Purpose With the prevalence of the sharing economy phenomenon, there are an increasing number of hosts on Airbnb who manage more than one listing. Managing more listings likely makes hosts more seasoned in terms of serving guests, but it may undermine host quality due to hosts’ constrained capability. This paper aims to examine the effects of host quality attributes and the number of listings per host on the reservation performance of these listings. Design/methodology/approach Using a large-scale but granular data set of 5,805 active listings of 4,608 Airbnb hosts in Austin, Texas, this study estimates the effects of host attributes (host quality and listing quantity) on the performance of the hosts’ Airbnb listings through a blend of regression models. Findings This study evidences that host quality attributes significantly influence listing performance through cue-based trust. In addition, this study finds a “trade-off” between host quality and the quantity of their listings. As the number of listings managed by a host increases, the performance effects of host quality diminish. Research limitations/implications The business implications of this study include the suggestion that sharing economy businesses such as Airbnb should sustain service quality through incentivizing hosts to improve host quality while balancing the quantity of listings managed. Originality/value This study contributes to the literature through its meaningful theoretical extension in the sharing economy context and unique data-driven insights enabled by an analytical approach. It addresses the critical but less researched topic of host quality and listing quantity and generates important practical business and policy implications.
Purpose This paper aims to identify a wide array of utility-based attributes of Airbnb listings and measures the effects of these attributes on consumers’ valuation of Airbnb listings. Design/methodology/approach A hedonic price model was developed to test the effects of a group of utility-based attributes on the price of Airbnb listings, including the characteristics of Airbnb listings, attributes of hosts, reputation of listings and market competition. The authors examined attributes as they relate to the price of Airbnb listings and, therefore, estimated consumers’ willingness to pay for the specific attributes. The model was tested by using a dataset of 5,779 Airbnb listings managed by 4,602 hosts in 41 census tracts of Austin, Texas in the USA over a period from Airbnb’s launch in Texas up until November 2015. Findings The authors found that the functional characteristics of Airbnb listings were significantly associated to the price of the listings, and that three of five behavioral attributes of hosts were statistically significant. However, the effect of reputation of listings on the price of Airbnb listings was weak. Originality/value This study inspires what they call a factor-endowment valuation of Airbnb listings. It shows that the intrinsic attributes that an Airbnb listing endows are the primary source of consumer utilities, and thus consumer valuation of the listing is grounded on its functionality as an accommodation. This conclusion can shed light on the examination of competition between Airbnb and hotel accommodations that are built on the same or similar intrinsic attributes.
Purpose This study aims to measures the effects of managerial response on consumer electronic word-of-mouth (eWOM) and hotel performance. Design/methodology/approach A sample of 56,284 consumer reviews and 10,793 managerial responses for 1,045 hotels was retrieved from TripAdvisor, along with 30,232 performance records matched to these hotels on a quarterly basis. Findings This study finds that managerial response leads to an average increase of 0.235 stars in the TripAdvisor ratings of the sampled hotels, as well as a 17.3 per cent increase in the volume of subsequent consumer eWOM. Moreover, managerial response moderates the influence of ratings and volume of consumer eWOM on hotel performance. Practical implications This study offers a practical model that enables hotel managers to orchestrate social media marketing approaches and efforts toward an optimal social media strategy. Originality/value This study differs from extant literature that has extensively focused on consumer reviews by providing a new perspective of management intervention in the social media context. By examining the interplay of managerial response and consumer eWOM at the individual hotel level, this study provides empirical evidence of managerial response affecting hotel performance through the increased ratings and volume of consumer eWOM. This study also offers insights into the practical importance of crafting intervention opportunities to cultivate the continued engagement of consumers on social media and increased hotel performance.
The business value of online consumer reviews has emerged in recent year as one of utmost importance for hotel marketers. This study examines how online consumer reviews affect offline hotel popularity. Using time-series data of 56,284 hotel reviews posted for more than 1000 hotels listed on TripAdvisor, this paper estimates the effect of factors of online consumer review, including quality, quantity, consistency, and recency, on the offline hotel occupancy (i.e. how popular the hotel is among consumers). The empirical evidence shows the relative effect of online consumer review factors on offline hotel popularity when controlling for other hotel characteristics. In particular, the effect of review quality lasts for at least a couple of quarters, whereas that of other online consumer review factors remains short-term. The findings provide a managerial basis to improve the online presence of hotels on social media platforms by strategically utilizing important review factors.
Purpose Trust has been widely recognized as the crucial factor of consumer purchase intention when shopping on peer-to-peer short-term rental platforms where hosts and renters are strangers. However, the specific attributes of hosts that help build trust with potential renters and drive their purchase of short-term rentals remain unknown. This study aims to explore the effects of host attributes on renter purchases made on Xiaozhu.com, one of the top short-term rental platforms in China, while controlling for short-term rental characteristics. Design/methodology/approach A crawler program was developed by Python to collect the host attributes and their short-term rental characteristics of 935 hosts in Beijing from November 18, 2015 to February 14, 2016. The authors use Poisson regression models to estimate the effects of host attributes on renter reservations. They also conduct a series of robustness checks for the estimated results. Findings The authors found that host attributes such as the time of reservation confirmation, the acceptance rate of renter reservations, the number of listings owned, whether a personal profile page is disclosed and gender of the host significantly affect renter reservations, whereas the response rate of the host does not influence renters when purchasing short-term rentals online. Originality/value This study identifies which host attributes are perceived as trustworthy and affect renters’ purchase decisions, a topic of both theoretical and practical importance but currently less researched. The findings add to emerging literature by providing insights on trust-building in the peer-to-peer economy. Useful suggestions are also provided on strengthening the trust mechanism on short-term rental platforms to facilitate peer-to-peer transactions. Notably, the study is the first attempt to examine the perception of Chinese users toward short-term rentals despite its global prevalence. The analytical insights revealed from large scale but granular online observations data of host attributes and actual renter reservations greatly supplement findings of extant literature using survey and experiment approaches.
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