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Show Results For
- All HBS Web
(2,830)
- People (14)
- News (648)
- Research (1,560)
- Events (19)
- Multimedia (9)
- Faculty Publications (830)
- August 2018 (Revised October 2020)
- Case
Tailor Brands: Artificial Intelligence-Driven Branding
By: Jill Avery
Using proprietary artificial intelligence technology, startup Tailor Brands set out to democratize branding by allowing small businesses to create their brand identities by automatically generating logos in just minutes at minimal cost with no branding or design skills... View Details
Keywords: Startup; Services; Artificial Intelligence; Machine Learning; Digital Marketing; Brand Management; Big Data; Internet Marketing; Analytics; Marketing; Marketing Strategy; Brands and Branding; Information Technology; Entrepreneurship; Venture Capital; Business Model; Consumer Behavior; AI and Machine Learning; Analytics and Data Science; Advertising Industry; Service Industry; Technology Industry; United States; North America; Israel
Avery, Jill. "Tailor Brands: Artificial Intelligence-Driven Branding." Harvard Business School Case 519-017, August 2018. (Revised October 2020.)
- 24 Jan 2005
- Research & Ideas
Entrepreneurial Hospital Pioneers New Model
roll out a similar model beyond India—maybe even into Europe and the U.S. What's the secret? According to HBS professor Tarun Khanna, the success of the hospital, called Narayana Hrudayalaya, is due to the vision and tireless work of a... View Details
- 23 Jan 2012
- News
Ernest Shackleton: Role Model for Today's Leaders?
- Article
Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy
By: Edward Glaeser, Andrew Hillis, Scott Duke Kominers and Michael Luca
The proliferation of big data makes it possible to better target city services like hygiene inspections, but city governments rarely have the in-house talent needed for developing prediction algorithms. Cities could hire consultants, but a cheaper alternative is to... View Details
Keywords: User-generated Content; Operations; Tournaments; Policy-making; Machine Learning; Online Platforms; Analytics and Data Science; Mathematical Methods; City; Infrastructure; Business Processes; Government and Politics
Glaeser, Edward, Andrew Hillis, Scott Duke Kominers, and Michael Luca. "Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy." American Economic Review: Papers and Proceedings 106, no. 5 (May 2016): 114–118.
- July 2019
- Teaching Note
Miroglio Fashion
By: Sunil Gupta
Teaching Note for HBS Nos. 519-053, 519-070, and 519-072. View Details
- 2012
- Working Paper
Prominent Job Advertisements, Group Learning and Wage Dispersion
By: Julio J. Rotemberg
A model is presented in which people base their labor search strategy on the average wage and the average unemployment duration of people who belong to their peer group. It is shown that, if the distribution of wage offers is not stationary so lower wage offers tend to... View Details
Rotemberg, Julio J. "Prominent Job Advertisements, Group Learning and Wage Dispersion." NBER Working Paper Series, No. 18638, December 2012.
- 2024
- Working Paper
The Cram Method for Efficient Simultaneous Learning and Evaluation
By: Zeyang Jia, Kosuke Imai and Michael Lingzhi Li
We introduce the "cram" method, a general and efficient approach to simultaneous learning and evaluation using a generic machine learning (ML) algorithm. In a single pass of batched data, the proposed method repeatedly trains an ML algorithm and tests its empirical... View Details
Keywords: AI and Machine Learning
Jia, Zeyang, Kosuke Imai, and Michael Lingzhi Li. "The Cram Method for Efficient Simultaneous Learning and Evaluation." Working Paper, March 2024.
- 27 Aug 2014
- Lessons from the Classroom
Learning From Japan’s Remarkable Disaster Recovery
leadership in mobilizing people and resources in highly dynamic situations.” Each winter, 900 HBS students dispatch around the world to see businesses up close, learn what they can about how they are run, and share their own knowledge... View Details
- 07 Sep 2011
- News
Lessons Learned from Skydeck
- Article
Algorithms Need Managers, Too
By: Michael Luca, Jon Kleinberg and Sendhil Mullainathan
Algorithms are powerful predictive tools, but they can run amok when not applied properly. Consider what often happens with social media sites. Today many use algorithms to decide which ads and links to show users. But when these algorithms focus too narrowly on... View Details
Keywords: Machine Learning; Algorithms; Predictive Analytics; Management; Big Data; Analytics and Data Science
Luca, Michael, Jon Kleinberg, and Sendhil Mullainathan. "Algorithms Need Managers, Too." Harvard Business Review 94, nos. 1/2 (January–February 2016): 96–101.
- 07 Jan 2012
- News
What Minnesota can learn from Germany
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... View Details
- 26 Mar 2007
- Research & Ideas
Learning from Failed Political Leadership
international objectives are in jeopardy today. To the extent that business strategies are based on these same erroneous notions, they are also at great risk. Q: What can a business executive learn about leadership from your research? A:... View Details
Keywords: by Martha Lagace
- 24 Apr 2024
- News
What Managers Can Learn from Jazz Improvisation
- 2003
- Working Paper
Dynamic Mixed Duopoly: A Model Motivated by Linux vs. Windows
By: Ramon Casadesus-Masanell and Pankaj Ghemawat
This paper analyzes a dynamic mixed duopoly in which a profit-maximizing competitor interacts with a competitor that prices at zero (or marginal cost), with the cumulation of output affecting their relative positions over time. The modeling effort is motivated by... View Details
Keywords: Business Model; Competition; Open Source Distribution; Balance and Stability; Applications and Software; Network Effects; Duopoly and Oligopoly
Casadesus-Masanell, Ramon, and Pankaj Ghemawat. "Dynamic Mixed Duopoly: A Model Motivated by Linux vs. Windows." Harvard Business School Working Paper, No. 04-012, August 2003.
- 2023
- Article
Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju
One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause... View Details
Srinivas, Suraj, Sebastian Bordt, and Himabindu Lakkaraju. "Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 08 Sep 2015
- Research & Ideas
Knowledge Transfer: You Can't Learn Surgery By Watching
corporate roles is to improve upon traditional vicarious learning models. ©iStock.com/cacaroot Instead, Myers envisions a model of coactive vicarious learning. “The major shift theoretically is moving from a... View Details
- Teaching Interest
Overview
Teaching has been a lifelong passion of mine. As the third generation of academics in my family, I see good teaching as a means to give back and to encourage others to share my passion for discovery. I’ve been very lucky to have many teaching opportunities, both as an... View Details
Keywords: Big Data; Technology Strategy; Machine Learning; Data Science; ＂Marketing Analytics＂; Data Visualization; Analysis; Technological Innovation; Innovation and Invention; Intellectual Property; Corporate Strategy; Software; Information Technology; Entrepreneurship; Marketing; Technology Industry; Information Technology Industry; Green Technology Industry; Computer Industry; Advertising Industry
- September 2018 (Revised December 2019)
- Case
Zebra Medical Vision
By: Shane Greenstein and Sarah Gulick
An Israeli startup founded in 2014, Zebra Medical Vision developed algorithms that produced diagnoses from X-rays, mammograms, and CT-scans. The algorithms used deep learning and digitized radiology scans to create software that could assist doctors in making... View Details
Keywords: Radiology; Machine Learning; X-ray; CT Scan; Medical Technology; Probability; FDA 510(k); Diagnosis; Business Startups; Health Care and Treatment; Information Technology; Applications and Software; Competitive Strategy; Product Development; Commercialization; Decision Choices and Conditions; Health Industry; Medical Devices and Supplies Industry; Technology Industry; Israel
Greenstein, Shane, and Sarah Gulick. "Zebra Medical Vision." Harvard Business School Case 619-014, September 2018. (Revised December 2019.)
- April 2011
- Article
What Can We Learn from 'Great Negotiations'?
What can one legitimately learn-analytically and/or prescriptively-from detailed historical case studies of "great negotiations," chosen more for their salience than their analytic characteristics or comparability? Taking a number of such cases compiled by Stanton... View Details
Keywords: Learning; International Relations; History; Agreements and Arrangements; Negotiation Process; Conflict and Resolution
Sebenius, James K. "What Can We Learn from 'Great Negotiations'?" Negotiation Journal 27, no. 2 (April 2011).