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  • All HBS Web  (684)
    • News  (145)
    • Research  (424)
    • Events  (20)
    • Multimedia  (12)
  • Faculty Publications  (303)

Show Results For

  • All HBS Web  (684)
    • News  (145)
    • Research  (424)
    • Events  (20)
    • Multimedia  (12)
  • Faculty Publications  (303)
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  • 1999
  • Article

Effects of Instructional Style on Problem-Solving Creativity

By: A. M. Ruscio and T. M. Amabile
This study sought to determine the impact of 2 differing instructional approaches on creative problem-solving performance. Eighty-two college students completed a novel structure-building task after receiving algorithmic instruction (providing a rote, step-by-step... View Details
Keywords: Training; Creativity; Cognition and Thinking; Performance; Learning
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Ruscio, A. M., and T. M. Amabile. "Effects of Instructional Style on Problem-Solving Creativity." Creativity Research Journal 12, no. 4 (1999): 251–266.
  • 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
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Yang, Jeremy, Juanjuan Zhang, and Yuhan Zhang. "First Law of Motion: Influencer Video Advertising on TikTok." Working Paper, March 2021.
  • February 2011 (Revised February 2012)
  • Case

Online Marketing at Big Skinny

By: Benjamin Edelman and Scott Duke Kominers
Describes a wallet maker's application of seven Internet marketing technologies: display ads, algorithmic search, sponsored search, social media, interactive content, online distributors, and A/B testing. Provides concise introductions to the key features of each... View Details
Keywords: Advertising Campaigns; Digital Marketing; Resource Allocation; Marketing Strategy; Performance Evaluation; Internet and the Web; Retail Industry
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Edelman, Benjamin, and Scott Duke Kominers. "Online Marketing at Big Skinny." Harvard Business School Case 911-033, February 2011. (Revised February 2012.) (request a courtesy copy.)
  • Article

Vungle Inc. Improves Monetization Using Big-Data Analytics

By: Bert De Reyck, Ioannis Fragkos, Yael Grushka-Cockayne, Casey Lichtendahl, Hammond Guerin and Andrew Kritzer
The advent of big data has created opportunities for firms to customize their products and services to unprecedented levels of granularity. Using big data to personalize an offering in real time, however, remains a major challenge. In the mobile advertising industry,... View Details
Keywords: Big Data; Monetization; Data and Data Sets; Advertising; Mobile Technology; Customization and Personalization; Performance Improvement
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De Reyck, Bert, Ioannis Fragkos, Yael Grushka-Cockayne, Casey Lichtendahl, Hammond Guerin, and Andrew Kritzer. "Vungle Inc. Improves Monetization Using Big-Data Analytics." Interfaces 47, no. 5 (September–October 2017): 454–466.
  • September 2020 (Revised February 2024)
  • Teaching Note

Artea (A), (B), (C), and (D): Designing Targeting Strategies

By: Eva Ascarza and Ayelet Israeli
Teaching Note for HBS No. 521-021,521-022,521-037,521-043. This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and... View Details
Keywords: Targeted Advertising; Targeting; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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Ascarza, Eva, and Ayelet Israeli. "Artea (A), (B), (C), and (D): Designing Targeting Strategies." Harvard Business School Teaching Note 521-041, September 2020. (Revised February 2024.)
  • October 2019
  • Article

Making Sense of Recommendations

By: Michael Yeomans, Anuj Shah, Sendhil Mullainathan and Jon Kleinberg
Computer algorithms are increasingly being used to predict people's preferences and make recommendations. Although people frequently encounter these algorithms because they are cheap to scale, we do not know how they compare to human judgment. Here, we compare computer... View Details
Keywords: Recommender Systems; Artificial Intelligence; Interpretability; Information Technology; Forecasting and Prediction; Decision Making; Attitudes
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Yeomans, Michael, Anuj Shah, Sendhil Mullainathan, and Jon Kleinberg. "Making Sense of Recommendations." Journal of Behavioral Decision Making 32, no. 4 (October 2019): 403–414.
  • Article

Adaptive Machine Unlearning

By: Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi and Chris Waites
Data deletion algorithms aim to remove the influence of deleted data points from trained models at a cheaper computational cost than fully retraining those models. However, for sequences of deletions, most prior work in the non-convex setting gives valid guarantees... View Details
Keywords: Machine Learning; AI and Machine Learning
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Gupta, Varun, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, and Chris Waites. "Adaptive Machine Unlearning." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
  • August 2021 (Revised November 2024)
  • Case

Intenseye: Powering Workplace Health and Safety with AI (A)

By: Michael W. Toffel and Youssef Abdel Aal
Intenseye was a Turkey-based technology startup that deployed machine learning algorithms to workplace camera feeds in order to identify unsafe worker actions and unsafe working conditions, in order to help improve worker safety. The case describes how Intenseye’s... View Details
Keywords: Privacy; Product Development; Operations; Technological Innovation; Value Creation; Production; Distribution; Safety; Risk and Uncertainty; Technology Industry; Manufacturing Industry; Distribution Industry; Turkey; Middle East; United States
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Toffel, Michael W., and Youssef Abdel Aal. "Intenseye: Powering Workplace Health and Safety with AI (A)." Harvard Business School Case 622-037, August 2021. (Revised November 2024.)
  • 2025
  • Working Paper

Warnings and Endorsements: Improving Human-AI Collaboration in the Presence of Outliers

By: Matthew DosSantos DiSorbo, Kris Ferreira, Maya Balakrishnan and Jordan Tong
Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). How can humans and algorithms work together to make... View Details
Keywords: AI and Machine Learning; Decision Choices and Conditions
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DosSantos DiSorbo, Matthew, Kris Ferreira, Maya Balakrishnan, and Jordan Tong. "Warnings and Endorsements: Improving Human-AI Collaboration in the Presence of Outliers." Working Paper, May 2025.
  • 2020
  • Working Paper

Machine Learning for Pattern Discovery in Management Research

By: Prithwiraj Choudhury
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used as an observation for further inductive or abductive research, but should not be treated as the result of a... View Details
Keywords: Machine Learning; Theory Building; Induction; Decision Trees; Random Forests; K-nearest Neighbors; Neural Network; P-hacking; Analytics and Data Science; Analysis
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Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Harvard Business School Working Paper, No. 19-032, September 2018. (Revised June 2020.)
  • 21 Mar 2019
  • Working Paper Summaries

Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions

Keywords: by Blasco, Andrea, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian, and Karim R. Lakhani; Health
  • 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
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Casadesus-Masanell, Ramon, Karen Elterman, and Oliver Gassmann. "Sportradar (A): From Data to Storytelling." Harvard Business School Case 719-429, November 2018.
  • Article

Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions

By: Andrea Blasco, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian and Karim R. Lakhani
Open data science and algorithm development competitions offer a unique avenue for rapid discovery of better computational strategies. We highlight three examples in computational biology and bioinformatics research where the use of competitions has yielded significant... View Details
Keywords: Computational Biology; Bioinformatics; Innovation Competitions; Research; Collaborative Innovation and Invention
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Blasco, Andrea, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian, and Karim R. Lakhani. "Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions." PLoS ONE 14, no. 9 (September 2019).
  • February 2021 (Revised March 2022)
  • Case

Marvin: A Personalized Telehealth Approach to Mental Health

By: Regina E. Herzlinger, Eshani Sharma, Andrew Nguyen, Thomas Arsenault, Carin-Isabel Knoop and Julia Kelley
More than one third of Americans were said to suffer some type of behavioral health ailment at some point in their lifetime, with many people requiring chronic therapy or intervention. Despite significant clinical needs, access to reliable treatment has been difficult... View Details
Keywords: Mental Health; Applications; Startup Management; Telehealth; Health Care Entrepreneurship; Health & Wellness; Health Care; Health Care and Treatment; Customization and Personalization; Internet and the Web; Entrepreneurship; Growth and Development Strategy; Applications and Software
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Herzlinger, Regina E., Eshani Sharma, Andrew Nguyen, Thomas Arsenault, Carin-Isabel Knoop, and Julia Kelley. "Marvin: A Personalized Telehealth Approach to Mental Health." Harvard Business School Case 321-127, February 2021. (Revised March 2022.)
  • 28 Mar 2017
  • Working Paper Summaries

CEO Behavior and Firm Performance

Keywords: by Oriana Bandiera, Stephen Hansen, Andrea Pratt, and Raffaella Sadun
  • 08 Nov 2016
  • First Look

November 8, 2016

in power. A mass shooting increases the number of enacted laws that loosen gun restrictions by 75% in states with Republican-controlled legislatures. We find no significant effect of mass shootings on laws enacted when there is a Democrat-controlled legislature. View Details
Keywords: Sean Silverthorne
  • 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
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Israeli, Ayelet, and David Lane. "DayTwo: Going to Market with Gut Microbiome." Harvard Business School Case 519-010, March 2019.
  • September–October 2023
  • Article

Interpretable Matrix Completion: A Discrete Optimization Approach

By: Dimitris Bertsimas and Michael Lingzhi Li
We consider the problem of matrix completion on an n × m matrix. We introduce the problem of interpretable matrix completion that aims to provide meaningful insights for the low-rank matrix using side information. We show that the problem can be... View Details
Keywords: Mathematical Methods
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Bertsimas, Dimitris, and Michael Lingzhi Li. "Interpretable Matrix Completion: A Discrete Optimization Approach." INFORMS Journal on Computing 35, no. 5 (September–October 2023): 952–965.
  • Winter 2017
  • Article

Why Big Data Isn't Enough

By: Sen Chai and Willy C. Shih
There is a growing belief that sophisticated algorithms can explore huge databases and find relationships independent of any preconceived hypotheses. But in businesses that involve scientific research and technological innovation, this approach is misguided and... View Details
Keywords: Big Data; Science-based; Science; Scientific Research; Data Analytics; Data Science; Data-driven Management; Data Scientists; Technological Innovation; Analytics and Data Science; Mathematical Methods; Theory
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Chai, Sen, and Willy C. Shih. "Why Big Data Isn't Enough." Art. 58227. MIT Sloan Management Review 58, no. 2 (Winter 2017): 57–61.
  • February 2024
  • Module Note

Data-Driven Marketing in Retail Markets

By: Ayelet Israeli
This note describes an eight-class sessions module on data-driven marketing in retail markets. The module aims to familiarize students with core concepts of data-driven marketing in retail, including exploring the opportunities and challenges, adopting best practices,... View Details
Keywords: Data; Data Analytics; Retail; Retail Analytics; Data Science; Business Analytics; "Marketing Analytics"; Omnichannel; Omnichannel Retailing; Omnichannel Retail; DTC; Direct To Consumer Marketing; Ethical Decision Making; Algorithmic Bias; Privacy; A/B Testing; Descriptive Analytics; Prescriptive Analytics; Predictive Analytics; Analytics and Data Science; E-commerce; Marketing Channels; Demand and Consumers; Marketing Strategy; Retail Industry
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Israeli, Ayelet. "Data-Driven Marketing in Retail Markets." Harvard Business School Module Note 524-062, February 2024.
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