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- 2023
- Working Paper
Rapport in Organizations: Evidence from Fast Food
By: Achyuta Adhvaryu, Parker Howell, Anant Nyshadham and Jorge Tamayo
Common identity often provides a foundation for workplace rapport. Though gender is perhaps the most frequently studied dimension of identity among workers, little is known about how gender match between managers and their workers might affect team performance. Using... View Details
- December 12, 2023
- Article
Prices for Common Services at Quaternary vs Nonquaternary Hospitals
By: Brandon W. Yan, Maximilian J. Pany and Leemore S. Dafny
Using commercial health insurance claims data from 2017-2019, we assessed whether quaternary hospitals charged higher prices for common, unspecialized services also offered by nonquaternary hospitals. We found quaternary-hospital price premiums of 8.2 percent, on... 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
- December 4, 2023
- Comment
The Great Resignation, Employment, and Wages in Health Care
By: Amitabh Chandra and Louis-Jonas Heizlsperger
Notwithstanding concerns about staffing levels and burnout in health care, federal wage and employment data does not support the suggestion that a COVID-19 pandemic-related spike in quitting has had an enduring impact for hospitals or physician offices. Employment in... View Details
- December 2023
- Article
Association of Hospital System Affiliation with COVID-19 Capacity Burden
By: Zachary Levin, Pinar Karaca-Mandic, Richard J. Boxer and Regina E. Herzlinger
What is the message? The COVID-19 pandemic exposed the highly variable and uncoordinated responses by hospitals. The authors found that while the non-top ten system affiliated hospitals had a larger COVID-19 share index relative to independent hospitals, top-ten system... View Details
- 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,... View Details
- 2023
- Book
Beyond AI: ChatGPT, Web3, and the Business Landscape of Tomorrow
By: Ken Huang, Yang Wang, Feng Zhu, Xi Chen and Chunxiao Xing
This book explores the transformative potential of ChatGPT, Web3, and their impact on productivity and various industries. It delves into Generative AI (GenAI) and its representative platform ChatGPT, their synergy with Web3, and how they can revolutionize business... View Details
- September 2023
- Article
Customer Churn and Intangible Capital
By: Scott R. Baker, Brian Baugh and Marco Sammon
Intangible capital is a crucial and growing piece of firms’ capital structure, but many of its distinct components are difficult to measure. We develop and make available several new firm-level metrics regarding a key component of intangible capital – firms’ customer... 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
- 2023
- Other Article
The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications
By: Mirac Suzgun, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers and Stuart Shieber
Innovation is a major driver of economic and social development, and information about many kinds of innovation is embedded in semi-structured data from patents and patent applications. Though the impact and novelty of innovations expressed in patent data are difficult... 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
- December 2023
- Article
When Should the Off-Grid Sun Shine at Night? Optimum Renewable Generation and Energy Storage Investments
By: Christian Kaps, Simone Marinesi and Serguei Netessine
Globally, 1.5 billion people live off the grid, their only access to electricity often limited to operationally-expensive fossil fuel generators. Solar power has risen as a sustainable and less costly option, but its generation is variable during the day and... View Details
- 2023
- Article
Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju
One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause... View Details
- November 2023 (Revised March 2024)
- Technical Note
Customer Data Privacy
By: Eva Ascarza and Ta-Wei Huang
This note provides an overview of the evolving landscape of customer data privacy in 2023. It highlights two pivotal aspects that make privacy a central concern for businesses: building and maintaining customer trust and navigating the intricate regulatory... View Details
- 2023
- Working Paper
Learning by Investing: Entrepreneurial Spillovers from Venture Capital
By: Josh Lerner, Jinlin Li and Tong Liu
This paper studies how investing in venture capital (VC) affects the entrepreneurial outcomes of individual limited partners (LPs). Using comprehensive administrative data on entrepreneurial activities and VC fundraising and investments in China, we first document that... View Details
- 2023
- Working Paper
Flow-Driven ESG Returns
I show that the recent returns to ESG investing are strongly driven by price impact
from flows towards ESG funds. Using data on institutional trades, I estimate the
market’s ability to accommodate the demand of ESG funds, which is given by the
elasticity of... 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
- 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
Veeva Systems: The Next Frontier
By: Satish Tadikonda and William Marks
Born out of a desire to bring technological advances in enterprise software into the healthcare vertical, Peter Gassner and Matt Wallach founded Veeva to bring life sciences companies into the digital age for data management in both the commercial and R&D sectors. Over... View Details