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Publications

Publications

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  • All HBS Web  (54)
    • Faculty Publications  (4)

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    • All HBS Web  (54)
      • Faculty Publications  (4)

      Image InterpretationRemove Image Interpretation →

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      • 2023
      • Chapter

      Marketing Through the Machine’s Eyes: Image Analytics and Interpretability

      By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
      he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
      Keywords: Transparency; Marketing Research; Algorithmic Bias; AI and Machine Learning; Marketing
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      Zhang, Shunyuan, Flora Feng, and Kannan Srinivasan. "Marketing Through the Machine’s Eyes: Image Analytics and Interpretability." Chap. 8 in Artificial Intelligence in Marketing. 20, edited by Naresh K. Malhotra, K. Sudhir, and Olivier Toubia, 217–238. Review of Marketing Research. Emerald Publishing Limited, 2023.
      • August 2022
      • Article

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

      By: Shunyuan Zhang, Dokyun Lee, Param Vir Singh and Kannan Srinivasan
      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 dataset... View Details
      Keywords: Sharing Economy; Airbnb; Property Demand; Computer Vision; Deep Learning; Image Feature Extraction; Content Engineering; Property; Marketing; Demand and Consumers
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      Zhang, Shunyuan, Dokyun Lee, Param Vir Singh, and Kannan Srinivasan. "What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features." Management Science 68, no. 8 (August 2022): 5644–5666.
      • Article

      Development of a Deep Learning Algorithm for Periapical Disease Detection in Dental Radiographs

      By: Michael G. Endres, Florian Hillen, Marios Salloumis, Ahmad R. Sedaghat, Stefan M. Niehues, Olivia Quatela, Henning Hanken, Ralf Smeets, Benedicta Beck-Broichsitter, Carsten Rendenbach, Karim R. Lakhani, Max Helland and Robert A. Gaudin
      Periapical radiolucencies, which can be detected on panoramic radiographs, are one of the most common radiographic findings in dentistry and have a differential diagnosis including infections, granuloma, cysts, and tumors. In this study, we seek to investigate the... View Details
      Keywords: Artificial Intelligence; Diagnosis; Computer-assisted; Image Interpretation; Machine Learning; Radiography; Panoramic Radiograph; AI and Machine Learning
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      Endres, Michael G., Florian Hillen, Marios Salloumis, Ahmad R. Sedaghat, Stefan M. Niehues, Olivia Quatela, Henning Hanken, Ralf Smeets, Benedicta Beck-Broichsitter, Carsten Rendenbach, Karim R. Lakhani, Max Helland, and Robert A. Gaudin. "Development of a Deep Learning Algorithm for Periapical Disease Detection in Dental Radiographs." Diagnostics 10, no. 6 (June 2020).
      • Research Summary

      Corporate Reputation

      By: Stephen A. Greyser
      Stephen A. Greyser is undertaking an empirical analysis of corporate reputation based on interviews conducted by Opinion Research Corporation with more than four thousand executives in nineteen countries. His study is examining public awareness of, familiarity with,... View Details
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