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- All HBS Web
(4,126)
- Faculty Publications (552)
- June 2024
- Case
SnapTravel: Betting on 'Super.com'
By: Reza Satchu and Tom Quinn
This case explores SnapTravel, a travel startup offering discounted hotel rooms, and its founders’ desire to pivot to a “super app” that saved customers money across many different purchase types. During the COVID-19 pandemic, Hussein Fazal and Henry Shi saw SnapTravel... View Details
Keywords: Business Growth and Maturation; Business Plan; Business Startups; Change Management; Disruption; Transformation; Volatility; Customer Focus and Relationships; Customer Value and Value Chain; Decisions; Income; Entrepreneurship; Geographic Scope; Cross-Cultural and Cross-Border Issues; Health Pandemics; Surveys; Knowledge Acquisition; Knowledge Use and Leverage; Leading Change; Crisis Management; Goals and Objectives; Risk Management; Consumer Behavior; Game Theory; Risk and Uncertainty; Adaptation; Diversification; Expansion; System Shocks; Accommodations Industry; Technology Industry; Canada; United States; Las Vegas
- June 2024
- Teaching Note
Beamery: Using Skills and AI to Modernize HR
By: Boris Groysberg, David Lane, Susan Pinckney and Alexis Lefort
Teaching Note for HBS Case No. 424-004. Unicorn human relationships startup Beamery evaluates it growth versus depth strategy as its strategic partners and customers could become future competitors in a quickly changing AI based human resources and talent management... View Details
Keywords: Analysis; Business Growth and Maturation; Business Model; Business Startups; Business Plan; Disruption; Transformation; Talent and Talent Management; Decisions; Diversity; Ethnicity; Gender; Nationality; Race; Residency; Higher Education; Learning; Entrepreneurship; Fairness; Cross-Cultural and Cross-Border Issues; Global Strategy; Growth and Development; AI and Machine Learning; Digital Platforms; Disruptive Innovation; Technological Innovation; Job Offer; Job Search; Knowledge Acquisition; Knowledge Use and Leverage; Product; Mission and Purpose; Strategic Planning; Problems and Challenges; Corporate Strategy; Equality and Inequality; Valuation; Value Creation; Employment Industry; United Kingdom
- June 2024 (Revised August 2024)
- Case
Revlon India's Turnaround: Navigating Online-Offline Decisions Using a Balanced Scorecard
By: Tatiana Sandino and Samuel Grad
Revlon India was founded as a joint venture in 1995, pairing the industrial conglomerate UMG with the global beauty brand Revlon, Inc. to bring international color cosmetics to India. After growing rapidly and pioneering the Beauty Advisor (BA) model in India, the... View Details
Keywords: Balanced Scorecard; Restructuring; Training; Supply Chain Management; Distribution; E-commerce; Business Model; Business Plan; Decision Choices and Conditions; Marketing Strategy; Alignment; Brands and Branding; Negotiation; Joint Ventures; Strategic Planning; Salesforce Management; Competition; Beauty and Cosmetics Industry; Beauty and Cosmetics Industry; Beauty and Cosmetics Industry; India
Sandino, Tatiana, and Samuel Grad. "Revlon India's Turnaround: Navigating Online-Offline Decisions Using a Balanced Scorecard." Harvard Business School Case 124-107, June 2024. (Revised August 2024.)
- June 2024
- Teaching Note
Major League Baseball: Changing the Rules of America's Pastime
By: Stephen A. Greyser, Mac Levin and Brent Schwarz
Teaching Note for HBS Case No. 924-307. The Teaching Note offers suggestions for using the case as a “product innovation” for different levels of students and their knowledge of baseball. Discussion plan questions for instructors are provided in the context of MLB’s... View Details
- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
Keywords: Heterogeneous Treatment Effect; Multi-task Learning; Representation Learning; Personalization; Promotion; Deep Learning; Field Experiments; Customer Focus and Relationships; Customization and Personalization
Huang, Ta-Wei, Eva Ascarza, and Ayelet Israeli. "Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization." Harvard Business School Working Paper, No. 24-076, June 2024.
- June 2024
- Article
Defining Who You Are by Whom You Serve? Strategies for Prosocial–Professional Identity Integration with Clients
By: Lakshmi Ramarajan and Julie Yen
Many professionals want to both achieve professional success and contribute to society. Yet, in some professional contexts, these aims are in tension because serving elite clients is considered the pinnacle of professional success, but professionals themselves may view... View Details
Keywords: Identity; Experience and Expertise; Corporate Social Responsibility and Impact; Behavior; Social Entrepreneurship
Ramarajan, Lakshmi, and Julie Yen. "Defining Who You Are by Whom You Serve? Strategies for Prosocial–Professional Identity Integration with Clients." Administrative Science Quarterly 69, no. 2 (June 2024): 515–567.
- June 2024
- Article
Rationalizing Outcomes: Interdependent Learning in Competitive Markets
By: Anoop R. Menon and Dennis Yao
In this article we use simulation models to explore interdependent learning in competitive markets. Such interactions require attention to both the mental representations held by the management of the focal firm as well as the beliefs of that management about the... View Details
Keywords: Mental Models; Strategic Interactions; Rationalization; Explanation-based View; Competition
Menon, Anoop R., and Dennis Yao. "Rationalizing Outcomes: Interdependent Learning in Competitive Markets." Strategy Science 9, no. 2 (June 2024): 97–117.
- 2024
- Working Paper
The Value of AI Innovations
By: Wilbur Xinyuan Chen, Terrence Tianshuo Shi and Suraj Srinivasan
We study the value of AI innovations as it diffuses across general and application sectors, using the United States Patent and Trademark Office’s (USPTO) AI patent dataset. Investors value these innovations more than others, as AI patents exhibit a 9% value premium,... View Details
Keywords: AI and Machine Learning; Valuation; Technological Innovation; Open Source Distribution; Patents; Policy; Knowledge Sharing; Technology Industry
Chen, Wilbur Xinyuan, Terrence Tianshuo Shi, and Suraj Srinivasan. "The Value of AI Innovations." Harvard Business School Working Paper, No. 24-069, May 2024.
- May 2024
- Article
Financial Innovation in the 21st Century: Evidence from U.S. Patents
By: Josh Lerner, Amit Seru, Nick Short and Yuan Sun
We develop a unique dataset of 24 thousand U.S. finance patents granted over the last two decades to explore the evolution and production of financial innovation. We use machine learning to identify the financial patents and extensively audit the results to ensure... View Details
Keywords: Banking; Investment Banks; Information Technology; Regulation; Patents; Innovation and Invention; Trends
Lerner, Josh, Amit Seru, Nick Short, and Yuan Sun. "Financial Innovation in the 21st Century: Evidence from U.S. Patents." Journal of Political Economy 132, no. 5 (May 2024): 1391–1449.
- 2024
- Working Paper
Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions
By: Caleb Kwon, Ananth Raman and Jorge Tamayo
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,... View Details
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... View Details
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.
- April–May 2024
- Article
Gone with the Big Data: Institutional Lender Demand for Private Information
By: Jung Koo Kang
I explore whether big-data sources can crowd out the value of private information acquired through lending relationships. Institutional lenders have been shown to exploit their access to borrowers’ private information by trading on it in financial markets. As a shock... View Details
Keywords: Analytics and Data Science; Borrowing and Debt; Financial Markets; Value; Knowledge Dissemination; Financing and Loans
Kang, Jung Koo. "Gone with the Big Data: Institutional Lender Demand for Private Information." Art. 101663. Journal of Accounting & Economics 77, nos. 2-3 (April–May 2024).
- 2024
- Working Paper
Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference
By: Michael Lindon, Dae Woong Ham, Martin Tingley and Iavor I. Bojinov
Linear regression adjustment is commonly used to analyze randomized controlled experiments due to its efficiency and robustness against model misspecification. Current testing and interval estimation procedures leverage the asymptotic distribution of such estimators to... View Details
Lindon, Michael, Dae Woong Ham, Martin Tingley, and Iavor I. Bojinov. "Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference." Harvard Business School Working Paper, No. 24-060, March 2024.
- February 2024
- Case
Levels.fyi: How Negotiations Coaching and Pay Transparency Change Job Market Outcomes
By: Zoë B. Cullen
Salary information is everywhere. What impact does it have on compensation? How should employees and employers use salary information in negotiations? This case brings to light how pay information affects behavior and job market outcomes in surprising ways. View Details
Cullen, Zoë B. "Levels.fyi: How Negotiations Coaching and Pay Transparency Change Job Market Outcomes." Harvard Business School Case 824-078, February 2024.
- 2025
- Working Paper
Warnings and Endorsements: Improving Human-AI Collaboration in the Presence of Outliers
By: Matthew DosSantos DiSorbo, Kris Ferreira, Maya Balakrishnan and Jordan Tong
Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). How can humans and algorithms work together to make... View Details
DosSantos DiSorbo, Matthew, Kris Ferreira, Maya Balakrishnan, and Jordan Tong. "Warnings and Endorsements: Improving Human-AI Collaboration in the Presence of Outliers." Working Paper, May 2025.
- January 2024 (Revised June 2024)
- Case
Equal Justice Initiative: Mercy, Truth and Dignity
By: V. Kasturi Rangan, Gerald Chertavian and Brittany Logan
In 1989, the Equal Justice Initiative was established as a non-profit, public interest law firm by Harvard Law School graduate, Bryan Stevenson.
EJI provides legal assistance to condemned prisoners, people wrongly convicted or unfairly sentenced, children in... View Details
EJI provides legal assistance to condemned prisoners, people wrongly convicted or unfairly sentenced, children in... View Details
- January 2024
- Supplement
Buurtzorg
By: Ethan Bernstein and Tatiana Sandino
As co-founders of home nursing company Buurtzorg, Jos de Blok and Gonnie Kronenberg prized both self-management and organizational learning. Buurtzorg’s 10,000 nurses across 950 neighborhood nursing teams in the Netherlands were empowered to manage themselves, both in... View Details
Keywords: Organizational Design; Management Style; Business Model; Knowledge Dissemination; Learning; Organizational Culture; Health Industry; Netherlands
Bernstein, Ethan, and Tatiana Sandino. "Buurtzorg." Harvard Business School Multimedia/Video Supplement 424-705, January 2024.
- 2024
- Working Paper
The Value of Open Source Software
By: Manuel Hoffmann, Frank Nagle and Yanuo Zhou
The value of a non-pecuniary (free) product is inherently difficult to assess. A pervasive
example is open source software (OSS), a global public good that plays a vital role in the economy
and is foundational for most technology we use today. However, it is... View Details
Hoffmann, Manuel, Frank Nagle, and Yanuo Zhou. "The Value of Open Source Software." Harvard Business School Working Paper, No. 24-038, January 2024.
- January 2024
- Article
Fencing Off Silicon Valley: Cross-Border Venture Capital and Technology Spillovers
By: Ufuk Akcigit, Sina T. Ates, Josh Lerner, Richard Townsend and Yulia Zhestkova
The treatment of foreign investors is a contentious topic in U.S. entrepreneurship policy. We
model a setting where foreign corporate investments in Silicon Valley may allow U.S. entrepreneurs to pursue technologies that they could not otherwise, but may also lead to... View Details
Akcigit, Ufuk, Sina T. Ates, Josh Lerner, Richard Townsend, and Yulia Zhestkova. "Fencing Off Silicon Valley: Cross-Border Venture Capital and Technology Spillovers." Journal of Monetary Economics 141 (January 2024): 14–39.
- 2024
- Conference Paper
Quantifying Uncertainty in Natural Language Explanations of Large Language Models
By: Himabindu Lakkaraju, Sree Harsha Tanneru and Chirag Agarwal
Large Language Models (LLMs) are increasingly used as powerful tools for several
high-stakes natural language processing (NLP) applications. Recent prompting
works claim to elicit intermediate reasoning steps and key tokens that serve as
proxy explanations for LLM... View Details
Lakkaraju, Himabindu, Sree Harsha Tanneru, and Chirag Agarwal. "Quantifying Uncertainty in Natural Language Explanations of Large Language Models." Paper presented at the Society for Artificial Intelligence and Statistics, 2024.