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- All HBS Web
(4,266)
- Faculty Publications (783)
- August 2023 (Revised January 2024)
- Case
Jake Becraft and Strand Therapeutics: The Making of an Entrepreneur
By: Satish Tadikonda, William Marks and Ananya Zutshi
Jake Becraft, a PhD student at MIT disillusioned in pursuit of his dreams of becoming an academic, serendipitously finds himself discussing the potential commercial applications of his work with Tasuku Kitada, his former postdoctoral research mentor. The two decide to... View Details
Tadikonda, Satish, William Marks, and Ananya Zutshi. "Jake Becraft and Strand Therapeutics: The Making of an Entrepreneur." Harvard Business School Case 824-046, August 2023. (Revised January 2024.)
- August 2023
- Case
WayCool: Reimagining the Food Supply Chain
By: Paul Gompers and Kairavi Dey
Founded in 2015, WayCool, is an Indian agri-tech start-up that built a B2B operation acquiring fruits and vegetables from product-specific agriculture companies and small-holding farmers. It sold them to business customers, such as local retail stores, restaurants, and... View Details
Keywords: Agribusiness; Digital Transformation; Operations; Business Strategy; Supply Chain; Performance; Business Startups; Growth and Development Strategy; Agriculture and Agribusiness Industry; Food and Beverage Industry; Technology Industry; Web Services Industry; Asia; South Asia
Gompers, Paul, and Kairavi Dey. "WayCool: Reimagining the Food Supply Chain." Harvard Business School Case 224-011, August 2023.
- July 2023
- Case
HealthVerity: Real World Data and Evidence
By: Satish Tadikonda
Andrew Kress (CEO and founder) and his team had built a promising marketplace business at HealthVerity serving its core market in healthcare, with a focus on pharmaceutical R&D and services. Thus far, HealthVerity’s products had been unique to the pharma and pharma... View Details
Tadikonda, Satish. "HealthVerity: Real World Data and Evidence." Harvard Business School Case 824-019, July 2023.
- July 2023 (Revised July 2023)
- Background Note
Generative AI Value Chain
By: Andy Wu and Matt Higgins
Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details
Keywords: AI; Artificial Intelligence; Model; Hardware; Data Centers; AI and Machine Learning; Applications and Software; Analytics and Data Science; Value
Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
- July 13, 2023
- Article
Threads Foreshadows a Big—and Surprising—Shift in Social Media
By: Scott Duke Kominers and Liang Wu
Threads, Meta’s Twitter competitor, has become the fastest downloaded app in history. One of the reasons for this is because it allows users to port over their profiles and follows from the already popular social media platform Instagram, also owned by Meta—a feature... View Details
Keywords: Decentralization; Twitter; Facebook; Instagram; Crypto Economy; Blockchain; Network; Industrial Organization; Competition; Open Innovation; Open Platforms; Open Source Innovation; Social Networks; Social Media; Applications and Software; Information Technology Industry
Kominers, Scott Duke, and Liang Wu. "Threads Foreshadows a Big—and Surprising—Shift in Social Media." Harvard Business Review Digital Articles (July 13, 2023).
- 2023
- Working Paper
The Complexity of Economic Decisions
By: Xavier Gabaix and Thomas Graeber
We propose a theory of the complexity of economic decisions. Leveraging a macroeconomic framework of production functions, we conceptualize the mind as a cognitive economy, where a task’s complexity is determined by its composition of cognitive operations. Complexity... View Details
Gabaix, Xavier, and Thomas Graeber. "The Complexity of Economic Decisions." Harvard Business School Working Paper, No. 24-049, February 2024.
- June 2023
- Supplement
Clash of Two Giants Simulation Exercise
By: Feng Zhu and Marco Iansiti
Many markets are organized around platforms that connect consumers with complementary applications and services. These platforms are two-sided because both sides - consumers and those providing applications or services - need access to the same platform to interact. A... View Details
- June 2023
- Exercise
Clash of Two Giants Simulation Exercise Instructions
By: Feng Zhu and Marco Iansiti
Many markets are organized around platforms that connect consumers with complimentary applications and services. These platforms are two-sided because both sides - consumers and those providing applications or services - need access to the same platform to interact. A... View Details
Keywords: Platform Strategies; Technology Platform; Customer Acquisition; Network Effects; Digital Platforms; Marketplace Matching; Strategy
Zhu, Feng, and Marco Iansiti. "Clash of Two Giants Simulation Exercise Instructions." Harvard Business School Exercise 623-092, June 2023.
- June 2023 (Revised October 2024)
- Teaching Note
Clash of Two Giants Simulation Exercise Teaching Note
By: Feng Zhu
Teaching Note for HBS Case No. 623-092. Many markets are organized around platforms that connect consumers with complimentary applications and services. These platforms are two-sided because both sides—consumers and those providing applications or services—need access... View Details
- June 19, 2023
- Article
Should You Start a Generative AI Company?
Many entrepreneurs are considering starting companies that leverage the latest generative AI technology, but they must ask themselves whether they have what it takes to compete on increasingly commoditized foundational models, or whether they should instead... View Details
De Freitas, Julian. "Should You Start a Generative AI Company?" Harvard Business Review (website) (June 19, 2023).
- 2023
- Working Paper
Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation
By: Dae Woong Ham, Michael Lindon, Martin Tingley and Iavor Bojinov
Randomized experiments have become the standard method for companies to evaluate the performance of new products or services. In addition to augmenting managers’ decision-making, experimentation mitigates risk by limiting the proportion of customers exposed to... View Details
Keywords: Performance Evaluation; Research and Development; Analytics and Data Science; Consumer Behavior
Ham, Dae Woong, Michael Lindon, Martin Tingley, and Iavor Bojinov. "Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation." Harvard Business School Working Paper, No. 23-070, May 2023.
- 2023
- Working Paper
Digital Lending and Financial Well-Being: Through the Lens of Mobile Phone Data
By: AJ Chen, Omri Even-Tov, Jung Koo Kang and Regina Wittenberg-Moerman
To mitigate information asymmetry about borrowers in developing economies, digital lenders utilize machine-learning algorithms and nontraditional data from borrowers’ mobile devices. Consequently, digital lenders have managed to expand access to credit for millions of... View Details
Keywords: Borrowing and Debt; Credit; AI and Machine Learning; Welfare; Well-being; Developing Countries and Economies; Equality and Inequality
Chen, AJ, Omri Even-Tov, Jung Koo Kang, and Regina Wittenberg-Moerman. "Digital Lending and Financial Well-Being: Through the Lens of Mobile Phone Data." Harvard Business School Working Paper, No. 23-076, April 2023. (Revised November 2023. SSRN Working Paper Series, November 2023)
- 2023
- Working Paper
Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs
By: Jacqueline N. Lane, Karim R. Lakhani and Roberto Fernandez
Competence development in digital technologies, analytics, and artificial intelligence is increasingly important to all types of organizations and their workforce. Universities and corporations are investing heavily in developing training programs, at all tenure... View Details
Keywords: STEM; Selection and Staffing; Gender; Prejudice and Bias; Training; Equality and Inequality; Competency and Skills
Lane, Jacqueline N., Karim R. Lakhani, and Roberto Fernandez. "Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs." Harvard Business School Working Paper, No. 23-066, April 2023. (Accepted by Organization Science.)
- May 2023
- Article
Where Sales Technology (Really) Helps
Interest in Sales Enablement (SE), the catch-all term for attempts to increase sales productivity with AI and other technologies, is driven by multiple factors. One is the declining costs of the tools. Also, selling is now data-hungry work and not just in tech sectors.... View Details
- April 2023 (Revised February 2024)
- Case
AI Wars
By: Andy Wu, Matt Higgins, Miaomiao Zhang and Hang Jiang
In February 2024, the world was looking to Google to see what the search giant and long-time putative technical leader in artificial intelligence (AI) would do to compete in the massively hyped technology of generative AI. Over a year ago, OpenAI released ChatGPT, a... View Details
Keywords: AI; Artificial Intelligence; AI and Machine Learning; Technology Adoption; Competitive Strategy; Technological Innovation
Wu, Andy, Matt Higgins, Miaomiao Zhang, and Hang Jiang. "AI Wars." Harvard Business School Case 723-434, April 2023. (Revised February 2024.)
- April 2023 (Revised September 2023)
- Case
Levels: The Remote, Asynchronous, Deep Work Management System
By: Joseph B. Fuller and George Gonzalez
Levels is a highly innovative startup in the health care space. They intend to revolutionize health by linking behavior—eating, exercise, sleeping, etc.—to changes in metabolism. They believe metabolic health can be managed through careful monitoring of changes in... View Details
Keywords: Applications and Software; Business Startups; Organizational Culture; Management Style; Technology Industry; United States
Fuller, Joseph B., and George Gonzalez. "Levels: The Remote, Asynchronous, Deep Work Management System." Harvard Business School Case 323-069, April 2023. (Revised September 2023.)
- 2023
- Working Paper
Applications or Approvals: What Drives Racial Disparities in the Paycheck Protection Program?
By: Sergey Chernenko, Nathan Kaplan, Asani Sarkar and David S. Scharfstein
We use the 2020 Small Business Credit Survey to study the sources of racial disparities in use of the Paycheck Protection Program (PPP). Black-owned firms are 8.9 percentage points less likely than observably similar white-owned firms to receive PPP loans. About 55% of... View Details
Chernenko, Sergey, Nathan Kaplan, Asani Sarkar, and David S. Scharfstein. "Applications or Approvals: What Drives Racial Disparities in the Paycheck Protection Program?" NBER Working Paper Series, No. 31172, April 2023.
- 2023
- Working Paper
The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities
By: David S. Scharfstein and Sergey Chernenko
We show that the use of algorithms to predict race has significant limitations in measuring and understanding the sources of racial disparities in finance, economics, and other contexts. First, we derive theoretically the direction and magnitude of measurement bias in... View Details
Keywords: Racial Disparity; Paycheck Protection Program; Measurement Error; AI and Machine Learning; Race; Measurement and Metrics; Equality and Inequality; Prejudice and Bias; Forecasting and Prediction; Outcome or Result
Scharfstein, David S., and Sergey Chernenko. "The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities." Working Paper, April 2023.
- March 2023
- Teaching Note
VideaHealth: Building the AI Factory
By: Karim R. Lakhani
Teaching Note for HBS Case No. 621-021. The case “VideaHealth: Building the AI Factory” examines the creation of dental startup VideaHealth (Videa) and the development of its artificial intelligence (AI)-led business strategy through the eyes of founder and CEO Florian... View Details
- March 2023 (Revised June 2023)
- Case
Layoffs in the Tech Industry: 2022–2023
By: Sandra J. Sucher and Marilyn Morgan Westner
This case examines the mass layoffs that swept through the tech industry (2022-2023) through the lens of four companies: Twitter, Stripe, Meta, and Google. How these companies implemented workforce change through mass layoffs raises critical questions applicable beyond... View Details
Keywords: Layoffs; Human Resource Management; Workforce Reductions; Ethics; Human Resources; Management; Values and Beliefs; Employee Relationship Management; Resignation and Termination; Compensation and Benefits; Technology Industry; United States; United Kingdom
Sucher, Sandra J., and Marilyn Morgan Westner. "Layoffs in the Tech Industry: 2022–2023." Harvard Business School Case 323-095, March 2023. (Revised June 2023.)