Image features and demand in the sharing economy: A study of Airbnb

Jiaxiu He, Bingqing Li and Wang, Xin (Shane)

International Journal of Research in Marketing, 2023, vol. 40, issue 4, 760-780

Abstract: Peer-to-peer marketplaces and the sharing economy are reshaping many markets. Airbnb is attractive to many customers because of its non-standardized, diverse selections and superior value over hotels, but Airbnb properties also come with more uncertainty than hotels. Images of the property can help resolve uncertainty. This study focuses on the background image (the image displayed in search results) and examines how the background image’s content features (living room, bedroom, and interior design) and aesthetic features (clarity, brightness, and contrast) affect the booking rate during a 16-night end-of-year holiday period. The authors develop a model that includes the amount of visual information, property characteristics, and host characteristics, and correct for endogeneity by using a pair of markets (New York City and San Francisco) to calculate propensity scores and construct instrumental variables. The results show that having a background image that features the living room and shows more interior design elements increases the booking rate, while featuring a bedroom decreases it. The effects of the content features are larger than the effects of the aesthetic features, and the effects are economically significant: for example, the effect of featuring the living room in the background image translates into a 35% increase in the booking rate, which amounts to $728 more revenue during the holiday period.

Keywords: Airbnb; Image analysis; Machine learning; Sharing economy; Visual information (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ijrema:v:40:y:2023:i:4:p:760-780

DOI: 10.1016/j.ijresmar.2023.04.001

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