data science - Publications - Faculty & Research

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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

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Overview

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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Paradise Lost (and Restored?): A Study of Psychological Safety over Time

By: Derrick P. Bransby, Michaela Kerrissey and Amy C. Edmondson

Although prior research indicates that psychological safety can fluctuate, questions about when and why remain. To gain insights into the emergence and temporal dynamics of psychological safety, we explored longitudinal data representing more than 10,000 health care... View Details

Keywords: Analytics and Data Science; Research; Attitudes; Working Conditions; Well-being; Health Industry

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Performance Impact of Continuous Replenishment Systems

By: Janice H. Hammond

Janice H. Hammond has conducted (with Ted Clark of Hong Kong University of Science and Technology) a survey of U.S. retailers to determine how the implementation of continuous replenishment programs between manufacturers and retailers affects supply channel... View Details

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Reforming Social Science

By: Max H. Bazerman

Social science research affects all of us. When researchers learned organ donation rates are higher in countries where human organs are automatically available for donation unless you specifically “opt-out” of the system, as opposed to countries like the U.S., where... View Details

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Slowly Varying Regression Under Sparsity

By: Dimitris Bertsimas, Vassilis Digalakis Jr, Michael Lingzhi Li and Omar Skali Lami

We consider the problem of parameter estimation in slowly varying regression models with sparsity constraints. We formulate the problem as a mixed integer optimization problem and demonstrate that it can be reformulated exactly as a binary convex optimization problem... View Details

Keywords: Mathematical Methods; Analytics and Data Science