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November 2024
Article

A National Analysis of General Pediatric Inpatient Unit Closures and Openings, 2011–2018

By: Carolyn San Soucie, Nancy D. Beaulieu, Jason D. Buxbaum, David Cutler, JoAnna K. Leyenaar, Sarah C. McBride, Olivia Zhao and Alyna T. Chien

OBJECTIVES: This paper provides an examination of: (1) the frequency and net rates of change for general pediatric inpatient (GPI) unit closures and openings nationally and by state; (2) how often closures or openings are caused by GPI unit changes only or caused by... View Details

Keywords: Health Industry

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

Keywords: AI and Machine Learning; Mathematical Methods; Analytics and Data Science

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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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2023
Working Paper

Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation

By: Dae Woong Ham, Michael Lindon, Martin Tingley and Iavor Bojinov

Randomized experiments have become the standard method for companies to evaluate the performance of new products or services. In addition to augmenting managers’ decision-making, experimentation mitigates risk by limiting the proportion of customers exposed to... View Details

Keywords: Performance Evaluation; Research and Development; Analytics and Data Science; Consumer Behavior

10 Mar 2010
Working Paper Summaries

A Reexamination of Tunneling and Business Groups: New Data and New Methods

Keywords: by Jordan I. Siegel & Prithwiraj Choudhury

December 2022 (Revised January 2025)
Case

Akooda: Charging Toward Operational Intelligence

By: Christopher Stanton and Mel Martin

The Akooda case describes the challenges confronting founder and CEO Yuval Gonczarowski (MBA ‘17) in 2022 as he attempts to boost sales. Launched in November 2020, Akooda was an AI company that mined 20 different sources of digital data, from tools like Slack, Google... View Details

Keywords: Data Mining; Productivity; Monitoring; Data Analysis; AI and Machine Learning; Knowledge Management; Operations; Problems and Challenges; Employee Relationship Management; Information Technology Industry; Technology Industry; Information Industry; Boston; Israel

April 2014 (Revised March 2015)
Case

GE and the Industrial Internet

By: Karim R. Lakhani, Marco Iansiti and Kerry Herman

CEO Jeff Immelt considers whether GE is moving fast enough on its new Industrial Internet initiative. The undertaking includes building out an Industrial Internet, connecting machines and devices, collecting their data and operations, and providing services to clients... View Details

August 2021
Article

Multiple Imputation Using Gaussian Copulas

By: F.M. Hollenbach, I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward and A. Volfovsky

Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this paper, we present a simple-to-use... View Details

Keywords: Missing Data; Bayesian Statistics; Imputation; Categorical Data; Estimation

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August 2019 (Revised February 2020)
Teaching Note

Sidewalk Labs: Privacy in a City Built from the Internet Up

By: Leslie John and Mitch Weiss

Email mking@hbs.edu for a courtesy copy.

The case serves as a microcosm of issues of digital privacy: the availability of data – personal data in particular – has tremendous potential to improve people’s lives... View Details

Keywords: Privacy; Privacy By Design; Privacy Regulation; Platforms; Data; Data Security; Behavioral Science; Analytics and Data Science; Safety; Entrepreneurship; Business and Government Relations; Consumer Behavior; Digital Platforms

August 2017 (Revised July 2019)
Case

GROW: Using Artificial Intelligence to Screen Human Intelligence

By: Ethan Bernstein, Paul McKinnon and Paul Yarabe

Over 10% of all 2017 university graduates in Japan used GROW, an artificial intelligence platform and mobile app developed by Tokyo-based people analytics startup IGS, to recruit for a job. This case puts participants in the shoes of IGS founder and CEO Masahiro... View Details

Keywords: Big Data; Artificial Intelligence; Talent and Talent Management; Recruitment; Selection and Staffing; Human Resources; Information Technology; AI and Machine Learning; Analytics and Data Science; Financial Services Industry; Air Transportation Industry; Advertising Industry; Manufacturing Industry; Technology Industry; Japan

2018
Working Paper

Bayesian Ensembles of Binary-Event Forecasts: When Is It Appropriate to Extremize or Anti-Extremize?

By: Kenneth C. Lichtendahl Jr., Yael Grushka-Cockayne, Victor Richmond R. Jose and Robert L. Winkler

Many organizations face critical decisions that rely on forecasts of binary events. In these situations, organizations often gather forecasts from multiple experts or models and average those forecasts to produce a single aggregate forecast. Because the average... View Details

Keywords: Forecast Aggregation; Linear Opinion Pool; Generalized Additive Model; Generalized Linear Model; Stacking.; Forecasting and Prediction

Teaching Interest

Overview

Teaching has been a lifelong passion of mine. As the third generation of academics in my family, I see good teaching as a means to give back and to encourage others to share my passion for discovery. I’ve been very lucky to have many teaching opportunities, both as an... View Details

August 2022
Supplement

Zalora: Data-Driven Pricing Recommendations

By: Ayelet Israeli

This exercise can be used in conjunction with the main case "Zalora: Data-Driven Pricing" to facilitate class discussion without requiring data analysis from the students. Instead, the exercise presents reports that were created by the data science team to answer the... View Details

Keywords: Pricing; Pricing Algorithms; Dynamic Pricing; Ecommerce; Pricing Strategy; Pricing And Revenue Management; Apparel; Singapore; Startup; Demand Estimation; Data Analysis; Data Analytics; Exercise; Price; Internet and the Web; Apparel and Accessories Industry; Retail Industry; Fashion Industry; Singapore

August 2015 (Revised January 2017)
Technical Note

From Correlation to Causation

By: Feng Zhu and Karim R. Lakhani

To make sound business decisions, managers must be comfortable with the concepts of correlation and causation. This background note provides an overview of correlation and causation using examples and explains why the former does not imply the latter. It also describes... View Details

Keywords: Statistics; Regression; Data Analytics; Decisions; Forecasting and Prediction; Judgments

2016
Working Paper

Markets for Ideas: Prize Structure, Entry Limits, and the Design of Ideation Contests

By: Pavel Kireyev

Contests are a popular mechanism for the procurement of innovation. In marketing, design, and other creative industries, firms use freelance marketplaces to organize contests and obtain high-quality ideas for ads, new products, and even business strategies from... View Details

Keywords: Idea Generation; Crowdsourcing; Contest Design; Structural Estimation; Motivation and Incentives; Competition; Innovation and Invention

Article

Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)

By: Eva Ascarza and Ayelet Israeli

An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details

Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods

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

Article

DEA Model with Shared Resources and Efficiency Decomposition

By: Yao Chen, Juan Du, H. David Sherman and Joe Zhu

Data envelopment analysis (DEA) has proved to be an excellent approach for measuring performance of decision making units (DMUs) that use multiple inputs to generate multiple outputs. In many real world scenarios, DMUs have a two-stage network process with shared input... View Details

Keywords: Data Envelopment Analysis (DEA); Efficiency; Intermediate Measure; Performance Efficiency

September 2020 (Revised July 2022)
Technical Note

Algorithmic Bias in Marketing

By: Ayelet Israeli and Eva Ascarza

This note focuses on algorithmic bias in marketing. First, it presents a variety of marketing examples in which algorithmic bias may occur. The examples are organized around the 4 P’s of marketing – promotion, price, place and product—characterizing the marketing... View Details

December 2014
Supplement

Interview with Anders Byriel and Mads Nygård: Kvadrat

By: Boris Groysberg and Sarah L. Abbott

Anders Byriel, CEO of the family-owned Danish textiles company, Kvadrat, and Mads Nygård, SVP of Strategy & Organization at Kvadrat, discuss the challenges and opportunities faced by the company. They elaborate on areas covered in the case including: 1.) Asia; 2.) Soft... View Details

Keywords: General Management; Organization Behavior; Strategy; Performance Management; Leadership; Business or Company Management; Growth and Development Strategy; Management Practices and Processes; Human Resources; Manufacturing Industry; Denmark

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