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Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation
By: Maya Balakrishnan, Kris Ferreira and Jordan Tong
Even if algorithms make better predictions than humans on average, humans may sometimes have private information which an algorithm does not have access to that can improve performance. How can we help humans effectively use and adjust recommendations made by... View Details
Keywords: AI and Machine Learning; Analytics and Data Science; Forecasting and Prediction; Digital Marketing
Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation." Management Science (forthcoming).
- Research Summary
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By: Iavor I. Bojinov
Over the last decade, technology companies like Amazon, Google, and Netflix have pioneered data-driven research and development processes centered on massive experimentation. However, as companies increase the breadth and scale of their experiments to millions of... View Details
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By: John A. Deighton
Professor Deighton conducts research at the intersection of information technology and marketing. He is interested in the complementary uses of human and artificial intelligence and creativity in areas such as advertising, content creation, and online retailing. He... View Details
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By: Chiara Farronato
Based on a broad interest in the economics of innovation and the Internet, Professor Farronato concentrates her research on the evolution of e-commerce and peer-to-peer online platforms, including platform adoption, economies of scale, and drivers of heterogeneous... View Details
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Professor Ferreira's research primarily focuses on how retailers can use algorithms to make better revenue management decisions, including pricing, product display, and assortment planning. In the retail industry, anticipating consumer demand is arguably one of the... View Details
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By: Ayelet Israeli
Professor Israeli utilizes econometric methods and field experiments to study data driven decision making in marketing context. Her research focuses on data-driven marketing, with an emphasis on how businesses can leverage their own data, customer data, and market data... View Details
- Forthcoming
- Article
The Effect of a System for Sharing Best Practices Within Pre-existing Peer Networks
By: Shelley Xin Li and Tatiana Sandino
Peer networks, such as enterprise social networks (ESNs), can facilitate knowledge transfer across employees. However, such systems can also lead to information overload or difficulty in finding useful information. We examine data from a natural field experiment where... View Details
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