Publications

2025
Working Paper

Balancing Engagement and Polarization: Multi-Objective Alignment of News Content Using LLMs

By: Mengjie Cheng, Elie Ofek and Hema Yoganarasimhan

We study how media firms can use LLMs to generate news content that aligns with multiple objectives—making content more engaging while maintaining a preferred level of polarization/slant consistent with the firm’s editorial policy. Using news articles from The New York... View Details

Keywords: Large Language Models; Content Creation; Media; Polarization; Generative Ai; Direct Preference Optimization; AI and Machine Learning; News; Perspective; Digital Marketing; Policy; Media and Broadcasting Industry

SSRN

2025
Working Paper

Warnings and Endorsements: Improving Human-AI Collaboration in the Presence of Outliers

By: Matthew DosSantos DiSorbo, Kris Ferreira, Maya Balakrishnan and Jordan Tong

Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). How can humans and algorithms work together to make... View Details

Keywords: AI and Machine Learning; Decision Choices and Conditions

2004
Article

Mergers and Acquisitions: An Experimental Analysis of Synergies, Externalities and Dynamics

By: R. Croson, A. Gomes, K. L. McGinn and M. Nöth

Keywords: Mergers and Acquisitions; Theory

Article

Heuristics Guide the Implementation of Social Preferences in One-Shot Prisoner's Dilemma Experiments

By: Jillian J. Jordan, Valerio Capraro and David G. Rand

Cooperation in one-shot anonymous interactions is a widely documented aspect of human behavior. Here we shed light on the motivations behind this behavior by experimentally exploring cooperation in a one-shot continuous-strategy Prisoner’s Dilemma (i.e. one-shot... View Details

Keywords: Human Behavior; Social Evolution; Behavior; Cooperation; Decision Making; Game Theory

Research Summary

Overview

Paul is primarily interested in studying explainable machine learning (ML), digital transformation, and data science operations. He works on research that explores how stakeholders within organizations can use machine learning to make better decisions. In particular,... View Details

2010
Book Review

Book review of Explorations in Transactional Analysis: The Meech Lake Papers

Keywords: Information; Theory

09 May 2014
Working Paper Summaries

‘My Bad!’ How Internal Attribution and Ambiguity of Responsibility Affect Learning from Failure

Keywords: by Christopher G. Myers, Bradley R. Staats & Francesca Gino

09 Feb 2018
Research & Ideas

Big Hits: The Best of the 2018 Super Bowl Ads

public’s interest and underscore its anxiety regarding artificial intelligence, playing with themes of machines with minds of their own, the loss View Details

Keywords: Re: Multiple Faculty; Telecommunications

2007
Working Paper

Correlated Equilibrium and Nash Equilibrium as an Observer's Assessment of the Game

By: John Hillas, Elon Kohlberg and John W. Pratt

Noncooperative games are examined from the point of view of an outside observer who believes that the players are rational and that they know at least as much as the observer. The observer is assumed to be able to observe many instances of the play of the game; these... View Details

Keywords: Decision Choices and Conditions; Game Theory; Cooperation

February 2007
Article

The Effect of File Sharing on Record Sales: An Empirical Analysis

By: Felix Oberholzer-Gee and Koleman Strumpf

Keywords: Information Technology; Sales; Theory

22 Feb 2011
Research & Ideas

The Most Important Management Trends of the (Still Young) Twenty-First Century

we could only dream of just a few years ago, ranging from unobtrusive physiological and neurological measures to massive databases on billions of individuals' decisions about consuming, saving, investing,... View Details

Keywords: by Sean Silverthorne

December 2015
Article

What Is Disruptive Innovation?

By: Clayton M. Christensen, Michael Raynor and Rory McDonald

For the past 20 years, the theory of disruptive innovation has been enormously influential in business circles and a powerful tool for predicting which industry entrants will succeed. Unfortunately, the theory has also been widely misunderstood, and the "disruptive"... View Details

Keywords: Disruptive Innovation; Theory

05 Oct 2016
What Do You Think?

Can the US Economy Regain the Growth and Prosperity of the Past?

graduates and former students who are exploring innovations such as battery technology, superconductivity, magnetism, and superintelligent computers. My feelings are buoyed when I read about a “second machine age” fueled by digital... View Details

Keywords: by James Heskett

18 Sep 2006
Research & Ideas

When Words Get in the Way: The Failure of Fiscal Language

labeling conventions—representing, in the words of the authors, "an exercise in linguistics, not economics." Like Einstein's General Theory of Relativity, which... View Details

Keywords: by Julia Hanna

02 Oct 2008
Working Paper Summaries

Nameless + Harmless = Blameless: When Seemingly Irrelevant Factors Influence Judgment of (Un)ethical Behavior

Keywords: by Francesca Gino, Lisa L. Shu & Max H. Bazerman

Article

Third-Party Punishment as a Costly Signal of High Continuation Probabilities in Repeated Games

By: Jillian J. Jordan and David G. Rand

Why do individuals pay costs to punish selfish behavior, even as third-party observers? A large body of research suggests that reputation plays an important role in motivating such third-party punishment (TPP). Here we focus on a recently proposed reputation-based... View Details

Keywords: Direct Reciprocity; Evolution; Dispersal; Cooperation; Trust; Reputation; Game Theory

November 2024 (Revised January 2025)
Case

MiDAS: Automating Unemployment Benefits

By: Shikhar Ghosh and Shweta Bagai

In 2015, the state of Michigan considered whether to nominate its Michigan Integrated Data Automated System (MiDAS) for a prestigious state technology award. Launched in 2013 amid severe budget pressures, the $47 million automated fraud detection system was designed to... View Details