Publications

Educators

Research Summary

Overview

By: Antonio Moreno

Professor Moreno’s research explores how digital technologies are reshaping operational processes, with a particular focus on retail and service industries. His early work examined omnichannel retail—the integration of online and offline channels to create seamless... View Details

Keywords: Omnichannel; Omni-channel; Omnichannel Retail; Omnichannel Retailing; Retail; Operations; Supply Chain Management; Digital Transformation; Digital Strategy; Retail Industry; Technology Industry; Service Industry; Europe; Spain; Latin America

29 May 2018
News

A Study of NASA Scientists Shows How to Overcome Barriers to Open Innovation

2024
Working Paper

The Cram Method for Efficient Simultaneous Learning and Evaluation

By: Zeyang Jia, Kosuke Imai and Michael Lingzhi Li

We introduce the "cram" method, a general and efficient approach to simultaneous learning and evaluation using a generic machine learning (ML) algorithm. In a single pass of batched data, the proposed method repeatedly trains an ML algorithm and tests its empirical... View Details

Keywords: AI and Machine Learning

November 2015 (Revised May 2016)
Case

Aspiring Minds

By: Karim R. Lakhani, Marco Iansiti and Christine Snively

By 2015, India-based employment assessment and certification provider Aspiring Minds had helped facilitate over 300,000 job matches through its assessment tools. Aspiring Minds' flagship product, the Aspiring Minds Computer Adaptive Test (AMCAT), used machine learning... View Details

Keywords: Information Technology; Strategy; Higher Education; Technological Innovation; Employment; Technology Industry; India; China

Educators

Article

Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM

By: Katrina Ligett, Seth Neel, Aaron Leon Roth, Bo Waggoner and Steven Wu

Traditional approaches to differential privacy assume a fixed privacy requirement ϵ for a computation, and attempt to maximize the accuracy of the computation subject to the privacy constraint. As differential privacy is increasingly deployed in practical settings, it... View Details

Keywords: Differential Privacy; Empirical Risk Minimization; Accuracy First

20 Apr 2021
News

10 Things Your Artificial Intelligence Initiative Needs to Succeed

October 2022
Exercise

Shanty Real Estate: Confidential Information for Homebuyer 1

By: Michael Luca, Jesse M. Shapiro and Nathan Sun

Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details

Keywords: Data-driven Decision-making; Decisions; Negotiation; Bids and Bidding; Valuation; Consumer Behavior; Real Estate Industry

October 2022
Exercise

Shanty Real Estate: Confidential Information for iBuyer 2

By: Michael Luca, Jesse M. Shapiro and Nathan Sun

Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details

Keywords: Decision Choices and Conditions; Decision Making; Market Timing; Measurement and Metrics

November 2020
Teaching Note

DayTwo: Going to Market with Gut Microbiome

By: Ayelet Israeli

Teaching Note for HBS Case No. 519-010. DayTwo is a young Israeli startup that applies research on the gut microbiome and machine learning algorithms to deliver personalized nutritional recommendations to its users in order to minimize blood sugar spikes after meals.... View Details

2023
Working Paper

PRIMO: Private Regression in Multiple Outcomes

By: Seth Neel

We introduce a new differentially private regression setting we call Private Regression in Multiple Outcomes (PRIMO), inspired the common situation where a data analyst wants to perform a set of l regressions while preserving privacy, where the covariates... View Details

Keywords: Analytics and Data Science; Mathematical Methods

03 Sep 2019
News

Wait Wait…Tell Me!

October 2022
Exercise

Shanty Real Estate: Confidential Information for Homebuyer 3

By: Michael Luca, Jesse M. Shapiro and Nathan Sun

Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details

Keywords: Decision Choices and Conditions; Decision Making; Measurement and Metrics; Market Timing

20 Apr 2020
News

Digital Transformation: Business Leaders Still Struggling to Cope

October 2022
Exercise

Shanty Real Estate: Confidential Information for Homebuyer 2

By: Michael Luca, Jesse M. Shapiro and Nathan Sun

Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details

Keywords: Decision Choices and Conditions; Decision Making; Measurement and Metrics; Market Timing

2023
Working Paper

Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness

By: Neil Menghani, Edward McFowland III and Daniel B. Neill

In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false... View Details

Keywords: AI and Machine Learning; Forecasting and Prediction; Prejudice and Bias

27 Feb 2018
HBS Seminar

Lin William Cong, University of Chicago Booth School of Business

2024
Working Paper

Principles and Content for Downstream Emissions Disclosures

By: Robert S. Kaplan and Karthik Ramanna

In a previous paper, we proposed the E-liability carbon accounting algorithm for companies to measure and subsequently reduce their own and their suppliers’ emissions. Some investors and stakeholders, however, want companies to also be accountable for downstream... View Details

Keywords: Carbon Emissions; Disclosure; Carbon Footprint; Climate Change; Measurement and Metrics; Corporate Disclosure; Environmental Sustainability; Corporate Social Responsibility and Impact

2016
Chapter

Deriving an Optimally Deceptive Policy in Two-Player Iterated Games

By: Elisabeth Paulson and Christopher Griffin

We formulate the problem of determining an optimally deceptive strategy in a repeated game framework. We assume that two players are engaged in repeated play. During an initial time period, Player 1 may deceptively train his opponent to expect a specific strategy. The... View Details

Keywords: Deception; Strategy; Game Theory