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- January 2025
- Case
Redwood & Strong: The Value of a Consulting Engagement
By: David G. Fubini and Patrick Sanguineti
The board of Redwood & Strong LLP (R&S), the American branch of a large global law firm, is meeting to review the findings of a recent strategic initiative designed to identify potential merger candidates. The request for the engagement originated from Daniel Crawford,... View Details
- October 2024 (Revised October 2024)
- Case
AI and Brand Management: Promises and Perils
By: Julian De Freitas and Elie Ofek
As AI gains traction across industries, companies anticipate that AI will revolutionize both backend processes and customer-facing interactions—with brands eager to leverage AI for tailored marketing materials and automated consumer engagements. Yet, despite a dramatic... View Details
De Freitas, Julian, and Elie Ofek. "AI and Brand Management: Promises and Perils." Harvard Business School Case 525-021, October 2024. (Revised October 2024.)
- September–October 2024
- Article
The Crowdless Future? Generative AI and Creative Problem-Solving
The rapid advances in generative artificial intelligence (AI) open up attractive opportunities for creative problem-solving through human-guided AI partnerships. To explore this potential, we initiated a crowdsourcing challenge focused on sustainable, circular economy... View Details
Keywords: Large Language Models; Generative Ai; Crowdsourcing; AI and Machine Learning; Creativity; Technological Innovation
Boussioux, Léonard, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic, and Karim R. Lakhani. "The Crowdless Future? Generative AI and Creative Problem-Solving." Organization Science 35, no. 5 (September–October 2024): 1589–1607.
- June 2024
- Article
Real Growth in Space Manufacturing Output Substantially Exceeds Growth in the Overall Space Economy
By: Tina Highfill and Matthew Weinzierl
Accurately measuring real economic output in the space economy is made difficult by the rapid increase in capabilities and decrease in prices of launch and satellite technologies achieved over the past two decades. Nominal measures of output in space will tend to... View Details
Highfill, Tina, and Matthew Weinzierl. "Real Growth in Space Manufacturing Output Substantially Exceeds Growth in the Overall Space Economy." Acta Astronautica 219 (June 2024): 236–242.
- 2024
- Working Paper
The Efficiency of Patent Litigation
By: Samuel Antill, Murat Alp Celik, Xu Tian and Toni M. Whited
How efficient is the U.S. patent litigation system? We quantify the extent to which the litigation system shapes innovation using a novel dynamic model, in which heterogeneous firms innovate and face potential patent lawsuits. We show that the impact of a litigation... View Details
Keywords: Innovation and Invention; Lawsuits and Litigation; Growth and Development; Welfare; Patents
Antill, Samuel, Murat Alp Celik, Xu Tian, and Toni M. Whited. "The Efficiency of Patent Litigation." Working Paper, May 2024.
- 2023
- Working Paper
New Facts and Data about Professors and Their Research
By: Kyle Myers, Wei Yang Tham, Jerry Thursby, Marie Thursby, Nina Cohodes, Karim R. Lakhani, Rachel Mural and Yilun Xu
We introduce a new survey of professors at roughly 150 of the most research-intensive institutions of higher education in the US. We document seven new features of how research-active professors are compensated, how they spend their time, and how they perceive their... View Details
Keywords: Research; Higher Education; Compensation and Benefits; Measurement and Metrics; Equality and Inequality; Performance Productivity
Myers, Kyle, Wei Yang Tham, Jerry Thursby, Marie Thursby, Nina Cohodes, Karim R. Lakhani, Rachel Mural, and Yilun Xu. "New Facts and Data about Professors and Their Research." Harvard Business School Working Paper, No. 24-036, December 2023.
- 2023
- Article
Post Hoc Explanations of Language Models Can Improve Language Models
By: Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh and Himabindu Lakkaraju
Large Language Models (LLMs) have demonstrated remarkable capabilities in performing complex tasks. Moreover, recent research has shown that incorporating human-annotated rationales (e.g., Chain-of-Thought prompting) during in-context learning can significantly enhance... View Details
Krishna, Satyapriya, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, and Himabindu Lakkaraju. "Post Hoc Explanations of Language Models Can Improve Language Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- November 2023 (Revised March 2024)
- Case
Infarm: Betting the (Indoor) Farm on Food Security
By: Elie Ofek
In the summer of 2023, the co-founders of Infarm, a controlled environment agriculture (CEA) company, were contemplating a major pivot going forward. While Infarm had successfully shown it could grow over 75 products—mainly herbs, leafy greens and mushrooms—in modular... View Details
Keywords: Plant-Based Agribusiness; Business Model; Market Entry and Exit; Science-Based Business; Business Strategy; Transition; Agriculture and Agribusiness Industry; Europe; North America; Toronto; Northeastern United States
Ofek, Elie. "Infarm: Betting the (Indoor) Farm on Food Security." Harvard Business School Case 524-043, November 2023. (Revised March 2024.)
- October 2023
- Article
Product Variety, the Cost of Living, and Welfare Across Countries
By: Alberto Cavallo, Robert C. Feenstra and Robert Inklaar
We use the structure of the Melitz (2003) model to compute the cost of living and welfare across 47 countries, and compare these to conventional measures of prices and real consumption from the International Comparisons Project (ICP). The cost of living is inferred... View Details
Cavallo, Alberto, Robert C. Feenstra, and Robert Inklaar. "Product Variety, the Cost of Living, and Welfare Across Countries." American Economic Journal: Macroeconomics 15, no. 4 (October 2023): 40–66.
- 2025
- Working Paper
Better Keep the Twenty Dollars: Incentivizing Innovation in Open Source
By: Annamaria Conti, Vansh Gupta, Jorge Guzman and Maria P. Roche
Open source is key to innovation yet is assumed to be done largely through intrinsic motivation. How can we incentivize it? In this paper, we examine the impact of a program providing monetary incentives to motivate innovators to contribute to open source. The Sponsors... View Details
Keywords: Open Source; Innovation; Incentives; Financial Rewards; Crowding Out; Open Source Distribution; Innovation and Invention; Motivation and Incentives; Technology Industry
Conti, Annamaria, Vansh Gupta, Jorge Guzman, and Maria P. Roche. "Better Keep the Twenty Dollars: Incentivizing Innovation in Open Source." Harvard Business School Working Paper, No. 24-014, September 2023. (Revised January 2025. NBER Working Paper Series, No. 31668, September 2023)
- 2023
- Article
On the Impact of Actionable Explanations on Social Segregation
By: Ruijiang Gao and Himabindu Lakkaraju
As predictive models seep into several real-world applications, it has become critical to ensure that individuals who are negatively impacted by the outcomes of these models are provided with a means for recourse. To this end, there has been a growing body of research... View Details
Gao, Ruijiang, and Himabindu Lakkaraju. "On the Impact of Actionable Explanations on Social Segregation." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 10727–10743.
- 2024
- Working Paper
The Crowdless Future? Generative AI and Creative Problem Solving
The rapid advances in generative artificial intelligence (AI) open up attractive opportunities for creative problem-solving through human-guided AI partnerships. To explore this potential, we initiated a crowdsourcing challenge focused on sustainable, circular economy... View Details
Keywords: Large Language Models; Crowdsourcing; Generative Ai; Creative Problem-solving; Organizational Search; AI-in-the-loop; Prompt Engineering; AI and Machine Learning; Innovation and Invention
Boussioux, Léonard, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic, and Karim R. Lakhani. "The Crowdless Future? Generative AI and Creative Problem Solving." Harvard Business School Working Paper, No. 24-005, July 2023. (Revised July 2024.)
- 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 2023
- Article
Marketplace Scalability and Strategic Use of Platform Investment
By: Jin Li, Gary Pisano, Richard Xu and Feng Zhu
The scalability of a marketplace depends on the operations of the marketplace platform as well as its sellers’ capacities. In this study, we explore one strategy that a marketplace platform can use to enhance its scalability: providing an ancillary service to sellers.... View Details
Li, Jin, Gary Pisano, Richard Xu, and Feng Zhu. "Marketplace Scalability and Strategic Use of Platform Investment." Management Science 69, no. 7 (July 2023): 3958–3975.
- 2023
- Working Paper
Sovereign Default and the Decline in Interest Rates
By: Max Miller, James Paron and Jessica Wachter
Sovereign debt yields have declined dramatically over the last half-century. Standard explanations, including aging populations and increases in asset demand from abroad, encounter difficulties when confronted with the full range of evidence. We propose an explanation... View Details
- 2023
- Article
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse
By: Martin Pawelczyk, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci and Himabindu Lakkaraju
As machine learning models are increasingly being employed to make consequential decisions in real-world settings, it becomes critical to ensure that individuals who are adversely impacted (e.g., loan denied) by the predictions of these models are provided with a means... View Details
Pawelczyk, Martin, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci, and Himabindu Lakkaraju. "Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse." Proceedings of the International Conference on Learning Representations (ICLR) (2023).
- 2023
- Working Paper
Feature Importance Disparities for Data Bias Investigations
By: Peter W. Chang, Leor Fishman and Seth Neel
It is widely held that one cause of downstream bias in classifiers is bias present in the training data. Rectifying such biases may involve context-dependent interventions such as training separate models on subgroups, removing features with bias in the collection... View Details
Chang, Peter W., Leor Fishman, and Seth Neel. "Feature Importance Disparities for Data Bias Investigations." Working Paper, March 2023.
- April 2023
- Article
On the Privacy Risks of Algorithmic Recourse
By: Martin Pawelczyk, Himabindu Lakkaraju and Seth Neel
As predictive models are increasingly being employed to make consequential decisions, there is a growing emphasis on developing techniques that can provide algorithmic recourse to affected individuals. While such recourses can be immensely beneficial to affected... View Details
Pawelczyk, Martin, Himabindu Lakkaraju, and Seth Neel. "On the Privacy Risks of Algorithmic Recourse." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 206 (April 2023).
- 2023
- Chapter
Marketing Through the Machine’s Eyes: Image Analytics and Interpretability
By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
Zhang, Shunyuan, Flora Feng, and Kannan Srinivasan. "Marketing Through the Machine’s Eyes: Image Analytics and Interpretability." Chap. 8 in Artificial Intelligence in Marketing. 20, edited by Naresh K. Malhotra, K. Sudhir, and Olivier Toubia, 217–238. Review of Marketing Research. Emerald Publishing Limited, 2023.
- March, 2023
- Article
Academic Entrepreneurship: Entrepreneurial Advisors and Their Advisees' Outcomes
By: Maria P. Roche
The transfer of complex knowledge and skills is difficult, often requiring intensive interaction and extensive periods of co-working between a mentor and mentee, which is particularly true in apprenticeship-like settings and on-the-job training. This paper studies a... View Details
Keywords: Entrepreneurship; Higher Education; Training; Personal Development and Career; Knowledge Dissemination
Roche, Maria P. "Academic Entrepreneurship: Entrepreneurial Advisors and Their Advisees' Outcomes." Organization Science 34, no. 2 (March, 2023): 959–986.