Publications
Publications
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- Faculty Publications (20)
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- 2021
- Working Paper
Dynamic Pricing Algorithms, Consumer Harm, and Regulatory Response
By: Alexander J. MacKay and Samuel Weinstein
Pricing algorithms are rapidly transforming markets, from ride-sharing apps, to air travel, to online retail. Regulators and scholars have watched this development with a wary eye. Their focus so far has been on the potential for pricing algorithms to facilitate...
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- November 2021 (Revised December 2021)
- Supplement
PittaRosso (B): Human and Machine Learning
By: Ayelet Israeli
This case supplements the "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion" case, and provides major highlights on what happened at the company since the first case.
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Keywords:
Artificial Intelligence;
Pricing;
Pricing Algorithm;
Pricing Decisions;
Pricing Strategy;
Pricing Structure;
Promotion;
Promotions;
Online Marketing;
Data-driven Decision-making;
Data-driven Management;
Retail;
Retail Analytics;
Price;
Advertising Campaigns;
Data and Data Sets;
Analysis;
Online Advertising;
Budgets and Budgeting;
Marketing Strategy;
Marketing;
Transformation;
Decision Making;
Retail Industry;
Italy
- October 2021 (Revised January 2022)
- Supplement
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli and Fabrizio Fantini
PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once...
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Keywords:
Artificial Intelligence;
Pricing;
Pricing Algorithm;
Pricing Decisions;
Pricing Strategy;
Pricing Structure;
Promotion;
Promotions;
Online Marketing;
Data-driven Decision-making;
Data-driven Management;
Retail;
Retail Analytics;
Price;
Advertising Campaigns;
Data and Data Sets;
Analysis;
Online Advertising;
Budgets and Budgeting;
Marketing Strategy;
Marketing;
Transformation;
Decision Making;
Retail Industry;
Italy
- October 2021 (Revised December 2021)
- Case
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli
PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once...
View Details
Keywords:
Artificial Intelligence;
Pricing;
Pricing Algorithm;
Pricing Decisions;
Pricing Strategy;
Pricing Structure;
Promotion;
Promotions;
Online Marketing;
Data-driven Decision-making;
Data-driven Management;
Retail;
Retail Analytics;
Price;
Advertising Campaigns;
Data and Data Sets;
Analysis;
Online Advertising;
Budgets and Budgeting;
Marketing Strategy;
Marketing;
Transformation;
Decision Making;
Retail Industry;
Italy
- September–October 2021
- Article
Frontiers: Can an AI Algorithm Mitigate Racial Economic Inequality? An Analysis in the Context of Airbnb
By: Shunyuan Zhang, Nitin Mehta, Param Singh and Kannan Srinivasan
We study the effect of Airbnb’s smart-pricing algorithm on the racial disparity in the daily revenue earned by Airbnb hosts. Our empirical strategy exploits Airbnb’s introduction of the algorithm and its voluntary adoption by hosts as a quasi-natural experiment. Among...
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- September 17, 2021
- Article
AI Can Help Address Inequity—If Companies Earn Users' Trust
By: Shunyuan Zhang, Kannan Srinivasan, Param Singh and Nitin Mehta
While companies may spend a lot of time testing models before launch, many spend too little time considering how they will work in the wild. In particular, they fail to fully consider how rates of adoption can warp developers’ intent. For instance, Airbnb launched a...
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- Article
The Pitfalls of Pricing Algorithms: Be Mindful of How They Can Hurt Your Brand
By: Marco Bertini and Oded Koenigsberg
More and more companies are relying on pricing algorithms to maximize profits. The use of artificial intelligence and machine learning enables real-time price adjustments based on supply and demand, competitors’ activities, delivery schedules, and so forth. But...
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- November 2020
- Teaching Note
DayTwo: Going to Market with Gut Microbiome
By: Ayelet Israeli
Teaching Note for HBS Case No. 519-010. 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....
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Keywords:
Start-up Growth;
Startup;
Positioning;
Targeting;
Go To Market Strategy;
B2B Vs. B2C;
B2B2C;
Health ＆ Wellness;
AI;
Machine Learning;
Female Ceo;
Female Protagonist;
Science-based;
Science And Technology Studies;
Ecommerce;
Applications;
DTC;
Direct To Consumer Marketing;
US Health Care;
＂USA,＂;
Innovation;
Pricing;
Business Growth;
Segmentation;
Distribution Channels;
Growth and Development Strategy;
Business Startups;
Science-Based Business;
Health;
Innovation and Invention;
Marketing;
Technology;
Business Growth and Maturation;
Health Industry;
Technology Industry;
Insurance Industry;
Information Technology Industry;
Food and Beverage Industry;
Israel;
United States
- Oct 2020
- Conference Presentation
Optimal, Truthful, and Private Securities Lending
By: Emily Diana, Michael J. Kearns, Seth Neel and Aaron Leon Roth
We consider a fundamental dynamic allocation problem motivated by the problem of securities lending in financial markets, the mechanism underlying the short selling of stocks. A lender would like to distribute a finite number of identical copies of some scarce resource...
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- September 2020
- 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...
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Keywords:
Algorithmic Data;
Race And Ethnicity;
Promotion;
＂Marketing Analytics＂;
Marketing And Society;
Big Data;
Privacy;
Data-driven Management;
Data Analysis;
Data Analytics;
E-Commerce Strategy;
E-commerce;
Discrimination;
Targeting;
Targeted Advertising;
Pricing Algorithms;
Ethical Decision Making;
Customer Heterogeneity;
Marketing;
Race;
Ethnicity;
Gender;
Diversity;
Prejudice and Bias;
Marketing Communications;
Data and Data Sets;
Analysis;
Decision Making;
Ethics;
Customer Relationship Management;
Retail Industry;
Apparel and Accessories Industry;
United States
- September 2020 (Revised April 2021)
- 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...
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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;
E-Commerce Strategy;
Discrimination;
Targeted Advertising;
Targeted Policies;
Targeting;
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;
Retail Industry;
Apparel and Accessories Industry;
United States
- 2019
- Article
More Amazon Effects: Online Competition and Pricing Behaviors
By: Alberto Cavallo
I study how online competition, with its shrinking margins, algorithmic pricing technologies, and the transparency of the web, can change the pricing behavior of large retailers in the U.S. and affect aggregate inflation dynamics. In particular, I show that in the past...
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- 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
Keywords:
Start-up Growth;
Startup;
Positioning;
Targeting;
Go To Market Strategy;
B2B2C;
B2B Vs. B2C;
Health ＆ Wellness;
AI;
Machine Learning;
Female Ceo;
Female Protagonist;
Science-based;
Science And Technology Studies;
Ecommerce;
Applications;
DTC;
Direct To Consumer Marketing;
US Health Care;
＂USA,＂;
Innovation;
Pricing;
Business Growth;
Segmentation;
Distribution Channels;
Growth and Development Strategy;
Business Startups;
Science-Based Business;
Health;
Innovation and Invention;
Marketing;
Technology;
Business Growth and Maturation;
Health Industry;
Technology Industry;
Insurance Industry;
Information Technology Industry;
Food and Beverage Industry;
Israel;
United States
- November–December 2018
- Article
Online Network Revenue Management Using Thompson Sampling
By: Kris J. Ferreira, David Simchi-Levi and He Wang
We consider a network revenue management problem where an online retailer aims to maximize revenue from multiple products with limited inventory constraints. As common in practice, the retailer does not know the consumer's purchase probability at each price and must...
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Keywords:
Online Marketing;
Revenue Management;
Revenue;
Management;
Marketing;
Internet;
Price;
Mathematical Methods
- May 2018
- Article
Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change
By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
Data from digital platforms have the potential to improve our understanding of gentrification and enable new measures of how neighborhoods change in close to real time. Combining data on businesses from Yelp with data on gentrification from the Census, Federal Housing...
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- Winter 2016
- Article
Analytics for an Online Retailer: Demand Forecasting and Price Optimization
By: Kris J. Ferreira, Bin Hong Alex Lee and David Simchi-Levi
We present our work with an online retailer, Rue La La, as an example of how a retailer can use its wealth of data to optimize pricing decisions on a daily basis. Rue La La is in the online fashion sample sales industry, where they offer extremely limited-time...
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- Forthcoming
- Article
Competition in Pricing Algorithms
By: Zach Y. Brown and Alexander J. MacKay
We document new facts about pricing technology using high-frequency data, and we examine the implications for competition. Some online retailers employ technology that allows for more frequent price changes and automated responses to price changes by rivals. Motivated...
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- Forthcoming
- Article
Demand Learning and Pricing for Varying Assortments
By: Kris Ferreira and Emily Mower
Problem Definition: We consider the problem of demand learning and pricing for retailers who offer assortments of substitutable products that change frequently, e.g., due to limited inventory, perishable or time-sensitive products, or the retailer’s desire to...
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- Research Summary
Overview
Professor MacKay combines theory and measurement to deliver new insights about price competition and consumer preferences. In current and published papers, his research addresses how strategic pricing decisions may be influenced by algorithms, long-term contracts,...
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- Research Summary
Overview
In her research, Professor Ferreira focuses on helping e-commerce companies make more profitable revenue-management decisions. Although the overarching goal of revenue management is relatively well-defined – typically to maximize either revenue or profit – companies...
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