Publications
Publications
Show Results For
- All HBS Web
(574)
- Faculty Publications (141)
Page 1 of 141
Results →
- September–October 2024
- Article
Where Data-Driven Decision-Making Can Go Wrong
By: Michael Luca and Amy C. Edmondson
When considering internal data or the results of a study, often business leaders either take the evidence presented as gospel or dismiss it altogether. Both approaches are misguided. What leaders need to do instead is conduct rigorous discussions that assess any... View Details
- 2024
- Working Paper
The Financial Anatomy of Climate Solutions: A Large Language Model Approach to Company Classification and Analysis
By: Shirley Lu and George Serafeim
Leveraging advancements in large language models (LLM), we study the financial characteristics of firms offering climate solutions-products and services aimed at fostering a transition to a low-carbon economy. We use a new measure that applies LLM to 10-K Item 1... View Details
- 2024
- Working Paper
People, Practices, and Productivity: A Review of New Advances in Personnel Economics
By: Mitchell Hoffman and Christopher T. Stanton
This chapter surveys recent advances in personnel economics. We begin by presenting evidence showing substantial and persistent productivity variation among workers in the same roles. We discuss new research on incentives and compensation; hiring practices; the... View Details
- July 2024
- Case
Roja Garimella: Developing a Founder's Judgment
By: Reza Satchu and Patrick Sanguineti
Roja Garimella’s path to becoming a founder was anything but straight. Setting her sights on a career in medicine since childhood, she committed to medical school with her acceptance to college. And yet, throughout her studies, she continually explored alternative... View Details
- 2024
- Working Paper
The Value of Silence: The Effect of UMG’s Licensing Dispute with TikTok on Music Demand
By: Mengjie (Magie) Cheng, Elie Ofek and Hema Yoganarasimhan
Social media platforms like TikTok have transformed how music is discovered, consumed, and
monetized. This study examines the implications of the dispute between TikTok and Universal Music
Group (UMG), which resulted in UMG excluding its music from TikTok from... View Details
- 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
- June 2024
- Article
The Monitoring Role of Social Media
By: Jonas Heese and Joseph Pacelli
In this study, we examine whether social media activity can reduce corporate misconduct. We use the staggered introduction of 3G mobile broadband access across the United States to identify exogenous increases in social media activity and test whether access to 3G... View Details
- April 2024
- Article
A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification
By: Hsin-Hsiao Scott Wang, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow and Caleb Nelson
Backgrounds: Urinary Tract Dilation (UTD) classification has been designed to be a more objective grading system to evaluate antenatal and post-natal UTD. Due to unclear association between UTD classifications to specific anomalies such as vesico-ureteral reflux (VUR),... View Details
- 2023
- Working Paper
An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
By: Biyonka Liang and Iavor I. Bojinov
Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the... View Details
- 2023
- Working Paper
Design-Based Inference for Multi-arm Bandits
By: Dae Woong Ham, Iavor I. Bojinov, Michael Lindon and Martin Tingley
Multi-arm bandits are gaining popularity as they enable real-world sequential decision-making across application areas, including clinical trials, recommender systems, and online decision-making. Consequently, there is an increased desire to use the available... View Details
- March 2024
- Article
Investigation of Divergent Thinking among Surgeons and Surgeon Trainees in Canada (IDEAS): A Mixed-methods Study
By: Alex Thabane, Tyler McKechnie, Vikram Arora, Goran Calic, Jason W Busse, Ranil Sonnadara and Mohit Bhandari
Objective: To assess the creative potential of surgeons and surgeon trainees, as measured by divergent thinking. The secondary objectives were to identify factors associated with divergent thinking, assess confidence in creative problem-solving and the perceived effect... View Details
- 2024
- Chapter
Managing for Organisational Integrity: My Take After Three Decades
By: Lynn S. Paine
This chapter revisits core ideas from my 1994 article “Managing for Organizational Integrity” and explores a critical issue not discussed in the article: the role of corporate boards. In the chapter, I first re-examine the article’s ideas about the origins of... View Details
- Working Paper
Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application
By: Flora Feng, Charis Li and Shunyuan Zhang
Peer-to-peer (P2P) marketplaces have seen exponential growth in recent years featured by unique offerings from individual providers. Despite the perceived value of uniqueness, scalable quantification of visual uniqueness in P2P platforms like Airbnb has been largely... View Details
- 2023
- Working Paper
Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach
By: Ta-Wei Huang and Eva Ascarza
Data-driven targeted interventions have become a powerful tool for organizations to optimize business outcomes
by utilizing individual-level data from experiments. A key element of this process is the estimation
of Conditional Average Treatment Effects (CATE), which... View Details
- October 2023 (Revised March 2024)
- Case
Fortinet: Cybersecurity Pioneer Ken Xie Considers the Long Game
By: Tsedal Neeley, Jeff Huizinga and Emily Grandjean
Ken Xie, cofounder of cybersecurity giant Fortinet, faced a critical decision that would validate his leadership. Fortinet became the industry’s second-largest pureplay cybersecurity firm by developing differentiated hardware and investing in R&D. However, after a... View Details
- 2023
- Working Paper
Are Hospital Quality Indicators Causal?
By: Amitabh Chandra, Maurice Dalton and Douglas O. Staiger
Hospitals play a key role in patient outcomes and spending, but efforts to improve their quality are hindered because we do not know whether hospital quality indicators are causal or biased. We evaluate the validity of commonly used quality indicators, such as... View Details
- 2023
- Working Paper
Emotion Regulation Contagion
By: Michael Pinus, Eran Halperin, Yajun Cao, Alin Coman, James Gross and Amit Goldenberg
In intergroup conflicts, emotion regulation interventions can decrease negative intergroup emotions and increase support for concessions. However, it is usually infeasible to provide emotion regulation interventions to everyone in a population of interest. This raises... View Details
- September 2023
- Article
Measuring Time Use in Rural India: Design and Validation of a Low-Cost Survey Module
By: Erica Field, Rohini Pande, Natalia Rigol, Simone Schaner, Elena Stacy and Charity Troyer Moore
Time use data can help us understand individual labor supply choices, especially
for women who often provide unpaid care and home production. Although
enumerator-assisted diary-based time use data collection is suitable for
low-literacy populations, it is costly and... View Details
- 2023
- Article
On Minimizing the Impact of Dataset Shifts on Actionable Explanations
By: Anna P. Meyer, Dan Ley, Suraj Srinivas and Himabindu Lakkaraju
The Right to Explanation is an important regulatory principle that allows individuals to request actionable explanations for algorithmic decisions. However, several technical challenges arise when providing such actionable explanations in practice. For instance, models... View Details
- Article
Update on E-liability Accounting
By: Robert Kaplan, Karthik Ramanna and Piyush Jha
Since publication of the original E-liability carbon accounting paper (HBR, Nov 2021), we created the E-liability Institute to help companies, governments, and nonprofits implement the method. The Institute’s mission is to test and validate the method, and develop... View Details