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- April 2024
- Article
Detecting Routines: Applications to Ridesharing CRM
By: Ryan Dew, Eva Ascarza, Oded Netzer and Nachum Sicherman
Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which we define as repeated behaviors with recurring, temporal...
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Keywords:
Ride-sharing;
Routine;
Machine Learning;
Customer Relationship Management;
Consumer Behavior;
Segmentation
Dew, Ryan, Eva Ascarza, Oded Netzer, and Nachum Sicherman. "Detecting Routines: Applications to Ridesharing CRM." Journal of Marketing Research (JMR) 61, no. 2 (April 2024): 368–392.
- March 2024
- Exercise
"Storrowed": A Generative AI Exercise
By: Mitchell Weiss
"Storrowed" is an exercise to help participants raise their capacity and curiosity for generative AI. It focuses on generative AI for problem understanding and ideation, but can be adapted for use more broadly. Participants use generative AI tools to understand a...
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Keywords:
AI and Machine Learning
- March 2024
- Supplement
Madrigal: Conducting a Customer-Base Audit
By: Eva Ascarza, Peter Fader, Bruce G.S. Hardie and Michael Ross
This case presents a scenario where Madrigal, a U.S. retailer with a rich 20-year history and a solid loyalty program, faces a turning point with the arrival of a new CEO. This leadership change reveals a critical gap in understanding the customer base, prompting an...
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- March 2024
- Supplement
Madrigal: Conducting a Customer-Base Audit
By: Eva Ascarza, Bruce Hardie, Peter S. Fader and Michael Ross
This case presents a scenario where Madrigal, a U.S. retailer with a rich 20-year history and a solid loyalty program, faces a turning point with the arrival of a new CEO. This leadership change reveals a critical gap in understanding the customer base, prompting an...
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- March 2024
- Supplement
Madrigal: Conducting a Customer-Base Audit
By: Eva Ascarza, Bruce Hardie, Peter S. Fader and Michael Ross
This case presents a scenario where Madrigal, a U.S. retailer with a rich 20-year history and a solid loyalty program, faces a turning point with the arrival of a new CEO. This leadership change reveals a critical gap in understanding the customer base, prompting an...
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- March 2024
- Teaching Note
Madrigal: Conducting a Customer-Base Audit
By: Eva Ascarza, Peter S. Fader, Bruce Hardie and Michael Ross
Teaching Note for HBS Case No. 524-046. This case presents a scenario where Madrigal, a U.S. retailer with a rich 20-year history and a solid loyalty program, faces a turning point with the arrival of a new CEO. This leadership change reveals a critical gap in...
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- March 2024
- Case
Madrigal: Conducting a Customer-Base Audit
By: Eva Ascarza, Bruce Hardie, Michael Ross and Peter S. Fader
This case presents a scenario where Madrigal, a U.S. retailer with a rich 20-year history and a solid loyalty program, faces a turning point with the arrival of a new CEO. This leadership change reveals a critical gap in understanding the customer base, prompting an...
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Ascarza, Eva, Bruce Hardie, Michael Ross, and Peter S. Fader. "Madrigal: Conducting a Customer-Base Audit." Harvard Business School Case 524-046, March 2024.
- March 2024
- Teaching Note
Sensing (and Monetizing) Happiness at Hitachi
By: Ethan Bernstein and Cara Mazzucco
Please use the abstract, brief description, learning objectives, etc. from the case for which this is a teaching note.
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- 2023
- Working Paper
An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
By: Biyonka Liang and Iavor I. Bojinov
Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the...
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Liang, Biyonka, and Iavor I. Bojinov. "An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits." Harvard Business School Working Paper, No. 24-057, March 2024.
- March 2024
- Case
Governing OpenAI
By: Lynn S. Paine, Suraj Srinivasan and Will Hurwitz
In late November 2023, OpenAI’s new board of directors took stock of the situation. The company, which sought to develop artificial general intelligence (AGI)—computer systems with capabilities exceeding human abilities—was looking to regain its footing after a chaotic...
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Keywords:
Artificial Intelligence;
Board Of Directors;
Board Decisions;
Board Dynamics;
Business Ethics;
Corporate Boards;
Governance Changes;
Governance Structure;
Leadership Change;
Legal Aspects Of Business;
Nonprofit;
Nonprofit Governance;
Open Source;
Partnerships;
Regulation;
Strategy And Execution;
Technological Change;
AI and Machine Learning;
Corporate Governance;
Leadership;
Management;
Mission and Purpose;
Technological Innovation;
Technology Industry;
San Francisco;
United States
- March 2024
- Case
Unintended Consequences of Algorithmic Personalization
By: Eva Ascarza and Ayelet Israeli
“Unintended Consequences of Algorithmic Personalization” (HBS No. 524-052) investigates algorithmic bias in marketing through four case studies featuring Apple, Uber, Facebook, and Amazon. Each study presents scenarios where these companies faced public criticism for...
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Keywords:
Race;
Gender;
Marketing;
Diversity;
Customer Relationship Management;
Technology Industry;
Retail Industry;
United States
Ascarza, Eva, and Ayelet Israeli. "Unintended Consequences of Algorithmic Personalization." Harvard Business School Case 524-052, March 2024.
- March 2024
- Module Note
Navigating the Future: Managing Financial Forecasts
By: Mark Egan
This module note guides instructors on delivering a course module that focuses on understanding, developing, and using financial forecasts from a chief financial officer’s (CFO) perspective. The cases in the module equip students with an understanding of the techniques...
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Egan, Mark. "Navigating the Future: Managing Financial Forecasts." Harvard Business School Module Note 224-075, March 2024.
- February 2024
- Teaching Note
P-Will at DISCO
By: Ethan Bernstein
Please use the abstract, brief description, learning objectives, etc. from the case for which this is a teaching note.
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- February 2024
- Course Overview Note
The Anatomy of Fraud
By: Jonas Heese
Corporate fraud remains a serious problem. Learning how to detect and prevent it, and make better investment decisions has broad applicability for private and public market investors, as well as for people joining or running companies. This course note describes a...
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Heese, Jonas. "The Anatomy of Fraud." Harvard Business School Course Overview Note 124-076, February 2024.
- 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...
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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).
- February 2024
- Case
Taffi: Entrepreneurship in Saudi Arabia
By: Paul A. Gompers and Fares Khrais
Taffi was a tech-enabled fashion styling startup founded by Shahad Geoffrey in Saudi Arabia in 2020. Within three years of operating, Geoferry had pivoted the business multiple times. In 2023, Geoferry was attempting the business’s most ambitious pivot yet, shifting...
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- February 2024
- Teaching Note
Data-Driven Denim: Financial Forecasting at Levi Strauss
By: Mark Egan
Teaching Note for HBS Case No. 224-029. Levi Strauss & Co. (“Levi Strauss”) partnered with the IT services company Wipro to incorporate more sophisticated methods, such as machine learning, into their financial forecasting process starting in 2018. The decision to...
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- February 6, 2024
- Article
Find the AI Approach That Fits the Problem You’re Trying to Solve
By: George Westerman, Sam Ransbotham and Chiara Farronato
AI moves quickly, but organizations change much more slowly. What works in a lab may be wrong for your company right now. If you know the right questions to ask, you can make better decisions, regardless of how fast technology changes. You can work with your technical...
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Westerman, George, Sam Ransbotham, and Chiara Farronato. "Find the AI Approach That Fits the Problem You’re Trying to Solve." Harvard Business Review Digital Articles (February 6, 2024).
- February 2024
- Case
Continuity & Change at Boston Consulting Group
By: David G. Fubini, Suraj Srinivasan and David Lane
As the new CEO of Boston Consulting Group (BCG) since autumn 2021, Christoph Schweizer had big shoes to fill—his predecessor, Rich Lesser, had tripled the partnership’s total revenues and created digital initiatives that contributed 40+% of 2021 revenues, more than...
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Keywords:
Business Growth and Maturation;
Business Organization;
Change Management;
Talent and Talent Management;
Governance;
AI and Machine Learning;
Environmental Sustainability;
Leading Change;
Risk Management;
Organizational Culture;
Organizational Design;
Partners and Partnerships;
Consulting Industry
Fubini, David G., Suraj Srinivasan, and David Lane. "Continuity & Change at Boston Consulting Group." Harvard Business School Case 124-011, February 2024.
- February 2024
- Case
ReSpo.Vision: The Kickstart of an AI Sports Revolution
By: Paul A. Gompers, Elena Corsi and Nikolina Jonsson
This case study explores the growth journey of Polish computer vision sports start-up ReSpo.Vision in an emerging entrepreneurial ecosystem. By providing 3D data and analysis to soccer clubs, ReSpo.Vision achieved significant milestones with a €1 million seed round, an...
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Keywords:
Business Startups;
Business Plan;
Experience and Expertise;
Talent and Talent Management;
Decisions;
Decision Choices and Conditions;
Forecasting and Prediction;
Entrepreneurship;
Venture Capital;
AI and Machine Learning;
Analytics and Data Science;
Applications and Software;
Sports Industry;
Technology Industry;
Poland;
Europe