Consumer valuation of Airbnb listings: a hedonic pricing approach

Abstract

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.

Peer-to-Peer Accommodation Networks

“…If this is the chosen interpretation, then there is not much new about the price drivers of Airbnb listings for entire properties in major city destinations. This latter interpretation is in line with the view that consumer evaluation of Airbnb listings is very similar to that of hotel listings, and that functionality is more important than interpersonal factors (Chen and Xie, 2017).…”

“…This study offers a few key insights for Airbnb listings in Vienna: first of all, location is still the primary driver of price in cities, very much in line with drivers of price in the established commercial tourism accommodation sector (Espinet et al, 2003;Thrane, 2005;Thrane, 2007;Andersson, 2010;Chen and Rothschild, 2010;Lee and Jang, 2011;Rigall-I-Torrent et al, 2011) and results from other Airbnb pricing studies (Chen and Xie, 2017;Gibbs et al, 2017). Second, properties with more amenities can and do charge a higher price.…”

Humanize your business. The role of personal reputation in the sharing economy

“…Second, an analysis of the sharing economy topic in the hospitality industry literature over the last three years (2015-2017) demonstrates the interest of scholars towards the case Airbnb. The main research themes are presented in Table 1 and primarily revolve around these areas: i) value creation practices (Camilleri and Neuhofer, 2017;Johnson and Neuhofer, 2017), ii) effects on consumers' preferences and decisions (Varma et al, 2016;Tussyadiah, 2015;Mao and Lyu, 2017;Poon and Huang, 2017;Tussyadiah and Zach, 2017), iii) impacts on the hotel sector and changing relationships between the actors Guttentag and Smith, 2017;Mody et al, 2017), iv) effects of attributes of Airbnb listings on performance (Xie and Mao, 2017) and v) pricing (Chen and Xie, 2017;Wang and Nicolau, 2017).…”

When individuals behave as marketing firms: Probability discounting and reputation in peer‐to‐peer markets

“…Based on hedonic price modeling, which assumes that prices reflect the internal attributes of goods and services as well as external factors affecting them, Teubner, Hawlitschek, and Dann () also encountered positive and statistically significant effects of average rating score (number of stars) on the prices of properties listed on Airbnb in 86 German cities. Similarly, both Dogru and Pekin () and Chen and Xie () found positive and significant effects of overall ratings on the prices of properties located in Boston, Massachusetts, and Austin, Texas, respectively (although, in both cases, impact was relatively weak in light of the effect of other property attributes).…”