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- May–June 2024
- Article
Should Your Brand Hire a Virtual Influencer?
By: Serim Hwang, Shunyuan Zhang, Xiao Liu and Kannan Srinivasan
Followers respond more favorably to sponsored posts by virtual influencers versus those by humans, costs are lower, and creating an influencer from scratch allows marketers to introduce more diversity.
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Hwang, Serim, Shunyuan Zhang, Xiao Liu, and Kannan Srinivasan. "Should Your Brand Hire a Virtual Influencer?" Harvard Business Review 102, no. 3 (May–June 2024): 56–60.
- 2024
- Working Paper
Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions
We investigate whether corporate officers should grant managers discretion to override AI-driven demand forecasts and labor scheduling tools. Analyzing five years of administrative data from a large grocery retailer using such an AI tool, encompassing over 500 stores,...
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Keywords:
AI and Machine Learning;
Forecasting and Prediction;
Working Conditions;
Performance Productivity
Kwon, Caleb, Ananth Raman, and Jorge Tamayo. "Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions." Working Paper, April 2024.
- 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
- Case
Teamworks: Tackling a Forecasting Fumble (A)
By: N. Louis Shipley and Stacy Straaberg
In late March 2018, Teamworks CEO Zach Maurides learned Q1 2018 sales were at risk for a large forecasting miss. Founded in 2004, Teamworks’s software application assisted support staff in messaging, scheduling, and sharing documents with collegiate and professional...
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Keywords:
Acquisition;
Business Growth and Maturation;
Communication Strategy;
Decisions;
Forecasting and Prediction;
Business Cycles;
Technological Innovation;
Sports;
Growth and Development Strategy;
Resource Allocation;
Marketing;
Sales;
Business Strategy;
Expansion;
Sports Industry;
Technology Industry;
United States;
North Carolina
- March 2024
- Supplement
Teamworks: Tackling a Forecasting Fumble (B)
By: N. Louis Shipley, Stacy Straaberg and Tom Quinn
In late March 2018, Teamworks CEO Zach Maurides learned Q1 2018 sales were at risk for a large forecasting miss. Founded in 2004, Teamworks’s software application assisted support staff in messaging, scheduling, and sharing documents with collegiate and professional...
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Keywords:
Acquisition;
Business Growth and Maturation;
Communication Strategy;
Decisions;
Forecasting and Prediction;
Business Cycles;
Technological Innovation;
Sports;
Growth and Development Strategy;
Resource Allocation;
Marketing;
Sales;
Business Strategy;
Expansion;
Sports Industry;
Technology Industry;
United States;
North Carolina
- March 2024
- Simulation
'Storrowed'
By: Mitchell Weiss
The game was built to accompany "Storrowed": A Generative AI Exercise, available through Harvard Business Publishing. The game adds a timing element to "Storrowed" and enables the teacher to reward teams for strong prompts or penalize teams for believing AI...
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Keywords:
AI and Machine Learning
- March 2024
- Teaching Note
'Storrowed': A Generative AI Exercise
By: Mitchell Weiss
Teaching Note for HBS Exercise No. 824-188. “Storrowed” is an exercise to help participants raise their proficiency with generative AI. It begins by highlighting a problem: trucks getting wedged underneath bridges in Boston, Massachusetts on the city’s Storrow Drive....
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- 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
Weiss, Mitchell. "'Storrowed': A Generative AI Exercise." Harvard Business School Exercise 824-188, March 2024.
- 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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Keywords:
Customer Relationship Management;
Analysis;
Growth and Development Strategy;
Retail Industry;
United States
Ascarza, Eva, Bruce Hardie, Michael Ross, and Peter S. Fader. "Madrigal: Conducting a Customer-Base Audit." Harvard Business School Case 524-046, March 2024.
- 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;
Prejudice and Bias;
Customization and Personalization;
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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Keywords:
CFO;
Forecasting;
Corporate Finance;
Forecasting and Prediction;
Financial Management;
United States
Egan, Mark. "Navigating the Future: Managing Financial Forecasts." Harvard Business School Module Note 224-075, March 2024.
- 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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