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    • All HBS Web  (142)
      • Faculty Publications  (20)

      Algorithmic Pricing Remove Algorithmic Pricing →

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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...  View Details
      Keywords: Competition Policy; Regulation; Algorithmic Pricing; Dynamic Pricing; Law And Economics; Law And Regulation; Consumer Protection; Competition; Policy; Price; Governing Rules, Regulations, and Reforms; Economics
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      MacKay, Alexander J., and Samuel Weinstein. "Dynamic Pricing Algorithms, Consumer Harm, and Regulatory Response." Harvard Business School Working Paper, No. 22-050, January 2022. (Direct download.)
      • 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.  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; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Marketing; Transformation; Decision Making; AI and Machine Learning; Retail Industry; Italy
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      Israeli, Ayelet. "PittaRosso (B): Human and Machine Learning." Harvard Business School Supplement 522-047, November 2021. (Revised December 2021.)
      • October 2021 (Revised March 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...  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; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Marketing; Transformation; Decision Making; Retail Industry; Italy
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      Israeli, Ayelet, and Fabrizio Fantini. "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion." Harvard Business School Spreadsheet Supplement 522-710, October 2021. (Revised March 2022.)
      • October 2021 (Revised March 2022)
      • 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; AI; Price; Advertising Campaigns; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Marketing; Transformation; Decision Making; AI and Machine Learning; Retail Industry; Italy
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      Israeli, Ayelet. "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion." Harvard Business School Case 522-046, October 2021. (Revised March 2022.)
      • 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...  View Details
      Keywords: Smart Pricing; Pricing Algorithm; Machine Bias; Discrimination; Racial Disparity; Social Inequality; Airbnb Revenue; Revenue; Race; Equality and Inequality; Prejudice and Bias; Price; Mathematical Methods; Accommodations Industry
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      Zhang, Shunyuan, Nitin Mehta, Param Singh, and Kannan Srinivasan. "Frontiers: Can an AI Algorithm Mitigate Racial Economic Inequality? An Analysis in the Context of Airbnb." Marketing Science 40, no. 5 (September–October 2021): 813–820.
      • 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...  View Details
      Keywords: Artificial Intelligence; Algorithmic Bias; Technological Innovation; Perception; Diversity; Equality and Inequality; Trust; AI and Machine Learning
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      Zhang, Shunyuan, Kannan Srinivasan, Param Singh, and Nitin Mehta. "AI Can Help Address Inequity—If Companies Earn Users' Trust." Harvard Business Review Digital Articles (September 17, 2021).
      • 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...  View Details
      Keywords: Algorithmic Pricing; Dynamic Pricing; Price; Change; Information Technology; Brands and Branding; Perception; Consumer Behavior
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      Bertini, Marco, and Oded Koenigsberg. "The Pitfalls of Pricing Algorithms: Be Mindful of How They Can Hurt Your Brand." Harvard Business Review 99, no. 5 (September–October 2021): 74–83.
      • 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....  View Details
      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; Information Technology; Business Growth and Maturation; Health Industry; Technology Industry; Insurance Industry; Information Technology Industry; Food and Beverage Industry; Israel; United States
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      Israeli, Ayelet. "DayTwo: Going to Market with Gut Microbiome." Harvard Business School Teaching Note 521-052, November 2020.
      • 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...  View Details
      Keywords: Differential Privacy; Mechanism Design; Finance; Mathematical Methods
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      Diana, Emily, Michael J. Kearns, Seth Neel, and Aaron Leon Roth. "Optimal, Truthful, and Private Securities Lending." Paper presented at the 1st Association for Computing Machinery (ACM) International Conference on AI in Finance (ICAIF), October 2020.
      • 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...  View Details
      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; Analytics and Data Science; Analysis; Decision Making; Ethics; Customer Relationship Management; Retail Industry; Apparel and Accessories Industry; United States
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      Israeli, Ayelet, and Eva Ascarza. "Algorithmic Bias in Marketing." Harvard Business School Technical Note 521-020, September 2020.
      • 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...  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; 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
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      Ascarza, Eva, and Ayelet Israeli. "Artea: Designing Targeting Strategies." Harvard Business School Exercise 521-021, September 2020. (Revised April 2021.)
      • 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...  View Details
      Keywords: Amazon; Online Prices; Inflation; Uniform Pricing; Price Stickiness; Monetary Economics; Economics; Macroeconomics; Inflation and Deflation; System Shocks; United States
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      Cavallo, Alberto. "More Amazon Effects: Online Competition and Pricing Behaviors." Jackson Hole Economic Symposium Conference Proceedings (Federal Reserve Bank of Kansas City) (2019).
      • 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; Information Technology; Business Growth and Maturation; Health Industry; Technology Industry; Insurance Industry; Information Technology Industry; Food and Beverage Industry; Israel; United States
      Citation
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      Israeli, Ayelet, and David Lane. "DayTwo: Going to Market with Gut Microbiome." Harvard Business School Case 519-010, March 2019.
      • 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...  View Details
      Keywords: Online Marketing; Revenue Management; Revenue; Management; Marketing; Internet and the Web; Price; Mathematical Methods
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      Ferreira, Kris J., David Simchi-Levi, and He Wang. "Online Network Revenue Management Using Thompson Sampling." Operations Research 66, no. 6 (November–December 2018): 1586–1602.
      • 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...  View Details
      Keywords: Forecasting Models; Simulation Methods; Regional Economic Activity: Growth, Development, Environmental Issues, And Changes; Geographic Location; Local Range; Transition; Analytics and Data Science; Measurement and Metrics; Economic Growth; Forecasting and Prediction
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      Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change." AEA Papers and Proceedings 108 (May 2018): 77–82.
      • 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...  View Details
      Keywords: Internet and the Web; Price; Forecasting and Prediction; Revenue; Sales; Retail Industry
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      Ferreira, Kris J., Bin Hong Alex Lee, and David Simchi-Levi. "Analytics for an Online Retailer: Demand Forecasting and Price Optimization." Manufacturing & Service Operations Management 18, no. 1 (Winter 2016): 69–88.
      • 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...  View Details
      Keywords: Pricing Algorithms; Pricing Frequency; Commitment; Online Competition; Price; Information Technology; Competition
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      Brown, Zach Y., and Alexander J. MacKay. "Competition in Pricing Algorithms." American Economic Journal: Microeconomics (forthcoming).
      • 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...  View Details
      Keywords: Experiments; Pricing And Revenue Management; Retailing; Demand Estimation; Pricing Algorithm; Marketing; Price; Demand and Consumers; Mathematical Methods
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      Ferreira, Kris, and Emily Mower. "Demand Learning and Pricing for Varying Assortments." Manufacturing & Service Operations Management (forthcoming).
      • Research Summary

      Overview

      By: Alexander J. MacKay
      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,...  View Details
      Keywords: Price Effects; Competition Policy; Algorithms; Online Competition; Dynamic Pricing; Beliefs; Preferences; Preference Heterogeneity; Preference Measurement; Competition; Microeconomics; Strategy; Integration; Cooperation
      • Research Summary

      Overview

      By: Kris Johnson Ferreira
      Professor Ferreira's research primarily focuses on how retailers can use algorithms to make better revenue management decisions, including pricing, product display, and assortment planning. In the retail industry, anticipating consumer demand is arguably one of the...  View Details
      Keywords: E-commerce; Analytics; Revenue Management; Pricing; Assortment Planning; Field Experiments; Operations; Supply Chain; Supply Chain Management; Retail Industry
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