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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
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.
- 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
- 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.
- November–December 2023
- Article
Iterative Coordination and Innovation: Prioritizing Value over Novelty
By: Sourobh Ghosh and Andy Wu
An innovating organization faces the challenge of how to prioritize distinct goals of novelty and value, both of which underlie innovation. Popular practitioner frameworks like Agile management suggest that organizations can adopt an iterative approach of frequent...
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Keywords:
Innovation;
Novelty;
Goals;
Specialization;
Coordination;
Field Experiment;
Software Development;
Agile;
Scrum;
Iteration;
Iterative;
Organizations;
Innovation and Invention;
Value;
Goals and Objectives;
Integration;
Applications and Software
Ghosh, Sourobh, and Andy Wu. "Iterative Coordination and Innovation: Prioritizing Value over Novelty." Organization Science 34, no. 6 (November–December 2023): 2182–2206.
- 2023
- Working Paper
Polarizing Corporations: Does Talent Flow to "Good" Firms?
By: Emanuele Colonnelli, Tim McQuade, Gabriel Ramos, Thomas Rauter and Olivia Xiong
We conduct a field experiment in partnership with the largest job platform in Brazil to study how environmental, social, and governance (ESG) practices
of firms affect talent allocation. We find both an average job-seeker’s preference for ESG and a large degree of...
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Keywords:
Corporate Social Responsibility and Impact;
Job Search;
Talent and Talent Management;
Wages;
Attitudes
Colonnelli, Emanuele, Tim McQuade, Gabriel Ramos, Thomas Rauter, and Olivia Xiong. Polarizing Corporations: Does Talent Flow to "Good" Firms? Working Paper, November 2023.
- 2023
- Working Paper
The Buy-In Effect: When Increasing Initial Effort Motivates Behavioral Follow-Through
By: Holly Dykstra, Shibeal O'Flaherty and A.V. Whillans
Behavioral interventions often focus on reducing friction to encourage behavior change. In
contrast, we provide evidence that adding friction can promote long-term behavior change when
behaviors involve repeated costly efforts over longer time horizons. In...
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Dykstra, Holly, Shibeal O'Flaherty, and A.V. Whillans. "The Buy-In Effect: When Increasing Initial Effort Motivates Behavioral Follow-Through." Harvard Business School Working Paper, No. 24-020, October 2023.
- 2023
- Working Paper
Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality
By: Fabrizio Dell'Acqua, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon and Karim R. Lakhani
The public release of Large Language Models (LLMs) has sparked tremendous interest in how humans will use Artificial Intelligence (AI) to accomplish a variety of tasks. In our study conducted with Boston Consulting Group, a global management consulting firm, we examine...
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Keywords:
Large Language Model;
AI and Machine Learning;
Performance Efficiency;
Performance Improvement
Dell'Acqua, Fabrizio, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon, and Karim R. Lakhani. "Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality." Harvard Business School Working Paper, No. 24-013, September 2023.
- Fall 2023
- Article
Infringing Use as a Path to Legal Consumption: Evidence from a Field Experiment
By: Hong Luo and Julie Holland Mortimer
Digitization has transformed how users find and use copyrighted goods, but many existing legal options remain difficult to access, possibly leading to infringement. In a field experiment, we contact firms that are caught infringing on expensive digital images. Emails...
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Luo, Hong, and Julie Holland Mortimer. "Infringing Use as a Path to Legal Consumption: Evidence from a Field Experiment." Special Issue on Field Experiments edited by Michael Luca and Sarah Moshary. Journal of Economics & Management Strategy 32, no. 3 (Fall 2023): 523–542.
- July–August 2023
- Article
Demand Learning and Pricing for Varying Assortments
By: Kris Ferreira and Emily Mower
Problem Definition: We consider the problem of demand learning and pricing for retailers who offer assortments of substitutable products that change frequently, e.g., due to limited inventory, perishable or time-sensitive products, or the retailer’s desire to...
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Keywords:
Experiments;
Pricing And Revenue Management;
Retailing;
Demand Estimation;
Pricing Algorithm;
Marketing;
Price;
Demand and Consumers;
Mathematical Methods
Ferreira, Kris, and Emily Mower. "Demand Learning and Pricing for Varying Assortments." Manufacturing & Service Operations Management 25, no. 4 (July–August 2023): 1227–1244. (Finalist, Practice-Based Research Competition, MSOM (2021) and Finalist, Revenue Management & Pricing Section Practice Award, INFORMS (2019).)
- July 2023
- Article
Before or After? The Effects of Payment Decision Timing in Pay-What-You-Want Contexts
By: Raghabendra P. KC, Vincent Mak and Elie Ofek
We study how payment decision timing—before versus after product delivery—influences consumer payment under pay-what-you-want pricing. We focus on situations where there is minimal change in consumer uncertainty regarding the product before versus after receiving it....
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KC, Raghabendra P., Vincent Mak, and Elie Ofek. "Before or After? The Effects of Payment Decision Timing in Pay-What-You-Want Contexts." Journal of Marketing 87, no. 4 (July 2023): 618–635.