Start Date
11-12-2016 12:00 AM
Description
Consumers using sharing economy platforms such as Airbnb are challenged with high product uncertainty and search cost. To ameliorate these issues, Airbnb has implemented many strategies such as professionally taking high quality photos for hosts and calling them verified. In this paper we study the impact of having unit list's photos verified. To assess the aesthetic quality of images, we use machine learning techniques. Employing Difference-in-Difference analysis, we find that on average, rooms with verified photos are 9% more frequently booked. We further separate the effect of photo verification from photo quality and room reviews and find an extra $2,455 in yearly earnings brought by high photo quality. Lastly, we look at the properties in the same neighborhood and find asymmetric spillover effects. On the neighborhood level, the results suggest higher overall demand if more rooms have verified photos.
Recommended Citation
Zhang, Shunyuan; Lee, Dokyun; Singh, Param Vir; and SRINIVASAN, KANNAN, "How Much Is An Image Worth? An Empirical Analysis of Property’s Image Aesthetic Quality on Demand at AirBNB" (2016). ICIS 2016 Proceedings. 8.
https://aisel.aisnet.org/icis2016/Crowdsourcing/Presentations/8
How Much Is An Image Worth? An Empirical Analysis of Property’s Image Aesthetic Quality on Demand at AirBNB
Consumers using sharing economy platforms such as Airbnb are challenged with high product uncertainty and search cost. To ameliorate these issues, Airbnb has implemented many strategies such as professionally taking high quality photos for hosts and calling them verified. In this paper we study the impact of having unit list's photos verified. To assess the aesthetic quality of images, we use machine learning techniques. Employing Difference-in-Difference analysis, we find that on average, rooms with verified photos are 9% more frequently booked. We further separate the effect of photo verification from photo quality and room reviews and find an extra $2,455 in yearly earnings brought by high photo quality. Lastly, we look at the properties in the same neighborhood and find asymmetric spillover effects. On the neighborhood level, the results suggest higher overall demand if more rooms have verified photos.