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- October 6, 2020
- Article
Test Your Board's Readiness for the Post-COVID Era
By: Lynn S. Paine
Research suggests that well-run boards take the process of self-evaluation quite seriously, often using a combination of director surveys and personal interviews to assess the functioning and effectiveness of the board, its committees, and its individual members. As... View Details
- October 2020 (Revised November 2023)
- Case
COVID-19 Testing at Everlywell
By: Jeffrey J. Bussgang and Olivia Hull
In March 2020, as COVID-19 spreads rapidly across the U.S., Everlywell founder Julia Cheek considers how to respond as a small start-up specializing in at-home lab testing. After making dramatic budget cuts, she decides to pivot the organization to address the... View Details
Keywords: Entrepreneurship; Business Strategy; Venture Capital; Health Care and Treatment; Health Disorders; Leading Change; Technology Adoption; Digital Platforms; Competitive Strategy; Science; Adaptation; Corporate Social Responsibility and Impact; Crisis Management; Social Entrepreneurship; Ethics; Government Legislation; Health; Health Testing and Trials; Health Pandemics; Consumer Products Industry; Health Industry; Technology Industry; Texas; United States
- October 2020
- Teaching Note
Testing Autonomy in Pittsburgh
By: Mitchell Weiss and Mariana Oseguera Rodriguez
- 2022
- Working Paper
Heterogeneity of Gain-Loss Attitudes and Expectations-Based Reference Points
By: Pol Campos-Mercade, Lorenz Goette, Thomas Graeber, Alex Kellogg and Charles Sprenger
Existing tests of reference-dependent preferences assume universal loss aversion. This paper examines heterogeneity in gain-loss attitudes, and explores its implications for identifying models of the reference point. In two experimental settings we measure gain-loss... View Details
- 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
- September 2020 (Revised July 2022)
- Exercise
Artea (B): Including Customer-Level Demographic Data
By: Eva Ascarza and Ayelet Israeli
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 targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details
- September 2020 (Revised July 2022)
- Exercise
Artea (C): Potential Discrimination through Algorithmic Targeting
By: Eva Ascarza and Ayelet Israeli
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 targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details
- September 2020 (Revised July 2022)
- Exercise
Artea (D): Discrimination through Algorithmic Bias in Targeting
By: Eva Ascarza and Ayelet Israeli
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 targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details
- September 2020 (Revised June 2023)
- Exercise
Artea: Designing Targeting Strategies
By: Eva Ascarza and Ayelet Israeli
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 targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details
Keywords: Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; ＂Marketing Analytics＂; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analytics; Data Analysis; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Targeting; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; Algorithmic Bias; Marketing; Race; Gender; Diversity; Customer Relationship Management; Marketing Communications; Advertising; Decision Making; Ethics; E-commerce; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; United States
- September 2020 (Revised June 2023)
- Supplement
Spreadsheet Supplement to Artea Teaching Note
By: Eva Ascarza and Ayelet Israeli
Spreadsheet Supplement to Artea Teaching Note 521-041. 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
- September 2020
- Case
Merck: COVID-19 Vaccines
By: Willy C. Shih
COVID-19 infections were still climbing across the U.S. and many other parts of the world in September 2020, and it seemed that every time Ken Frazier, the CEO of Merck & Co. consented to an interview in recent months he always seemed to hear the same question,... View Details
- September 2020 (Revised July 2021)
- Case
Moderna (A)
By: Marco Iansiti, Karim R. Lakhani, Hannah Mayer and Kerry Herman
In summer 2020, Stephane Bancel, CEO of biotech firm Moderna, faces several challenges as his company races to develop a vaccine for COVID-19. The case explores how a company builds a digital organization, and leverages artificial intelligence and other digital... View Details
- September 2020 (Revised September 2021)
- Supplement
Student Success at Georgia State University (B)
By: Michael W. Toffel, Robin Mendelson and Julia Kelley
This is a supplement to the Student Success at Georgia State University (A) case. The (B) case includes the results of a randomized control trial that Georgia State conducted to test education technology start-up AdmitHub’s chatbot solution as a strategy for improving... View Details
Keywords: Education; Higher Education; Learning; Curriculum and Courses; Demographics; Diversity; Ethnicity; Income; Race; Values and Beliefs; Leadership; Goals and Objectives; Measurement and Metrics; Operations; Organizations; Mission and Purpose; Organizational Culture; Outcome or Result; Performance; Performance Effectiveness; Performance Evaluation; Performance Improvement; Planning; Strategic Planning; Social Enterprise; Nonprofit Organizations; Social Issues; Wealth and Poverty; Equality and Inequality; Information Technology; Digital Platforms; Education Industry; Atlanta
- September 2020
- Article
Customer Supercharging in Experience-Centric Channels
By: David R. Bell, Santiago Gallino and Antonio Moreno
We conjecture that for online retailers, experience-centric offline store formats do not simply expand market coverage, but rather, serve to significantly amplify future positive customer behaviors, both online and offline. We term this phenomenon “supercharging” and... View Details
- 2020
- Working Paper
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted... View Details
- September 2020
- Article
How Multimedia Shape Crowdfunding Outcomes: The Overshadowing Effect of Images and Videos on Text in Campaign Information
By: J Yang, Y Li, Goran Calic and Anton Shevchenko
This study aims to explore the moderating effect of the number of images and videos on the relationship between text length in crowdfunding campaign descriptions and crowdfunding outcomes. We use data from 13,622 technology campaigns on the Kickstarter website to test... View Details
- September 2020
- Article
Regulatory Sandboxes: A Cure for mHealth Pilotitis?
By: Abhishek Bhatia, Rahul Matthan, Tarun Khanna and Satchit Balsari
Mobile health (mHealth) and related digital health interventions in the past decade have not always scaled globally as anticipated earlier despite large investments by governments and philanthropic foundations. The implementation of digital health tools has suffered... View Details
- September–October 2020
- Article
The Past, Present, and (Near) Future of Gene Therapy and Gene Editing
By: Julia Pian, Amitabh Chandra and Ariel Dora Stern
Emerging gene therapy and gene-editing technologies will have a growing impact on patient lives and health-care delivery. We analyzed a decade of data on clinical trials and venture capital investments to understand the likely trajectory of genetically focused... View Details
- August 2020 (Revised September 2020)
- Technical Note
Assessing Prediction Accuracy of Machine Learning Models
The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools... View Details
- August 2020
- Article
Do Physician Incentives Increase Patient Medication Adherence?
By: Edward Kong, John Beshears, David Laibson, Brigitte Madrian, Kevin Volpp, George Loewenstein, Jonathan Kolstad and James J. Choi
We conducted a randomized experiment (911 primary care practices and 8,935 nonadherent patients) to test the effect of paying physicians for increasing patient medication adherence in three drug classes: diabetes medication, antihypertensives, and statins. We measured... View Details