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Publications

Publications

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  • All HBS Web  (287)
    • Faculty Publications  (9)

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    • All HBS Web  (287)
      • Faculty Publications  (9)

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      • April 2025
      • Article

      Serving with a Smile on Airbnb: Analyzing the Economic Returns and Behavioral Underpinnings of the Host’s Smile

      By: Shunyuan Zhang, Elizabeth Friedman, Kannan Srinivasan, Ravi Dhar and Xupin Zhang
      Non-informational cues, such as facial expressions, can significantly influence judgments and interpersonal impressions. While past research has explored how smiling affects business outcomes in offline or in-store contexts, relatively less is known about how smiling... View Details
      Keywords: Sharing Economy; Airbnb; Image Feature Extraction; Machine Learning; Facial Expressions; Prejudice and Bias; Nonverbal Communication; E-commerce; Consumer Behavior; Perception
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      Zhang, Shunyuan, Elizabeth Friedman, Kannan Srinivasan, Ravi Dhar, and Xupin Zhang. "Serving with a Smile on Airbnb: Analyzing the Economic Returns and Behavioral Underpinnings of the Host’s Smile." Journal of Consumer Research 51, no. 6 (April 2025): 1073–1097.
      • Working Paper

      AI in Disguise—How AI-generated Ads' Visual Cues Shape Consumer Perception and Performance

      By: Yannick Exner, Jochen Hartmann, Oded Netzer and Shunyuan Zhang
      Generative AI’s recent advancements in creating content have offered vast potential to transform the advertising industry. This research investigates the impact of generative AI-enabled visual ad creation on real-world advertising effectiveness. For this purpose, we... View Details
      Keywords: Digital Marketing; AI and Machine Learning; Advertising; Consumer Behavior; Advertising Industry
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      Exner, Yannick, Jochen Hartmann, Oded Netzer, and Shunyuan Zhang. "AI in Disguise—How AI-generated Ads' Visual Cues Shape Consumer Perception and Performance." SSRN Working Paper Series, No. 5096969.
      • 2024
      • Working Paper

      Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization

      By: Ta-Wei Huang, Eva Ascarza and Ayelet Israeli
      This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
      Keywords: Heterogeneous Treatment Effect; Multi-task Learning; Representation Learning; Personalization; Promotion; Deep Learning; Field Experiments; Customer Focus and Relationships; Customization and Personalization
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      Huang, Ta-Wei, Eva Ascarza, and Ayelet Israeli. "Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization." Harvard Business School Working Paper, No. 24-076, June 2024.
      • May 2024
      • Article

      Moral Thin-Slicing: Forming Moral Impressions from a Brief Glance

      By: Julian De Freitas and Alon Hafri
      Despite the modern rarity with which people are visual witness to moral transgressions involving physical harm, such transgressions are more accessible than ever thanks to their availability on social media and in the news. On one hand, the literature suggests that... View Details
      Keywords: Moral Judgement; Thin Slices; Social Media; Fake News; Misinformation; Moral Sensibility; News; Behavior
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      De Freitas, Julian, and Alon Hafri. "Moral Thin-Slicing: Forming Moral Impressions from a Brief Glance." Art. 104588. Journal of Experimental Social Psychology 112 (May 2024).
      • 2022
      • Article

      OpenXAI: Towards a Transparent Evaluation of Model Explanations

      By: Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik and Himabindu Lakkaraju
      While several types of post hoc explanation methods have been proposed in recent literature, there is very little work on systematically benchmarking these methods. Here, we introduce OpenXAI, a comprehensive and extensible opensource framework for evaluating and... View Details
      Keywords: Measurement and Metrics; Analytics and Data Science
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      Agarwal, Chirag, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, and Himabindu Lakkaraju. "OpenXAI: Towards a Transparent Evaluation of Model Explanations." Advances in Neural Information Processing Systems (NeurIPS) (2022).
      • 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.
      • 2010
      • Book

      The New Science of Retailing: How Analytics Are Transforming the Supply Chain and Improving Performance

      By: Marshall Fisher and Ananth Raman
      Retailers today are drowning in data but lacking in insight: They have huge volumes of information at their disposal. But they're unsure of how to sort through it and use it to make smart decisions. The result? They're struggling with profit-sapping supply chain... View Details
      Keywords: Profit; Knowledge Use and Leverage; Logistics; Supply Chain Management; Mathematical Methods; Retail Industry
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      Fisher, Marshall, and Ananth Raman. The New Science of Retailing: How Analytics Are Transforming the Supply Chain and Improving Performance. Harvard Business Press, 2010.
      • Research Summary

      Overview

      By: Shunyuan Zhang
      Professor Zhang uses machine learning to address marketing problems that have arisen within the nascent sharing economy. She conducts rigorous analyses of structured and unstructured data generated by new sharing economy platforms to address important issues emerging... View Details
      • Forthcoming
      • Article

      Reputation Burning: Analyzing the Impact of Brand Sponsorship on Social Influencers

      By: Mengjie Cheng and Shunyuan Zhang
      The growth of the influencer marketing industry warrants an empirical examination of the effect of posting sponsored videos on influencers' reputations. We collected a novel dataset of user-generated YouTube videos created by prominent English-speaking influencers in... View Details
      Keywords: Reputation; Mathematical Methods; Marketing Reference Programs; Social Media; Brands and Branding
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      Cheng, Mengjie, and Shunyuan Zhang. "Reputation Burning: Analyzing the Impact of Brand Sponsorship on Social Influencers." Management Science (forthcoming). (Pre-published online October 18, 2024.)
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