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Show Results For
- All HBS Web
(10,120)
- People (64)
- News (3,426)
- Research (4,041)
- Events (30)
- Multimedia (61)
- Faculty Publications (1,455)
- September 2020
- Article
Regulatory Sandboxes: A Cure for mHealth Pilotitis?
By: Abhishek Bhatia, Rahul Matthan, Tarun Khanna and Satchit Balsari
Mobile health (mHealth) and related digital health interventions in the past decade have not always scaled globally as anticipated earlier despite large investments by governments and philanthropic foundations. The implementation of digital health tools has suffered... View Details
Keywords: COVID-19; mHealth; Digital Health; Design Thinking; Regulation; Intervention; Regulatory Sandbox; Health Care and Treatment; Technological Innovation; Design; Governing Rules, Regulations, and Reforms; India
Bhatia, Abhishek, Rahul Matthan, Tarun Khanna, and Satchit Balsari. "Regulatory Sandboxes: A Cure for mHealth Pilotitis?" Journal of Medical Internet Research 22, no. 9 (September 2020).
- 2022
- Article
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.
By: Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay and Himabindu Lakkaraju
As machine learning (ML) models become more widely deployed in high-stakes applications, counterfactual explanations have emerged as key tools for providing actionable model explanations in practice. Despite the growing popularity of counterfactual explanations, a... View Details
Keywords: Machine Learning Models; Counterfactual Explanations; Adversarial Examples; Mathematical Methods
Pawelczyk, Martin, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, and Himabindu Lakkaraju. "Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 25th (2022).
- 2021
- Working Paper
Who Closed the Schools?
By: Joshua D. Coval
This paper examines the differences in characteristics between U.S. public schools that opted for virtual instruction because of COVID-19, and schools that did not. Much of the variation can be explained by measures of the degree to which districts favored teachers... View Details
Keywords: Public Education; COVID-19; Virtual Learning; Education; Health Pandemics; Teaching; Internet and the Web; Policy; Outcome or Result; United States
Coval, Joshua D. "Who Closed the Schools?" Harvard Business School Working Paper, No. 21-127, June 2021.
- July 2019 (Revised November 2019)
- Case
Osaro: Picking the Best Path
By: William R. Kerr, James Palano and Bastiane Huang
The founder of Osaro saw the potential of deep reinforcement learning to allow robots to be applied to new applications. Osaro targeted warehousing, already a dynamic industry for robotics and automation, for its initial product—a system which would allow robotic arms... View Details
Keywords: Artificial Intelligence; Machine Learning; Robotics; Robots; Ecommerce; Fulfillment; Warehousing; AI; Startup; Technology Commercialization; Business Startups; Entrepreneurship; Logistics; Order Taking and Fulfillment; Information Technology; Commercialization; Learning; Complexity; Competition; E-commerce
Kerr, William R., James Palano, and Bastiane Huang. "Osaro: Picking the Best Path." Harvard Business School Case 820-012, July 2019. (Revised November 2019.)
- 1995
- Article
The Positive Impact of Creative Activity: Effects of Creative Task Engagement and Motivational Focus on College Student's Learning
By: R. Conti, T. M. Amabile and S. Pollack
This study assessed the effectiveness of engaging students in a creative activity on a topic as a means of encouraging an active cognitive set toward learning that topic area. This technique was examined in three motivational contexts. Before reading a short... View Details
Keywords: Creativity; Cognition and Thinking; Behavior; Performance; Motivation and Incentives; Training
Conti, R., T. M. Amabile, and S. Pollack. "The Positive Impact of Creative Activity: Effects of Creative Task Engagement and Motivational Focus on College Student's Learning." Personality and Social Psychology Bulletin 21 (1995): 1107–1116.
- 17 Nov 2020
External Partner Event: MBA Information Session Hosted by the HBS Club of the Philippines
Join the HBS Club of the Philippines to meet local alumni and learn about the value of Harvard Business School’s MBA. The event will run from 7:30pm-9:00pm Philippine Standard Time. This link goes directly to the Zoom room. The password... View Details
- 2013
- Article
The Strategic Fitness Process: A Collaborative Action Research Method for Developing Organizational Prototypes and Dynamic Capabilities
By: Michael Beer
Organizations underperform and sometimes fail because their leaders are unable to learn the unvarnished truth from relevant stakeholders about how the design and behavior of the organization is misaligned with its goals and strategy. The Strategic Fitness Process (SFP)... View Details
Keywords: Organization Alignment; Dynamic Capabilities; Organization Design; Organizational Prototyping; Organizational Silence; Organizational Learning; Organizational Change and Adaptation; Strategic Planning; Organizational Design
Beer, Michael. "The Strategic Fitness Process: A Collaborative Action Research Method for Developing Organizational Prototypes and Dynamic Capabilities." Journal of Organization Design 2, no. 1 (2013).
- 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
- September 2018
- Article
Discretionary Task Ordering: Queue Management in Radiological Services
By: Maria Ibanez, Jonathan R. Clark, Robert S. Huckman and Bradley R. Staats
Work-scheduling research typically prescribes task sequences implemented by managers. Yet employees often have discretion to deviate from their prescribed sequence. Using data from 2.4 million radiological diagnoses, we find that doctors prioritize similar tasks... View Details
Keywords: Discretion; Scheduling; Queue; Healthcare; Learning; Experience; Decentralization; Operations; Service Operations; Service Delivery; Performance; Performance Effectiveness; Performance Efficiency; Performance Improvement; Performance Productivity; Decisions; Time Management; Cost vs Benefits; Health Industry
Ibanez, Maria, Jonathan R. Clark, Robert S. Huckman, and Bradley R. Staats. "Discretionary Task Ordering: Queue Management in Radiological Services." Management Science 64, no. 9 (September 2018): 4389–4407. (Working paper available here. Winner of the 2017 Best Paper Competition of the POMS College of Healthcare Operations Management. Featured in Forbes, Quartz, and Inc.)
- 2010
- Working Paper
Commodity Chains: What Can We Learn from a Business History of the Rubber Chain? (1870-1910)
By: Felipe Tamega Fernandes
The literature on the rubber boom applied a Dependendist view of rubber production in the Brazilian Amazon. Even though a sizable surplus was generated in the rubber chain, it was mostly appropriated by foreigners. This view is in tune with the Global Commodity Chain... View Details
Keywords: Cross-Cultural and Cross-Border Issues; Business History; Supply Chain; Manufacturing Industry; Rubber Industry; Brazil
Fernandes, Felipe Tamega. "Commodity Chains: What Can We Learn from a Business History of the Rubber Chain? (1870-1910)." Harvard Business School Working Paper, No. 10-089, April 2010.
- 01 Jun 2020
- News
Homeschooled
SK: I think it’s going to be a blend. We started the Khan Lab School because we believe so much in in-person instruction, especially with the younger age groups. In terms of higher education, by the time... View Details
- 14 Aug 2017
- Conference Presentation
A Convex Framework for Fair Regression
By: Richard Berk, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel and Aaron Roth
We introduce a flexible family of fairness regularizers for (linear and logistic) regression problems. These regularizers all enjoy convexity, permitting fast optimization, and they span the range from notions of group fairness to strong individual fairness. By varying... View Details
Berk, Richard, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel, and Aaron Roth. "A Convex Framework for Fair Regression." Paper presented at the 4th Workshop on Fairness, Accountability, and Transparency in Machine Learning, Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), August 14, 2017.
- 25 Jun 2019
- Blog Post
Learning the Language of Business and Science – The MS/MBA Biotechnology: Life Sciences Program
My path into the field of biotechnology began at a young age. I was largely influenced by my mother, who is a chemical engineer with an MBA, and by my upbringing in Boston, which exposed me to one of the... View Details
- 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).
- 07 Jan 2015
- Research & Ideas
The Quest for Better Layoffs
A few years ago, Sandra J. Sucher received worried emails from two MBA students in her first-year Leadership and Corporate Accountability (LCA) class at Harvard Business School. Elana Green (now Elana Silver) and David Rosales (both HBS MBA 2010) had been troubled... 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
- October 2023
- Article
Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA
By: Matthew S. Johnson, David I. Levine and Michael W. Toffel
We study how a regulator can best target inspections. Our case study is a U.S. Occupational Safety and Health Administration (OSHA) program that randomly allocated some inspections. On average, each inspection averted 2.4 serious injuries (9%) over the next five years.... View Details
Keywords: Safety Regulations; Regulations; Regulatory Enforcement; Machine Learning Models; Safety; Operations; Service Operations; Production; Forecasting and Prediction; Decisions; United States
Johnson, Matthew S., David I. Levine, and Michael W. Toffel. "Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA." American Economic Journal: Applied Economics 15, no. 4 (October 2023): 30–67. (Profiled in the Regulatory Review.)
- Article
Towards Robust and Reliable Algorithmic Recourse
By: Sohini Upadhyay, Shalmali Joshi and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision making (e.g., loan
approvals), there has been growing interest in post-hoc techniques which provide recourse to affected
individuals. These techniques generate recourses under the assumption... View Details
Keywords: Machine Learning Models; Algorithmic Recourse; Decision Making; Forecasting and Prediction
Upadhyay, Sohini, Shalmali Joshi, and Himabindu Lakkaraju. "Towards Robust and Reliable Algorithmic Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- July 2017
- Teaching Note
Designing Transformational Customer Experiences
By: Stefan Thomke
Keywords: Customer Experience; Design; Exercise; Learning By Doing; LEGO; Storytelling; Transformation