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Show Results For
- All HBS Web
(4,045)
- People (2)
- News (559)
- Research (2,862)
- Events (51)
- Multimedia (21)
- Faculty Publications (2,064)
- Article
Integrating: A Managerial Practice that Enables Implementation in Fragmented Health Care Environments
By: Michaela J. Kerrissey, Patricia Satterstrom, Nicholas Leydon, Gordon Schiff and Sara J. Singer
How some organizations improve while others remain stagnant is a key question in health care research. This inductive qualitative study examines primary care clinics implementing improvement efforts in order to identify mechanisms that enable implementation despite... View Details
Keywords: Organization And Management Theory; Quality Improvement; Health Care and Treatment; Performance Improvement; Integration; Cooperation
Kerrissey, Michaela J., Patricia Satterstrom, Nicholas Leydon, Gordon Schiff, and Sara J. Singer. "Integrating: A Managerial Practice that Enables Implementation in Fragmented Health Care Environments." Health Care Management Review 42, no. 3 (July–September 2017): 213–225.
- April 2024
- Article
Detecting Routines: Applications to Ridesharing CRM
By: Ryan Dew, Eva Ascarza, Oded Netzer and Nachum Sicherman
Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which we define as repeated behaviors with recurring, temporal... View Details
Keywords: Ride-sharing; Routine; Machine Learning; Customer Relationship Management; Consumer Behavior; Segmentation
Dew, Ryan, Eva Ascarza, Oded Netzer, and Nachum Sicherman. "Detecting Routines: Applications to Ridesharing CRM." Journal of Marketing Research (JMR) 61, no. 2 (April 2024): 368–392.
- 2021
- Conference Presentation
An Algorithmic Framework for Fairness Elicitation
By: Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Leon Roth, Logan Stapleton and Zhiwei Steven Wu
We consider settings in which the right notion of fairness is not captured by simple mathematical definitions (such as equality of error rates across groups), but might be more complex and nuanced and thus require elicitation from individual or collective stakeholders.... View Details
Jung, Christopher, Michael J. Kearns, Seth Neel, Aaron Leon Roth, Logan Stapleton, and Zhiwei Steven Wu. "An Algorithmic Framework for Fairness Elicitation." Paper presented at the 2nd Symposium on Foundations of Responsible Computing (FORC), 2021.
- 2016
- Working Paper
Explaining the Persistence of Gender Inequality: The Work-Family Narrative as a Social Defense Against the 24/7 Work Culture
By: Irene Padavic, Robin J. Ely and Erin M. Reid
It is widely accepted that the conflict women experience between family obligations and professional jobs’ long hours lies at the heart of their stalled advancement. Yet research suggests that this “work-family narrative” is partial at best: men, too, experience... View Details
Keywords: 24/7 Work Culture; Hegemonic Narrative; Social Defense; Work-family Conflict; Systems Psychodynamic Theory; Work-Life Balance; Personal Development and Career; Gender; Equality and Inequality; Organizational Culture
Padavic, Irene, Robin J. Ely, and Erin M. Reid. "Explaining the Persistence of Gender Inequality: The Work-Family Narrative as a Social Defense Against the 24/7 Work Culture." Harvard Business School Working Paper, No. 17-038, October 2016.
- 16 Apr 2001
- Research & Ideas
Breaking the Code of Change
Two dramatically different approaches to organizational change are being employed in the world today, according to our observations, research, and experience. We call these Theory E and Theory O View Details
Keywords: by Michael Beer & Nitin Nohria
- 2014
- Article
Corporate Social Responsibility Reporting in China: Symbol or Substance?
By: Christopher Marquis and Cuili Qian
This study focuses on how and why firms strategically respond to government signals regarding appropriate corporate activity. We integrate institutional theory and research on corporate political strategy to develop a political dependence model that explains (a) how... View Details
Keywords: Institutional Theory; Political Strategy; Non-market Strategy; China; Corporate Social Responsibility; Corporate Disclosure; Corporate Social Responsibility and Impact; Emerging Markets; Government and Politics; China
Marquis, Christopher, and Cuili Qian. "Corporate Social Responsibility Reporting in China: Symbol or Substance?" Organization Science 25, no. 1 (January–February 2014): 127–148.
- May 2021
- Case
The International Space Station, Principal-Agent Problems, and NASA's Quest to Keep Humans in Space
By: Matthew Weinzierl and Mehak Sarang
In building the International Space Station (ISS), NASA opened the door to the development of a robust in-space economy in low-Earth Orbit, and yet the decision to build the station, and continue to extend its lifetime, placed a huge burden on NASA’s Human Spaceflight... View Details
Keywords: Aerospace; Nasa; Space Economy; Principal-agent Theory; Policy; Commercialization; Aerospace Industry
Weinzierl, Matthew, and Mehak Sarang. "The International Space Station, Principal-Agent Problems, and NASA's Quest to Keep Humans in Space." Harvard Business School Case 721-054, May 2021.
- Article
Oracle Efficient Private Non-Convex Optimization
By: Seth Neel, Aaron Leon Roth, Giuseppe Vietri and Zhiwei Steven Wu
One of the most effective algorithms for differentially private learning and optimization is objective perturbation. This technique augments a given optimization problem (e.g. deriving from an ERM problem) with a random linear term, and then exactly solves it.... View Details
Neel, Seth, Aaron Leon Roth, Giuseppe Vietri, and Zhiwei Steven Wu. "Oracle Efficient Private Non-Convex Optimization." Proceedings of the International Conference on Machine Learning (ICML) 37th (2020).
- 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).
- 2018
- Working Paper
Two Hundred Years of Health and Medical Care: The Importance of Medical Care for Life Expectancy Gains
By: Maryaline Catillon, David Cutler and Thomas Getzen
Using two hundred years of national and Massachusetts data on medical care and health, we examine how central medical care is to life expectancy gains. While common theories about medical care cost growth stress growing demand, our analysis highlights the importance of... View Details
Keywords: Mortality; Life Expectancy; Medical Care; Productivity; Public Health; Healthcare Spending; Spending Per Year Of Life Gained; Personal Medicine; Technophysio Evolution; Health; Economics; Health Care and Treatment; Spending; Data and Data Sets; Health Industry
Catillon, Maryaline, David Cutler, and Thomas Getzen. "Two Hundred Years of Health and Medical Care: The Importance of Medical Care for Life Expectancy Gains." NBER Working Paper Series, No. 25330, December 2018.
- October 2023 (Revised June 2024)
- Case
ReUp Education: Can AI Help Learners Return to College?
By: Kris Ferreira, Christopher Thomas Ryan and Sarah Mehta
Founded in 2015, ReUp Education helps “stopped out students”—learners who have stopped making progress towards graduation—achieve their college completion goals. The company relies on a team of success coaches to engage with learners and help them reenroll. In 2019,... View Details
Keywords: AI; Algorithms; Machine Learning; Edtech; Education Technology; Analysis; Higher Education; AI and Machine Learning; Customization and Personalization; Failure; Education Industry; Technology Industry; United States
Ferreira, Kris, Christopher Thomas Ryan, and Sarah Mehta. "ReUp Education: Can AI Help Learners Return to College?" Harvard Business School Case 624-007, October 2023. (Revised June 2024.)
- 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 2013
- Article
Learning from My Successes and from Others' Failures: Evidence from Minimally Invasive Cardiac Surgery
By: D. KC, B. Staats and F. Gino
Learning from past experience is central to an organization's adaptation and survival. A key dimension of prior experience is whether an outcome was successful or unsuccessful. While empirical studies have investigated the effects of success and failure in... View Details
Keywords: Healthcare; Health Care; Knowledge Work; Attribution Theory; Quality; Success; Medical Specialties; Health Care and Treatment; Failure; Learning; Health Industry
KC, D., B. Staats, and F. Gino. "Learning from My Successes and from Others' Failures: Evidence from Minimally Invasive Cardiac Surgery." Management Science 59, no. 11 (November 2013): 2435–2449.
- 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).
- 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.
- December 2020
- Supplement
VIA Science (B)
By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman
Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the... View Details
Keywords: Data Analytics; Machine Learning; Artificial Intelligence; Strategy; Business Startups; AI and Machine Learning; Telecommunications Industry; Utilities Industry; United States; Japan
Alcácer, Juan, Rembrand Koning, Annelena Lobb, and Kerry Herman. "VIA Science (B)." Harvard Business School Supplement 721-368, December 2020.
- 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.)
- Article
Deep Down My Enemy Is Good: Thinking about the True Self Reduces Intergroup Bias
By: Julian De Freitas and Mina Cikara
Intergroup bias—preference for one's in-group relative to out-groups—is one of the most robust phenomena in all of psychology. Here we investigate whether a positive bias that operates at the individual-level, belief in a good true self, may be leveraged to reduce... View Details
De Freitas, Julian, and Mina Cikara. "Deep Down My Enemy Is Good: Thinking about the True Self Reduces Intergroup Bias." Journal of Experimental Social Psychology 74 (January 2018): 307–316.
- 12 Oct 2020
- News
MBA/DBA Alum Wins Nobel Prize in Economics
news: He and fellow Stanford professor Paul Milgrom had won the 2020 Nobel Prize in Economics for their improvements to auction theory and inventions of new auction formats. Milgrom had his phone in Do Not... View Details