Work

Understanding patterns and competitions of short‐ and long‐term rental markets: Evidence from London

Year: 2022

Type: article

Abstract: In this article, we compare short‐term rental (STR) and long‐term rental (LTR) price patterns in London using one of the most popular STR platforms, Airbnb, and the LTR platform, Zoopla property website. This research aims to enhance our understanding of both LTR and STR price patterns; as well as STR dynamics specifically, using predictive modeling to analyze how the patterns might evolve. We used the coefficient of variation and correlation analysis to examine the rental price patterns of both short‐ and long‐term markets. Then we developed a rent‐based gravity model to predict STR price pattern that is sensitive to the changes in visits to tourist destinations. Based on our analysis, we concluded that: (1) STR prices tend to be higher overall with an indication of higher volatility (less stability) compared to LTR; (2) there is statistical evidence supporting the arguments that STR and LTR markets are indeed in competition; and (3) the proposed gravity model provides a robust prediction of the STR pattern with a characteristic that higher‐priced short‐term properties are found to be geographically concentrated in the core city areas and those surrounding residential areas with easy access to popular tourist attractions.

Source: Transactions in GIS

DOI: 10.1111/tgis.12989

Authors: Zahratu Shabrina, Robin Morphet

Institutions: King's College London, University College London

Language: English

Topic: Sharing Economy and Platforms

Subfield: Marketing

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Sustainable cities and communities

Open Access status: hybrid

Estimated APC paid: $3,350