratings to rate features of their stay, while both guests and hosts are encouraged to post public reviews of each stay on the platform (Zervas et al, 2016).…”

Section: The Airbnb Casementioning

confidence: 99%

Tourism and the Sharing Economy. An Evidence from Airbnb Usage in Italy and Romania

Cesarani¹,

Nechita²

2017

Symphonya. Emerging Issues in Management

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Tourism in the era of the sharing economy adopts a model based on a global concept with a local practice. The traditional tourism offer is based on the attractiveness of a destination, expressed by a system of characteristics of the destination itself and a range of services related to accommodation, transport and food. The tourism model of sharing economy, instead, is based on the development of shared services that stimulate the flows of tourists. Traditional destinations are then alongside new destinations that, thanks to some factors that drive the development of sharing economy platforms, attract tourists, change behaviours and modify competitive dynamics. The new paradigm of could be briefly described by the 4 Ts of sharing economy: Trust, Togetherness, Technology and Transformation.

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The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry

Cited by 45 publications

References 32 publications

Los datos geolocalizados de las redes sociales en el estudio de cuestiones urbanas complejas: cinco temas, cinco redes

Los datos geolocalizados de las redes sociales en el estudio de cuestiones urbanas complejas: cinco temas, cinco redes

Digital Multisided Platforms and Women's Health: An Empirical Analysis of Peer-to-Peer Lending

Tourism and the Sharing Economy. An Evidence from Airbnb Usage in Italy and Romania

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