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Show Results For
- All HBS Web
(4,852)
- People (10)
- News (1,053)
- Research (2,961)
- Events (70)
- Multimedia (35)
- Faculty Publications (1,724)
- March 2022 (Revised January 2025)
- Technical Note
Prediction & Machine Learning
By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional... View Details
Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation; AI and Machine Learning
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Prediction & Machine Learning." Harvard Business School Technical Note 622-101, March 2022. (Revised January 2025.)
- 15 Apr 2014
- News
Bertarelli Foundation Gift Names Deans' Health & Life Sciences Challenge Prize
with his family. One of the businesses of which Waypoint is comprised is Gurnet Point Capital, a health care and life sciences fund recently established and based in Boston. In... View Details
- 29 Jun 2015
- News
Study Suggests Google Harms Consumers by Skewing Search Results
- 2007
- Working Paper
I'll Have the Ice Cream Soon and the Vegetables Later: A Study of Online Grocery Purchases and Order Lead Time
By: Katherine L. Milkman, Todd Rogers and Max H. Bazerman
How do decisions made for tomorrow or two days in the future differ from decisions made for several days in the future? We use data from an online grocer to address this question. In general, we find that as the delay between order completion and delivery increases,... View Details
Keywords: Internet and the Web; Food; Decision Choices and Conditions; Conflict and Resolution; Emotions; Cognition and Thinking; Food and Beverage Industry; Food and Beverage Industry
Milkman, Katherine L., Todd Rogers, and Max H. Bazerman. "I'll Have the Ice Cream Soon and the Vegetables Later: A Study of Online Grocery Purchases and Order Lead Time." Harvard Business School Working Paper, No. 07-078, April 2007. (Revised December 2007, May 2008, September 2008.)
- Article
Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications
By: Daniel Elsner, Pouya Aleatrati Khosroshahi, Alan MacCormack and Robert Lagerström
Existing application performance management (APM) solutions lack robust anomaly detection capabilities and root cause analysis techniques that do not require manual efforts and domain knowledge. In this paper, we develop a density-based unsupervised machine learning... View Details
Keywords: Big Data; Data Science And Analytics Management; Governance And Compliance; Organizational Systems And Technology; Anomaly Detection; Application Performance Management; Machine Learning; Enterprise Architecture; Analytics and Data Science
Elsner, Daniel, Pouya Aleatrati Khosroshahi, Alan MacCormack, and Robert Lagerström. "Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications." Proceedings of the Hawaii International Conference on System Sciences 52nd (2019): 5827–5836.
- 2019
- Working Paper
Using Technology to Augment Professionals, Instead of Replacing Them, for Innovative Problem Solving
By: Hila Lifshitz - Assaf, Felicia Ng, Aniket Kittur and Robert Kraut
While in some technological and scientific areas innovation is flourishing, in others it is stalling, leaving important problems unsolved for decades. One explanation is professionals’ limitations as problem solvers, as accumulating depth of knowledge enhances one’s... View Details
- Article
Paradise Lost (and Restored?): A Study of Psychological Safety over Time
By: Derrick P. Bransby, Michaela Kerrissey and Amy C. Edmondson
Although prior research indicates that psychological safety can fluctuate, questions about when and why remain. To gain insights into the emergence and temporal dynamics of psychological safety, we explored longitudinal data representing more than 10,000 health care... View Details
Keywords: Analytics and Data Science; Research; Attitudes; Working Conditions; Well-being; Health Industry
Bransby, Derrick P., Michaela Kerrissey, and Amy C. Edmondson. "Paradise Lost (and Restored?): A Study of Psychological Safety over Time." Academy of Management Discoveries (in press). (Pre-published online March 14, 2024.)
- 20 Jun 2019
- Blog Post
What is the MS/MBA Biotechnology: Life Sciences Program? A Q&A with Bill Anderson, Senior Lecturer on Stem Cell and Regenerative Biology
this field. Furthermore, these advances raise a host of ethical issues in terms of diseases targeted, types of therapies, and accessibility. Given the rich experience of translational science in the Harvard... View Details
- 31 Oct 2019
- Blog Post
5 Things on My Mind in the Second Year of the MS/MBA: Engineering Sciences Program
ambiguity, form an opinion, and defend it with while keeping an open mind when listening to others. In the second year of the program, we choose electives based on our interests. I am particularly enjoying my Strategy View Details
- July 2006
- Article
Exploring the Structure of Complex Software Designs: An Empirical Study of Open Source and Proprietary Code
By: Alan MacCormack, John Rusnak and Carliss Y. Baldwin
MacCormack, Alan, John Rusnak, and Carliss Y. Baldwin. "Exploring the Structure of Complex Software Designs: An Empirical Study of Open Source and Proprietary Code." Management Science 52, no. 7 (July 2006).
- March 2010
- Article
I'll Have the Ice Cream Soon and the Vegetables Later: A Study of Online Grocery Purchases and Order Lead Time
By: Katherine L. Milkman, Todd Rogers and Max Bazerman
How do decisions made for tomorrow or two days in the future differ from decisions made for several days in the future? We use data from an online grocer to address this question. In general, we find that as the delay between order completion and delivery increases,... View Details
Keywords: Time Management; Service Delivery; Internet and the Web; Decisions; Customers; Retail Industry
Milkman, Katherine L., Todd Rogers, and Max Bazerman. "I'll Have the Ice Cream Soon and the Vegetables Later: A Study of Online Grocery Purchases and Order Lead Time." Marketing Letters 21, no. 1 (March 2010): 17–35.
The Value of Descriptive Analytics: Evidence from Online Retailers - Marketing Science
Does the adoption of descriptive analytics impact online retailer performance, and if so, how? We use the synthetic difference-in-differences method to analyze the staggered adoption of a retail analytics dashboard by more than 1,500 e-commerce websites, and we... View Details
- 01 Apr 2001
- News
Khoo Teng Chye: Technology Turnaround in Singapore
productivity has multiplied four- or fivefold in the last fifteen years,” beams Khoo Teng Chye (110th AMP), group president of PSA. “Our company is a world leader in applying technology to port management View Details
- 2022
- Book
The Role of Innovation and Entrepreneurship in Economic Growth
By: Michael J. Andrews, Aaron Chatterji, Josh Lerner and Scott Stern
We live in an era in which innovation and entrepreneurship seem ubiquitous, particularly in regions like Silicon Valley, Boston, and the Research Triangle Park. But many metrics of economic growth, such as productivity growth and business dynamism, have been at best... View Details
Keywords: Productivity Growth; Production Technologies; Innovation and Invention; Entrepreneurship; Economic Growth; Competition; Organizational Design; Economic Slowdown and Stagnation
Andrews, Michael J., Aaron Chatterji, Josh Lerner, and Scott Stern, eds. The Role of Innovation and Entrepreneurship in Economic Growth. Chicago: University of Chicago Press, 2022.
- June 2022 (Revised January 2025)
- Technical Note
Causal Inference
By: Iavor I Bojinov, Michael Parzen and Paul Hamilton
This note provides an overview of causal inference for an introductory data science course. First, the note discusses observational studies and confounding variables. Next the note describes how randomized experiments can be used to account for the effect of... View Details
Keywords: Causal Inference; Causality; Experiment; Experimental Design; Data Science; Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Causal Inference." Harvard Business School Technical Note 622-111, June 2022. (Revised January 2025.)
- 1 Apr 2005 - 4 Apr 2005
- Conference Presentation
Exploring the Structure of Complex Software Designs: An Empirical Study of Open Source and Proprietary Code
By: Alan MacCormack
- July 2019
- Teaching Note
AT&T, Retraining, and the Workforce of Tomorrow
By: William R. Kerr and Carl Kreitzberg
A Teaching Note for the "AT&T, Retraining, and the Workforce of Tomorrow" case study (HBS#820-017). The case describes how AT&T designed and implemented a program to retrain 100,000 of its workers. The case first reviews the technological forces that compelled AT&T to... View Details
Keywords: AT＆T; Workforce; Future Of Work; Telecommunications; Unions; Technological Change; Layoffs; MOOCS; Strategic Planning; Employees; Training; Labor; Learning; Labor Unions; Technology Adoption; Talent and Talent Management; Transformation; Telecommunications Industry; Communications Industry; United States
- May–June 2025
- Article
Algorithmic Assortment Curation: An Empirical Study of Buybox in Online Marketplaces
By: Santiago Gallino, Nil Karacaoglu and Antonio Moreno
Most online sales worldwide take place in marketplaces that connect sellers and buyers. The presence of numerous third-party sellers leads to a proliferation of listings for each product, making it difficult for customers to choose between the available options. Online... View Details
Keywords: Algorithms; Marketplaces; Marketplace Matching; E-commerce; Demand and Consumers; Customer Focus and Relationships; Market Participation; Technology Adoption
Gallino, Santiago, Nil Karacaoglu, and Antonio Moreno. "Algorithmic Assortment Curation: An Empirical Study of Buybox in Online Marketplaces." Manufacturing & Service Operations Management 27, no. 3 (May–June 2025): 917–934.
- 2019
- Article
An Empirical Study of Rich Subgroup Fairness for Machine Learning
By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
Kearns et al. [2018] recently proposed a notion of rich subgroup fairness intended to bridge the gap between statistical and individual notions of fairness. Rich subgroup fairness picks a statistical fairness constraint (say, equalizing false positive rates across... View Details
Kearns, Michael J., Seth Neel, Aaron Leon Roth, and Zhiwei Steven Wu. "An Empirical Study of Rich Subgroup Fairness for Machine Learning." Proceedings of the Conference on Fairness, Accountability, and Transparency (2019): 100–109.