The Platformization of Student Housing and the Rise of Mid‐Term Rentals. The Case of Uniplaces in Lisbon.
Published In: Tijdschrift voor Economische en Sociale Geografie (Journal of Economic & Social Geography), 2023, v. 114, n. 5. P. 431 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Cocola‐Gant, Agustín; Malet Calvo, Daniel 3 of 3
Abstract
The most common approach to student housing has been articulated by studentification literature. Furthermore, authors have highlighted how student demand attracts institutional investors to develop Purpose‐Built Student Accommodation (PBSA). In this paper, we complement these approaches with a conceptualization of how digital platforms have restructured the supply of student rooms in houses of multiple occupation. Relying on business and software understandings of platforms, we first explore the case of Uniplaces in Lisbon, a platform that has imitated the Airbnb model and today is present in more than 130 cities in various countries. Second, we depict Uniplaces within a landscape of mid‐term rental platforms that cater for different profiles of mobile populations, who stay in destinations for a short‐ or mid‐term period of time. We conclude with a discussion about the potential of this market to further advance processes of transnational gentrification and weaken the position of tenants. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Tijdschrift voor Economische en Sociale Geografie (Journal of Economic & Social Geography). 2023/12, Vol. 114, Issue 5, p431
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2023
- ISSN:0040-747X
- DOI:10.1111/tesg.12560
- Accession Number:173988340
- Copyright Statement:Copyright of Tijdschrift voor Economische en Sociale Geografie (Journal of Economic & Social Geography) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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