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- News (73)
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- Faculty Publications (148)
Show Results For
-
All HBS Web
(376)
- News (73)
- Research (251)
- Events (6)
- Multimedia (1)
- Faculty Publications (148)
- 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...
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Keywords:
by Rachel Layne
- 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...
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by Kara Baskin
- March 2022
- Article
Learning to Rank an Assortment of Products
By: Kris Ferreira, Sunanda Parthasarathy and Shreyas Sekar
We consider the product ranking challenge that online retailers face when their customers typically behave as “window shoppers”: they form an impression of the assortment after browsing products ranked in the initial positions and then decide whether to continue...
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Keywords:
Online Learning;
Product Ranking;
Assortment Optimization;
Learning;
Internet and the Web;
Product Marketing;
Consumer Behavior;
E-commerce
Ferreira, Kris, Sunanda Parthasarathy, and Shreyas Sekar. "Learning to Rank an Assortment of Products." Management Science 68, no. 3 (March 2022): 1828–1848.
- November 2021 (Revised December 2021)
- Supplement
PittaRosso (B): Human and Machine Learning
By: Ayelet Israeli
This case supplements the "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion" case, and provides major highlights on what happened at the company since the first case.
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Keywords:
Artificial Intelligence;
Pricing;
Pricing Algorithm;
Pricing Decisions;
Pricing Strategy;
Pricing Structure;
Promotion;
Promotions;
Online Marketing;
Data-driven Decision-making;
Data-driven Management;
Retail;
Retail Analytics;
Price;
Advertising Campaigns;
Analytics and Data Science;
Analysis;
Digital Marketing;
Budgets and Budgeting;
Marketing Strategy;
Marketing;
Transformation;
Decision Making;
AI and Machine Learning;
Retail Industry;
Italy
Israeli, Ayelet. "PittaRosso (B): Human and Machine Learning." Harvard Business School Supplement 522-047, November 2021. (Revised December 2021.)
- Article
Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions
By: Andrea Blasco, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian and Karim R. Lakhani
Open data science and algorithm development competitions offer a unique avenue for rapid discovery of better computational strategies. We highlight three examples in computational biology and bioinformatics research where the use of competitions has yielded significant...
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Keywords:
Computational Biology;
Bioinformatics;
Innovation Competitions;
Research;
Collaborative Innovation and Invention
Blasco, Andrea, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian, and Karim R. Lakhani. "Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions." PLoS ONE 14, no. 9 (September 2019).
- 25 May 2021
- Research & Ideas
White Airbnb Hosts Earn More. Can AI Shrink the Racial Gap?
White people who host rental properties on Airbnb earn significantly more per year than Black hosts, but a “race blind” pricing algorithm could help close that income gap, new research shows. Black hosts who rely on Airbnb’s View Details
- September 2022 (Revised November 2022)
- Teaching Note
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli
Teaching Note for HBS Case No. 522-046.
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Keywords:
Artificial Intelligence;
Pricing;
Pricing Algorithm;
Pricing Decisions;
Pricing Strategy;
Pricing Structure;
Promotion;
Promotions;
Online Marketing;
Data-driven Decision-making;
Data-driven Management;
Retail;
Retail Analytics;
Price;
Advertising Campaigns;
Analytics and Data Science;
Analysis;
Digital Marketing;
Budgets and Budgeting;
Marketing Strategy;
Transformation;
Decision Making;
AI and Machine Learning;
Retail Industry;
Italy
- 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...
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Neel, Seth, Aaron Leon Roth, and Zhiwei Steven Wu. "How to Use Heuristics for Differential Privacy." Proceedings of the IEEE Annual Symposium on Foundations of Computer Science (FOCS) 60th (2019).
- Research Summary
Overview
By: Iavor I. Bojinov
My research focuses on overcoming the methodological and operational challenges of developing data science capabilities, what I call data science operations. Today, within leading digital companies, data science is no longer confined to technical teams but is pervasive...
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- 2022
- Working Paper
Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing
By: Kirk Bansak and Elisabeth Paulson
This study proposes two new dynamic assignment algorithms to match refugees and asylum seekers to geographic localities within a host country. The first, currently implemented in a multi-year pilot in Switzerland, seeks to maximize the average predicted employment...
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Bansak, Kirk, and Elisabeth Paulson. "Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing." Harvard Business School Working Paper, No. 23-048, January 2022.
- September 2017
- Article
It Doesn't Hurt to Ask: Question-asking Increases Liking
By: K. Huang, M. Yeomans, A.W. Brooks, J. Minson and F. Gino
Conversation is a fundamental human experience, one that is necessary to pursue intrapersonal and interpersonal goals across myriad contexts, relationships, and modes of communication. In the current research, we isolate the role of an understudied conversational...
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Keywords:
Question-asking;
Liking;
Responsiveness;
Conversation;
Natural Language Processing;
Interpersonal Communication;
Behavior
Huang, K., M. Yeomans, A.W. Brooks, J. Minson, and F. Gino. "It Doesn't Hurt to Ask: Question-asking Increases Liking." Journal of Personality and Social Psychology 113, no. 3 (September 2017): 430–452.
- Article
Conversational Receptiveness: Expressing Engagement with Opposing Views
By: M. Yeomans, J. Minson, H. Collins, H. Chen and F. Gino
We examine “conversational receptiveness”—the use of language to communicate one’s willingness to thoughtfully engage with opposing views. We develop an interpretable machine-learning algorithm to identify the linguistic profile of receptiveness (Studies 1A-B). We then...
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Keywords:
Receptiveness;
Natural Language Processing;
Disagreement;
Interpersonal Communication;
Relationships;
Conflict Management
Yeomans, M., J. Minson, H. Collins, H. Chen, and F. Gino. "Conversational Receptiveness: Expressing Engagement with Opposing Views." Organizational Behavior and Human Decision Processes 160 (September 2020): 131–148.
- Blog
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...
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- 15 Nov 2022
- Op-Ed
Why TikTok Is Beating YouTube for Eyeball Time (It’s Not Just the Dance Videos)
five times faster than the United Breaks Guitars video. The reason, it seemed, was that it spread not from person to person, but by algorithm. It spread because the algorithm noticed that if the song was served to people on TikTok, many...
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Keywords:
by John Deighton and Leora Kornfeld
- September 2020 (Revised February 2024)
- Teaching Note
Artea (A), (B), (C), and (D): Designing Targeting Strategies
By: Eva Ascarza and Ayelet Israeli
Teaching Note for HBS No. 521-021,521-022,521-037,521-043. This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and...
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- September 2019 (Revised September 2019)
- Case
Facebook Fake News in the Post-Truth World
By: John R. Wells, Carole A. Winkler and Benjamin Weinstock
In August 2019, Mark Zuckerberg, founder and CEO of Facebook, was surrounded by controversy. The first major storm of protest followed the surprise election of Donald Trump as President of the United States on November 8, 2016; many put the blame at the door of fake...
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Keywords:
Facebook;
Fake News;
Mark Zuckerberg;
Donald Trump;
Algorithms;
Social Networks;
Partisanship;
Social Media;
App Development;
Instagram;
WhatsApp;
Smartphone;
Silicon Valley;
Office Space;
Digital Strategy;
Democracy;
Entry Barriers;
Online Platforms;
Controversy;
Tencent;
Agility;
Social Networking;
Gaming;
Gaming Industry;
Computer Games;
Mobile Gaming;
Messaging;
Monetization Strategy;
Advertising;
Digital Marketing;
Business Ventures;
Acquisition;
Mergers and Acquisitions;
Business Growth and Maturation;
Business Headquarters;
Business Organization;
For-Profit Firms;
Trends;
Communication;
Communication Technology;
Forms of Communication;
Interactive Communication;
Interpersonal Communication;
Talent and Talent Management;
Crime and Corruption;
Voting;
Demographics;
Entertainment;
Games, Gaming, and Gambling;
Moral Sensibility;
Values and Beliefs;
Initial Public Offering;
Profit;
Revenue;
Geography;
Geographic Location;
Global Range;
Local Range;
Country;
Cross-Cultural and Cross-Border Issues;
Globalized Firms and Management;
Globalized Markets and Industries;
Governing Rules, Regulations, and Reforms;
Government and Politics;
International Relations;
National Security;
Political Elections;
Business History;
Recruitment;
Selection and Staffing;
Information Management;
Information Publishing;
News;
Newspapers;
Innovation and Management;
Innovation Strategy;
Technological Innovation;
Knowledge Dissemination;
Human Capital;
Law;
Leadership Development;
Leadership Style;
Leading Change;
Business or Company Management;
Crisis Management;
Goals and Objectives;
Growth and Development Strategy;
Growth Management;
Management Practices and Processes;
Management Style;
Management Systems;
Management Teams;
Managerial Roles;
Marketing Channels;
Social Marketing;
Network Effects;
Market Entry and Exit;
Digital Platforms;
Marketplace Matching;
Industry Growth;
Industry Structures;
Monopoly;
Media;
Product Development;
Service Delivery;
Corporate Social Responsibility and Impact;
Mission and Purpose;
Organizational Change and Adaptation;
Organizational Culture;
Organizational Structure;
Public Ownership;
Problems and Challenges;
Business and Community Relations;
Business and Government Relations;
Groups and Teams;
Networks;
Rank and Position;
Opportunities;
Behavior;
Emotions;
Identity;
Power and Influence;
Prejudice and Bias;
Reputation;
Social and Collaborative Networks;
Status and Position;
Trust;
Society;
Civil Society or Community;
Culture;
Public Opinion;
Social Issues;
Societal Protocols;
Strategy;
Adaptation;
Business Strategy;
Commercialization;
Competition;
Competitive Advantage;
Competitive Strategy;
Corporate Strategy;
Customization and Personalization;
Diversification;
Expansion;
Horizontal Integration;
Segmentation;
Information Technology;
Internet and the Web;
Mobile and Wireless Technology;
Applications and Software;
Information Infrastructure;
Valuation;
Advertising Industry;
Communications Industry;
Entertainment and Recreation Industry;
Information Industry;
Information Technology Industry;
Journalism and News Industry;
Media and Broadcasting Industry;
Service Industry;
Technology Industry;
Telecommunications Industry;
Video Game Industry;
United States;
California;
Sunnyvale;
Russia
Wells, John R., Carole A. Winkler, and Benjamin Weinstock. "Facebook Fake News in the Post-Truth World." Harvard Business School Case 720-373, September 2019. (Revised September 2019.)
- 2020
- Working Paper
Machine Learning for Pattern Discovery in Management Research
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used as an observation for further inductive or abductive research, but should not be treated as the result of a...
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Keywords:
Machine Learning;
Theory Building;
Induction;
Decision Trees;
Random Forests;
K-nearest Neighbors;
Neural Network;
P-hacking;
Analytics and Data Science;
Analysis
Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Harvard Business School Working Paper, No. 19-032, September 2018. (Revised June 2020.)
- 2023
- Article
On the Impact of Actionable Explanations on Social Segregation
By: Ruijiang Gao and Himabindu Lakkaraju
As predictive models seep into several real-world applications, it has become critical to ensure that individuals who are negatively impacted by the outcomes of these models are provided with a means for recourse. To this end, there has been a growing body of research...
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Gao, Ruijiang, and Himabindu Lakkaraju. "On the Impact of Actionable Explanations on Social Segregation." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 10727–10743.
- 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.
- May 2020
- Article
Scalable Holistic Linear Regression
By: Dimitris Bertsimas and Michael Lingzhi Li
We propose a new scalable algorithm for holistic linear regression building on Bertsimas & King (2016). Specifically, we develop new theory to model significance and multicollinearity as lazy constraints rather than checking the conditions iteratively. The resulting...
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Bertsimas, Dimitris, and Michael Lingzhi Li. "Scalable Holistic Linear Regression." Operations Research Letters 48, no. 3 (May 2020): 203–208.