Use of dynamic pricing strategies by Airbnb hosts

Abstract

Purpose The purpose of this paper is to provide a comprehensive analysis of dynamic pricing by Airbnb hosts. Design/methodology/approach This study uses attribute and sales information from 39,837 Airbnb listings and hotel data from 1,025 hotels across five markets to test different hypotheses which explore the extent to which Airbnb hosts use dynamic pricing and how their pricing strategies compare to those of hotels. Findings Airbnb is a unique and complex platform in terms of dynamic pricing where hosts make limited use of dynamic pricing strategies, especially as compared to hotels. Notwithstanding their limited use, hosts who own listings in high-demand leisure markets, manage entire places, manage more listings and have more experience vary prices the most. Practical implications This study identified a great need for Airbnb to encourage dynamic pricing among its hosts, but also warned of the potential perils of dynamic pricing in the sharing economy context. The findings also demonstrated challenges for hotel managers interested in actionable information related to Airbnb as a competitor. Originality/value This is the first Airbnb study to use a comprehensive set of data over a continuous period in multiple markets to look at a number of listing and host factors and determine their relation with dynamic pricing strategies.

Home sharing in marketing and tourism at a tipping point: What do we know, how do we know, and where should we be heading?

“…Yet, it is equally concerning that platform-related antecedents, such as customer service, cybersecurity, quality assurance, and system functionality ( Huang et al, 2020 , Tussyadiah and Pesonen, 2018 ), were found to negatively influence the actual stays of guests (eight negative votes), which indicates that platform-related antecedents are likely to be responsible for the intention–behavior gap in home sharing. Whereas, algorithmic management in home-sharing platforms, such as Bayesian social learning and dynamic pricing, was a platform-related antecedent that had a noteworthy impact on the pricing of home sharing (six positive votes, one neutral vote, and four negative votes), which in turn, corresponds to the economic returns encountered by hosts ( Gibbs et al, 2018 , Koh et al, 2019 , Kwok and Xie, 2019 ). Finally, the absence of third-order knowledge relating to cause-and-effect is noted, and given that home-sharing platforms are technologically-enabled, it may be worthwhile for future research to pursue eye-tracking experiments that could potentially reveal novel insights with respect to the content and navigational features that guests and hosts pay most attention to when they use the platforms to book or list shared homes, thereby strengthening theory in this area.…”

The 7 Ps marketing mix of home-sharing services: Mining travelers’ online reviews on Airbnb

“…It is plausible that most descriptions and the pictures attached to the Airbnb listings genuinely reflect on what the travelers saw or experienced in person. As a result, they might not find the needs to make such comments as “the listing is pretty close to the images posted” unless they found themselves in a situation like “this place is even more adorable and quaint than the pictures show, if that’s possible :)” Meanwhile, even though price is a critical indicator of a lodging product’s service quality ( Xie and Kwok, 2017 ), it is also a variable that the hosts can easily manipulate ( Gibbs et al, 2018 ; Kwok and Xie, 2019 ). When travelers browse the available listings in a market, they have already seen the price and the fee structure of a listing.…”

“…Multi-unit hosts and single-unit hosts might end up offering a different experience to travelers, which will very likely reflect on the marketing mix of the services they provided. More importantly, multi-unit hosts may create even more significant threats to hoteliers because they can achieve higher revenues in the market through the effective use of pricing strategies (e.g., Gibbs et al, 2018 ; Kwok and Xie, 2018 ; Magno et al, 2018 ) and differentiated operational strategies (e.g., Xie et al, 2020b ). Along this line of research, Mauri et al (2018) also found that the number of connected accounts (i.e., the number of units that a host manages) has a significant negative impact on a listing’s popularity as measured in rating, the number of reviews, times saved to a traveler’s wish lists, and the likelihood of the host being categorized as a superhost.…”

Impacts of the peer-to-peer market on tourist accommodation on the Balearic Islands of Mallorca and Menorca

“…For example, it appears that professional hosts obtain higher income, higher occupancy rates, and a lower probability of abandoning the market than non-professional hosts (Li et al, 2016). Moreover, professional hosts seem to better adapt to demand fluctuations by applying dynamic pricing strategies (Gibbs, Guttentag, Gretzel, Yao, & Morton, 2018).…”