Purpose
This paper aims to examine the question of whether commercial, peer-to-peer accommodation platforms (Airbnb, in particular) and hotels are in fierce competition with each other with the possible presence of substitution threats, and compares the time series of the occupancy values across two supplier types.
Design/methodology/approach
The cities of Milan and Rome are used as case studies for this analysis. To assess the extent of synchronization, the series of Airbnb and hotels are transformed into a series of symbols that render their rhythmic behavior, and a mutual information metric is used to measure the effect.
Findings
The results show that Airbnb hosts and hotels have different seasonal patterns. The diverse occupancy trends support the absence of direct competition between Airbnb and hotels. The findings are consistent in the two analyzed cities (Milan and Rome). Interestingly, there are higher similarities between seasonal occupancy series of Airbnb listings in Milan and Rome, on one side, and hotels in Milan and Rome, on the other, than between Airbnb and hotels in the same city.
Research limitations/implications
The findings show a progressive de-synchronization (within mutual information) among the five groups of Airbnb hosts triggered by the rising professionalization degree. This result suggests the existence of a partial different business model for multi-listing hosts.
Practical implications
The study illustrates an absence of any substitution threat between Airbnb and hotels in both cities. This could have important consequences, especially for the pricing and revenue management policy. In fact, the higher the substitution threat, the higher the attention that Airbnb entrepreneurs should pay to the pricing strategy implemented by hotels, and vice versa.
Originality/value
This study sheds new light on the competition threat between Airbnb and hotels. In this study, hotels and Airbnb hosts appear as two very separate markets.
Complex Dual Tree Wavelet Multi-Level Feature Based Transformation Parameter Estimation for 3d Medical Image Registration
