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- July 2024 (Revised July 2024)
- Case
Dynamic Pricing at Wendy’s: Where’s the Beef?
By: Elie Ofek, Alicia Dadlani and Martha Hostetter
In early 2024, Wendy’s new CEO announced on an earnings call that the company would install digital menus in its US locations so it could begin testing dynamic pricing—changing prices up or down in response to shifts in supply and demand – as well as allow engaging in... View Details
- July 2024
- Supplement
Fail Safe Testing, Inc. (A)
By: Richard S. Ruback and Royce Yudkoff
Pre-Abstract: Instructors should consider the timing of making videos available to students, as they may reveal key case details.
Abstract: Fail Safe Testing, Inc., founded in 1988, was the leading provider of fire hose pressure testing, ground ladder and pump... View Details
Abstract: Fail Safe Testing, Inc., founded in 1988, was the leading provider of fire hose pressure testing, ground ladder and pump... View Details
- July 2024
- Supplement
Fail Safe Testing, Inc. (B)
By: Richard S. Ruback and Royce Yudkoff
Pre-Abstract: Instructors should consider the timing of making videos available to students, as they may reveal key case details.
Abstract: Fail Safe Testing, Inc., founded in 1988, was the leading provider of fire hose pressure testing, ground ladder and pump... View Details
Abstract: Fail Safe Testing, Inc., founded in 1988, was the leading provider of fire hose pressure testing, ground ladder and pump... View Details
- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
- October 2023 (Revised February 2024)
- Technical Note
Design and Evaluation of Targeted Interventions
By: Eva Ascarza and Ta-Wei (David) Huang
Targeted interventions serve as a pivotal tool in business strategy, streamlining decisions for enhanced efficiency and effectiveness. This note delves into two central facets of such interventions: first, the design of potent decision guidelines, or targeting... View Details
- June 2023
- Simulation
Artea Dashboard and Targeting Policy Evaluation
By: Ayelet Israeli and Eva Ascarza
Companies deploy A/B experiments to gain valuable insights about their customers in order to answer strategic business problems. In marketing, A/B tests are often used to evaluate marketing interventions intended to generate incremental outcomes for the firm. The Artea... View Details
Keywords: Algorithm Bias; Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analysis; Data Analytics; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; 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
- 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
- June 2023
- Article
National Customer Orientation: An Empirical Test across 112 Countries
By: Ofer Mintz, Imran S. Currim and Rohit Deshpandé
Customer orientation is a central tenet of marketing. However, less is known about how customer orientation varies across countries and time. Mintz, Currim, and Deshpandé (Eur. J. Mark., 56: 1014–1041, 2022) propose a country-level construct, national customer... View Details
- January–February 2023
- Article
External Interfaces and Internal Processes: Market Positioning and Divergent Professionalization Paths in Young Ventures
By: Alicia DeSantola, Ranjay Gulati and Pavel Zhelyazkov
We explore how the initial market positioning of entrepreneurial ventures shapes how they professionalize over time, focusing specifically on the development of functional roles. In contrast to existing literature, which has presumed a uniform march toward... View Details
- December 2022
- Article
I Don't 'Recall': The Decision to Delay Innovation Launch to Avoid Costly Product Failure
By: Byungyeon Kim, Oded Koenigsberg and Elie Ofek
Innovations embody novel features or cutting-edge components aimed at delivering desired customer benefits.
Oftentimes, however, we observe the need to recall new products shortly after their introduction. Indeed, a firm
may rush an innovation to market in an attempt... View Details
- April 2022
- Article
National Customer Orientation: A Framework, Propositions and Agenda for Future Research
By: Ofer Mintz, Imran S. Currim and Rohit Deshpandé
Purpose: This paper aims to propose a new country-level construct, national customer orientation, to provide a benchmark for global headquartered managers’ decisions and scholars investigating cross-national research.
Design/methodology/approach: A conceptual... View Details
Design/methodology/approach: A conceptual... View Details
- August 2021
- Case
Orchadio's First Two Split Experiments
By: Iavor I. Bojinov, Marco Iansiti and David Lane
Orchadio, a direct-to-consumer grocery business, needs to conduct its first two A/B tests—one to evaluate the effectiveness and functioning of its newly redesigned website, and one to market-test four versions of a new banner for the website. To do so, it will rely on... View Details
Keywords: Information Management; Technological Innovation; Knowledge Use and Leverage; Resource Allocation; Marketing; Measurement and Metrics; Customization and Personalization; Information Technology; Internet and the Web; Digital Platforms; Information Technology Industry; Food and Beverage Industry
- July 2021 (Revised July 2022)
- Case
Brigham & Women's Hospital: Using Patient Reported Outcomes to Improve Breast Cancer Care
By: Robert S. Kaplan, Navraj S. Nagra and Syed S. Shehab
Dr. Andrea Pusic, breast cancer reconstruction surgeon, wants to extend outcomes measurement beyond traditional surgical metrics of infections, complications, and survival rates. The case describes her development of a new mobile phone app, which collects patients’... View Details
- 2021
- Working Paper
Dirty Money: How Banks Influence Financial Crime
By: Joseph Pacelli, Janet Gao, Jan Schneemeier and Yufeng Wu
On September 21st, 2020, a consortium of international journalists leaked nearly 2,500 suspicious activity reports (SAR) obtained from the U.S. Financial Crimes Enforcement Network, exposing nearly $2 trillion of money laundering activity. The event raises important... View Details
- July 2021
- Article
Information Transparency, Multihoming, and Platform Competition: A Natural Experiment in the Daily Deals Market
By: Hui Li and Feng Zhu
Platform competition is shaped by the likelihood of multi-homing (i.e., complementors or consumers adopt more than one platform). To take advantage of multi-homing, platform firms often attempt to motivate their rivals’ high-performing complementors to adopt their own... View Details
- June 23, 2021
- Article
Research: When A/B Testing Doesn't Tell You the Whole Story
By: Eva Ascarza
When it comes to churn prevention, marketers traditionally start by identifying which customers are most likely to churn, and then running A/B tests to determine whether a proposed retention intervention will be effective at retaining those high-risk customers. While... View Details
Keywords: Customer Retention; Churn; Targeting; Market Research; Marketing; Investment Return; Customers; Retention; Research
- May–June 2021
- Article
Why Start-ups Fail
If you’re launching a business, the odds are against you: Two-thirds of start-ups never show a positive return. Unnerved by that statistic, a professor of entrepreneurship at Harvard Business School set out to discover why. Based on interviews and surveys with hundreds... View Details
- March 2021
- Supplement
Artea (A), (B), (C), and (D): Designing Targeting Strategies
By: Eva Ascarza and Ayelet Israeli
Power Point Supplement to 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... View Details
Keywords: Targeted Advertising; Targeting; Algorithmic Data; Bias; A/B Testing; Experiment; Advertising; Gender; Race; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
- March 2021
- Case
VideaHealth: Building the AI Factory
By: Karim R. Lakhani and Amy Klopfenstein
Florian Hillen, co-founder and CEO of VideaHealth, a startup that used artificial intelligence (AI) to detect dental conditions on x-rays, spent the early years of his company laying the groundwork for an AI factory. A process for quickly building and iterating on new... View Details
Keywords: Artificial Intelligence; Innovation and Invention; Disruptive Innovation; Technological Innovation; Information Technology; Applications and Software; Technology Adoption; Digital Platforms; Entrepreneurship; AI and Machine Learning; Technology Industry; Medical Devices and Supplies Industry; North and Central America; United States; Massachusetts; Cambridge
- 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