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- 2024
- Working Paper
The Real Effects of Bankruptcy Forum Shopping
By: Samuel Antill and Aymeric Bellon
Many non-Delaware firms strategically file for bankruptcy in Delaware. Should this "forum shopping" be allowed? This question has motivated six congressional bill proposals over decades of policy debate. Using a novel natural experiment and Census-Bureau microdata, we... View Details
Antill, Samuel, and Aymeric Bellon. "The Real Effects of Bankruptcy Forum Shopping." Working Paper, December 2024.
- 2024
- Working Paper
Generative AI and the Nature of Work
By: Manuel Hoffmann, Sam Boysel, Frank Nagle, Sida Peng and Kevin Xu
Recent advances in artificial intelligence (AI) technology demonstrate considerable potential to
complement human capital intensive activities. While an emerging literature documents wide-ranging productivity
effects of AI, relatively little attention has been paid... View Details
Keywords: Generative Ai; Digital Work; Open Source Software; Knowledge Economy; AI and Machine Learning; Open Source Distribution; Organizational Structure; Performance Productivity; Labor
Hoffmann, Manuel, Sam Boysel, Frank Nagle, Sida Peng, and Kevin Xu. "Generative AI and the Nature of Work." Harvard Business School Working Paper, No. 25-021, October 2024.
- October 2024
- Article
Canary Categories
By: Eric Anderson, Chaoqun Chen, Ayelet Israeli and Duncan Simester
Past customer spending in a category is generally a positive signal of future customer spending. We show that there exist “canary categories” for which the reverse is true. Purchases in these categories are a signal that customers are less likely to return to that... View Details
Keywords: Churn; Churn Management; Churn/retention; Assortment Planning; Retail; Retailing; Retailing Industry; Preference Heterogeneity; Assortment Optimization; Customers; Retention; Consumer Behavior; Forecasting and Prediction; Retail Industry
Anderson, Eric, Chaoqun Chen, Ayelet Israeli, and Duncan Simester. "Canary Categories." Journal of Marketing Research (JMR) 61, no. 5 (October 2024): 872–890.
- 2024
- Book
Retiring: Creating a Life That Works for You
By: Teresa M. Amabile, Lotte Bailyn, Marcy Crary, Douglas T. Hall and Kathy E. Kram
Retirement, as a major life transition, can be both thrilling and challenging in unexpected ways. Written by acclaimed authors in the fields of business leadership, careers, and work, this book goes beyond the typical financial and health-related advice on retirement,... View Details
Keywords: Retirement
Amabile, Teresa M., Lotte Bailyn, Marcy Crary, Douglas T. Hall, and Kathy E. Kram. Retiring: Creating a Life That Works for You. Routledge, 2024.
- 2024
- Working Paper
The Effect of a System for Sharing Best Practices Within Pre-existing Peer Networks
By: Shelley Xin Li and Tatiana Sandino
Peer networks, such as enterprise social networks (ESNs), can facilitate knowledge transfer across employees. However, such systems can also lead to information overload or difficulty in finding useful information. We examine data from a natural field experiment where... View Details
Li, Shelley Xin, and Tatiana Sandino. "The Effect of a System for Sharing Best Practices Within Pre-existing Peer Networks." Working Paper, October 2024.
- September 2024
- Article
A Potential Pitfall of Passion: Passion Is Associated with Performance Overconfidence
By: Erica R. Bailey, Kai Krautter, Wen Wu, Adam D. Galinsky and Jon M. Jachimowicz
Having passion is almost universally lauded. People strive to follow their passion at work, and organizations increasingly seek out passionate employees. Supporting the benefits of passion, prior research finds a robust relationship between passion and higher levels of... View Details
Bailey, Erica R., Kai Krautter, Wen Wu, Adam D. Galinsky, and Jon M. Jachimowicz. "A Potential Pitfall of Passion: Passion Is Associated with Performance Overconfidence." Social Psychological & Personality Science 15, no. 7 (September 2024): 769–779.
- 2024
- Working Paper
The Wade Test: Generative AI and CEO Communication
By: Prithwiraj Choudhury, Bart S. Vanneste and Amirhossein Zohrehvand
Can generative artificial intelligence (AI) transform the role of the CEO by effectively automating CEO
communication? This study investigates whether AI can mimic a human CEO and whether employees’
perception of the communication’s source matter. In a field... View Details
Choudhury, Prithwiraj, Bart S. Vanneste, and Amirhossein Zohrehvand. "The Wade Test: Generative AI and CEO Communication." Harvard Business School Working Paper, No. 25-008, August 2024.
- 2024
- Working Paper
The Narrative AI Advantage? A Field Experiment on Generative AI-Augmented Evaluations of Early-Stage Innovations
By: Jacqueline N. Lane, Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh and Pei-Hsin Wang
The rise of generative artificial intelligence (AI) is transforming creative problem-solving, necessitating new approaches for evaluating innovative solutions. This study explores how human-AI collaboration can enhance early-stage evaluations, focusing on the interplay... View Details
Lane, Jacqueline N., Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh, and Pei-Hsin Wang. "The Narrative AI Advantage? A Field Experiment on Generative AI-Augmented Evaluations of Early-Stage Innovations." Harvard Business School Working Paper, No. 25-001, August 2024. (Revised August 2024.)
- Working Paper
The Returns to Skills During the Pandemic: Experimental Evidence from Uganda
By: Livia Alfonsi, Vittorio Bassi, Imran Rasul and Elena Spadini
The Covid-19 pandemic represents one of the most significant labor market shocks to the world economy in recent times. We present evidence from a field experiment to understand whether and why skilled and unskilled workers were differentially impacted by the shock, in... View Details
Keywords: COVID-19 Pandemic; System Shocks; Labor; Competency and Skills; Development Economics; Uganda
Alfonsi, Livia, Vittorio Bassi, Imran Rasul, and Elena Spadini. "The Returns to Skills During the Pandemic: Experimental Evidence from Uganda." Harvard Business School Working Paper, No. 25-003, August 2024. (NBER Working Paper Series, No. 32785, August 2024.)
- July 2024
- Article
Chatbots and Mental Health: Insights into the Safety of Generative AI
By: Julian De Freitas, Ahmet Kaan Uğuralp, Zeliha Uğuralp and Stefano Puntoni
Chatbots are now able to engage in sophisticated conversations with consumers. Due to the ‘black box’ nature of the algorithms, it is impossible to predict in advance how these conversations will unfold. Behavioral research provides little insight into potential safety... View Details
Keywords: Autonomy; Chatbots; New Technology; Brand Crises; Mental Health; Large Language Model; AI and Machine Learning; Behavior; Well-being; Technological Innovation; Ethics
De Freitas, Julian, Ahmet Kaan Uğuralp, Zeliha Uğuralp, and Stefano Puntoni. "Chatbots and Mental Health: Insights into the Safety of Generative AI." Journal of Consumer Psychology 34, no. 3 (July 2024): 481–491.
- July–August 2024
- Article
Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals
By: Ta-Wei Huang and Eva Ascarza
Firms are increasingly interested in developing targeted interventions for customers with the best response,
which requires identifying differences in customer sensitivity, typically through the conditional average treatment
effect (CATE) estimation. In theory, to... View Details
Keywords: Long-run Targeting; Heterogeneous Treatment Effect; Statistical Surrogacy; Customer Churn; Field Experiments; Consumer Behavior; Customer Focus and Relationships; AI and Machine Learning; Marketing Strategy
Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Marketing Science 43, no. 4 (July–August 2024): 863–884.
- July 2024
- Article
Whether to Apply
By: Katherine B. Coffman, Manuela Collis and Leena Kulkarni
Labor market outcomes depend, in part, upon an individual’s willingness to put herself forward for different opportunities. We use a series of experiments to explore gender differences in willingness to apply for higher return, more challenging work. We find that, in... View Details
Coffman, Katherine B., Manuela Collis, and Leena Kulkarni. "Whether to Apply." Management Science 70, no. 7 (July 2024): 4649–4669.
- 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... View Details
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, Fabrizio 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... View Details
Kellogg, Katherine C., Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Fabrizio 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... View Details
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.
- May 2024
- Case
HarvEast
By: Jeremy Friedman and Natalie Kindred
In late 2023, Dmitry Skornyakov, CEO of Ukrainian agribusiness HarvEast, was navigating the turmoil caused by Russia’s invasion of Ukraine that began in 2014 and escalated into full-scale war in February 2022. Before the full-scale invasion, HarvEast managed 127,000... View Details
Keywords: Goods and Commodities; Natural Resources; Food; Problems and Challenges; Adaptation; Innovation and Management; Crisis Management; Logistics; Supply Chain; Risk and Uncertainty; Loss; Trust; Human Needs; War; Agriculture and Agribusiness Industry; Chile; South America; Latin America; Ukraine
- May–June 2024
- Article
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
Lane, Jacqueline N., Karim R. Lakhani, and Roberto Fernandez. "Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs." Organization Science 35, no. 3 (May–June 2024): 911–927.
- 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... View Details
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... View Details
Aydin, Deniz, and Olivia S. Kim. "Precautionary Debt Capacity." Harvard Business School Working Paper, No. 24-053, February 2024.
- 2024
- Working Paper
Does Pension Automatic Enrollment Increase Debt? Evidence from a Large-Scale Natural Experiment
By: John Beshears, Matthew Blakstad, James J. Choi, Christopher Firth, John Gathergood, David Laibson, Richard Notley, Jesal D. Sheth, Will Sandbrook and Neil Stewart
Does automatic enrollment into retirement saving increase household debt? We study the randomized roll-out of automatic enrollment pensions to ~160,000 employers in the United Kingdom with 2-29 employees. We find that the additional savings generated through automatic... View Details
Keywords: Retirement; Saving; Personal Finance; Borrowing and Debt; Credit; Compensation and Benefits
Beshears, John, Matthew Blakstad, James J. Choi, Christopher Firth, John Gathergood, David Laibson, Richard Notley, Jesal D. Sheth, Will Sandbrook, and Neil Stewart. "Does Pension Automatic Enrollment Increase Debt? Evidence from a Large-Scale Natural Experiment." Working Paper, October 2024.