Analyzing and predicting the spatial penetration of Airbnb in U.S. cities
- Submitting institution
-
Middlesex University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1346
- Type
- D - Journal article
- DOI
-
10.1140/epjds/s13688-018-0156-6
- Title of journal
- EPJ Data Science
- Article number
- 31
- First page
- 1
- Volume
- 7
- Issue
- 1
- ISSN
- 2193-1127
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2018
- URL
-
http://eprints.mdx.ac.uk/25516/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 12
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- In the hospitality industry, Airbnb is accused of not being properly regulated. Unfortunately, there is little quantitative evidence upon which to base any legislation. To support evidence-based policy making, we study and model the relationship between Airbnb’s penetration in a variety of cities and each city’s geographic, demographic, and socio-economic characteristics. We find that all analysed cities exhibit the same pattern of Airbnb adoption. This work is significant because the results’ consistency across the analysed cities suggests that our model could be applied to a city that has not been previously analysed and plan data-driven interventions.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -