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    • All HBS Web  (159)
      • Faculty Publications  (28)

      Pricing Algorithms Remove Pricing Algorithms →

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      • 2022
      • Working Paper

      Price Monitoring and Response: A Supply Side Characterization

      By: Ayelet Israeli and Eric Anderson
      With the growth of e-commerce and increasing price transparency, there has been tremendous interest in the adoption and competitive consequences of algorithmic pricing. A premise of algorithmic pricing is that firms monitor competitors' prices and then their pricing...  View Details
      Keywords: Algorithmic Pricing; Ecommerce; Price Monitoring; Price; Competition; Retail Industry
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      Israeli, Ayelet, and Eric Anderson. "Price Monitoring and Response: A Supply Side Characterization." Working Paper, October 2022.
      • 2022
      • Article

      Dynamic Pricing Algorithms, Consumer Harm, and Regulatory Response

      By: Alexander MacKay and Samuel N. 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; Economics; Law And Economics; Law And Regulation; Consumer Protection; Antitrust Law; Industrial Organization; Antitrust Issues And Policies; Technological Change: Choices And Consequences; Competition; Policy; Price; Governing Rules, Regulations, and Reforms; Microeconomics; Duopoly and Oligopoly; Law
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      MacKay, Alexander, and Samuel N. Weinstein. "Dynamic Pricing Algorithms, Consumer Harm, and Regulatory Response." Washington University Law Review 100, no. 1 (2022): 111–174. (Direct download.)
      • September 2022 (Revised November 2022)
      • Teaching Note

      PittaRosso: Artificial Intelligence-Driven Pricing and Promotion

      By: Ayelet Israeli
      Teaching Note for HBS Case No. 522-046.  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: Artificial Intelligence-Driven Pricing and Promotion." Harvard Business School Teaching Note 523-020, September 2022. (Revised November 2022.)
      • August 2022
      • Supplement

      Zalora: Data-Driven Pricing Recommendations

      By: Ayelet Israeli
      This exercise can be used in conjunction with the main case "Zalora: Data-Driven Pricing" to facilitate class discussion without requiring data analysis from the students. Instead, the exercise presents reports that were created by the data science team to answer the...  View Details
      Keywords: Pricing; Pricing Algorithms; Dynamic Pricing; Ecommerce; Pricing Strategy; Pricing And Revenue Management; Apparel; Singapore; Startup; Demand Estimation; Data Analysis; Data Analytics; Exercise; Price; Internet and the Web; Apparel and Accessories Industry; Retail Industry; Fashion Industry; Singapore
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      Israeli, Ayelet. "Zalora: Data-Driven Pricing Recommendations." Harvard Business School Supplement 523-032, August 2022.
      • 2022
      • Working Paper

      Dynamic Pricing and Demand Volatility: Evidence from Restaurant Food Delivery

      By: Alexander J. MacKay, Dennis Svartbäck and Anders G. Ekholm
      Pricing technology that allows firms to rapidly adjust prices has two potential benefits. Prices can respond more rapidly to demand shocks, leading to higher revenues. On the other hand, time-varying prices can be used to smooth out demand across periods, reducing...  View Details
      Keywords: Pricing Algorithms; Dynamic Pricing; Demand Volatility; Delivery Services
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      MacKay, Alexander J., Dennis Svartbäck, and Anders G. Ekholm. "Dynamic Pricing and Demand Volatility: Evidence from Restaurant Food Delivery." Harvard Business School Working Paper, No. 23-007, July 2022.
      • July 7, 2022
      • Other Article

      Are Online Prices Higher Because of Pricing Algorithms?

      By: Zach Y. Brown and Alexander J. MacKay
      This article reviews recent work examining pricing strategies of major online retailers and the potential effects of pricing algorithms. We describe how pricing algorithms can lead to higher prices in a number of ways, even if some characteristics of these algorithms...  View Details
      Keywords: Pricing Algorithms; Online Marketplace; Digital Strategy; Internet and the Web; Retail Industry
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      Brown, Zach Y., and Alexander J. MacKay. "Are Online Prices Higher Because of Pricing Algorithms?" Brookings Series: The Economics and Regulation of Artificial Intelligence and Emerging Technologies (July 7, 2022).
      • May 2022 (Revised August 2022)
      • Case

      LOOP: Driving Change in Auto Insurance Pricing

      By: Elie Ofek and Alicia Dadlani
      John Henry and Carey Anne Nadeau, co-founders and co-CEOs of LOOP, an insurtech startup based in Austin, Texas, were on a mission to modernize the archaic $250 billion automobile insurance market. They sought to create equitably priced insurance by eliminating pricing...  View Details
      Keywords: AI and Machine Learning; Technological Innovation; Equality and Inequality; Prejudice and Bias; Growth and Development Strategy; Customer Relationship Management; Price; Insurance Industry; Financial Services Industry
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      Ofek, Elie, and Alicia Dadlani. "LOOP: Driving Change in Auto Insurance Pricing." Harvard Business School Case 522-073, May 2022. (Revised August 2022.)
      • 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 June 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 June 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).
      • 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; E-commerce; Applications and Software; 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 (Revised July 2022)
      • 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; 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; E-commerce; 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. (Revised July 2022.)
      • 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 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; E-commerce; Analytics and Data Science; 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; E-commerce; Applications and Software; Health Industry; Technology Industry; Insurance Industry; Information Technology Industry; Food and Beverage Industry; Israel; United States
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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.
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