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(671)
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Show Results For
- All HBS Web
(671)
- News (144)
- Research (432)
- Events (20)
- Multimedia (12)
- Faculty Publications (312)
- 11 May 2022
- News
Finding It Hard to Get a New Job? Robot Recruiters Might Be to Blame
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
We introduce a new family of fairness definitions that interpolate between statistical and individual notions of fairness, obtaining some of the best properties of each. We show that checking whether these notions are satisfied is computationally hard in the worst... View Details
- 2021
- Article
Fair Influence Maximization: A Welfare Optimization Approach
By: Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice and Milind Tambe
Several behavioral, social, and public health interventions, such as suicide/HIV prevention or community preparedness against natural disasters, leverage social network information to maximize outreach. Algorithmic influence maximization techniques have been proposed... View Details
Rahmattalabi, Aida, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice, and Milind Tambe. "Fair Influence Maximization: A Welfare Optimization Approach." Proceedings of the AAAI Conference on Artificial Intelligence 35th (2021).
Making Workplaces Safer Through Machine Learning
Government agencies can use machine learning to improve the effectiveness of regulatory inspections. Our study found that OSHA could prevent as much as twice as many injuries—translating to up to 16,000 fewer workers injured and nearly $800 million in social... View Details
- February 2024
- Module Note
Data-Driven Marketing in Retail Markets
By: Ayelet Israeli
This note describes an eight-class sessions module on data-driven marketing in retail markets. The module aims to familiarize students with core concepts of data-driven marketing in retail, including exploring the opportunities and challenges, adopting best practices,... View Details
Keywords: Data; Data Analytics; Retail; Retail Analytics; Data Science; Business Analytics; ＂Marketing Analytics＂; Omnichannel; Omnichannel Retailing; Omnichannel Retail; DTC; Direct To Consumer Marketing; Ethical Decision Making; Algorithmic Bias; Privacy; A/B Testing; Descriptive Analytics; Prescriptive Analytics; Predictive Analytics; Analytics and Data Science; E-commerce; Marketing Channels; Demand and Consumers; Marketing Strategy; Retail Industry
Israeli, Ayelet. "Data-Driven Marketing in Retail Markets." Harvard Business School Module Note 524-062, February 2024.
- September–October 2023
- Article
Interpretable Matrix Completion: A Discrete Optimization Approach
By: Dimitris Bertsimas and Michael Lingzhi Li
We consider the problem of matrix completion on an n × m matrix. We introduce the problem of interpretable matrix completion that aims to provide meaningful insights for the low-rank matrix using side information. We show that the problem can be... View Details
Keywords: Mathematical Methods
Bertsimas, Dimitris, and Michael Lingzhi Li. "Interpretable Matrix Completion: A Discrete Optimization Approach." INFORMS Journal on Computing 35, no. 5 (September–October 2023): 952–965.
- 26 Mar 2025
- News
Behind the Research: Elisabeth Paulson
- 05 Mar 2020
- News
What one game show reveals about the American economy
- 2025
- Working Paper
Is Love Blind? AI-Powered Trading with Emotional Dividends
By: De-Rong Kong and Daniel Rabetti
We leverage the non-fungible tokens (NFTs) setting to assess the valuation of emotional dividends (LOVE), a long-standing empirical challenge in private-value markets such as art, antiques, and collectibles. Having created and validated our proxy, we use deep learning... View Details
Kong, De-Rong, and Daniel Rabetti. "Is Love Blind? AI-Powered Trading with Emotional Dividends." Working Paper, February 2025.
- 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
Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Strategic Management Journal 42, no. 1 (January 2021): 30–57.
- Article
Fast Subset Scan for Multivariate Spatial Biosurveillance
By: Daniel B. Neill, Edward McFowland III and Huanian Zheng
We extend the recently proposed ‘fast subset scan’ framework from univariate to multivariate data, enabling computationally efficient detection of irregular space-time clusters even when the numbers of spatial locations and data streams are large. These fast algorithms... View Details
- 09 Nov 2020
- News
Best Business Books 2020: Technology & innovation
- 13 May 2014
- News
Why Twitter Needs India
- 2017
- Working Paper
Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity
By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
Can new data sources from online platforms help to measure local economic activity? Government datasets from agencies such as the U.S. Census Bureau provide the standard measures of economic activity at the local level. However, these statistics typically appear only... View Details
Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity." Harvard Business School Working Paper, No. 18-022, September 2017. (Revised October 2017.)
- March 2007 (Revised April 2007)
- Case
The University of Utah and the Computer Graphics Revolution
By: H. Kent Bowen and Courtney Purrington
Computer science departments were new to universities in the 1960s, and the one created at the University of Utah by David Evans and Ivan Sutherland had a research mission to invent the field of computer graphics. Details the research process that led to many of the... View Details
Keywords: Engineering; Entrepreneurship; Management Practices and Processes; Mission and Purpose; Research and Development; Technology Adoption; Computer Industry; Education Industry; Utah
Bowen, H. Kent, and Courtney Purrington. "The University of Utah and the Computer Graphics Revolution." Harvard Business School Case 607-036, March 2007. (Revised April 2007.)
- September 2015
- Article
Design and Implementation of a Privacy Preserving Electronic Health Record Linkage Tool in Chicago
By: Abel Kho, John Cashy, Kathryn Jackson, Adam Pah, Satyender Goel, Jorn Boehnke, John Eric Humphries, Scott Duke Kominers and et al.
Objective
To design and implement a tool that creates a secure, privacy preserving linkage of electronic health record (EHR) data across multiple sites in a large metropolitan area in the United States (Chicago, IL), for use in clinical... View Details
To design and implement a tool that creates a secure, privacy preserving linkage of electronic health record (EHR) data across multiple sites in a large metropolitan area in the United States (Chicago, IL), for use in clinical... View Details
Keywords: Information; Customers; Safety; Rights; Ethics; Entrepreneurship; Health Care and Treatment; Health Industry; Chicago
Kho, Abel, John Cashy, Kathryn Jackson, Adam Pah, Satyender Goel, Jorn Boehnke, John Eric Humphries, Scott Duke Kominers, and et al. "Design and Implementation of a Privacy Preserving Electronic Health Record Linkage Tool in Chicago." Journal of the American Medical Informatics Association 22, no. 5 (September 2015): 1072–1080.
- March 2015 (Revised June 2015)
- Case
Medalogix
By: Richard G. Hamermesh and Matthew G. Preble
This case examines an exciting new approach to health care that will help care providers identify when hospice services are the appropriate type of care for patients. The company, Medalogix, already has a product on the market that uses a proprietary algorithm to... View Details
Keywords: Health Care; Health Care Entrepreneurship; Health Care Services; Implementing Strategy; Dissemination; Innovation; Market Selection; Health; Health Care and Treatment; Analytics and Data Science; Marketing Strategy; Innovation and Management; Innovation Strategy; Health Industry; United States
Hamermesh, Richard G., and Matthew G. Preble. "Medalogix." Harvard Business School Case 815-116, March 2015. (Revised June 2015.)
Ayelet Israeli
Ayelet Israeli is the Marvin Bower Associate Professor of Business Administration at the Harvard Business School Marketing Unit. She is the co-founder of the Customer Intelligence Lab at the Digital Data Design (D^3) Institute at Harvard Business School. She teaches... View Details
- February 26, 2024
- Article
Making Workplaces Safer Through Machine Learning
By: Matthew S. Johnson, David I. Levine and Michael W. Toffel
Machine learning algorithms can dramatically improve regulatory effectiveness. This short article describes the authors' scholarly work that shows how the U.S. Occupational Safety and Health Administration (OSHA) could have reduced nearly twice as many occupational... View Details
Keywords: Government Experimentation; Auditing; Inspection; Evaluation; Process Improvement; Government Administration; AI and Machine Learning; Safety; Governing Rules, Regulations, and Reforms
Johnson, Matthew S., David I. Levine, and Michael W. Toffel. "Making Workplaces Safer Through Machine Learning." Regulatory Review (February 26, 2024).
- 22 Sep 2021
- News