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- Faculty Publications (453)
Show Results For
-
All HBS Web
(865)
- People (1)
- News (152)
- Research (549)
- Events (10)
- Multimedia (3)
- Faculty Publications (453)
- Article
How to Use Heuristics for Differential Privacy
By: Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
We develop theory for using heuristics to solve computationally hard problems in differential privacy. Heuristic approaches have enjoyed tremendous success in machine learning, for which performance can be empirically evaluated. However, privacy guarantees cannot be...
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Neel, Seth, Aaron Leon Roth, and Zhiwei Steven Wu. "How to Use Heuristics for Differential Privacy." Proceedings of the IEEE Annual Symposium on Foundations of Computer Science (FOCS) 60th (2019).
- 2023
- Working Paper
The Customer Journey as a Source of Information
By: Nicolas Padilla, Eva Ascarza and Oded Netzer
In the face of heightened data privacy concerns and diminishing third-party data access,
firms are placing increased emphasis on first-party data (1PD) for marketing decisions.
However, in environments with infrequent purchases, reliance on past purchases 1PD...
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Keywords:
Customer Journey;
Privacy;
Consumer Behavior;
Analytics and Data Science;
AI and Machine Learning;
Customer Focus and Relationships
Padilla, Nicolas, Eva Ascarza, and Oded Netzer. "The Customer Journey as a Source of Information." Harvard Business School Working Paper, No. 24-035, October 2023. (Revised October 2023.)
- Research Summary
Overview
By: Shunyuan Zhang
Professor Zhang uses machine learning to address marketing problems that have arisen within the nascent sharing economy. She conducts rigorous analyses of structured and unstructured data generated by new sharing economy platforms to address important issues emerging...
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- September 15, 2021
- Article
Improving Deconvolution Methods in Biology Through Open Innovation Competitions: An Application to the Connectivity Map
By: Andrea Blasco, Ted Natoli, Michael G. Endres, Rinat A. Sergeev, Steven Randazzo, Jin Hyun Paik, N.J. Maximilian Macaluso, Rajiv Narayan, Xiaodong Lu, David Peck, Karim R. Lakhani and Aravind Subramanian
A recurring problem in biomedical research is how to isolate signals of distinct populations (cell types, tissues, and genes) from composite measures obtained by a single analyte or sensor. Existing computational deconvolution approaches work well in many specific...
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Keywords:
Deconvolution;
Methods;
Open Innovation Competition;
Genomics;
Research;
Innovation and Invention
Blasco, Andrea, Ted Natoli, Michael G. Endres, Rinat A. Sergeev, Steven Randazzo, Jin Hyun Paik, N.J. Maximilian Macaluso, Rajiv Narayan, Xiaodong Lu, David Peck, Karim R. Lakhani, and Aravind Subramanian. "Improving Deconvolution Methods in Biology Through Open Innovation Competitions: An Application to the Connectivity Map." Bioinformatics 37, no. 18 (September 15, 2021).
- 2023
- Working Paper
Beyond the Hype: Unveiling the Marginal Benefits of 3D Virtual Tours in Real Estate
By: Mengxia Zhang and Isamar Troncoso
3D virtual tours (VTs) have become a popular digital tool in real estate platforms, enabling potential buyers to virtually walk through the houses they search for online. In this paper, we study home sellers’ adoption of VTs and the VTs’ relative benefits compared to...
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Zhang, Mengxia, and Isamar Troncoso. "Beyond the Hype: Unveiling the Marginal Benefits of 3D Virtual Tours in Real Estate." Harvard Business School Working Paper, No. 24-003, July 2023.
- February 2021
- Case
Digital Manufacturing at Amgen
By: Shane Greenstein, Kyle R. Myers and Sarah Mehta
This case discusses efforts made by biotechnology (biotech) company Amgen to introduce digital technologies into its manufacturing processes. Doing so is complicated by the fact that the process for manufacturing biologics—or therapeutics made from living cells—is...
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Keywords:
Digital Technologies;
Change;
Change Management;
Decision Making;
Cost vs Benefits;
Decisions;
Information;
Analytics and Data Science;
Innovation and Invention;
Innovation and Management;
Innovation Leadership;
Innovation Strategy;
Technological Innovation;
Jobs and Positions;
Knowledge;
Leadership;
Organizational Culture;
Science;
Strategy;
Information Technology;
Technology Adoption;
Biotechnology Industry;
Pharmaceutical Industry;
United States;
California;
Puerto Rico;
Rhode Island
Greenstein, Shane, Kyle R. Myers, and Sarah Mehta. "Digital Manufacturing at Amgen." Harvard Business School Case 621-008, February 2021.
- 2020
- Working Paper
(When) Does Appearance Matter? Evidence from a Randomized Controlled Trial
By: Prithwiraj Choudhury, Tarun Khanna, Christos A. Makridis and Subhradip Sarker
While there is evidence about labor market discrimination based on race, religion, and gender, we know little about whether physical appearance leads to discrimination in labor market outcomes. We deploy a randomized experiment on 1,000 respondents in India between...
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Keywords:
Behavioral Economics;
Coronavirus;
Discrimination;
Homophily;
Labor Market Mobility;
Limited Attention;
Resumes;
Personal Characteristics;
Prejudice and Bias
Choudhury, Prithwiraj, Tarun Khanna, Christos A. Makridis, and Subhradip Sarker. "(When) Does Appearance Matter? Evidence from a Randomized Controlled Trial." Harvard Business School Working Paper, No. 21-038, September 2020.
- Research Summary
Overview
Ms. Fedyk's main research interests lie at the intersection of asset pricing and behavioral finance, with a particular focus on information and belief formation. Her job market paper is part of a broader research agenda on the way in which information is incorporated...
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- 2018
- Working Paper
Some Facts of High-Tech Patenting
By: Michael Webb, Nick Short, Nicholas Bloom and Josh Lerner
Patenting in software, cloud computing, and artificial intelligence has grown rapidly in recent years. Such patents are acquired primarily by large U.S. technology firms such as IBM, Microsoft, Google, and HP, as well as by Japanese multinationals such as Sony, Canon,...
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Webb, Michael, Nick Short, Nicholas Bloom, and Josh Lerner. "Some Facts of High-Tech Patenting." Harvard Business School Working Paper, No. 19-014, August 2018. (NBER Working Paper Series, No. 24793, July 2018.)
- May 2021
- Teaching Note
From Globalization to Dual Digital Transformation: CEO Thierry Breton Leading Atos Into 'Digital Shockwaves'
By: Tsedal Neeley
Teaching Note for HBS Case Nos. 419-027 and 419-046. Thierry Breton, chairman and CEO of IT company Atos, faces a pivotal juncture. After spending eight intense years scaling the company globally to over 100,000 employees in 70 countries, he sees digital shockwaves...
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- July 2023 (Revised August 2024)
- Case
Revenue Recognition at Stride Funding: Making Sense of Revenues for a Fintech Startup
By: Paul M. Healy and Jung Koo Kang
The case explores the challenges of revenue recognition and financial reporting for Stride Funding (Stride), a fintech startup that has disrupted the student loan market. Stride leveraged proprietary machine learning and financial models to underwrite alternative...
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Keywords:
Revenue Recognition;
Financial Reporting;
Entrepreneurial Finance;
Business Startups;
Growth and Development Strategy;
Governance Compliance;
Accrual Accounting;
Financial Services Industry;
United States
Healy, Paul M., and Jung Koo Kang. "Revenue Recognition at Stride Funding: Making Sense of Revenues for a Fintech Startup." Harvard Business School Case 124-015, July 2023. (Revised August 2024.)
- July 2023 (Revised July 2023)
- Background Note
Generative AI Value Chain
By: Andy Wu and Matt Higgins
Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are...
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Keywords:
AI;
Artificial Intelligence;
Model;
Hardware;
Data Centers;
AI and Machine Learning;
Applications and Software;
Analytics and Data Science;
Value
Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
- March 1, 2022
- Article
Widespread Use of National Academies Consensus Reports by the American Public
By: Diana Hicks, Matteo Zullo, Ameet Doshi and Omar Isaac Asensio
In seeking to understand how to protect the public information sphere from corruption, researchers understandably focus on dysfunction. However, parts of the public information ecosystem function very well, and understanding this as well will help in protecting and...
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Keywords:
Reports;
Surveys;
AI and Machine Learning;
Knowledge Dissemination;
Knowledge Use and Leverage
Hicks, Diana, Matteo Zullo, Ameet Doshi, and Omar Isaac Asensio. "Widespread Use of National Academies Consensus Reports by the American Public." e2107760119. Proceedings of the National Academy of Sciences 119, no. 9 (March 1, 2022).
Linda A. Hill
Linda A. Hill is the Wallace Brett Donham Professor of Business Administration at the Harvard Business School and Faculty Chair of the Leadership Initiative. Hill is regarded as one of the top experts on leadership and innovation. Hill is... View Details
- May 2021 (Revised February 2024)
- Teaching Note
THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)
By: Ayelet Israeli and Jill Avery
THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on...
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Keywords:
Data;
Data Analytics;
Artificial Intelligence;
AI;
AI Algorithms;
AI Creativity;
Fashion;
Retail;
Retail Analytics;
E-Commerce Strategy;
Platform;
Platforms;
Big Data;
Preference Elicitation;
Predictive Analytics;
App Development;
"Marketing Analytics";
Advertising;
Mobile App;
Mobile Marketing;
Apparel;
Online Advertising;
Referral Rewards;
Referrals;
Female Ceo;
Female Entrepreneur;
Female Protagonist;
Analytics and Data Science;
Analysis;
Creativity;
Marketing Strategy;
Brands and Branding;
Consumer Behavior;
Demand and Consumers;
Forecasting and Prediction;
Marketing Channels;
Digital Marketing;
Internet and the Web;
Mobile and Wireless Technology;
AI and Machine Learning;
E-commerce;
Digital Platforms;
Fashion Industry;
Retail Industry;
Apparel and Accessories Industry;
Consumer Products Industry;
United States
- May 2024
- Article
Financial Innovation in the 21st Century: Evidence from U.S. Patents
By: Josh Lerner, Amit Seru, Nick Short and Yuan Sun
We develop a unique dataset of 24 thousand U.S. finance patents granted over the last two decades to explore the evolution and production of financial innovation. We use machine learning to identify the financial patents and extensively audit the results to ensure...
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Keywords:
Banking;
Investment Banks;
Information Technology;
Regulation;
Patents;
Innovation and Invention;
Trends
Lerner, Josh, Amit Seru, Nick Short, and Yuan Sun. "Financial Innovation in the 21st Century: Evidence from U.S. Patents." Journal of Political Economy 132, no. 5 (May 2024): 1391–1449.
- April 2021
- Article
Work-From-Anywhere: The Productivity Effects of Geographical Flexibility
By: Prithwiraj Choudhury, Cirrus Foroughi and Barbara Larson
An emerging form of remote work allows employees to work-from-anywhere, so that the worker can choose to live in a preferred geographic location. While traditional work-from-home (WFH) programs offer the worker temporal flexibility, work-from-anywhere (WFA) programs...
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Keywords:
Geographic Flexibility;
Work-from-anywhere;
Remote Work;
Telecommuting;
Geographic Mobility;
USPTO;
Employees;
Geographic Location;
Performance Productivity
Choudhury, Prithwiraj, Cirrus Foroughi, and Barbara Larson. "Work-From-Anywhere: The Productivity Effects of Geographical Flexibility." Strategic Management Journal 42, no. 4 (April 2021): 655–683.
Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development
Predictive model development is understudied despite its importance to modern businesses. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms) as the primary driver of model quality, the value of...
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- 2023
- Article
Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability
By: Usha Bhalla, Suraj Srinivas and Himabindu Lakkaraju
With the increased deployment of machine learning models in various real-world applications, researchers and practitioners alike have emphasized the need for explanations of model behaviour. To this end, two broad strategies have been outlined in prior literature to...
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Bhalla, Usha, Suraj Srinivas, and Himabindu Lakkaraju. "Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 2023
- Article
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse
By: Martin Pawelczyk, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci and Himabindu Lakkaraju
As machine learning models are increasingly being employed to make consequential decisions in real-world settings, it becomes critical to ensure that individuals who are adversely impacted (e.g., loan denied) by the predictions of these models are provided with a means...
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Pawelczyk, Martin, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci, and Himabindu Lakkaraju. "Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse." Proceedings of the International Conference on Learning Representations (ICLR) (2023).