Publications

September 2020 (Revised March 2022)
Case

JOANN: Joannalytics Inventory Allocation Tool

By: Kris Ferreira and Srikanth Jagabathula

Michael Joyce, Vice President of Inventory Management at JOANN, championed an effort to develop and implement an inventory allocation analytics tool that used advanced analytics to predict in-season demand of seasonal items for each of JOANN’s nearly 900 stores and... View Details

Keywords: Analytics; Machine Learning; Optimization; Inventory Management; Mathematical Methods; Decision Making; Operations; Supply Chain Management; Resource Allocation; Distribution; Technology Adoption; Applications and Software; Change Management; Fashion Industry; Consumer Products Industry; Retail Industry; United States; Ohio

Educators

October 20, 2020
Article

Expanding AI's Impact with Organizational Learning

By: Sam Ransbotham, Shervin Khodabandeh, David Kiron, François Candelon, Michael Chu and Burt LaFountain

Most companies developing AI capabilities have yet to gain significant financial benefits from their efforts. Only when organizations add the ability to learn with AI do significant benefits become likely. View Details

Keywords: AI and Machine Learning; Learning; Adoption

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2020
Book

Work, Mate, Marry, Love: How Machines Shape Our Human Destiny

By: Debora L. Spar

Covering a time frame that ranges from 8000 BC to the present, and drawing upon both Marxist and feminist theories, the book argues that nearly all the decisions we make in our most intimate lives—whom to marry, how to have children, how to have sex, how to think about... View Details

2021
Working Paper

First Law of Motion: Influencer Video Advertising on TikTok

By: Jeremy Yang, Juanjuan Zhang and Yuhan Zhang

This paper engineers an intuitive feature that is predictive of the causal effect of influencer video advertising on product sales. We propose the concept of m-score, a summary statistic that captures the extent to which a product is advertised in the most engaging... View Details

Keywords: Influencer Advertising; Video Advertising; Computer Vision; Machine Learning; Advertising; Online Technology

SSRN

2024
Working Paper

Learning to Cover: Online Learning and Optimization with Irreversible Decisions

By: Alexander Jacquillat and Michael Lingzhi Li

Keywords: Buildings and Facilities; AI and Machine Learning; Geographic Location; Strategic Planning

29 May 2013
Blog Post

Reflections and learnings

So, without further ado, the 7* lessons that made this all worthwhile for me: Winning is not easy: It’s easy to look at an industry leader like Sephora and imagine a seamlessly polished machine cranking out innovation after the next. Not... View Details

Keywords: Consumer Products / Retail

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

2024
Working Paper

Advancing Personalization: How to Experiment, Learn & Optimize

By: Aurelie Lemmens, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela and Oded Netzer

Personalization has become the heartbeat of modern marketing. Advances in causal inference and machine learning enable companies to understand how the same marketing action can impact the choices of individual customers differently. This article provides an academic... View Details

Keywords: Personalization; Targeting; Experiments; Observational Studies; Policy Implementation; Policy Evaluation; Customization and Personalization; Marketing Strategy; AI and Machine Learning

SSRN

February 2018
Article

Retention Futility: Targeting High-Risk Customers Might Be Ineffective.

By: Eva Ascarza

Companies in a variety of sectors are increasingly managing customer churn proactively, generally by detecting customers at the highest risk of churning and targeting retention efforts towards them. While there is a vast literature on developing churn prediction models... View Details

Keywords: Retention/churn; Proactive Churn Management; Field Experiments; Heterogeneous Treatment Effect; Machine Learning; Customer Relationship Management; Risk Management

Article

Algorithms Need Managers, Too

By: Michael Luca, Jon Kleinberg and Sendhil Mullainathan

Algorithms are powerful predictive tools, but they can run amok when not applied properly. Consider what often happens with social media sites. Today many use algorithms to decide which ads and links to show users. But when these algorithms focus too narrowly on... View Details

Keywords: Machine Learning; Algorithms; Predictive Analytics; Management; Big Data; Analytics and Data Science

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July 2019
Teaching Note

Miroglio Fashion

By: Sunil Gupta

Teaching Note for HBS Nos. 519-053, 519-070, and 519-072. View Details

Keywords: Inventory Management; Demand Forecasting; Artificial Intelligence; Machine Learning; Forecasting and Prediction; Operations; Management; Decision Making; Marketing; AI and Machine Learning; Apparel and Accessories Industry; Fashion Industry

2021
Working Paper

Invisible Primes: Fintech Lending with Alternative Data

By: Marco Di Maggio, Dimuthu Ratnadiwakara and Don Carmichael

We exploit anonymized administrative data provided by a major fintech platform to investigate whether using alternative data to assess borrowers’ creditworthiness results in broader credit access. Comparing actual outcomes of the fintech platform’s model to... View Details

Keywords: Fintech Lending; Alternative Data; Machine Learning; Algorithm Bias; Finance; Information Technology; Financing and Loans; Analytics and Data Science; Credit

Article

Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error

By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III

Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving... View Details

Keywords: Autoencoder Networks; Pattern Detection; Subset Scanning; Computer Vision; Statistical Methods And Machine Learning; Machine Learning; Deep Learning; Data Mining; Big Data; Large-scale Systems; Mathematical Methods; Analytics and Data Science

September 2018 (Revised December 2019)
Case

Zebra Medical Vision

By: Shane Greenstein and Sarah Gulick

An Israeli startup founded in 2014, Zebra Medical Vision developed algorithms that produced diagnoses from X-rays, mammograms, and CT-scans. The algorithms used deep learning and digitized radiology scans to create software that could assist doctors in making... View Details

Educators

August 2018 (Revised October 2020)
Case

Tailor Brands: Artificial Intelligence-Driven Branding

By: Jill Avery

Using proprietary artificial intelligence technology, startup Tailor Brands set out to democratize branding by allowing small businesses to create their brand identities by automatically generating logos in just minutes at minimal cost with no branding or design skills... View Details

Educators

September 2014
Article

Advancing Consumer Neuroscience

By: Ale Smidts, Ming Hsu, Alan G. Sanfey, Maarten A. S. Boksem, Richard B. Ebstein, Scott A. Huettel, Joe W. Kable, Uma R. Karmarkar, Shinobu Kitayama, Brian Knutson, Israel Liberzon, Terry Lohrenz, Mirre Stallen and Carolyn Yoon

In the first decade of consumer neuroscience, strong progress has been made in understanding how neuroscience can inform consumer decision making. Here, we sketch the development of this discipline and compare it to that of the adjacent field of neuroeconomics. We... View Details

Keywords: Consumer Neuroscience; Neuroeconomics; Social Neuroscience; Genes; Machine Learning; Meta-analysis; Consumer Behavior; Decision Making; Science

Research Summary

Overview

By: Prithwiraj Choudhury

Prithwiraj (Raj) Choudhury is the Lumry Family Associate Professor at the Harvard Business School. He was an Assistant Professor at Wharton prior to joining Harvard. His research is focused on studying the Future of Work, especially the changing Geography of Work. In... View Details

Keywords: Geography; Mobility; Migration; Multinational; Productivity; Crucible Experiences; Machine Learning; Geographic Location; Technology Industry; India; United States; China

Article

Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy

By: Edward Glaeser, Andrew Hillis, Scott Duke Kominers and Michael Luca

The proliferation of big data makes it possible to better target city services like hygiene inspections, but city governments rarely have the in-house talent needed for developing prediction algorithms. Cities could hire consultants, but a cheaper alternative is to... View Details

Keywords: User-generated Content; Operations; Tournaments; Policy-making; Machine Learning; Online Platforms; Analytics and Data Science; Mathematical Methods; City; Infrastructure; Business Processes; Government and Politics