2018
DOI: 10.1108/ijchm-09-2016-0540
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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… Show more

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citations
Cited by 157 publications
(147 citation statements)
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References 26 publications
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“…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.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…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.…”
Section: Resultsmentioning
confidence: 99%
“…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.…”
Section: The Research Background and Relevant Literaturementioning
confidence: 99%
“…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.…”
Section: What Do We Know?mentioning
confidence: 99%
“…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).…”
Section: Exponential Growthmentioning
confidence: 99%