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- August 5, 2025
- Article
Data-driven Equation Discovery Reveals Nonlinear Reinforcement Learning in Humans
By: Kyle J. LaFollette, Janni Yuval, Roey Schurr, David Melnikoff and Amit Goldenberg
Computational models of reinforcement learning (RL) have significantly contributed to our understanding of human behavior and decision-making. Traditional RL models, however, often adopt a linear approach to updating reward expectations, potentially oversimplifying the... View Details
Keywords: AI and Machine Learning; Behavior; Learning; Motivation and Incentives; Mathematical Methods
LaFollette, Kyle J., Janni Yuval, Roey Schurr, David Melnikoff, and Amit Goldenberg. "Data-driven Equation Discovery Reveals Nonlinear Reinforcement Learning in Humans." Proceedings of the National Academy of Sciences 122, no. 31 (August 5, 2025).
- 2025
- Article
Difference-in-Differences Subset Scan
By: Will Stamey, Sriram Somanchi and Edward McFowland III
Difference-in-differences (DiD) has been extensively applied in the literature to elicit the average causal effect of an intervention or policy. Though researchers explore heterogeneity in the treatment effect with respect to time or some observed covariate (usually... View Details
Stamey, Will, Sriram Somanchi, and Edward McFowland III. "Difference-in-Differences Subset Scan." Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining 31st (2025): 2656–2667.
- Article
Using Gen AI for Early-Stage Market Research
By: James Brand, Ayelet Israeli and Donald Ngwe
Generative AI, particularly large language models (LLMs), offers a promising new tool for early-stage market research by simulating customer responses to product concepts. This can allow companies to draw conclusions similar to those they’d obtain by surveying... View Details
Keywords: Large Language Models; Large Language Model; Generative Ai; Artificial Intelligence; Market Research; Research; Marketing; AI and Machine Learning; Analytics and Data Science; Analysis; Customers; Consumer Behavior; Technology Industry; Information Technology Industry
Brand, James, Ayelet Israeli, and Donald Ngwe. "Using Gen AI for Early-Stage Market Research." Harvard Business Review (website) (July 18, 2025).
- 2025
- Working Paper
Data-driven Technologies and Local Information Advantages in Small Business Lending
By: Wilbur Chen, Jung Koo Kang and Aditya Mohan
We investigate whether banks' adoption of data-driven technologies influences competitive dynamics in local small business lending by diminishing the information advantages traditionally held by local banks. Using local newspaper closures as an adverse shock to the... View Details
Keywords: Data-driven Technologies; Local Information Advantages; Local Banks; Relationship Lending; Small Business Loans; Small Business; Local Range; Financing and Loans; Banks and Banking; Analytics and Data Science; Banking Industry
Chen, Wilbur, Jung Koo Kang, and Aditya Mohan. "Data-driven Technologies and Local Information Advantages in Small Business Lending." Harvard Business School Working Paper, No. 25-057, May 2025.
- April 2025
- Article
Transitioning Into Retirement: The Interplay of Self and Life Structure
By: Marcy Crary, Douglas T. (Tim) Hall, Kathy E. Kram, Teresa M. Amabile and Lotte Bailyn
This paper explores the psychological, social, and behavioral ways in which professionals end their corporate careers and reorient themselves and their lives in the transition from employment to retirement. Framed within life course theory, specifically the adult... View Details
Crary, Marcy, Douglas T. (Tim) Hall, Kathy E. Kram, Teresa M. Amabile, and Lotte Bailyn. "Transitioning Into Retirement: The Interplay of Self and Life Structure." Working, Aging and Retirement 11, no. 2 (April 2025): 175–196.
- 2025
- Working Paper
Private Equity and Workers: Modeling and Measuring Monopsony, Implicit Contracts, and Efficient Reallocation
By: Kyle Herkenhoff, Josh Lerner, Gordon M. Phillips, Francisca Rebelo and Benjamin Sampson
We measure the real effects of private equity buyouts on worker outcomes by building a new
database that links transactions to matched employer-employee data in the United States. To
guide our empirical analysis, we derive testable implications from three theories in... View Details
Herkenhoff, Kyle, Josh Lerner, Gordon M. Phillips, Francisca Rebelo, and Benjamin Sampson. "Private Equity and Workers: Modeling and Measuring Monopsony, Implicit Contracts, and Efficient Reallocation." Harvard Business School Working Paper, No. 25-046, March 2025. (Revised June 2025.)
- 2025
- Working Paper
Transferability MATTRs: Towards Understanding Antecedents of Strategic Licensing
By: Dafna F. Bearson and Maria P. Roche
This paper examines the antecedents of firms’ decisions to license intellectual property
(IP). We propose a conceptual framework emphasizing two critical factors: (1) transferability,
which we define as the ease of moving knowledge embodied in inventions across
firm... View Details
Bearson, Dafna F., and Maria P. Roche. "Transferability MATTRs: Towards Understanding Antecedents of Strategic Licensing." Harvard Business School Working Paper, No. 25-042, March 2025.
- 2025
- Working Paper
How to Choose Among Technologies with Learning Curves: Making Better Investment Decisions
By: Christian Kaps and Arielle Anderer
Learning curves, the fact that technologies improve as a function of cumulative experience or investment, are desirable-think inexpensive solar panels or higher performing semiconductors. But, for firms that need to pick one technology among several candidates, such as... View Details
Keywords: Learning Curve; Technology; Innovation; Batteries; Energy Storage; Sequential Decision Making; TELCO; Exploration; Exploitation; Problems and Challenges; Cost vs Benefits; Technology Adoption; Battery Industry
Kaps, Christian, and Arielle Anderer. "How to Choose Among Technologies with Learning Curves: Making Better Investment Decisions." Working Paper, March 2025.
- 2025
- Working Paper
Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning
Reinforcement learning (RL) offers potential for optimizing sequences of customer interactions by modeling the relationships
between customer states, company actions, and long-term value. However, its practical implementation often faces significant
challenges.... View Details
Keywords: Dynamic Policy; Deep Reinforcement Learning; Representation Learning; Dynamic Difficulty Adjustment; Latent Variable Models; Customer Relationship Management; Customer Value and Value Chain; Foreign Direct Investment; Analytics and Data Science
Ma, Liangzong, Ta-Wei Huang, Eva Ascarza, and Ayelet Israeli. "Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning." Harvard Business School Working Paper, No. 25-037, February 2025.
- February 2025
- Article
Sale of Private Equity–Owned Physician Practices and Physician Turnover
By: Victoria Berquist, Lev Klarnet and Leemore Dafny
Private equity (PE) ownership of physician practices is increasing, with owners targeting sales, or exits, in 3 to 7 years. Little is known about the association of exit with physician retention and subsequent employment. Using panel data over the period 2014-2020, we... View Details
Berquist, Victoria, Lev Klarnet, and Leemore Dafny. "Sale of Private Equity–Owned Physician Practices and Physician Turnover." JAMA Health Forum 6, no. 2 (February 2025).
- 2025
- Working Paper
Technology Choice, Spillovers, and the Concentration of R&D
By: Todd A. Lensman
The direction of innovation shapes both current technologies and future innovation
opportunities, as firms acquire expertise and create public knowledge through discovery.
But how do firms choose which technologies to develop? Do they ever fail to exploit... View Details
Lensman, Todd A. "Technology Choice, Spillovers, and the Concentration of R&D." Working Paper, January 2025.
- 2025
- Working Paper
Combining Complements: Theory and Evidence from Cancer Treatment Innovation
By: Rebekah Dix and Todd A. Lensman
Innovations often combine several components to achieve outcomes greater than the
“sum of the parts.” We argue that such combination innovations can introduce an understudied
inefficiency—a positive market expansion externality that benefits the owners of
the... View Details
Keywords: Innovation Strategy; Outcome or Result; Collaborative Innovation and Invention; Health Testing and Trials; Health Industry
Dix, Rebekah, and Todd A. Lensman. "Combining Complements: Theory and Evidence from Cancer Treatment Innovation." Working Paper, January 2025.
- 2024
- Working Paper
A Gender Backlash: Does Exposure to Female Labor Market Participation Fuel Gender Conservatism?
By: Paula Rettl, Diane Bolet, Catherine E. De Vries, Simone Cremaschi, Tarik Abou-Chadi and Sergi Pardos-Prado
The growing participation of women in the labor market has marked a significant societal transformation, coinciding with the rise of gender conservatism and far-right support. We study whether the economic consequences of labor market feminization and gender backlash... View Details
Keywords: Gender Bias; Gender Equality; Gender Inclusivity; Politics; Political Backlash; Political Culture; Conservatism; Gender; Government and Politics; Equality and Inequality; Prejudice and Bias; Labor
Rettl, Paula, Diane Bolet, Catherine E. De Vries, Simone Cremaschi, Tarik Abou-Chadi, and Sergi Pardos-Prado. "A Gender Backlash: Does Exposure to Female Labor Market Participation Fuel Gender Conservatism?" Harvard Business School Working Paper, No. 25-022, November 2024.
- November–December 2024
- Article
Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing
By: Kirk Bansak and Elisabeth Paulson
This study proposes two new dynamic assignment algorithms to match refugees and asylum seekers to geographic localities within a host country. The first, currently implemented in a multi-year pilot in Switzerland, seeks to maximize the average predicted employment... View Details
Bansak, Kirk, and Elisabeth Paulson. "Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing." Operations Research 72, no. 6 (November–December 2024): 2375–2390.
- November 2024
- Article
Perceptions About Monetary Policy
By: Michael D. Bauer, Carolin Pflueger and Adi Sunderam
We estimate perceptions about the Federal Reserve’s monetary policy rule from panel data on professional forecasts of interest rates and macroeconomic conditions. The perceived dependence of the federal funds rate on economic conditions varies substantially over time,... View Details
Bauer, Michael D., Carolin Pflueger, and Adi Sunderam. "Perceptions About Monetary Policy." Quarterly Journal of Economics 139, no. 4 (November 2024): 2227–2278.
- November 2024
- Article
Price Discounts and Cheapflation During the Post-Pandemic Inflation Surge
By: Alberto Cavallo and Oleksiy Kryvtsov
We study how within-store price variation changes with inflation, and whether households exploit it to attenuate the inflation burden. We use micro price data for food products sold by 91 large multi-channel retailers in ten countries between 2018 and 2024. Measuring... View Details
Keywords: Macroeconomics; Inflation and Deflation; Price; Consumer Behavior; Personal Finance; Product Positioning
Cavallo, Alberto, and Oleksiy Kryvtsov. "Price Discounts and Cheapflation During the Post-Pandemic Inflation Surge." Journal of Monetary Economics 148 (November 2024).
- October 2024
- Background Note
The Semiconductor Industry
By: Andy Wu, Steve Blank and Matt Higgins
The semiconductor industry powers modern technology, from consumer electronics to data centers. This background note explores the layers of the semiconductor inudstry value chain, including Integrated Device Manufacturers (IDMs), fabless companies, and foundries, while... View Details
- 2024
- Working Paper
The Operational Impact of Customer Location in On-Demand Services
By: Natalie Epstein, Santiago Gallino and Antonio Moreno
The rapid growth of on-demand delivery services, particularly in the food and grocery sectors, has driven the expansion of hyperlocal fulfillment centers (FCs). This paper uses data from an on-demand grocery delivery platform in Latin America to assess how customer... View Details
Keywords: Consumer Behavior; Logistics; Geographic Location; Service Delivery; Quality; Retail Industry; Latin America
Epstein, Natalie, Santiago Gallino, and Antonio Moreno. "The Operational Impact of Customer Location in On-Demand Services." Working Paper, September 2024.
- 2024
- Working Paper
Determinants of Top-Down Sabotage
By: Hashim Zaman and Karim R. Lakhani
We investigate the conditions that motivate managers to impede the growth of talented subordinates due to fears of future competition for their own positions. Our research expands on existing tournament and contest theory literature that considers peer-to-peer sabotage... View Details
Keywords: Succession Planning; Organizational Hierarchy; Compensation; Promotions; Tournaments; Talent and Talent Management; Organizational Structure; Employee Relationship Management; Performance Evaluation; Organizational Culture; Management Skills
Zaman, Hashim, and Karim R. Lakhani. "Determinants of Top-Down Sabotage." Harvard Business School Working Paper, No. 25-007, August 2024. (Revised December 2024.)
- 2024
- Article
Crucibles, Multiple Sensitive Periods, and Career Progression
By: Prithwiraj Choudhury, Sunasir Dutta, Hise O. Gibson and Eric Lin
We study the effects of crucible experiences along multiple sensitive periods on career progression. While prior literature has hinted that individuals can be imprinted during multiple sensitive periods, not just during the early career, there has been scant attention... View Details
Keywords: Military Service; Personal Development and Career; Transformation; Power and Influence; Learning; Human Capital
Choudhury, Prithwiraj, Sunasir Dutta, Hise O. Gibson, and Eric Lin. "Crucibles, Multiple Sensitive Periods, and Career Progression." Academy of Management Proceedings (2024).