Property Classification of Vacation Rental Properties during Covid-19
This work provides insights for policymakers and researchers analyzing vacation rental markets during crises, though it is incremental in applying standard clustering methods to new data.
This study used K-means and K-medoids clustering on a dataset of over one million vacation rental properties to identify homogeneous groups and their characteristics during the Covid-19 pandemic, enhancing understanding of vacation rental evaluations.
This study advocates for employing clustering techniques to classify vacation rental properties active during the Covid pandemic to identify inherent patterns and behaviours. The dataset, a collaboration between the ESRC funded Consumer Data Research Centre (CDRC) and AirDNA, encompasses data for over a million properties and hosts. Utilising K-means and K-medoids clustering techniques, we identify homogenous groups and their common characteristics. Our findings enhance comprehension of the intricacies of vacation rental evaluations and could potentially be utilised in the creation of targeted, cluster-specific policies.