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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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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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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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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

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

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

Research Summary

Overview

By: Himabindu Lakkaraju

I develop machine learning tools and techniques which enable human decision makers to make better decisions. More specifically, my research addresses the following fundamental questions pertaining to human and algorithmic decision-making:

1. How to build... View Details

Keywords: Artificial Intelligence; Machine Learning; Decision Analysis; Decision Support

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

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

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

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

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

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

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

2024
Working Paper

Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift

By: Matthew DosSantos DiSorbo and Kris Ferreira

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). These outliers often originate from covariate shift,... View Details

Keywords: AI and Machine Learning; Decision Choices and Conditions

28 Mar 2017
Working Paper Summaries

CEO Behavior and Firm Performance

Keywords: by Oriana Bandiera, Stephen Hansen, Andrea Pratt, and Raffaella Sadun

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

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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2025
Working Paper

Is Love Blind? AI-Powered Trading with Emotional Dividends

By: Valeria Fedyk, Daniel Rabetti and Stella Kong

We leverage the non-fungible tokens (NFTs) setting to assess the valuation of emotional dividends (LOVE), a long-standing empirical challenge in private-value markets such as art, antiques, and collectibles. Having created and validated our proxy, we use deep learning... View Details

Keywords: NFTs; Non-fungible Tokens; AI and Machine Learning; Valuation; Financial Markets

January 2021
Article

Machine Learning for Pattern Discovery in Management Research

By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres

Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect... View Details

Keywords: Machine Learning; Supervised Machine Learning; Induction; Abduction; Exploratory Data Analysis; Pattern Discovery; Decision Trees; Random Forests; Neural Networks; ROC Curve; Confusion Matrix; Partial Dependence Plots; AI and Machine Learning

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