Publications

SSRN

October 2023
Article

Matching Mechanisms for Refugee Resettlement

By: David Delacrétaz, Scott Duke Kominers and Alexander Teytelboym

Current refugee resettlement processes account for neither the preferences of refugees nor the priorities of hosting communities. We introduce a new framework for matching with multidimensional knapsack constraints that captures the (possibly multidimensional) sizes of... View Details

Keywords: Refugee Resettlement; Matching; Matching Markets; Matching Platform; Matching With Contracts; Algorithms; Refugees; Market Design

Find at Harvard

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

Educators

January 2021
Article

Machine Learning for Pattern Discovery in Management Research

By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres

Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect... View Details

Keywords: Machine Learning; Supervised Machine Learning; Induction; Abduction; Exploratory Data Analysis; Pattern Discovery; Decision Trees; Random Forests; Neural Networks; ROC Curve; Confusion Matrix; Partial Dependence Plots; AI and Machine Learning

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2023
Working Paper

Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detection

By: Edward McFowland III, Sriram Somanchi and Daniel B. Neill

In the recent literature on estimating heterogeneous treatment effects, each proposed method makes its own set of restrictive assumptions about the intervention’s effects and which subpopulations to explicitly estimate. Moreover, the majority of the literature provides... View Details

Keywords: Causal Inference; Program Evaluation; Algorithms; Distributional Average Treatment Effect; Treatment Effect Subset Scan; Heterogeneous Treatment Effects

October 2021 (Revised June 2022)
Case

PittaRosso: Artificial Intelligence-Driven Pricing and Promotion

By: Ayelet Israeli

PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once... View Details

Educators

05 May 2022
HBS Seminar

Caleb Kwon, Harvard Business School

October 2021 (Revised March 2022)
Supplement

PittaRosso: Artificial Intelligence-Driven Pricing and Promotion

By: Ayelet Israeli and Fabrizio Fantini

PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once... View Details

Seth Neel is an Assistant Professor housed in the Department of Technology and Operations Management (TOM) at HBS, and a Faculty Affiliate in Computer Science at SEAS. He is Principal Investigator of the Trustworthy AI Lab in Harvard's new View Details

2023
Article

Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten

By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma

The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an... View Details

Keywords: Analytics and Data Science; AI and Machine Learning; Decision Making; Governing Rules, Regulations, and Reforms

Research Summary

Overview

By: Kris Johnson Ferreira

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

Keywords: E-commerce; Analytics; Revenue Management; Pricing; Assortment Planning; Field Experiments; Operations; Supply Chain; Supply Chain Management; Retail Industry

2022
Working Paper

Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions

By: Caleb Kwon, Ananth Raman and Jorge Tamayo

We empirically analyze how managerial overrides to a commercial algorithm that forecasts demand and schedules labor affect store performance. We analyze administrative data from a large grocery retailer that utilizes a commercial algorithm to forecast demand and... View Details

Keywords: Employees; Human Capital; Performance; Applications and Software; Management Skills; Management Practices and Processes; Retail Industry

SSRN

14 Jun 2017
Working Paper Summaries

Minimizing Justified Envy in School Choice: The Design of New Orleans' OneApp

Keywords: by Atila Abdulkadiroglu, Yeon-Koo Che, Parag A. Pathak, Alvin E. Roth, and Oliver Tercieux; Education

26 Apr 2023
In Practice

Is AI Coming for Your Job?

gradually and then suddenly.” Companies will move slowly to deploy generative AI technology like that embodied in OpenAI’s ChatGPT. Harnessing the immense pool of data underlying it will require the development of proprietary... View Details

Keywords: by Kristen Senz; Technology

Descent-to-Delete: Gradient-Based Methods for Machine Unlearning

We study the data deletion problem for convex models. By leveraging techniques from convex optimization and reservoir sampling, we give the first data deletion algorithms that are able to handle an arbitrarily long sequence of adversarial updates while promising... View Details

Jeremy Yang

Jeremy Yang is an Assistant Professor of Business Administration in the Marketing Unit at Harvard Business School. He teaches Marketing in the MBA required curriculum. He develops data products for... View Details

Keywords: advertising; media; entertainment; information; consumer products

24 Jul 2023
Research & Ideas

Part-Time Employees Want More Hours. Can Companies Tap This ‘Hidden’ Talent Pool?

many such workers are caregivers, excluded from full-time jobs because short-sighted employers don’t offer them the flexibility they need. Filtered out by hiring algorithms due to employment gaps or other hiring “red flags,” these willing... View Details

Keywords: by Kara Baskin

Working Paper

Group Fairness in Dynamic Refugee Assignment

By: Daniel Freund, Thodoris Lykouris, Elisabeth Paulson, Bradley Sturt and Wentao Weng

Ensuring that refugees and asylum seekers thrive (e.g., find employment) in their host countries is a profound humanitarian goal, and a primary driver of employment is the geographic location within a host country to which the refugee or asylum seeker is... View Details

Keywords: Refugees; Geographic Location; Mathematical Methods; Employment; Fairness

18 Oct 2022
Research & Ideas

When Bias Creeps into AI, Managers Can Stop It by Asking the Right Questions

can amplify bias. Some companies try to address the issue by making sure that their algorithms don’t use data on protected characteristics such as race or gender. Yet, eliminating factors like race from an... View Details

Keywords: by Rachel Layne

Article

How to Use Heuristics for Differential Privacy

By: Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu

We develop theory for using heuristics to solve computationally hard problems in differential privacy. Heuristic approaches have enjoyed tremendous success in machine learning, for which performance can be empirically evaluated. However, privacy guarantees cannot be... View Details