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Show Results For
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All HBS Web
(648)
- News (146)
- Research (402)
- Events (13)
- Multimedia (10)
- Faculty Publications (288)
- 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,...
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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.
- Article
Vungle Inc. Improves Monetization Using Big-Data Analytics
By: Bert De Reyck, Ioannis Fragkos, Yael Grushka-Cockayne, Casey Lichtendahl, Hammond Guerin and Andrew Kritzer
The advent of big data has created opportunities for firms to customize their products and services to unprecedented levels of granularity. Using big data to personalize an offering in real time, however, remains a major challenge. In the mobile advertising industry,...
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Keywords:
Big Data;
Monetization;
Data and Data Sets;
Advertising;
Mobile Technology;
Customization and Personalization;
Performance Improvement
De Reyck, Bert, Ioannis Fragkos, Yael Grushka-Cockayne, Casey Lichtendahl, Hammond Guerin, and Andrew Kritzer. "Vungle Inc. Improves Monetization Using Big-Data Analytics." Interfaces 47, no. 5 (September–October 2017): 454–466.
- 25 Aug 2018
- News
Are Superstar Firms and Amazon Effects Reshaping the Economy?
- October 2019
- Article
Making Sense of Recommendations
By: Michael Yeomans, Anuj Shah, Sendhil Mullainathan and Jon Kleinberg
Computer algorithms are increasingly being used to predict people's preferences and make recommendations. Although people frequently encounter these algorithms because they are cheap to scale, we do not know how they compare to human judgment. Here, we compare computer...
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Keywords:
Recommender Systems;
Artificial Intelligence;
Interpretability;
Information Technology;
Forecasting and Prediction;
Decision Making;
Attitudes
Yeomans, Michael, Anuj Shah, Sendhil Mullainathan, and Jon Kleinberg. "Making Sense of Recommendations." Journal of Behavioral Decision Making 32, no. 4 (October 2019): 403–414.
- 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.)
- 14 Nov 2016
- News
Why Big Data Isn’t Enough
- 2019
- Article
More Amazon Effects: Online Competition and Pricing Behaviors
By: Alberto Cavallo
I study how online competition, with its shrinking margins, algorithmic pricing technologies, and the transparency of the web, can change the pricing behavior of large retailers in the U.S. and affect aggregate inflation dynamics. In particular, I show that in the past...
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Keywords:
Amazon;
Online Prices;
Inflation;
Uniform Pricing;
Price Stickiness;
Monetary Economics;
Economics;
Macroeconomics;
Inflation and Deflation;
System Shocks;
United States
Cavallo, Alberto. "More Amazon Effects: Online Competition and Pricing Behaviors." Jackson Hole Economic Symposium Conference Proceedings (Federal Reserve Bank of Kansas City) (2019).
Edward McFowland III
Edward McFowland III is an Assistant Professor in the Technology and Operations Management Unit at Harvard Business School. He teaches the first-year TOM course in the required curriculum.
Professor McFowland’s research interests – which lie at the... View Details
- Article
Adaptive Machine Unlearning
By: Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi and Chris Waites
Data deletion algorithms aim to remove the influence of deleted data points from trained models at a cheaper computational cost than fully retraining those models. However, for sequences of deletions, most prior work in the non-convex setting gives valid guarantees...
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Gupta, Varun, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, and Chris Waites. "Adaptive Machine Unlearning." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- 25 Sep 2015
- Blog Post
4 Challenges All Early-Stage Startups Face
During our first year at HBS, my classmates and I took the opportunity to build cleverlayover, a flight search engine that uses advanced algorithms to find flights hundreds of dollars cheaper than any other search engine. We were able to...
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- 21 Mar 2019
- Working Paper Summaries
Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions
- 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.)
- August 2021 (Revised April 2022)
- Case
Intenseye: Powering Workplace Health and Safety with AI
By: Michael W. Toffel and Youssef Abdel Aal
Intenseye was a Turkey-based technology startup that deployed machine learning algorithms to workplace camera feeds in order to identify unsafe worker actions and unsafe working conditions, in order to help improve worker safety. The case describes how Intenseye’s...
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Keywords:
Privacy;
Product Development;
Operations;
Technological Innovation;
Value Creation;
Production;
Distribution;
Safety;
Risk and Uncertainty;
Technology Industry;
Manufacturing Industry;
Distribution Industry;
Turkey;
Middle East;
United States
Toffel, Michael W., and Youssef Abdel Aal. "Intenseye: Powering Workplace Health and Safety with AI." Harvard Business School Case 622-037, August 2021. (Revised April 2022.)
- 15 Sep 2020
- Video
Competing in the Age of AI and Digital Transformation
- 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).
- February 2021 (Revised March 2022)
- Case
Marvin: A Personalized Telehealth Approach to Mental Health
By: Regina E. Herzlinger, Eshani Sharma, Andrew Nguyen, Thomas Arsenault, Carin-Isabel Knoop and Julia Kelley
More than one third of Americans were said to suffer some type of behavioral health ailment at some point in their lifetime, with many people requiring chronic therapy or intervention. Despite significant clinical needs, access to reliable treatment has been difficult...
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Keywords:
Mental Health;
Applications;
Startup Management;
Telehealth;
Health Care Entrepreneurship;
Health & Wellness;
Health Care;
Health Care and Treatment;
Customization and Personalization;
Internet and the Web;
Entrepreneurship;
Growth and Development Strategy;
Applications and Software
Herzlinger, Regina E., Eshani Sharma, Andrew Nguyen, Thomas Arsenault, Carin-Isabel Knoop, and Julia Kelley. "Marvin: A Personalized Telehealth Approach to Mental Health." Harvard Business School Case 321-127, February 2021. (Revised March 2022.)
- 06 May 2012
- News
FTC Wants in on Google Antitrust Action
- 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...
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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.
- 8:30 AM – 6:45 PM EDT, 15 Sep 2020
- Virtual Programming
Competing in the Age of AI and Digital Transformation
How are companies today using artificial intelligence (AI) to respond to business challenges? During this session, professors Karim Lakhani and Macro Iansiti, coauthors of the book Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the...
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