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- News (145)
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- Faculty Publications (289)
Show Results For
-
All HBS Web
(657)
- News (145)
- Research (402)
- Events (13)
- Multimedia (10)
- Faculty Publications (289)
- 27 May 2015
- Blog Post
What is an HBS Section?
10 sections of 90+ people in your first year. You find out during your first week at HBS which section you’ll be in (A-J), and they use an algorithm to make sure each section has a diverse cross-section of people from different countries,...
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- 17 May 2022
- Cold Call Podcast
Delivering a Personalized Shopping Experience with AI
Keywords:
Re: Jill J. Avery
- 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...
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Freund, Daniel, Thodoris Lykouris, Elisabeth Paulson, Bradley Sturt, and Wentao Weng. "Group Fairness in Dynamic Refugee Assignment." Harvard Business School Working Paper, No. 23-047, February 2023.
- November–December 2018
- Article
Online Network Revenue Management Using Thompson Sampling
By: Kris J. Ferreira, David Simchi-Levi and He Wang
We consider a network revenue management problem where an online retailer aims to maximize revenue from multiple products with limited inventory constraints. As common in practice, the retailer does not know the consumer's purchase probability at each price and must...
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Keywords:
Online Marketing;
Revenue Management;
Revenue;
Management;
Marketing;
Internet and the Web;
Price;
Mathematical Methods
Ferreira, Kris J., David Simchi-Levi, and He Wang. "Online Network Revenue Management Using Thompson Sampling." Operations Research 66, no. 6 (November–December 2018): 1586–1602.
- 17 Sep 2021
- News
AI Can Help Address Inequity — If Companies Earn Users’ Trust
- 2022
- Working Paper
Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions
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...
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Keywords:
Employees;
Human Capital;
Performance;
Applications and Software;
Management Skills;
Management Practices and Processes;
Retail Industry
Kwon, Caleb, Ananth Raman, and Jorge Tamayo. "Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions." Working Paper, December 2022.
- 14 Nov 2018
- HBS Seminar
Lindsey Cameron, University of Michigan Ross School of Business
- 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.
- Teaching Interest
Big Data Analytics and Machine Learning
Big data in the context of marketing, management, and innovation strategy. Machine Learning algorithms and tools.
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- September 2020 (Revised July 2022)
- Supplement
Spreadsheet Supplement to Artea (B) and (C)
By: Eva Ascarza and Ayelet Israeli
Spreadsheet Supplement to "Artea (B): Including Customer-level Demographic Data" and "Artea (C): Potential Discrimination through Algorithmic Targeting"
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- 14 Jun 2017
- Working Paper Summaries
Minimizing Justified Envy in School Choice: The Design of New Orleans' OneApp
- 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.
- Awards
John D. C. Little Award
By: Shunyuan Zhang
Nominated for the 2022 John D. C. Little Award for “Frontiers: Can an AI Algorithm Mitigate Racial Economic Inequality? An Analysis in the Context of Airbnb” (Marketing Science, September–October 2021) with Nitin Mehta, Param Singh, and Kannan Srinivasan.
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- 2019
- Article
An Empirical Study of Rich Subgroup Fairness for Machine Learning
By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
Kearns et al. [2018] recently proposed a notion of rich subgroup fairness intended to bridge the gap between statistical and individual notions of fairness. Rich subgroup fairness picks a statistical fairness constraint (say, equalizing false positive rates across...
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Kearns, Michael J., Seth Neel, Aaron Leon Roth, and Zhiwei Steven Wu. "An Empirical Study of Rich Subgroup Fairness for Machine Learning." Proceedings of the Conference on Fairness, Accountability, and Transparency (2019): 100–109.
- 16 Apr 2019
- News
Fewer small businesses expected to hire new employees in 2019
- 28 Mar 2018
- HBS Seminar
Tim O’Reilly, O’Reilly Media
- March 2017 (Revised September 2017)
- Case
Facebook Fake News in the Post-Truth World
By: John R. Wells and Carole A. Winkler
In January 2017, Mark Zuckerberg, founder and CEO of Facebook, was surrounded by controversy. The election of Donald Trump as the next president of the United States in November 2016 had triggered a national storm of protests, and many attributed Trump’s victory to...
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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;
Internet and the Web;
Applications and Software;
Information Infrastructure;
Digital Platforms;
Internet and the Web;
Mobile and Wireless Technology;
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., and Carole A. Winkler. "Facebook Fake News in the Post-Truth World." Harvard Business School Case 717-473, March 2017. (Revised September 2017.)
- 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).
- 11 May 2021
- News
Law Firms Are Building A.I. Expertise as Regulation Looms
- 2010
- Chapter
Deferred Acceptance Algorithms: History, Theory, Practice
By: Alvin E. Roth
The deferred acceptance algorithm proposed by Gale and Shapley (1962) has had a profound influence on market design, both directly, by being adapted into practical matching mechanisms, and indirectly, by raising new theoretical questions. Deferred acceptance algorithms...
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