Purpose – Accommodation sharing is a major trend shaping the hospitality industry, and Airbnb is the most prominent sharing platform driving this growth. While price convenience is reported as one of the main strengths of Airbnb accommodations, only a few studies have examined price determinants. In particular, it is unclear whether hosts dynamically adjust prices for shared accommodation based on their experience with price management and on the level of market demand. The purpose of this paper is to fill this gap by suggesting and testing a comprehensive hedonic pricing model. Design/methodology/approach – Data from all 1,056 Airbnb listings for accommodations available in the city of Verona, Italy on four booking dates in 2016 are collected and analysed through regression analysis. Findings – The results highlight that price is significantly related to the level of the host’s accumulated experience and the level of market demand on a specific booking date. The findings provide support for the ability of hosts to dynamically adjust prices for their accommodations. Practical implications – Drawing on the innovator’s dilemma theory, this study suggests some strategies that traditional hotels may adopt to react to the disruptive nature of Airbnb. Originality/value – This is one of the few studies to address hosts’ pricing strategies and specifically consider price adjustments owing to variations in host experience and market demand.

Accommodation prices on Airbnb: effects of host experience and market demand

Magno Francesca;Cassia Fabio
;
Ugolini Marta
2018-01-01

Abstract

Purpose – Accommodation sharing is a major trend shaping the hospitality industry, and Airbnb is the most prominent sharing platform driving this growth. While price convenience is reported as one of the main strengths of Airbnb accommodations, only a few studies have examined price determinants. In particular, it is unclear whether hosts dynamically adjust prices for shared accommodation based on their experience with price management and on the level of market demand. The purpose of this paper is to fill this gap by suggesting and testing a comprehensive hedonic pricing model. Design/methodology/approach – Data from all 1,056 Airbnb listings for accommodations available in the city of Verona, Italy on four booking dates in 2016 are collected and analysed through regression analysis. Findings – The results highlight that price is significantly related to the level of the host’s accumulated experience and the level of market demand on a specific booking date. The findings provide support for the ability of hosts to dynamically adjust prices for their accommodations. Practical implications – Drawing on the innovator’s dilemma theory, this study suggests some strategies that traditional hotels may adopt to react to the disruptive nature of Airbnb. Originality/value – This is one of the few studies to address hosts’ pricing strategies and specifically consider price adjustments owing to variations in host experience and market demand.
2018
Pricing, Online reviews, Hospitality, Sharing economy, Airbnb
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/985663
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