Publications
Publications
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- All HBS Web
(3,828)
- Faculty Publications (695)
- 2023
- Working Paper
Estimating Productivity in the Presence of Spillovers: Firm-Level Evidence from the U.S. Production Network
By: Ebehi Iyoha
This paper examines the extent to which productivity gains are transmitted across U.S. firms through buyer-supplier relationships. Many empirical studies measure firm-to-firm spillovers using firm-level productivity estimates derived from control function approaches.... View Details
- December 8, 2023
- Article
What Makes a Company Great at Producing Leaders?
By: Sarah Abbott, Robin Abrahams and Boris Groysberg
GE is well known as an “academy company”—a talent incubator that exports effective leaders to other organizations and even industries. To better understand which companies are top talent incubators today, the authors worked with the Official Board, a firm that provides... View Details
- 2023
- Article
M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities, and Models
By: Himabindu Lakkaraju, Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai and Haoyi Xiong
While Explainable Artificial Intelligence (XAI) techniques have been widely studied to explain predictions made by deep neural networks, the way to evaluate the faithfulness of explanation results remains challenging, due to the heterogeneity of explanations for... View Details
Keywords: AI and Machine Learning
- 2023
- Article
MoPe: Model Perturbation-based Privacy Attacks on Language Models
By: Marvin Li, Jason Wang, Jeffrey Wang and Seth Neel
Recent work has shown that Large Language Models (LLMs) can unintentionally leak sensitive information present in their training data. In this paper, we present Model Perturbations (MoPe), a new method to identify with high confidence if a given text is in the training... View Details
- December 2023
- Article
What Can Stockouts Tell Us About Inflation? Evidence from Online Micro Data
By: Alberto Cavallo and Oleksiy Kryvtsov
We use a detailed micro dataset on product availability and stockouts to construct a direct high-frequency measure of consumer product shortages during the 2020-2022 pandemic. We document a widespread multi-fold rise in stockouts in nearly all sectors early in the... View Details
- November–December 2023
- Article
Look the Part? The Role of Profile Pictures in Online Labor Markets
By: Isamar Troncoso and Lan Luo
Profile pictures are a key component of many freelancing platforms, a design choice that can impact hiring and matching outcomes. In this paper, we examine how appearance-based perceptions of a freelancer’s fit for the job (i.e., whether a freelancer "looks the part"... View Details
- November–December 2023
- Article
Network Centralization and Collective Adaptability to a Shifting Environment
By: Ethan S. Bernstein, Jesse C. Shore and Alice J. Jang
We study the connection between communication network structure and an organization’s collective adaptability to a shifting environment. Research has shown that network centralization—the degree to which communication flows disproportionately through one or more... View Details
- 2024
- Working Paper
What Do Impact Investors Do Differently?
In recent years, impact investors – private investors who seek to generate simultaneously financial and social returns – have attracted intense interest and controversy. We analyze a novel, comprehensive data set of impact and traditional investors to assess how the... View Details
- October 2023 (Revised April 2024)
- Case
TetraScience: Unlocking the Power of Scientific Data
By: Satish Tadikonda and William Marks
After pivoting from a focus on hardware to a focus on scientific data, TetraScience, led by veteran SaaS executive, Patrick Grady and Founder Spin Wang, has embarked on a journey from nearly cash-out to a player in the scientific data management space. This case... View Details
- 2023
- Working Paper
Black-box Training Data Identification in GANs via Detector Networks
By: Lukman Olagoke, Salil Vadhan and Seth Neel
Since their inception Generative Adversarial Networks (GANs) have been popular generative models across images, audio, video, and tabular data. In this paper we study whether given access to a trained GAN, as well as fresh samples from the underlying distribution, if... View Details
- 2023
- Working Paper
In-Context Unlearning: Language Models as Few Shot Unlearners
By: Martin Pawelczyk, Seth Neel and Himabindu Lakkaraju
Machine unlearning, the study of efficiently removing the impact of specific training points on the
trained model, has garnered increased attention of late, driven by the need to comply with privacy
regulations like the Right to be Forgotten. Although unlearning is... View Details
- October 2023
- Article
Innovation on Wings: When Do Nonstop Flights Matter for Global Innovation?
By: Dany Bahar, Prithwiraj Choudhury, Do Yoon Kim and Wesley Koo
We study whether, when, and how better connectivity through nonstop flights leads to positive innovation outcomes for firms in the global context. Using unique data of all flights emanating from 5,015 airports around the globe from 2005 to 2015 and exploiting a... View Details
- 2023
- Working Paper
The Impact of Input Inaccuracy on Leveraging AI Tools: Evidence from Algorithmic Labor Scheduling
By: Caleb Kwon, Antonio Moreno and Ananth Raman
Are the inputs used by your AI tool correct and up to date? In this paper, we show that the answer to this question: (i) is frequently a “no” in real business contexts, and (ii) has significant implications on the performance of AI tools. In the context of algorithmic... View Details
- 2023
- Working Paper
The Real Effects of Fair Workweek Laws on Work Schedules: Evidence from Chicago, Los Angeles, and Philadelphia
By: Caleb Kwon and Ananth Raman
Effective in eight jurisdictions and banned in four, Fair Workweek Laws (FWL) aim to increase the predictability and stability of work schedules. Among other requirements, these laws penalize employers for unilaterally adjusting work schedules without providing some... View Details
- 2023
- Working Paper
Words Can Hurt: How Political Communication Can Change the Pace of an Epidemic
By: Jessica Gagete-Miranda, Lucas Argentieri Mariani and Paula Rettl
While elite-cue effects on public opinion are well-documented, questions remain as
to when and why voters use elite cues to inform their opinions and behaviors. Using
experimental and observational data from Brazil during the COVID-19 pandemic, we
study how leader... View Details
Keywords: Elites; Public Engagement; Politics; Political Affiliation; Political Campaigns; Political Influence; Political Leadership; Political Economy; Survey Research; COVID-19; COVID-19 Pandemic; COVID; Cognitive Psychology; Cognitive Biases; Political Elections; Voting; Power and Influence; Identity; Behavior; Latin America; Brazil
- September 2023 (Revised January 2024)
- Case
AB InBev: Brewing Up Forecasts during COVID-19
By: Mark Egan, C. Fritz Foley, Esel Cekin and Emilie Billaud
In July 2021, the CEO of AB InBev's European operations and his team strategized to position the company for success post-pandemic. As the world's largest beer company, boasting over 500 brands, revenue of $46 billion, and a workforce of 160,000 in 2020, AB InBev... View Details
Keywords: Beer; Forecasting; COVID-19; Decision; Forecasting and Prediction; Analytics and Data Science; Crisis Management; Decisions; Financing and Loans; Investment Return; Resource Allocation; Distribution; Production; Business Processes; Strategic Planning; Health Pandemics; Digital Transformation; Markets; Food and Beverage Industry; Belgium; Europe; Latin America; North and Central America
- September 2023 (Revised December 2023)
- Case
TetraScience: Noise and Signal
By: Thomas R. Eisenmann and Tom Quinn
In 2019, TetraScience CEO “Spin” Wang needed advice. Five years earlier, he had cofounded a startup that saw early success with a hardware product designed to help laboratory scientists in the biotechnology and pharmaceutical spaces more easily collect data from... View Details
Keywords: Entrepreneurship; Business Growth and Maturation; Business Organization; Restructuring; Forecasting and Prediction; Digital Platforms; Analytics and Data Science; AI and Machine Learning; Organizational Structure; Network Effects; Competitive Strategy; Biotechnology Industry; Pharmaceutical Industry; United States; Boston
- 2025
- Working Paper
Better Keep the Twenty Dollars: Incentivizing Innovation in Open Source
By: Annamaria Conti, Vansh Gupta, Jorge Guzman and Maria P. Roche
Open source is key to innovation yet is assumed to be done largely through intrinsic motivation. How can we incentivize it? In this paper, we examine the impact of a program providing monetary incentives to motivate innovators to contribute to open source. The Sponsors... View Details
- September 2023
- Article
Consuming Contests: The Effect of Outcome Uncertainty on Spectator Attendance in the Australian Football League
By: Patrick Ferguson and Karim R. Lakhani
Contests that non-contestants consume for entertainment are a fixture of economic, cultural and political life. We exploit injury-induced changes to teams' line-ups in a professional sports setting to examine whether individuals prefer to consume contests that have... View Details
- September 2023
- Article
The Dynamics of Team Learning: Harmony and Rhythm in Teamwork Arrangements for Innovation
By: Jean-François Harvey, Johnathan R. Cromwell, Kevin J. Johnson and Amy C. Edmondson
Innovation teams must navigate inherent tensions between different learning activities to produce high levels of performance. Yet, we know little about how teams combine these activities—notably reflexive, experimental, vicarious, and contextual learning—most... View Details