Shunyuan Zhang’s research while affiliated with Harvard Medical School and other places

... In addition, these studies cannot detect the prevalence and value of these buyer segments, which are crucial factors for managers to evaluate a segment's attractiveness. Moreover, research has mainly provided insights into transactional engagement in the form of NFT purchase intentions (Yang, 2024;Yuan et al., 2024), NFT pricing (Mekacher et al., 2022;Hostetter et al., 2024;Xie et al., 2024), and NFT secondary market selling (Berghueser & Spann, 2024). To the best of our knowledge, only conceptual contributions have dealt with community engagement (e.g., Colicev, 2023) and no prior research has dealt with multiplier engagement. ...

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Unveiling investment vs. Ownership perspectives among NFT buyers: A segmentation study exploring engagement patterns in NFT markets

... AI's impact on operations management becomes even more pronounced in this phase, as AI-powered systems optimize supply chain management, logistics, and enterprise resource planning (ERP). AI models predict inventory demands, optimize warehouse distribution, and enhance supplier selection processes by analyzing historical sales data, transportation efficiency metrics, and supplier performance analytics (Feng & Zhang, 2024). AI-driven supply chain solutions, such as IBM Watson Supply Chain and SAP AI-driven ERP systems, use predictive analytics and prescriptive optimization to ensure just-in-time inventory management, cost reduction, and improved logistics coordination (Pan, 2024). ...

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AI-driven strategic decision-making on innovation: Scalable, ethical approaches and ai agents for startups

... Lastly, Bertolini, Clevert, and Montanari introduced an aggregation method that generalizes attribution maps between any two convolutional layers of a neural network (Bertolini, Clevert, and Montanari 2023). R-XAI has also been used in many applications, for instance in healthcare Weinberger, Lin, and Lee 2023) and business (Feng, Li, and Zhang 2023). ...

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REPEAT: Improving Uncertainty Estimation in Representation Learning Explainability

... The home-sharing economy involves uncertainty and information asymmetry between peer providers and customers, and photos can reduce the uncertainty by heightening social presence and the ability to visualize the experience (Ert, Fleischer, & Magen, 2016). Customers in the P2P context rely heavily on photos to make purchase decisions (Zhang, Mehta, Singh, & Srinivasan, 2019). Prior studies have tested several effects involving the photos of peer providers and properties. ...

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The impact of photo verification service on sales performance in the peer-to-peer economy: Moderating role of customer uncertainty

... This support can come from family recommendations or observed use by peers. Social influences are crucial as they affect how older adults think about and feel toward technology, influencing their digital engagement (Zhang S Y, et al., 2023). Despite the clear importance of these social aspects, research on leveraging this influence to promote elderly Fintech engagement is limited. ...

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Exploring the mechanisms driving elderly Fintech engagement: the role of social influence and the elderly’s digital literacy

... As both of these levers can further enhance generative text-to-image models' effectiveness (Jansen et al., 2024;Rombach et al., 2022), our results likely represent a lower bound for the performance of AI-generated marketing imagery. The emergence of future generative AI models will likely improve the synthetic images' perceptual ratings and realworld effectiveness, especially when combined with task-specific data for model calibration (Feng et al., 2023). ...

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The power of generative marketing: Can generative AI create superhuman visual marketing content?

... Emotion analysis is conducted using image processing techniques, with studies directly focusing on the human face. In a study by [14], they attempted to calculate the charisma score of the human face. They aimed to determine the visual attractiveness of celebrities by using both celebrities and noncelebrities. ...

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Analysis of Emotional Authenticity Displayed by Film Actors Using Image Processing Techniques

... While image analysis has been applied in some online retail studies (Zhang et al., 2022), this area is relatively unexplored, with many current publications relying only on text data (Marshan et al., 2023). For instance, a study (Zhang et al., 2022) found that the higher quality of professional images contributes significantly to increased occupancy rates in Airbnb. ...

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How Does the Color Palette Affect the Pricing of Abstract Paintings?

... A bank's lending decision, for instance, might be based on a statistical risk assessment algorithm that predicts applicants' likelihood of repaying the loan. As the use of algorithmic decision-making expands to other consequential domains, such as education, employment, and criminal justice, concerns have emerged that the underlying models may inadvertently perpetuate or even amplify human biases, resulting in discriminatory and inequitable outcomes [5][6][7]. For example, a widely used algorithm for assessing the risk of criminal re-offense (COMPAS) was found to produce biased ...

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Public perception of accuracy-fairness trade-offs in algorithmic decisions in the United States

... Race significantly shapes users' perceptions and trust in AI (M. K. Lee & Rich, 2021;S. Zhang et al., 2021). We argue that Non-White users in America are more likely to experience algorithmic aversion or automation bias compared to White users. ...

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Communicating and combating algorithmic bias: effects of data diversity, labeler diversity, performance bias, and user feedback on AI trust