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Show Results For
- All HBS Web
(1,194)
- People (1)
- News (232)
- Research (675)
- Events (17)
- Multimedia (8)
- Faculty Publications (560)
- Research Summary
Overview
Paul is primarily interested in studying explainable machine learning (ML), digital transformation, and data science operations. He works on research that explores how stakeholders within organizations can use machine learning to make better decisions. In particular,... View Details
- 2021
- Working Paper
An Empirical Study of Time Allotment and Delays in E-commerce Delivery
By: M. Balakrishnan, MoonSoo Choi and Natalie Epstein
Problem definition: We study how having more time allotted to deliver an order affects the speed of the delivery process. Furthermore, we seek to predict orders that are likely to be delayed early in the delivery process so that actions can be taken to avoid delays.... View Details
Keywords: Logistics; E-commerce; Mathematical Methods; AI and Machine Learning; Performance Productivity
Balakrishnan, M., MoonSoo Choi, and Natalie Epstein. "An Empirical Study of Time Allotment and Delays in E-commerce Delivery." Working Paper, December 2021.
Magie Cheng
Mengjie (Magie) Cheng is a Ph.D. student in Marketing at Harvard Business School. She received her B.S. in Finance from Chu Kochen Honors College at Zhejiang University and M.S. in Management Science and... View Details
- 19 Feb 2019
- First Look
New Research and Ideas, February 19, 2019
forthcoming Journal of Political Economy CEO Behavior and Firm Performance By: Bandiera, Oriana, Stephen Hansen, Andrea Prat, and Raffaella Sadun Abstract— We measure the behavior of 1,114 CEOs in six... View Details
Keywords: Sean Silverthorne
- Winter 2016
- Article
Analytics for an Online Retailer: Demand Forecasting and Price Optimization
By: Kris J. Ferreira, Bin Hong Alex Lee and David Simchi-Levi
We present our work with an online retailer, Rue La La, as an example of how a retailer can use its wealth of data to optimize pricing decisions on a daily basis. Rue La La is in the online fashion sample sales industry, where they offer extremely limited-time... View Details
Ferreira, Kris J., Bin Hong Alex Lee, and David Simchi-Levi. "Analytics for an Online Retailer: Demand Forecasting and Price Optimization." Manufacturing & Service Operations Management 18, no. 1 (Winter 2016): 69–88.
- 06 Jun 2017
- First Look
First Look at New Research and Ideas: June 6, 2017
understanding the lack of diversity in entrepreneurship and the venture capital industry. Download working paper: https://www.hbs.edu/faculty/Pages/item.aspx?num=52704 Cellophane, the New Visuality, and the... View Details
Keywords: Sean Silverthorne
- 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.
- 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).
- 01 Mar 2016
- News
Faculty Q&A: Price Check
- September 2020
- Case
True North: Pioneering Analytics, Algorithms and Artificial Intelligence
By: Karim R. Lakhani, Kairavi Dey and Hannah Mayer
True North was a private equity fund that specialized in the growth and buyout of mid-market, India-centric companies. The leadership team initially believed that technology was not core to traditional businesses and steered clear of new age technology-oriented... View Details
Keywords: Artificial Intelligence; Information Technology; Management; Operations; Organizations; Leadership; Innovation and Invention; Business Model; AI and Machine Learning; Computer Industry; Technology Industry
Lakhani, Karim R., Kairavi Dey, and Hannah Mayer. "True North: Pioneering Analytics, Algorithms and Artificial Intelligence." Harvard Business School Case 621-042, September 2020.
- 11 Dec 2019
- News
Are you ready for a robot boss? Many workers say that yes, they are
Shunyuan Zhang
Shunyuan Zhang is an assistant professor in the Marketing unit at Harvard Business School. She teaches the first-year Marketing course in the MBA required curriculum.
Professor Zhang studies the sharing economy and the marketing problems that the dynamics of... View Details
- September 2023 (Revised December 2023)
- Case
TetraScience: Noise and Signal
By: Thomas R. Eisenmann and Tom Quinn
In 2019, TetraScience CEO “Spin” Wang needed advice. Five years earlier, he had cofounded a startup that saw early success with a hardware product designed to help laboratory scientists in the biotechnology and pharmaceutical spaces more easily collect data from... View Details
Keywords: Entrepreneurship; Business Growth and Maturation; Business Organization; Restructuring; Forecasting and Prediction; Digital Platforms; Analytics and Data Science; AI and Machine Learning; Organizational Structure; Network Effects; Competitive Strategy; Biotechnology Industry; Pharmaceutical Industry; United States; Boston
Eisenmann, Thomas R., and Tom Quinn. "TetraScience: Noise and Signal." Harvard Business School Case 824-024, September 2023. (Revised December 2023.)
- 24 Jul 2019
- Blog Post
Data-Driven and in Demand
mining and exploratory analysis, and familiarized herself with the ins and outs of various machine learning... View Details
- October 2024
- Case
Reed Group and Succession in a Family Business: An Impossible Job to Fill?
By: Lauren H. Cohen and Tonia Labruyere
James Reed had taken over Reed Group, the recruitment and career services company his father had founded and built, in 1994. He was now reflecting on succession planning and other challenges that lay ahead: with no obvious choice among his family members, he needed to... View Details
Keywords: Charity; Succession Planning; Family Business; Values and Beliefs; Management Succession; Mission and Purpose; Family Ownership; Philanthropy and Charitable Giving; Family and Family Relationships; Recruitment; AI and Machine Learning; Employment Industry; United Kingdom; London
Cohen, Lauren H., and Tonia Labruyere. "Reed Group and Succession in a Family Business: An Impossible Job to Fill?" Harvard Business School Case 825-084, October 2024.
- March 2017
- Supplement
Donna Dubinsky, Numenta and Artificial Intelligence
By: David B. Yoffie
Donna Dubinsky, CEO of Numenta, discusses her views of the future of artificial intelligence and the strategic challenges of building a new platform. View Details
Keywords: Artificial Intelligence; Strategy; Technological Change; AI and Machine Learning; Technology Industry
Yoffie, David B. "Donna Dubinsky, Numenta and Artificial Intelligence." Harvard Business School Multimedia/Video Supplement 717-807, March 2017.
- 01 Dec 2022
- News
December 2022 Alumni and Faculty Books and Podcasts
determined quest. Auth will transport you in his spiritual time machine from Egypt’s Old Kingdom, through Greece and Rome, to medieval Europe; from the age of the Renaissance, through the Ages of Exploration... View Details
- 29 May 2018
- First Look
New Research and Ideas, May 29, 2018
incorporate these advancements to improve the way the functions work, how to incorporate machine learning and artificial intelligence that de facto improve productivity View Details
Keywords: Dina Gerdeman