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(1,217)
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- Multimedia (3)
- Faculty Publications (578)
Show Results For
- All HBS Web
(1,217)
- People (2)
- News (188)
- Research (810)
- Events (14)
- Multimedia (3)
- Faculty Publications (578)
- 2018
- Working Paper
Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning
By: Xiaojia Guo, Yael Grushka-Cockayne and Bert De Reyck
Problem definition: In collaboration with Heathrow Airport, we develop a predictive system that generates quantile forecasts of transfer passengers’ connection times. Sampling from the distribution of individual passengers’ connection times, the system also produces... View Details
Keywords: Quantile Forecasts; Regression Tree; Copula; Passenger Flow Management; Data-driven Operations; Forecasting and Prediction; Data and Data Sets
Guo, Xiaojia, Yael Grushka-Cockayne, and Bert De Reyck. "Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning." Harvard Business School Working Paper, No. 19-040, October 2018.
- Working Paper
Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application
By: Flora Feng, Charis Li and Shunyuan Zhang
Peer-to-peer (P2P) marketplaces have seen exponential growth in recent years featured by unique offerings from individual providers. Despite the perceived value of uniqueness, scalable quantification of visual uniqueness in P2P platforms like Airbnb has been largely... View Details
Keywords: Peer-to-peer Markets; Marketplace Matching; AI and Machine Learning; Demand and Consumers; Digital Platforms; Marketing
Feng, Flora, Charis Li, and Shunyuan Zhang. "Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application." SSRN Working Paper Series, No. 4665286, February 2024.
- Research Summary
Overview
Jenny is broadly interested in interpretable machine learning (ML), identity and inequality, and improving existing methods used to answer social and policy-relevant questions. Her recent projects have focused on developing tools that explore how LLMs are reshaping... View Details
- Article
Productivity and Selection of Human Capital with Machine Learning
By: Aaron Chalfin, Oren Danieli, Andrew Hillis, Zubin Jelveh, Michael Luca, Jens Ludwig and Sendhil Mullainathan
Keywords: Analytics and Data Science; Selection and Staffing; Performance Productivity; Mathematical Methods; Policy
Chalfin, Aaron, Oren Danieli, Andrew Hillis, Zubin Jelveh, Michael Luca, Jens Ludwig, and Sendhil Mullainathan. "Productivity and Selection of Human Capital with Machine Learning." American Economic Review: Papers and Proceedings 106, no. 5 (May 2016): 124–127.
- 04 Oct 2019
- Working Paper Summaries
Soul and Machine (Learning)
- Web
Machine Learning frameworks (Tensorflow, PyTorch, Keras, OpenCV) - Research Computing Services
Software Tools Machine Learning frameworks (Tensorflow, PyTorch, Keras, OpenCV) 2ms The HBSGrid offers artificial intelligence(AI) and machine View Details
- Article
When Dreaming Is Believing: The (Motivated) Interpretation of Dreams
By: Carey K. Morewedge and Michael I. Norton
This research investigated laypeople's interpretation of their dreams. Participants from both Eastern and Western cultures believed that dreams contain hidden truths (Study 1) and considered dreams to provide more meaningful information about the world than similar... View Details
Keywords: Anchoring; Attribution; Dreams; Motivated Reasoning; Unconscious Thought; Communication Intention and Meaning; Judgments; Values and Beliefs; Information; Behavior; Cognition and Thinking; Motivation and Incentives
Morewedge, Carey K., and Michael I. Norton. "When Dreaming Is Believing: The (Motivated) Interpretation of Dreams." Journal of Personality and Social Psychology 96, no. 2 (February 2009): 249–264. (Winner of Society for Personality and Social Psychology. Theoretical Innovation Prize For an article or book chapter judged to provide the most innovative theoretical contribution to social/personality psychology within a given year presented by Society for Personality and Social Psychology.)
- 14 Mar 2023
- News
Can AI and Machine Learning Help Park Rangers Prevent Poaching?
- January 2024 (Revised February 2024)
- Case
Data-Driven Denim: Financial Forecasting at Levi Strauss
By: Mark Egan
The case examines Levi Strauss’ journey in implementing machine learning and AI into its financial forecasting process. The apparel company partnered with the IT company Wipro in 2017 to develop a machine learning algorithm that could help Levi Strauss forecast its... View Details
Keywords: Investor Relations; Forecasting; Machine Learning; Artificial Intelligence; Apparel; Corporate Finance; Forecasting and Prediction; AI and Machine Learning; Digital Transformation; Apparel and Accessories Industry; United States
Egan, Mark. "Data-Driven Denim: Financial Forecasting at Levi Strauss." Harvard Business School Case 224-029, January 2024. (Revised February 2024.)
- 2023
- Chapter
Marketing Through the Machine’s Eyes: Image Analytics and Interpretability
By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
Zhang, Shunyuan, Flora Feng, and Kannan Srinivasan. "Marketing Through the Machine’s Eyes: Image Analytics and Interpretability." Chap. 8 in Artificial Intelligence in Marketing. 20, edited by Naresh K. Malhotra, K. Sudhir, and Olivier Toubia, 217–238. Review of Marketing Research. Emerald Publishing Limited, 2023.
- 2025
- Article
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Journal of Business & Economic Statistics 43, no. 1 (2025): 256–268.
- November 25, 2016
- Article
How to Tell If Machine Learning Can Solve Your Business Problem
By: Anastassia Fedyk
Fedyk, Anastassia. "How to Tell If Machine Learning Can Solve Your Business Problem." Harvard Business Review (website) (November 25, 2016).
- April 2018 (Revised February 2019)
- Supplement
Improving Worker Safety in the Era of Machine Learning (B)
By: Michael W. Toffel, Dan Levy, Astrid Camille Pineda, Jose Ramon Morales Arilla and Matthew S. Johnson
Supplements the (A) case. View Details
Toffel, Michael W., Dan Levy, Astrid Camille Pineda, Jose Ramon Morales Arilla, and Matthew S. Johnson. "Improving Worker Safety in the Era of Machine Learning (B)." Harvard Business School Supplement 618-064, April 2018. (Revised February 2019.)
- October 2018
- Article
The Operational Value of Social Media Information
By: Ruomeng Cui, Santiago Gallino, Antonio Moreno and Dennis J. Zhang
While the value of using social media information has been established in multiple business contexts, the field of operations and supply chain management have not yet explored the possibilities it offers in improving firms' operational decisions. This study attempts to... View Details
Cui, Ruomeng, Santiago Gallino, Antonio Moreno, and Dennis J. Zhang. "The Operational Value of Social Media Information." Special Issue on Big Data in Supply Chain Management. Production and Operations Management 27, no. 10 (October 2018): 1749–1774.
- February 2018 (Revised March 2018)
- Case
Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP)
By: Lauren Cohen, Christopher Malloy and William Powley
This case examines the intersection of two firms (Cogent Labs—a machine learning software firm in Tokyo; and Google, the technology infrastructure giant) attempting to exploit the benefits of artificial intelligence and machine learning in the financial services... View Details
Keywords: Technological Innovation; Finance; Growth and Development Strategy; Business Model; Applications and Software; Infrastructure; Technology Industry; Financial Services Industry
Cohen, Lauren, Christopher Malloy, and William Powley. "Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP)." Harvard Business School Case 218-080, February 2018. (Revised March 2018.)
- February 2024
- Teaching Note
Data-Driven Denim: Financial Forecasting at Levi Strauss
By: Mark Egan
Teaching Note for HBS Case No. 224-029. Levi Strauss & Co. (“Levi Strauss”) partnered with the IT services company Wipro to incorporate more sophisticated methods, such as machine learning, into their financial forecasting process starting in 2018. The decision to... View Details
The Experimentation Machine
Leverage AI to be a 10x Founder
Today’s most successful founders know that the startups that learn the fastest will win. In The Experimentation Machine, HBS professor, entrepreneur, and venture capitalist Jeffrey J. Bussgang reveals... View Details
- May 2022
- Case
AWS and Amazon SageMaker (A): The Commercialization of Machine Learning Services
By: Karim R. Lakhani, Shane Greenstein and Kerry Herman
Lakhani, Karim R., Shane Greenstein, and Kerry Herman. "AWS and Amazon SageMaker (A): The Commercialization of Machine Learning Services." Harvard Business School Case 622-060, May 2022.