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- 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...
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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.
- 2024
- Working Paper
Don’t Expect Juniors to Teach Senior Professionals to Use Generative AI: Emerging Technology Risks and Novice AI Risk Mitigation Tactics
By: Katherine C. Kellogg, Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Frabrizio Dell'Acqua, Edward McFowland III, François Candelon and Karim R. Lakhani
The literature on communities of practice demonstrates that a proven way for senior professionals to upskill
themselves in the use of new technologies that undermine existing expertise is to learn from junior
professionals. It notes that juniors may be better able...
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Kellogg, Katherine C., Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Frabrizio Dell'Acqua, Edward McFowland III, François Candelon, and Karim R. Lakhani. "Don’t Expect Juniors to Teach Senior Professionals to Use Generative AI: Emerging Technology Risks and Novice AI Risk Mitigation Tactics." Harvard Business School Working Paper, No. 24-074, June 2024.
- 2024
- Working Paper
Winner Take All: Exploiting Asymmetry in Factorial Designs
By: Matthew DosSantos DiSorbo, Iavor I. Bojinov and Fiammetta Menchetti
Researchers and practitioners have embraced factorial experiments to simultaneously test multiple treatments, each with different levels. With the rise of technologies like Generative AI, factorial experimentation has become even more accessible: it is easier than ever...
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Keywords:
Factorial Designs;
Fisher Randomizations;
Rank Estimators;
Employer Interventions;
Causal Inference;
Mathematical Methods;
Performance Improvement
DosSantos DiSorbo, Matthew, Iavor I. Bojinov, and Fiammetta Menchetti. "Winner Take All: Exploiting Asymmetry in Factorial Designs." Harvard Business School Working Paper, No. 24-075, June 2024.
- 2024
- Working Paper
Immigrant Entrepreneurship: New Estimates and a Research Agenda
By: Saheel Chodavadia, Sari Pekkala Kerr, William R. Kerr and Louis Maiden
Immigrants contribute disproportionately to entrepreneurship in many countries, accounting for a quarter of new employer businesses in the US. We review recent research on the measurement of immigrant entrepreneurship, the traits of immigrant founders, their economic...
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Keywords:
Immigrant Employment;
Immigration;
Entrepreneurship;
Demographics;
Innovation and Invention
Chodavadia, Saheel, Sari Pekkala Kerr, William R. Kerr, and Louis Maiden. "Immigrant Entrepreneurship: New Estimates and a Research Agenda." Harvard Business School Working Paper, No. 24-068, April 2024.
- 2024
- Working Paper
Old Moats for New Models: Openness, Control, and Competition in Generative AI
By: Pierre Azoulay, Joshua L. Krieger and Abhishek Nagaraj
Drawing insights from the field of innovation economics, we discuss the likely competitive environment shaping generative AI advances. Central to our analysis are the concepts of appropriability—whether firms in the industry are able to control the knowledge generated...
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Azoulay, Pierre, Joshua L. Krieger, and Abhishek Nagaraj. "Old Moats for New Models: Openness, Control, and Competition in Generative AI." NBER Working Paper Series, No. 7442, May 2024.
- 2024
- Working Paper
Greenlighting Innovative Projects: How Evaluation Format Shapes the Perceived Feasibility of Novel Ideas
By: Jacqueline N. Lane, Tianxi Cai, Michael Menietti, Griffin Weber and Eva C. Guinan
Evaluation of novel projects is essential for scientific and technological advancement. However,
evaluator bias toward a project’s potential can obscure its limitations. This study investigates
evaluation formats by contrasting combined assessments of novelty and...
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Lane, Jacqueline N., Tianxi Cai, Michael Menietti, Griffin Weber, and Eva C. Guinan. "Greenlighting Innovative Projects: How Evaluation Format Shapes the Perceived Feasibility of Novel Ideas." Harvard Business School Working Paper, No. 24-064, March 2024.
- 2024
- Working Paper
Precautionary Debt Capacity
By: Deniz Aydin and Olivia S. Kim
Firms with ample financial slack are unconstrained... or are they? In a field experiment
that randomly expands debt capacity on business credit lines, treated small-and-medium
enterprises (SMEs) draw down 35 cents on the dollar of expanded debt capacity in...
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Aydin, Deniz, and Olivia S. Kim. "Precautionary Debt Capacity." Harvard Business School Working Paper, No. 24-053, February 2024.
- February 2024
- Technical Note
AI Product Development Lifecycle
By: Michael Parzen, Jessie Li and Marily Nika
In this article, we will discuss the concept of AI Products, how they are changing our daily lives, how the field of AI & Product Management is evolving, and the AI Product Development Lifecycle.
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Keywords:
Artificial Intelligence;
Product Management;
Product Life Cycle;
Technology;
AI and Machine Learning;
Product Development
Parzen, Michael, Jessie Li, and Marily Nika. "AI Product Development Lifecycle." Harvard Business School Technical Note 624-070, February 2024.
- 2024
- Working Paper
Do Information Frictions and Corruption Perceptions Kill Competition? A Field Experiment on Public Procurement in Uganda
By: Emanuele Colonnelli, Francesco Loiacono, Edwin Muhumuza and Edoardo Teso
We study whether information frictions and corruption perceptions deter firms from doing business with the government. We conduct two nationwide randomized controlled trials (RCTs) in collaboration with the national public procurement supervisory and anti-corruption...
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Keywords:
Knowledge Use and Leverage;
Government and Politics;
Crime and Corruption;
Trust;
Perception;
Business and Government Relations
Colonnelli, Emanuele, Francesco Loiacono, Edwin Muhumuza, and Edoardo Teso. "Do Information Frictions and Corruption Perceptions Kill Competition? A Field Experiment on Public Procurement in Uganda." NBER Working Paper Series, No. 32170, February 2024.
- 2024
- Working Paper
Platform Information Provision and Consumer Search: A Field Experiment
By: Lu Fang, Yanyou Chen, Chiara Farronato, Zhe Yuan and Yitong Wang
Despite substantial efforts to help consumers search in more intuitive ways, text search remains the predominant tool for product discovery online. In this paper, we explore the effects of visual and textual cues for search refinement on consumer search and purchasing...
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Keywords:
Consumer Behavior;
E-commerce;
Decision Choices and Conditions;
Learning;
Internet and the Web
Fang, Lu, Yanyou Chen, Chiara Farronato, Zhe Yuan, and Yitong Wang. "Platform Information Provision and Consumer Search: A Field Experiment." NBER Working Paper Series, No. 32099, February 2024.
- January 2024
- Article
Investing with the Government: A Field Experiment in China
By: Emanuele Colonnelli, Bo Li and Ernest Liu
We study the demand for government participation in China’s venture capital and private equity market. We conduct a large-scale, non-deceptive field experiment in collaboration with the leading industry service provider, through which we survey both capital investors...
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Keywords:
Venture Capital;
Private Equity;
Business and Government Relations;
Entrepreneurship;
China
Colonnelli, Emanuele, Bo Li, and Ernest Liu. "Investing with the Government: A Field Experiment in China." Journal of Political Economy 132, no. 1 (January 2024): 248–294.
- 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...
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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.
- December 2023
- Case
Monsters in the Machine? Tackling the Challenge of Responsible AI
By: Paul M. Healy and Debora L. Spar
In November of 2022, the small tech company OpenAI released ChatGPT, an artificial intelligence chatbot which quickly captured the public’s imagination—becoming the world’s fastest-growing consumer application within months of its release. Though observers from across...
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Keywords:
Technological Innovation;
AI and Machine Learning;
Ethics;
Governing Rules, Regulations, and Reforms;
Technology Adoption;
Corporate Social Responsibility and Impact;
Technology Industry;
United States;
European Union;
China
Healy, Paul M., and Debora L. Spar. "Monsters in the Machine? Tackling the Challenge of Responsible AI." Harvard Business School Case 324-062, December 2023.
- 2023
- Article
Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset
By: Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu and Michael Lingzhi Li
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address this gap, we introduce CMExam,...
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Keywords:
Large Language Model;
AI and Machine Learning;
Analytics and Data Science;
Health Industry
Liu, Junling, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, and Michael Lingzhi Li. "Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 36 (2023).
- December 2023
- Article
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work
By: Mijeong Kwon, Julia Lee Cunningham and Jon M. Jachimowicz
Intrinsic motivation has received widespread attention as a predictor of positive work outcomes, including employees’ prosocial behavior. In the current research, we offer a more nuanced view by proposing that intrinsic motivation does not uniformly increase prosocial...
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Kwon, Mijeong, Julia Lee Cunningham, and Jon M. Jachimowicz. "Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work." Academy of Management Journal 66, no. 6 (December 2023): 1625–1650.
- 2023
- Chapter
Malleability Interventions in Intergroup Relations
By: Smadar Cohen-Chen, Amit Goldenberg, James J. Gross and Eran Halperin
One important characteristic of intergroup relations and conflicts is the fact that toxic or violent intergroup relations are often associated with fixed and stable perceptions of various entities, including the ingroup (stable and positive), the outgroup (stable and...
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Cohen-Chen, Smadar, Amit Goldenberg, James J. Gross, and Eran Halperin. "Malleability Interventions in Intergroup Relations." Chap. 7 in Psychological Intergroup Interventions: Evidence-based Approaches to Improve Intergroup Relations, by Eran Halperin, Boaz Hameiri, and Rebecca Littman. Routledge, 2023.
- December 2023
- Article
Save More Today or Tomorrow: The Role of Urgency in Precommitment Design
By: Joseph Reiff, Hengchen Dai, John Beshears, Katherine L. Milkman and Shlomo Benartzi
To encourage farsighted behaviors, past research suggests that marketers may be wise to invite consumers to pre-commit to adopt them “later.” However, the authors propose that people will draw different inferences from different types of pre-commitment offers, and that...
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Reiff, Joseph, Hengchen Dai, John Beshears, Katherine L. Milkman, and Shlomo Benartzi. "Save More Today or Tomorrow: The Role of Urgency in Precommitment Design." Journal of Marketing Research (JMR) 60, no. 6 (December 2023): 1095–1113.
- 2023
- Working Paper
The Uneven Impact of Generative AI on Entrepreneurial Performance
By: Nicholas G. Otis, Rowan Clarke, Solène Delecourt, David Holtz and Rembrand Koning
There is a growing belief that scalable and low-cost AI assistance can improve firm
decision-making and economic performance. However, running a business involves
a myriad of open-ended problems, making it hard to generalize from recent studies
showing that...
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Keywords:
AI and Machine Learning;
Performance Improvement;
Small Business;
Decision Choices and Conditions;
Kenya
Otis, Nicholas G., Rowan Clarke, Solène Delecourt, David Holtz, and Rembrand Koning. "The Uneven Impact of Generative AI on Entrepreneurial Performance." Harvard Business School Working Paper, No. 24-042, December 2023.
- 2023
- Book
How the Harvard Business School Changed the Way We View Organizations
By: Jay W. Lorsch
The story of the field of organizational behavior (which overlaps considerably with the origin story of Harvard Business School) and how it created the “medical model” of systems thinking—anchored in the practices of listening, observing, testing, and only then...
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Keywords:
Organizational Behavior;
Systems Thinking;
Medical Model;
Organizations;
Behavior;
System;
History
Lorsch, Jay W. How the Harvard Business School Changed the Way We View Organizations. Business Expert Press, 2023.
- November 2023 (Revised January 2024)
- Case
Bridgit: Persevere or Pivot?
By: Reza Satchu and Patrick Sanguineti
In late 2012, Mallorie Brodie and Lauren Lake, two young women in their final year of college, founded Bridgit, a technology startup that developed solutions to simplify vital but laborious processes within the construction industry. In the Fall of 2013, after months...
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