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Show Results For
- All HBS Web
(697)
- News (144)
- Research (428)
- Events (20)
- Multimedia (12)
- Faculty Publications (311)
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- September 2020 (Revised July 2022)
- Supplement
Spreadsheet Supplement to Artea (B) and (C)
By: Eva Ascarza and Ayelet Israeli
Spreadsheet Supplement to "Artea (B): Including Customer-level Demographic Data" and "Artea (C): Potential Discrimination through Algorithmic Targeting" View Details
- 2019
- Article
An Empirical Study of Rich Subgroup Fairness for Machine Learning
By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
Kearns et al. [2018] recently proposed a notion of rich subgroup fairness intended to bridge the gap between statistical and individual notions of fairness. Rich subgroup fairness picks a statistical fairness constraint (say, equalizing false positive rates across... View Details
Kearns, Michael J., Seth Neel, Aaron Leon Roth, and Zhiwei Steven Wu. "An Empirical Study of Rich Subgroup Fairness for Machine Learning." Proceedings of the Conference on Fairness, Accountability, and Transparency (2019): 100–109.
- Research Summary
Overview
Professor Ferreira's research primarily focuses on how retailers can use algorithms to make better revenue management decisions, including pricing, product display, and assortment planning. In the retail industry, anticipating consumer demand is arguably one of the... View Details
- November–December 2018
- Article
Online Network Revenue Management Using Thompson Sampling
By: Kris J. Ferreira, David Simchi-Levi and He Wang
We consider a network revenue management problem where an online retailer aims to maximize revenue from multiple products with limited inventory constraints. As common in practice, the retailer does not know the consumer's purchase probability at each price and must... View Details
Keywords: Online Marketing; Revenue Management; Revenue; Management; Marketing; Internet and the Web; Price; Mathematical Methods
Ferreira, Kris J., David Simchi-Levi, and He Wang. "Online Network Revenue Management Using Thompson Sampling." Operations Research 66, no. 6 (November–December 2018): 1586–1602.
- March 2017 (Revised September 2017)
- Case
Facebook Fake News in the Post-Truth World
By: John R. Wells and Carole A. Winkler
In January 2017, Mark Zuckerberg, founder and CEO of Facebook, was surrounded by controversy. The election of Donald Trump as the next president of the United States in November 2016 had triggered a national storm of protests, and many attributed Trump’s victory to... View Details
Keywords: Facebook; Fake News; Mark Zuckerberg; Donald Trump; Algorithms; Social Networks; Partisanship; Social Media; App Development; Instagram; WhatsApp; Smartphone; Silicon Valley; Office Space; Digital Strategy; Democracy; Entry Barriers; Online Platforms; Controversy; Tencent; Agility; Social Networking; Gaming; Gaming Industry; Computer Games; Mobile Gaming; Messaging; Monetization Strategy; Advertising; Digital Marketing; Business Ventures; Acquisition; Mergers and Acquisitions; Business Growth and Maturation; Business Headquarters; Business Organization; For-Profit Firms; Trends; Communication; Communication Technology; Forms of Communication; Interactive Communication; Interpersonal Communication; Talent and Talent Management; Crime and Corruption; Voting; Demographics; Entertainment; Games, Gaming, and Gambling; Moral Sensibility; Values and Beliefs; Initial Public Offering; Profit; Revenue; Geography; Geographic Location; Global Range; Local Range; Country; Cross-Cultural and Cross-Border Issues; Globalized Firms and Management; Globalized Markets and Industries; Governing Rules, Regulations, and Reforms; Government and Politics; International Relations; National Security; Political Elections; Business History; Recruitment; Selection and Staffing; Information Management; Information Publishing; News; Newspapers; Innovation and Management; Innovation Strategy; Technological Innovation; Knowledge Dissemination; Human Capital; Law; Leadership Development; Leadership Style; Leading Change; Business or Company Management; Crisis Management; Goals and Objectives; Growth and Development Strategy; Growth Management; Management Practices and Processes; Management Style; Management Systems; Management Teams; Managerial Roles; Marketing Channels; Social Marketing; Network Effects; Market Entry and Exit; Digital Platforms; Marketplace Matching; Industry Growth; Industry Structures; Monopoly; Media; Product Development; Service Delivery; Corporate Social Responsibility and Impact; Mission and Purpose; Organizational Change and Adaptation; Organizational Culture; Organizational Structure; Public Ownership; Problems and Challenges; Business and Community Relations; Business and Government Relations; Groups and Teams; Networks; Rank and Position; Opportunities; Behavior; Emotions; Identity; Power and Influence; Prejudice and Bias; Reputation; Social and Collaborative Networks; Status and Position; Trust; Society; Civil Society or Community; Culture; Public Opinion; Social Issues; Societal Protocols; Strategy; Adaptation; Business Strategy; Commercialization; Competition; Competitive Advantage; Competitive Strategy; Corporate Strategy; Customization and Personalization; Diversification; Expansion; Horizontal Integration; Segmentation; Information Technology; Internet and the Web; Mobile and Wireless Technology; Internet and the Web; Applications and Software; Information Infrastructure; Digital Platforms; Internet and the Web; Mobile and Wireless Technology; Valuation; Advertising Industry; Communications Industry; Entertainment and Recreation Industry; Information Industry; Information Technology Industry; Journalism and News Industry; Media and Broadcasting Industry; Service Industry; Technology Industry; Telecommunications Industry; Video Game Industry; United States; California; Sunnyvale; Russia
Wells, John R., and Carole A. Winkler. "Facebook Fake News in the Post-Truth World." Harvard Business School Case 717-473, March 2017. (Revised September 2017.)
- 08 May 2018
- First Look
First Look at New Research and Ideas, May 8, 2018
https://www.hbs.edu/faculty/Pages/item.aspx?num=52570 Algorithm Appreciation: People Prefer Algorithmic to Human Judgment By: Logg, Jennifer M., Julia A. Minson, and Don A. Moore Abstract—Even though... View Details
Keywords: Sean Silverthorne
- 14 Jun 2017
- Working Paper Summaries
Minimizing Justified Envy in School Choice: The Design of New Orleans' OneApp
- 17 May 2022
- Cold Call Podcast
Delivering a Personalized Shopping Experience with AI
Keywords: Re: Jill J. Avery
- Working Paper
Group Fairness in Dynamic Refugee Assignment
By: Daniel Freund, Thodoris Lykouris, Elisabeth Paulson, Bradley Sturt and Wentao Weng
Ensuring that refugees and asylum seekers thrive (e.g., find employment) in their host countries is a profound humanitarian goal, and a primary driver of employment is the geographic
location within a host country to which the refugee or asylum seeker is... View Details
Freund, Daniel, Thodoris Lykouris, Elisabeth Paulson, Bradley Sturt, and Wentao Weng. "Group Fairness in Dynamic Refugee Assignment." Harvard Business School Working Paper, No. 23-047, February 2023.
- 2022
- Working Paper
Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions
By: Caleb Kwon, Ananth Raman and Jorge Tamayo
We empirically analyze how managerial overrides to a commercial algorithm that forecasts demand and schedules labor affect store performance. We analyze administrative data from a large grocery retailer that utilizes a commercial algorithm to forecast demand and... View Details
Keywords: Employees; Human Capital; Performance; Applications and Software; Management Skills; Management Practices and Processes; Retail Industry
Kwon, Caleb, Ananth Raman, and Jorge Tamayo. "Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions." Working Paper, December 2022. (R&R Management Science.)
- 05 Oct 2015
- Working Paper Summaries
Online Network Revenue Management Using Thompson Sampling
- Article
Conversational Receptiveness: Expressing Engagement with Opposing Views
By: M. Yeomans, J. Minson, H. Collins, H. Chen and F. Gino
We examine “conversational receptiveness”—the use of language to communicate one’s willingness to thoughtfully engage with opposing views. We develop an interpretable machine-learning algorithm to identify the linguistic profile of receptiveness (Studies 1A-B). We then... View Details
Keywords: Receptiveness; Natural Language Processing; Disagreement; Interpersonal Communication; Relationships; Conflict Management
Yeomans, M., J. Minson, H. Collins, H. Chen, and F. Gino. "Conversational Receptiveness: Expressing Engagement with Opposing Views." Organizational Behavior and Human Decision Processes 160 (September 2020): 131–148.
- Forthcoming
- Article
Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation
By: Maya Balakrishnan, Kris Ferreira and Jordan Tong
Even if algorithms make better predictions than humans on average, humans may sometimes have private information which an algorithm does not have access to that can improve performance. How can we help humans effectively use and adjust recommendations made by... View Details
Keywords: AI and Machine Learning; Analytics and Data Science; Forecasting and Prediction; Digital Marketing
Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation." Management Science (forthcoming). (Pre-published online March 24, 2025.)
- November 2018
- Case
Sportradar (A): From Data to Storytelling
By: Ramon Casadesus-Masanell, Karen Elterman and Oliver Gassmann
In 2013, the Swiss sports data company Sportradar debated whether to expand from its core business of data provision to bookmakers into sports media products. Sports data was becoming a commodity, and in the future, sports leagues might reduce their dependence on... View Details
Keywords: Sports Data; Data; Sport; Sportradar; Football; Soccer; Gambling; Betting; Betting Markets; Statistics; Odds; Live Data; Bookmakers; Betradar; Visualization; Integrity; Monitoring; Gaming; Streaming; 2013; St.Gallen; Algorithm; Mathematical Modeling; Carsten Koerl; Betandwin; Bwin; Wagering; Probability; Sports; Analytics and Data Science; Mathematical Methods; Games, Gaming, and Gambling; Transition; Strategy; Media; Sports Industry; Technology Industry; Information Technology Industry; Media and Broadcasting Industry; Europe; Switzerland; Asia; Austria; Germany; England
Casadesus-Masanell, Ramon, Karen Elterman, and Oliver Gassmann. "Sportradar (A): From Data to Storytelling." Harvard Business School Case 719-429, November 2018.
- 2021
- Working Paper
First Law of Motion: Influencer Video Advertising on TikTok
By: Jeremy Yang, Juanjuan Zhang and Yuhan Zhang
This paper engineers an intuitive feature that is predictive of the causal effect of influencer video advertising on product sales. We propose the concept of m-score, a summary statistic that captures the extent to which a product is advertised in the most engaging... View Details
Keywords: Influencer Advertising; Video Advertising; Computer Vision; Machine Learning; Advertising; Online Technology
Yang, Jeremy, Juanjuan Zhang, and Yuhan Zhang. "First Law of Motion: Influencer Video Advertising on TikTok." Working Paper, March 2021.
- Article
How to Use Heuristics for Differential Privacy
By: Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
We develop theory for using heuristics to solve computationally hard problems in differential privacy. Heuristic approaches have enjoyed tremendous success in machine learning, for which performance can be empirically evaluated. However, privacy guarantees cannot be... View Details
Neel, Seth, Aaron Leon Roth, and Zhiwei Steven Wu. "How to Use Heuristics for Differential Privacy." Proceedings of the IEEE Annual Symposium on Foundations of Computer Science (FOCS) 60th (2019).
- 2023
- Article
Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten
By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma
The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an... View Details
Keywords: Analytics and Data Science; AI and Machine Learning; Decision Making; Governing Rules, Regulations, and Reforms
Lakkaraju, Himabindu, Satyapriya Krishna, and Jiaqi Ma. "Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 17808–17826.
- 2010
- Chapter
Deferred Acceptance Algorithms: History, Theory, Practice
By: Alvin E. Roth
The deferred acceptance algorithm proposed by Gale and Shapley (1962) has had a profound influence on market design, both directly, by being adapted into practical matching mechanisms, and indirectly, by raising new theoretical questions. Deferred acceptance algorithms... View Details
- 2025
- Article
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Journal of Business & Economic Statistics 43, no. 1 (2025): 256–268.
- 2023
- Article
On the Impact of Actionable Explanations on Social Segregation
By: Ruijiang Gao and Himabindu Lakkaraju
As predictive models seep into several real-world applications, it has become critical to ensure that individuals who are negatively impacted by the outcomes of these models are provided with a means for recourse. To this end, there has been a growing body of research... View Details
Gao, Ruijiang, and Himabindu Lakkaraju. "On the Impact of Actionable Explanations on Social Segregation." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 10727–10743.