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- 2024
- Working Paper
Dusting Off the Old Ones: Drug Licensing to Startups, Innovation Success and Efficiency
By: Mosab Hammoudeh, Joshua Lev Krieger and Jiajie Xu
This paper investigates whether moving R&D from incumbents to startups can increase
innovation. Using comprehensive drug development data, we examine the
outcomes of drug projects licensed from large firms to startups. We find that these
projects licensed to...
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Hammoudeh, Mosab, Joshua Lev Krieger, and Jiajie Xu. "Dusting Off the Old Ones: Drug Licensing to Startups, Innovation Success and Efficiency." Harvard Business School Working Paper, No. 24-067, March 2024.
- 2024
- Working Paper
Choosing and Using Information in Evaluation Decisions
By: Katherine Baldiga Coffman, Scott Kostyshak and Perihan O. Saygin
Most studies of gender discrimination consider how male versus female candidates are assessed given otherwise identical information about them. But, in many settings of interest, evaluators have a choice about how much information to acquire about a candidate before...
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- March 2024
- Article
Do Safety Management System Standards Indicate Safer Operations? Evidence from the OHSAS 18001 Occupational Health and Safety Standard
By: Kala Viswanathan, Matthew S. Johnson and Michael W. Toffel
Problem definition: Given the enormous disruptions and costs of occupational injuries, companies and buyers are increasingly looking to voluntary occupational health and safety standards to improve worker safety. Yet because these standards only require...
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Keywords:
Occupational Health;
Occupational Safety;
Program Evaluation;
Safety Performance;
Injuries;
OHSAS 18001;
ISO 45001;
Working Conditions;
Safety;
Standards
Viswanathan, Kala, Matthew S. Johnson, and Michael W. Toffel. "Do Safety Management System Standards Indicate Safer Operations? Evidence from the OHSAS 18001 Occupational Health and Safety Standard." Art. 106383. Safety Science 171 (March 2024).
- March 2024
- Article
Human Capital Affects Religious Identity: Causal Evidence from Kenya
By: Livia Alfonsi, Michal Bauer, Julie Chytilová and Edward Miguel
We study how human capital and economic conditions causally affect the choice of religious denomination. We utilize a longitudinal dataset monitoring the religious history of more than 5,000 Kenyans over 20 years, in tandem with a randomized experiment (deworming) that...
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Alfonsi, Livia, Michal Bauer, Julie Chytilová, and Edward Miguel. "Human Capital Affects Religious Identity: Causal Evidence from Kenya." Art. 103215. Journal of Development Economics 167 (March 2024).
- February 2024
- Case
Can Cities Beat the Heat? (A): A Comparative Analysis of Climate Actions and Change Enablers in 14 U.S. Cities
By: Rosabeth Moss Kanter and Jacob A. Small
Throughout the early 2000's, emphasis was placed on initiatives to adapt to and mitigate climate action in cities. This series presents overviews (snapshots) of 14 U.S. metropolitan regions to help identify similarities, differences, and opportunities for developing...
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Keywords:
Climate;
Climate Impact;
Innovation;
Mitigation Policies;
Carbon Footprint;
Investing;
Climate Finance;
Renewable;
Mobility;
City;
Climate Change;
Adaptation;
Renewable Energy;
Weather;
Problems and Challenges;
United States;
Boston;
Detroit;
Miami;
Minneapolis;
St. Paul;
Pittsburgh;
Seattle;
San Jose
- 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.
- 2024
- Working Paper
Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift
By: Matthew DosSantos DiSorbo and Kris Ferreira
Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). These outliers often originate from covariate shift,...
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DosSantos DiSorbo, Matthew, and Kris Ferreira. "Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift." Working Paper, February 2024.
- 2024
- Working Paper
Age at Immigrant Arrival and Career Mobility: Evidence from Vietnamese Refugee Migration and the Amerasian Homecoming Act
By: Sari Pekkala Kerr, William R. Kerr and Kendall Smith
We study the long-run career mobility of young immigrants, mostly refugees, from Vietnam who moved to the United States during 1989-1995. This third and final migration wave of young Vietnamese immigrants was sparked by unexpected events that culminated in the...
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Keywords:
Vietnam;
Vietnam War;
Assimilation;
Immigration;
Refugees;
Age;
Outcome or Result;
Personal Development and Career;
Viet Nam
Kerr, Sari Pekkala, William R. Kerr, and Kendall Smith. "Age at Immigrant Arrival and Career Mobility: Evidence from Vietnamese Refugee Migration and the Amerasian Homecoming Act." Harvard Business School Working Paper, No. 24-044, January 2024.
- January 2024
- Supplement
Winning Business at Russell Reynolds
By: Ethan Bernstein and Cara Mazzucco
In an effort to make compensation drive collaboration, Russell Reynolds Associates’ (RRA) CEO Clarke Murphy sought to re-engineer the bonus system for his executive search consultants in 2016. As his HR analytics guru, Kelly Smith, points out, that risks upsetting–and...
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Bernstein, Ethan, and Cara Mazzucco. "Winning Business at Russell Reynolds." Harvard Business School Multimedia/Video Supplement 424-704, January 2024.
- January–February 2024
- Article
Shared Service Delivery Can Increase Client Engagement: A Study of Shared Medical Appointments
By: Ryan W. Buell, Kamalini Ramdas, Nazlı Sönmez, Kavitha Srinivasan and Rengaraj Venkatesh
Problem Definition: Clients and service providers alike often consider one-on-one service delivery to be ideal, assuming – perhaps unquestioningly – that devoting individualized attention best improves client outcomes. In contrast, in shared service delivery, clients...
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Keywords:
Health Care and Treatment;
Customer Satisfaction;
Outcome or Result;
Performance Improvement
Buell, Ryan W., Kamalini Ramdas, Nazlı Sönmez, Kavitha Srinivasan, and Rengaraj Venkatesh. "Shared Service Delivery Can Increase Client Engagement: A Study of Shared Medical Appointments." Manufacturing & Service Operations Management 26, no. 1 (January–February 2024): 154–166.
- 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...
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Huang, Ta-Wei, and Eva Ascarza. "Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach." Harvard Business School Working Paper, No. 24-034, December 2023.
- 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).
- 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...
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Keywords:
AI and Machine Learning
Lakkaraju, Himabindu, Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai, and Haoyi Xiong. "M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities, and Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 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...
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Keywords:
USPTO;
Natural Language Processing;
Classification;
Summarization;
Patent Novelty;
Patent Trolls;
Patent Enforceability;
Patents;
Innovation and Invention;
Intellectual Property;
AI and Machine Learning;
Analytics and Data Science
Suzgun, Mirac, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers, and Stuart Shieber. "The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 36 (2023).
- 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...
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Lerner, Josh, Jinlin Li, and Tong Liu. "Learning by Investing: Entrepreneurial Spillovers from Venture Capital." Harvard Business School Working Paper, No. 24-029, November 2023.
- Working Paper
An AI Method to Score Celebrity Visual Potential from Human Faces
By: Flora Feng, Shunyuan Zhang, Xiao Liu, Kannan Srinivasan and Cait Lamberton
Celebrities have extraordinary abilities to attract and influence others. Predicting celebrity visual potential is important in the domains of business, politics, media, and entertainment. Can we use human faces to predict celebrity visual potential? If so, which...
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Feng, Flora, Shunyuan Zhang, Xiao Liu, Kannan Srinivasan, and Cait Lamberton. "An AI Method to Score Celebrity Visual Potential from Human Faces." SSRN Working Paper Series, No. 4071188, November 2023.
- November 2023
- Article
Effects of Remote Patient Monitoring Use on Care Outcomes Among Medicare Patients with Hypertension
By: Mitchell Tang, Carter Nakamoto, Ariel Dora Stern, Jose Zubizarreta, Felippe Marcondes, Lori Uscher-Pines, Lee Schwamm and Ateev Mehrotra
Background: Remote patient monitoring (RPM) is a promising tool for improving chronic disease management. Use of RPM for hypertension monitoring is growing rapidly, raising concerns about increased spending. However, the effects of RPM are still...
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Tang, Mitchell, Carter Nakamoto, Ariel Dora Stern, Jose Zubizarreta, Felippe Marcondes, Lori Uscher-Pines, Lee Schwamm, and Ateev Mehrotra. "Effects of Remote Patient Monitoring Use on Care Outcomes Among Medicare Patients with Hypertension." Annals of Internal Medicine 176, no. 11 (November 2023): 1465–1475.
- 2023
- Working Paper
Healthcare Provider Bankruptcies
By: Samuel Antill, Jessica Bai, Ashvin Gandhi and Adrienne Sabety
Healthcare firms are increasingly filing for Chapter 11 bankruptcy. Using two strategies, we show causal evidence that bankruptcies harm patients through increased worker turnover. First, in an online experiment, experienced nurses assess hypothetical employers and...
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Keywords:
Insolvency and Bankruptcy;
Health Care and Treatment;
Outcome or Result;
Retention;
Health Industry
Antill, Samuel, Jessica Bai, Ashvin Gandhi, and Adrienne Sabety. "Healthcare Provider Bankruptcies." 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.
- 2022
- Working Paper
Why Do Index Funds Have Market Power? Quantifying Frictions in the Index Fund Market
By: Zach Y. Brown, Mark Egan, Jihye Jeon, Chuqing Jin and Alex A. Wu
Index funds are one of the most common ways investors access financial markets and are perceived to be a transparent and low-cost alternative to active investment management. Despite these purported virtues of index fund investing and the introduction of new products...
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Keywords:
Mutual Funds;
Passive Investing;
Asset Management;
Financial Markets;
Investment Funds;
Financial Management;
Financial Services Industry;
United States
Brown, Zach Y., Mark Egan, Jihye Jeon, Chuqing Jin, and Alex A. Wu. "Why Do Index Funds Have Market Power? Quantifying Frictions in the Index Fund Market." Harvard Business School Working Paper, No. 24-019, October 2023. (NBER Working Paper Series, No. 31778, October 2023.)