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- All HBS Web
(3,354)
- Faculty Publications (800)
- 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... View Details
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... View Details
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,... View Details
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... View Details
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... View Details
Keywords: Restructuring; Talent and Talent Management; Compensation and Benefits; Growth and Development Strategy; Organizational Change and Adaptation; Organizational Culture; Performance Evaluation; Motivation and Incentives; Consulting Industry
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... View Details
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... View Details
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,... View Details
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... View Details
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... View Details
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... View Details
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.
- 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... View Details
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... View Details
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... View Details
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.)
- 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
Keywords: Leadership Development; Leadership Style; Marketing Strategy; Communication Strategy; Cybersecurity; Competitive Advantage; Information Technology Industry; United States; Sunnyvale
Neeley, Tsedal, Jeff Huizinga, and Emily Grandjean. "Fortinet: Cybersecurity Pioneer Ken Xie Considers the Long Game." Harvard Business School Case 424-016, October 2023. (Revised March 2024.)
- 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
Olagoke, Lukman, Salil Vadhan, and Seth Neel. "Black-box Training Data Identification in GANs via Detector Networks." Working Paper, October 2023.
- 2023
- Working Paper
No Revenge for Nerds? Evaluating the Careers of Ivy League Athletes
By: Natee Amornsiripanitch, Paul A. Gompers, George Hu, Will Levinson and Vladimir Mukharlyamov
This paper compares the careers of Ivy League athletes to those of their non-athlete classmates. Combining team-level information on all Ivy League athletes from 1970 to 2021 with resume data for all Ivy League graduates, we examine both post-graduate education and... View Details
Amornsiripanitch, Natee, Paul A. Gompers, George Hu, Will Levinson, and Vladimir Mukharlyamov. "No Revenge for Nerds? Evaluating the Careers of Ivy League Athletes." NBER Working Paper Series, No. 31753, October 2023.
- October 2023
- Article
Product Variety, the Cost of Living, and Welfare Across Countries
By: Alberto Cavallo, Robert C. Feenstra and Robert Inklaar
We use the structure of the Melitz (2003) model to compute the cost of living and welfare across 47 countries, and compare these to conventional measures of prices and real consumption from the International Comparisons Project (ICP). The cost of living is inferred... View Details
Cavallo, Alberto, Robert C. Feenstra, and Robert Inklaar. "Product Variety, the Cost of Living, and Welfare Across Countries." American Economic Journal: Macroeconomics 15, no. 4 (October 2023): 40–66.
- 2023
- Working Paper
The Effect of Childhood Environment on Political Behavior: Evidence from Young U.S. Movers, 1992–2021
By: Jacob R. Brown, Enrico Cantoni, Sahil Chinoy, Martin Koenen and Vincent Pons
We ask how childhood environment shapes political behavior. We measure young voters’ participation and party affiliation in nationally comprehensive voter files and reconstruct their childhood location histories based on their parents’ addresses. We compare outcomes of... View Details
Brown, Jacob R., Enrico Cantoni, Sahil Chinoy, Martin Koenen, and Vincent Pons. "The Effect of Childhood Environment on Political Behavior: Evidence from Young U.S. Movers, 1992–2021." NBER Working Paper Series, No. 31759, October 2023.
- 2023
- Working Paper
Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality
By: Fabrizio Dell'Acqua, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon and Karim R. Lakhani
The public release of Large Language Models (LLMs) has sparked tremendous interest in how humans will use Artificial Intelligence (AI) to accomplish a variety of tasks. In our study conducted with Boston Consulting Group, a global management consulting firm, we examine... View Details
Keywords: Large Language Model; AI and Machine Learning; Performance Efficiency; Performance Improvement
Dell'Acqua, Fabrizio, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon, and Karim R. Lakhani. "Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality." Harvard Business School Working Paper, No. 24-013, September 2023.