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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
- 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
- August 2020
- Article
Workplace Knowledge Flows
By: Jason Sandvik, Richard Saouma, Nathan Seegert and Christopher Stanton
We conducted a field experiment in a sales firm to test whether improving knowledge flows between coworkers affects productivity. Our design allows us to compare different management practices and to isolate whether frictions to knowledge transmission primarily reside... View Details
- July 2020
- Supplement
Instabeat—Crossing the Finish Line
By: Shikhar Ghosh, Nicole Tempest Keller and Alpana Thapar
Lebanese entrepreneur Hind Hobeika was just 21 years old when she launched her startup, Instabeat, which had developed the first real-time bio-feedback device for swimmers to monitor and improve their performance. It had been an extremely testing 10-year journey to... View Details
- Article
Forgoing Earned Incentives to Signal Pure Motives
By: Erika L. Kirgios, Edward H. Chang, Emma E. Levine, Katherine L. Milkman and Judd B. Kessler
Policy makers, employers, and insurers often provide financial incentives to encourage citizens, employees, and customers to take actions that are good for them or for society (e.g., energy conservation, healthy living, safe driving). Although financial incentives are... View Details
- July–September 2020
- Article
Innovation Contest: Effect of Perceived Support for Learning on Participation
By: Olivia Jung, Andrea Blasco and Karim R. Lakhani
Background: Frontline staff are well positioned to conceive improvement opportunities based on first-hand knowledge of what works and does not work. The innovation contest may be a relevant and useful vehicle to elicit staff ideas. However, the success of the... View Details