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Show Results For
- All HBS Web
(1,000)
- People (1)
- News (156)
- Research (633)
- Events (13)
- Multimedia (3)
- Faculty Publications (542)
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- 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... View Details
- 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... View Details
- 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... View Details
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).
- July 2023 (Revised October 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... View Details
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 October 2024.)
- 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... View Details
- 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... View Details
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.
- 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,... View Details
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 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... View Details
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... View Details
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.
- 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... View Details
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
- 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... View Details
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).
- January 2021
- Case
Anodot: Autonomous Business Monitoring
By: Antonio Moreno and Danielle Golan
Autonomous business monitoring platform Anodot leveraged machine learning to provide real-time alerts regarding business anomalies. Anodot’s solution was used in various industries in order to primarily monitor business health, such as revenue and payments, product... View Details
Keywords: Digital Platforms; Internet and the Web; Knowledge Sharing; Information Management; Sales; Value Creation; Product Positioning; Israel
Moreno, Antonio, and Danielle Golan. "Anodot: Autonomous Business Monitoring." Harvard Business School Case 621-084, January 2021.
- 2021
- Article
To Thine Own Self Be True? Incentive Problems in Personalized Law
By: Jordan M. Barry, John William Hatfield and Scott Duke Kominers
Recent years have seen an explosion of scholarship on “personalized law.” Commentators foresee a world in which regulators armed with big data and machine learning techniques determine the optimal legal rule for every regulated party, then instantaneously disseminate... View Details
Keywords: Personalized Law; Regulation; Regulatory Avoidance; Regulatory Arbitrage; Law And Economics; Law And Technology; Law And Artificial Intelligence; Futurism; Moral Hazard; Elicitation; Signaling; Privacy; Law; Governing Rules, Regulations, and Reforms; Information Technology; AI and Machine Learning
Barry, Jordan M., John William Hatfield, and Scott Duke Kominers. "To Thine Own Self Be True? Incentive Problems in Personalized Law." Art. 2. William & Mary Law Review 62, no. 3 (2021).
- 15 Oct 2001
- Op-Ed
Lessons from the Rubble
Pundits and investors spoke giddily of the end of national borders, of markets that spanned the globe and replaced the hefty weight of machines and plants with ephemeral bits of information. This may be true. We do have global markets and... View Details
Keywords: by Debora L. Spar
- 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... View Details
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
Experimental Evaluation of Individualized Treatment Rules
By: Kosuke Imai and Michael Lingzhi Li
The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a... View Details
Keywords: Causal Inference; Heterogeneous Treatment Effects; Precision Medicine; Uplift Modeling; Analytics and Data Science; AI and Machine Learning
Imai, Kosuke, and Michael Lingzhi Li. "Experimental Evaluation of Individualized Treatment Rules." Journal of the American Statistical Association 118, no. 541 (2023): 242–256.
- 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... View Details
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).
- 2021
- Article
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation
By: Chuang Gan, Jeremy Schwartz, Seth Alter, Damian Mrowca, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Michael Lingelbach, Aidan Curtis, Kevin Feigelis, Daniel M. Bear, Dan Gutfreund, David Cox, Antonio Torralba, James J. DiCarlo, Joshua B. Tenenbaum, Josh H. McDermott and Daniel L.K. Yamins
We introduce ThreeDWorld (TDW), a platform for interactive multi-modal physical simulation. TDW enables simulation of high-fidelity sensory data and physical interactions between mobile agents and objects in rich 3D environments. Unique properties include: real-time... View Details
Keywords: Artificial Intelligence; Platform; Interactive Physical Simulation; Virtual Environment; Multi-modal; AI and Machine Learning
Gan, Chuang, Jeremy Schwartz, Seth Alter, Damian Mrowca, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Michael Lingelbach, Aidan Curtis, Kevin Feigelis, Daniel M. Bear, Dan Gutfreund, David Cox, Antonio Torralba, James J. DiCarlo, Joshua B. Tenenbaum, Josh H. McDermott, and Daniel L.K. Yamins. "ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 35th (2021).
- 2024
- Working Paper
Igniting Innovation: Evidence from PyTorch on Technology Control in Open Collaboration
By: Daniel Yue and Frank Nagle
Many companies offer free access to their technology to encourage outside addon
innovation, hoping to later profit by raising prices or harnessing the power of the crowd
while continuing to steer the direction of innovation. They can achieve this balance by
opening... View Details
Keywords: Technological Innovation; Power and Influence; Collaborative Innovation and Invention; Corporate Governance
Yue, Daniel, and Frank Nagle. "Igniting Innovation: Evidence from PyTorch on Technology Control in Open Collaboration." Harvard Business School Working Paper, No. 25-013, September 2024.
- July 2024
- Technical Note
What Is AI?
By: Michael Parzen and Jo Ellery
This note discusses definitions of artificial intelligence and covers the broad types of learning used in training AI, as well as explaining in detail how neural networks are built, trained, and used. View Details
Keywords: AI and Machine Learning
Parzen, Michael, and Jo Ellery. "What Is AI?" Harvard Business School Technical Note 625-010, July 2024.