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What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features

Author

Listed:
  • Shunyuan Zhang

    (Harvard Business School, Harvard University, Cambridge, Massachusetts 02163)

  • Dokyun Lee

    (Questrom School of Business, Boston University, Boston, Massachusetts 02215)

  • Param Vir Singh

    (Tepper School University, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

  • Kannan Srinivasan

    (Tepper School University, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

Abstract

We study how Airbnb property demand changed after the acquisition of verified images (taken by Airbnb’s photographers) and explore what makes a good image for an Airbnb property. Using deep learning and difference-in-difference analyses on an Airbnb panel data set spanning 7,423 properties over 16 months, we find that properties with verified images had 8.98% higher occupancy than properties without verified images (images taken by the host). To explore what constitutes a good image for an Airbnb property, we quantify 12 human-interpretable image attributes that pertain to three artistic aspects—composition, color, and the figure-ground relationship—and we find systematic differences between the verified and unverified images. We also predict the relationship between each of the 12 attributes and property demand, and we find that most of the correlations are significant and in the theorized direction. Our results provide actionable insights for both Airbnb photographers and amateur host photographers who wish to optimize their images. Our findings contribute to and bridge the literature on photography and marketing (e.g., staging), which often either ignores the demand side (photography) or does not systematically characterize the images (marketing).

Suggested Citation

  • Shunyuan Zhang & Dokyun Lee & Param Vir Singh & Kannan Srinivasan, 2022. "What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features," Management Science, INFORMS, vol. 68(8), pages 5644-5666, August.
    • Handle: RePEc:inm:ormnsc:v:68:y:2022:i:8:p:5644-5666
    DOI: 10.1287/mnsc.2021.4175
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    1. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    2. Puneet Manchanda & Grant Packard & Adithya Pattabhiramaiah, 2015. "Social Dollars: The Economic Impact of Customer Participation in a Firm-Sponsored Online Customer Community," Marketing Science, INFORMS, vol. 34(3), pages 367-387, May.
    3. Marianne Bertrand & Dean Karlan & Sendhil Mullainathan & Eldar Shafir & Jonathan Zinman, 2010. "What's Advertising Content Worth? Evidence from a Consumer Credit Marketing Field Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(1), pages 263-306.
    4. Bertrand, Marianne & Karlan, Dean S. & Mullainathan, Sendhil & Shafir, Eldar & Zinman, Jonathan, 2005. "What's Psychology Worth? A Field Experiment in the Consumer Credit Market," Center Discussion Papers 28441, Yale University, Economic Growth Center.
    5. Aviv Nevo, 2000. "Mergers with Differentiated Products: The Case of the Ready-to-Eat Cereal Industry," RAND Journal of Economics, The RAND Corporation, vol. 31(3), pages 395-421, Autumn.
    6. Susan Athey & Guido W. Imbens, 2006. "Identification and Inference in Nonlinear Difference-in-Differences Models," Econometrica, Econometric Society, vol. 74(2), pages 431-497, March.
    7. Monic Sun & Feng Zhu, 2013. "Ad Revenue and Content Commercialization: Evidence from Blogs," Management Science, INFORMS, vol. 59(10), pages 2314-2331, October.
    8. DiPrete, Thomas A. & Gangl, Markus, 2004. "Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments," Discussion Papers, Research Unit: Labor Market Policy and Employment SP I 2004-101, WZB Berlin Social Science Center.
    9. Unnati Narang & Venkatesh Shankar, 2019. "Mobile App Introduction and Online and Offline Purchases and Product Returns," Marketing Science, INFORMS, vol. 38(5), pages 756-772, September.
    10. Laura A. Peracchio & Joan Meyers-Levy, 2005. "Using Stylistic Properties of Ad Pictures to Communicate with Consumers," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(1), pages 29-40, June.
    11. Scott, Linda M, 1994. "Images in Advertising: The Need for a Theory of Visual Rhetoric," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(2), pages 252-273, September.
    12. David H. Autor, 2003. "Outsourcing at Will: The Contribution of Unjust Dismissal Doctrine to the Growth of Employment Outsourcing," Journal of Labor Economics, University of Chicago Press, vol. 21(1), pages 1-42, January.
    13. Liu Liu & Daria Dzyabura & Natalie Mizik, 2020. "Visual Listening In: Extracting Brand Image Portrayed on Social Media," Marketing Science, INFORMS, vol. 39(4), pages 669-686, July.
    14. Elizabeth G. Miller & Barbara E. Kahn, 2005. "Shades of Meaning: The Effect of Color and Flavor Names on Consumer Choice," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(1), pages 86-92, June.
    15. Quan Wang & Beibei Li & Param Vir Singh, 2018. "Copycats vs. Original Mobile Apps: A Machine Learning Copycat-Detection Method and Empirical Analysis," Information Systems Research, INFORMS, vol. 29(2), pages 273-291, June.
    16. Peracchio, Laura A & Meyers-Levy, Joan, 1994. "How Ambiguous Cropped Objects in Ad Photos Can Affect Product Evaluations," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(1), pages 190-204, June.
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    Cited by:

    1. He, Jiaxiu & Li, Bingqing & Wang, Xin (Shane), 2023. "Image features and demand in the sharing economy: A study of Airbnb," International Journal of Research in Marketing, Elsevier, vol. 40(4), pages 760-780.
    2. Daria Dzyabura & Siham El Kihal & John R. Hauser & Marat Ibragimov, 2019. "Leveraging the Power of Images in Managing Product Return Rates," Working Papers w0259, New Economic School (NES).
    3. Alireza Aghasi & Arun Rai & Yusen Xia, 2024. "A Deep Learning and Image Processing Pipeline for Object Characterization in Firm Operations," INFORMS Journal on Computing, INFORMS, vol. 36(2), pages 616-634, March.
    4. Daria Dzyabura & Siham El Kihal & John R. Hauser & Marat Ibragimov, 2023. "Leveraging the Power of Images in Managing Product Return Rates," Marketing Science, INFORMS, vol. 42(6), pages 1125-1142, November.
    5. Jinyang Zheng & Youwei Wang & Yong Tan, 2023. "Platform Refund Insurance or Being Cast Out: Quantifying the Signaling Effect of Refund Options in the Online Service Marketplace," Information Systems Research, INFORMS, vol. 34(3), pages 910-934, September.
    6. Wang, Qiping & Yiu Keung Lau, Raymond, 2024. "Social mood and M&A performance: An empirical investigation enhanced by multimodal analytics," Journal of Business Research, Elsevier, vol. 176(C).
    7. Zhao, Lu & Zhang, Mingli & Tu, Jianbo & Li, Jialing & Zhang, Yan, 2023. "Can users embed their user experience in user-generated images? Evidence from JD.com," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).

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