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(946)
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- News (155)
- Research (626)
- Events (13)
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- Faculty Publications (534)
Show Results For
- All HBS Web
(946)
- People (1)
- News (155)
- Research (626)
- Events (13)
- Multimedia (3)
- Faculty Publications (534)
- Article
A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects
By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun
We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public... View Details
Keywords: Prescriptive Analytics; Heterogeneous Treatment Effects; Optimization; Observed Rank Utility Condition (OUR); Between-treatment Heterogeneity; Machine Learning; Decision Making; Analysis; Mathematical Methods
McFowland III, Edward, Sandeep Gangarapu, Ravi Bapna, and Tianshu Sun. "A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects." MIS Quarterly 45, no. 4 (December 2021): 1807–1832.
- October 2018
- Case
American Family Insurance and the Artificial Intelligence Opportunity
By: Rajiv Lal and Scott Johnson
Keywords: Artificial Intelligence; Machine Learning; Automation; Analytics; American Family; American Family Insurance; Insurance; Business Organization; Transformation; Talent and Talent Management; Employee Relationship Management; Innovation Strategy; Job Cuts and Outsourcing; Risk and Uncertainty; Mobile and Wireless Technology; Technology Adoption; Internet and the Web; Applications and Software; Corporate Strategy; AI and Machine Learning; Digital Transformation; Insurance Industry; Technology Industry; Wisconsin
- December 2018
- Case
Choosy
By: Jeffrey J. Bussgang and Julia Kelley
Founded in 2017, Choosy is a data-driven fashion startup that uses algorithms to identify styles trending on social media. After manufacturing similar items using a China-based supply chain, Choosy sells them to consumers through its website and social media pages.... View Details
Keywords: Artificial Intelligence; Algorithms; Machine Learning; Neural Networks; Instagram; Influencer; Fast Fashion; Design; Customer Satisfaction; Customer Focus and Relationships; Decision Making; Cost vs Benefits; Innovation and Invention; Brands and Branding; Product Positioning; Demand and Consumers; Supply Chain; Production; Logistics; Business Model; Expansion; Internet and the Web; Mobile and Wireless Technology; Digital Platforms; Social Media; Technology Industry; Fashion Industry; North and Central America; United States; New York (state, US); New York (city, NY)
- 2020
- Article
A Practical Approach to Sales Compensation: What Do We Know Now? What Should We Know in the Future?
By: Doug J. Chung, Byungyeon Kim and Niladri B. Syam
Personal selling represents one of the most important elements in the marketing mix, and appropriate management of the sales force is vital to achieving the organization’s objectives. Among the various instruments of sales management, compensation plays a pivotal role... View Details
Keywords: Sales Compensation; Sales Management; Sales Strategy; Principal-agent Theory; Structural Econometrics; Field Experiments; Machine Learning; Artificial Intelligence; Salesforce Management; Compensation and Benefits; Motivation and Incentives; AI and Machine Learning
Chung, Doug J., Byungyeon Kim, and Niladri B. Syam. "A Practical Approach to Sales Compensation: What Do We Know Now? What Should We Know in the Future?" Foundations and Trends® in Marketing 14, no. 1 (2020): 1–52.
- January–February 2022
- Article
Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion
By: Ryan Allen and Prithwiraj Choudhury
How does a knowledge worker’s level of domain experience affect their algorithm-augmented work performance? We propose and test theoretical predictions that domain experience has countervailing effects on algorithm-augmented performance: on one hand, domain experience... View Details
Keywords: Automation; Domain Experience; Algorithmic Aversion; Experts; Algorithms; Machine Learning; Future Of Work; Employees; Experience and Expertise; Decision Making; Performance
Allen, Ryan, and Prithwiraj Choudhury. "Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion." Organization Science 33, no. 1 (January–February 2022): 149–169. ("Best PhD Student Paper" at SMS conference 2020.)
- 2021
- Chapter
Towards a Unified Framework for Fair and Stable Graph Representation Learning
By: Chirag Agarwal, Himabindu Lakkaraju and Marinka Zitnik
As the representations output by Graph Neural Networks (GNNs) are increasingly employed in real-world applications, it becomes important to ensure that these representations are fair and stable. In this work, we establish a key connection between counterfactual... View Details
Agarwal, Chirag, Himabindu Lakkaraju, and Marinka Zitnik. "Towards a Unified Framework for Fair and Stable Graph Representation Learning." In Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence, edited by Cassio de Campos and Marloes H. Maathuis, 2114–2124. AUAI Press, 2021.
- 2024
- Working Paper
Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python
By: Melissa Ouellet and Michael W. Toffel
This paper describes a range of best practices to compile and analyze datasets, and includes some examples in Stata, R, and Python. It is meant to serve as a reference for those getting started in econometrics, and especially those seeking to conduct data analyses in... View Details
Keywords: Empirical Methods; Empirical Operations; Statistical Methods And Machine Learning; Statistical Interferences; Research Analysts; Analytics and Data Science; Mathematical Methods
Ouellet, Melissa, and Michael W. Toffel. "Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python." Harvard Business School Working Paper, No. 25-010, August 2024.
- 2020
- Working Paper
Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion
By: Ryan Allen and Prithwiraj Choudhury
Past research offers mixed perspectives on whether domain experience helps or hurts algorithm-augmented work performance. To reconcile these perspectives, we theorize that domain experience affects algorithm-augmented performance via two distinct countervailing... View Details
Keywords: Automation; Domain Experience; Algorithmic Aversion; Experts; Algorithms; Machine Learning; Decision-making; Future Of Work; Employees; Experience and Expertise; Decision Making; Performance
Allen, Ryan, and Prithwiraj Choudhury. "Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion." Harvard Business School Working Paper, No. 21-073, October 2020. (Revised September 2021.)
- June 30, 2020
- Article
Scaling Up Behavioral Science Interventions in Online Education
By: Rene F. Kizilcec, Justin Reich, Michael Yeomans, Christoph Dann, Emma Brunskill, Glenn Lopez, Selen Turkay, Joseph J. Williams and Dustin Tingley
Online education is rapidly expanding in response to rising demand for higher and continuing education, but many online students struggle to achieve their educational goals. Several behavioral science interventions have shown promise in raising student persistence and... View Details
Keywords: Online Learning; Behavioral Interventions; Scale; Education; Online Technology; Performance Improvement
Kizilcec, Rene F., Justin Reich, Michael Yeomans, Christoph Dann, Emma Brunskill, Glenn Lopez, Selen Turkay, Joseph J. Williams, and Dustin Tingley. "Scaling Up Behavioral Science Interventions in Online Education." Proceedings of the National Academy of Sciences 117, no. 26 (June 30, 2020).
- 2020
- Article
Public Sentiment and the Price of Corporate Sustainability
By: George Serafeim
Combining corporate sustainability performance scores based on environmental, social, and governance (ESG) data with big data measuring public sentiment about a company’s sustainability performance, I find that the valuation premium paid for companies with strong... View Details
Keywords: Sustainability; ESG; ESG (Environmental, Social, Governance) Performance; Investment Management; Investment Strategy; Big Data; Machine Learning; Environment; Environmental Sustainability; Corporate Governance; Performance; Asset Pricing; Investment; Management; Strategy; Human Capital; Public Opinion; Value; Analytics and Data Science
Serafeim, George. "Public Sentiment and the Price of Corporate Sustainability." Financial Analysts Journal 76, no. 2 (2020): 26–46.
- 26 Apr 2020
- Other Presentation
Towards Modeling the Variability of Human Attention
By: Kuno Kim, Megumi Sano, Julian De Freitas, Daniel Yamins and Nick Haber
Children exhibit extraordinary exploratory behaviors hypothesized to contribute to the building of models of their world. Harnessing this capacity in artificial systems promises not only more flexible technology but also cognitive models of the developmental processes... View Details
Keywords: Exploratory Learning Behaviors; Modeling; Artificial Intelligence; AI and Machine Learning
Kim, Kuno, Megumi Sano, Julian De Freitas, Daniel Yamins, and Nick Haber. "Towards Modeling the Variability of Human Attention." In Bridging AI and Cognitive Science (BAICS) Workshop. 8th International Conference on Learning Representations (ICLR), April 26, 2020.
- August 2018 (Revised October 2019)
- Case
C3.ai—Driven to Succeed
By: Robert Simons and George Gonzalez
CEO Tom Siebel navigates his artificial intelligence (ai) startup through a series of pivots, market expansions, and even an elephant attack to become a leading platform ad service provider. The case describes his unusual management approach emphasizing employee... View Details
Keywords: Strategy Execution; Performance Measurement; Critical Performance Variables; Strategic Boundaries; Internet Of Things; Artificial Intelligence; Software Development; Big Data; Machine Learning; Business Startups; Management Style; Business Strategy; Performance; Measurement and Metrics; Organizational Culture; AI and Machine Learning; Digital Transformation; Applications and Software; Digital Marketing; Analytics and Data Science; Technology Industry; United States; California
Simons, Robert, and George Gonzalez. "C3.ai—Driven to Succeed." Harvard Business School Case 119-004, August 2018. (Revised October 2019.)
- March 2019
- Case
DayTwo: Going to Market with Gut Microbiome
By: Ayelet Israeli and David Lane
DayTwo is a young Israeli startup that applies research on the gut microbiome and machine learning algorithms to deliver personalized nutritional recommendations to its users in order to minimize blood sugar spikes after meals. After a first year of trial rollout in... View Details
Keywords: Start-up Growth; Startup; Positioning; Targeting; Go To Market Strategy; B2B2C; B2B Vs. B2C; Health ＆ Wellness; AI; Machine Learning; Female Ceo; Female Protagonist; Science-based; Science And Technology Studies; Ecommerce; Applications; DTC; Direct To Consumer Marketing; US Health Care; ＂USA,＂; Innovation; Pricing; Business Growth; Segmentation; Distribution Channels; Growth and Development Strategy; Business Startups; Science-Based Business; Health; Innovation and Invention; Marketing; Information Technology; Business Growth and Maturation; E-commerce; Applications and Software; Health Industry; Technology Industry; Insurance Industry; Information Technology Industry; Food and Beverage Industry; Israel; United States
Israeli, Ayelet, and David Lane. "DayTwo: Going to Market with Gut Microbiome." Harvard Business School Case 519-010, March 2019.
- January–February 2025
- Article
Want Your Company to Get Better at Experimentation?: Learn Fast by Democratizing Testing
By: Iavor Bojinov, David Holtz, Ramesh Johari, Sven Schmit and Martin Tingley
For years, online experimentation has fueled the innovations of leading tech companies, enabling them to rapidly test and refine new ideas, optimize product features, personalize user experiences, and maintain a competitive edge. The widespread availability and lower... View Details
Keywords: Technological Innovation; AI and Machine Learning; Analytics and Data Science; Product Development; Competitive Advantage
Bojinov, Iavor, David Holtz, Ramesh Johari, Sven Schmit, and Martin Tingley. "Want Your Company to Get Better at Experimentation? Learn Fast by Democratizing Testing." Harvard Business Review 103, no. 1 (January–February 2025): 96–103.
- March 2019
- Case
Wattpad
By: John Deighton and Leora Kornfeld
How to run a platform to match four million writers of stories to 75 million readers? Use data science. Make money by doing deals with television and filmmakers and book publishers. The case describes the challenges of matching readers to stories and of helping writers... View Details
Keywords: Platform Businesses; Creative Industries; Publishing; Data Science; Machine Learning; Collaborative Filtering; Women And Leadership; Managing Data Scientists; Big Data; Recommender Systems; Digital Platforms; Information Technology; Intellectual Property; Analytics and Data Science; Publishing Industry; Entertainment and Recreation Industry; Canada; United States; Philippines; Viet Nam; Turkey; Indonesia; Brazil
Deighton, John, and Leora Kornfeld. "Wattpad." Harvard Business School Case 919-413, March 2019.
- November 2020
- Teaching Note
DayTwo: Going to Market with Gut Microbiome
By: Ayelet Israeli
Teaching Note for HBS Case No. 519-010. DayTwo is a young Israeli startup that applies research on the gut microbiome and machine learning algorithms to deliver personalized nutritional recommendations to its users in order to minimize blood sugar spikes after meals.... View Details
Keywords: Start-up Growth; Startup; Positioning; Targeting; Go To Market Strategy; B2B Vs. B2C; B2B2C; Health ＆ Wellness; AI; Machine Learning; Female Ceo; Female Protagonist; Science-based; Science And Technology Studies; Ecommerce; Applications; DTC; Direct To Consumer Marketing; US Health Care; ＂USA,＂; Innovation; Pricing; Business Growth; Segmentation; Distribution Channels; Growth and Development Strategy; Business Startups; Science-Based Business; Health; Innovation and Invention; Marketing; Information Technology; Business Growth and Maturation; E-commerce; Applications and Software; Health Industry; Technology Industry; Insurance Industry; Information Technology Industry; Food and Beverage Industry; Israel; United States
- March 2025
- Article
Novice Risk Work: How Juniors Coaching Seniors on Emerging Technologies Such as Generative AI Can Lead to Learning Failures
By: Katherine C. Kellogg, Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Fabrizio Dell'Acqua, Edward McFowland III, François Candelon and Karim R. Lakhani
The literature on communities of practice demonstrates that a proven way for senior professionals to upskill
themselves in the use of new technologies that undermine existing expertise is to learn from junior
professionals. It notes that juniors may be better able... View Details
Keywords: Rank and Position; Competency and Skills; Technology Adoption; Experience and Expertise; AI and Machine Learning
Kellogg, Katherine C., Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Fabrizio Dell'Acqua, Edward McFowland III, François Candelon, and Karim R. Lakhani. "Novice Risk Work: How Juniors Coaching Seniors on Emerging Technologies Such as Generative AI Can Lead to Learning Failures." Art. 100559. Information and Organization 35, no. 1 (March 2025).
Paul Hamilton
Paul studies the economic complements needed for firms to realize productivity gains from machine learning and artificial intelligence. These complements include data, human capital & skills, organizational processes, and business models.
View Details
- November 2024 (Revised January 2025)
- Case
MiDAS: Automating Unemployment Benefits
By: Shikhar Ghosh and Shweta Bagai
In 2015, the state of Michigan considered whether to nominate its Michigan Integrated Data Automated System (MiDAS) for a prestigious state technology award. Launched in 2013 amid severe budget pressures, the $47 million automated fraud detection system was designed to... View Details
Keywords: Artificial Intelligence; AI; Machine Learning Models; Algorithmic Data; Automation; Benefits; Compensation; Cost Reduction; Government; Fraud; Government Technology; Public Sector; Systems; Systems Integration; Unemployment Insurance; Waste Heat Recovery; AI and Machine Learning; Government Administration; Information Technology; Insurance; Decision Making; Digital Transformation; Employment; Public Administration Industry; United States; Michigan
Ghosh, Shikhar, and Shweta Bagai. "MiDAS: Automating Unemployment Benefits." Harvard Business School Case 825-100, November 2024. (Revised January 2025.)
Edward McFowland III
Edward McFowland III is an Assistant Professor in the Technology and Operations Management Unit at Harvard Business School. He teaches the first-year TOM course in the required curriculum.
Professor McFowland’s research interests – which lie at the... View Details