Filter Results:
(3,905)
Show Results For
- All HBS Web
(10,694)
- People (64)
- News (3,258)
- Research (3,905)
- Events (24)
- Multimedia (60)
- Faculty Publications (1,368)
Show Results For
- All HBS Web
(10,694)
- People (64)
- News (3,258)
- Research (3,905)
- Events (24)
- Multimedia (60)
- Faculty Publications (1,368)
Sort by
- Research Summary
Paper - Commodity Chains: what can we learn from a business history of the rubber chain? (1870-1910)
The literature on the rubber boom applied a Marxist/Dependendist view of rubber production in the Brazilian Amazon. Even though a sizeable surplus was generated in the rubber chain, it was mostly appropriated by foreigners. This view is in tune with the Global... View Details
- 07 Sep 2021
- Research & Ideas
Who Pays For Wildfire and Hurricane Damage? Everyone.
New Mexico homeowners might think their inland location buffers them from the financial toll of climate change, but they’re still paying for climate-related property damage occurring in coastal states. New research finds that homeowners in New Mexico and other states... View Details
- 29 Jul 2002
- Research & Ideas
Time Pressure and Creativity: Why Time is Not on Your Side
need to keep creative thinking in their organizations even as time pressures increase. Silverthorne: What was the genesis of the project? What fascinated you about the question of time pressure and creativity? Amabile: Over the course of... View Details
- 12 Oct 2021
- Research & Ideas
What Actually Draws Sports Fans to Games? It's Not Star Athletes.
suggests that spectators also value something far simpler: the suspense of not knowing who will win. In fact, stadiums sell more tickets when the outcome of a game is less predictable, says a study by Harvard Business School Professor... View Details
- 23 May 2023
- Research & Ideas
Face Value: Do Certain Physical Features Help People Get Ahead?
empirically predicted with a machine learning model, suggests work by Shunyuan Zhang, an assistant professor at Harvard Business School, and collaborators. “Our research represents the first empirical... View Details
Keywords: by Kara Baskin
- 27 Sep 2021
- Research & Ideas
Managers, Your Employees Don’t Want to Be Facebook ‘Friends’
Online—was coauthored by Nancy P. Rothbard, David Pottruck Professor of Management of the Wharton School of Business; Lakshmi Ramarajan, the Anna Spangler Nelson and Thomas C. Nelson Associate Professor of Business Administration at... View Details
Keywords: by Rachel Kim Raczka
- Article
Counterfactual Explanations Can Be Manipulated
By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh
Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate... View Details
Slack, Dylan, Sophie Hilgard, Himabindu Lakkaraju, and Sameer Singh. "Counterfactual Explanations Can Be Manipulated." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- 19 Jan 2015
- Research & Ideas
Is Wikipedia More Biased Than Encyclopædia Britannica?
institution announced it would no longer publish a print version of its multivolume compendium of knowledge. Though the Britannica would still be available online, the writing on the virtual wall was clear: It had been supplanted by the... View Details
- 29 Jul 2022
- Research & Ideas
Will Demand for Women Executives Finally Shrink the Gender Pay Gap?
problem, the researchers say. Despite growing awareness and activism, the wage gap has remained largely unchanged for the last 15 years, according to a recent study by the Pew Research Center, which found that in 2020, women earned 84... View Details
Keywords: by Kristen Senz
- 29 Feb 2024
- HBS Case
Beyond Goals: David Beckham's Playbook for Mobilizing Star Talent
its own right, amplified by the power of social media. “You can build a follower base that’s bigger than what traditional media can offer, and you can reproduce that talent on a much larger scale than before,” Elberse explains. “That... View Details
- Article
Faithful and Customizable Explanations of Black Box Models
By: Himabindu Lakkaraju, Ece Kamar, Rich Caruana and Jure Leskovec
As predictive models increasingly assist human experts (e.g., doctors) in day-to-day decision making, it is crucial for experts to be able to explore and understand how such models behave in different feature subspaces in order to know if and when to trust them. To... View Details
Lakkaraju, Himabindu, Ece Kamar, Rich Caruana, and Jure Leskovec. "Faithful and Customizable Explanations of Black Box Models." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2019).
- 2021
- Working Paper
Time and the Value of Data
By: Ehsan Valavi, Joel Hestness, Newsha Ardalani and Marco Iansiti
Managers often believe that collecting more data will continually improve the accuracy of their machine learning models. However, we argue in this paper that when data lose relevance over time, it may be optimal to collect a limited amount of recent data instead of... View Details
Keywords: Economics Of AI; Machine Learning; Non-stationarity; Perishability; Value Depreciation; Analytics and Data Science; Value
Valavi, Ehsan, Joel Hestness, Newsha Ardalani, and Marco Iansiti. "Time and the Value of Data." Harvard Business School Working Paper, No. 21-016, August 2020. (Revised November 2021.)
- 23 Jan 2023
- Research & Ideas
After High-Profile Failures, Can Investors Still Trust Credit Ratings?
During the financial crisis of 2008, major credit rating agencies faced sharp criticism for failing to recognize and warn of the risks of emerging instruments like mortgage-backed securities. Since that time, the results of a new study suggest, the agencies appear to... View Details
Keywords: by Ben Rand
- Summer 2020
- Article
Venture Capital's Role in Financing Innovation: What We Know and How Much We Still Need to Learn
By: Josh Lerner and Ramana Nanda
Venture capital is associated with some of the most high-growth and influential firms in the world. Academics and practitioners have effectively articulated the strengths of the venture model. At the same time, venture capital financing also has real limitations in its... View Details
Lerner, Josh, and Ramana Nanda. "Venture Capital's Role in Financing Innovation: What We Know and How Much We Still Need to Learn." Journal of Economic Perspectives 34, no. 3 (Summer 2020): 237–261.
- 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.)
- Article
Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error
By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving... View Details
Keywords: Autoencoder Networks; Pattern Detection; Subset Scanning; Computer Vision; Statistical Methods And Machine Learning; Machine Learning; Deep Learning; Data Mining; Big Data; Large-scale Systems; Mathematical Methods; Analytics and Data Science
Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error." Proceedings of the International Joint Conference on Artificial Intelligence 29th (2020).
- 08 Oct 2018
- Research & Ideas
Knowing What Your Boss Earns Can Make You Work Harder
percent fewer hours, the researchers found. In a global environment where companies are scrambling to find qualified workers to fill vacancies, another important finding emerged. When an employee learned a co-worker’s salary was 1 percent... View Details
Keywords: by Rachel Layne
- 12 Apr 2022
- Research & Ideas
Swiping Right: How Data Helped This Online Dating Site Make More Matches
The modern world is fueled by matchmaking. Going out on the town? Uber pairs you with a driver you can choose based on ratings, proximity, and even car model. Craving a vacation? Simply filter getaways based on locale and price through... View Details
Keywords: by Kara Baskin
- October–December 2022
- Article
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details
Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.
- November 2022
- Article
A Language-Based Method for Assessing Symbolic Boundary Maintenance between Social Groups
By: Anjali M. Bhatt, Amir Goldberg and Sameer B. Srivastava
When the social boundaries between groups are breached, the tendency for people to erect and maintain symbolic boundaries intensifies. Drawing on extant perspectives on boundary maintenance, we distinguish between two strategies that people pursue in maintaining... View Details
Keywords: Culture; Machine Learning; Natural Language Processing; Symbolic Boundaries; Organizations; Boundaries; Social Psychology; Interpersonal Communication; Organizational Culture
Bhatt, Anjali M., Amir Goldberg, and Sameer B. Srivastava. "A Language-Based Method for Assessing Symbolic Boundary Maintenance between Social Groups." Sociological Methods & Research 51, no. 4 (November 2022): 1681–1720.