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Show Results For
- All HBS Web
(647)
- News (142)
- Research (416)
- Events (13)
- Multimedia (11)
- Faculty Publications (291)
- 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
- 18 Oct 2022
- Research & Ideas
When Bias Creeps into AI, Managers Can Stop It by Asking the Right Questions
Most companies rely on artificial intelligence-based algorithms to make a wide variety of business decisions—from pinpointing the products customers prefer to determining which resumes should go to hiring managers. The problem for... View Details
Keywords: by Rachel Layne
- 24 May 2021
- News
White Airbnb Hosts Earn More. Can AI Shrink the Racial Gap?
Why Tik Tok is Beating YouTube for Eyeball Time
November 2022
Video clips might draw people to TikTok, but its algorithm keeps them watching. John Deighton and Leora Kornfeld explore why TikTok raced ahead of other platforms. First,... View Details
PittaRosso (B): Human and Machine LearningBy: 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
Israeli, Ayelet. "PittaRosso (B): Human and Machine Learning." Harvard Business School Supplement 522-047, November 2021. (Revised December 2021.)
Zebra Medical VisionBy: Shane Greenstein and Sarah Gulick
An Israeli startup founded in 2014, Zebra Medical Vision developed algorithms that produced diagnoses from X-rays, mammograms, and CT-scans. The algorithms used deep learning and digitized radiology scans to create software that could assist doctors in making... View Details
Keywords: Radiology; Machine Learning; X-ray; CT Scan; Medical Technology; Probability; FDA 510(k); Diagnosis; Business Startups; Health Care and Treatment; Information Technology; Applications and Software; Competitive Strategy; Product Development; Commercialization; Decision Choices and Conditions; Health Industry; Medical Devices and Supplies Industry; Technology Industry; Israel
Greenstein, Shane, and Sarah Gulick. "Zebra Medical Vision." Harvard Business School Case 619-014, September 2018. (Revised December 2019.)
Zalora: Data-Driven Pricing RecommendationsBy: 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
Israeli, Ayelet. "Zalora: Data-Driven Pricing Recommendations." Harvard Business School Supplement 523-032, August 2022.
Is AI Coming for Your Job?possibilities and chart a path for the future using data, algorithms, AI, and machine learning. AI serves to augment or improve human performance. When computational and machine-learning algorithms perform an ever-increasing number of... View Details
Data-Driven Denim: Financial Forecasting at Levi StraussBy: Mark Egan
The case examines Levi Strauss’ journey in implementing machine learning and AI into its financial forecasting process. The apparel company partnered with the IT company Wipro in 2017 to develop a machine learning algorithm that could help Levi Strauss forecast its... View Details
Keywords: Investor Relations; Forecasting; Machine Learning; Artificial Intelligence; Apparel; Corporate Finance; Forecasting and Prediction; AI and Machine Learning; Digital Transformation; Apparel and Accessories Industry; United States
Egan, Mark. "Data-Driven Denim: Financial Forecasting at Levi Strauss." Harvard Business School Case 224-029, January 2024. (Revised February 2024.)
Kate Kellogg, MITSeth NeelSeth Neel is an Assistant Professor housed in the Department of Technology and Operations Management (TOM) at HBS, and a Faculty Affiliate in Computer Science at SEAS. He is Principal Investigator of the Trustworthy AI Lab in Harvard's new
PittaRosso: Artificial Intelligence-Driven Pricing and PromotionBy: 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; Transformation; Decision Making; AI and Machine Learning; Retail Industry; Italy
Machine Learning Models for Prediction of Scope 3 Carbon EmissionsBy: George Serafeim and Gladys Vélez Caicedo
For most organizations, the vast amount of carbon emissions occur in their supply chain and in the post-sale processing, usage, and end of life treatment of a product, collectively labelled scope 3 emissions. In this paper, we train machine learning algorithms on 15... View Details
Keywords: Carbon Emissions; Climate Change; Environment; Carbon Accounting; Machine Learning; Artificial Intelligence; Digital; Data Science; Environmental Sustainability; Environmental Management; Environmental Accounting
Serafeim, George, and Gladys Vélez Caicedo. "Machine Learning Models for Prediction of Scope 3 Carbon Emissions." Harvard Business School Working Paper, No. 22-080, June 2022.
Scalable Holistic Linear RegressionBy: Dimitris Bertsimas and Michael Lingzhi Li
We propose a new scalable algorithm for holistic linear regression building on Bertsimas & King (2016). Specifically, we develop new theory to model significance and multicollinearity as lazy constraints rather than checking the conditions iteratively. The resulting... View Details
Bertsimas, Dimitris, and Michael Lingzhi Li. "Scalable Holistic Linear Regression." Operations Research Letters 48, no. 3 (May 2020): 203–208.
Defining Clusters of Related IndustriesThis paper develops a novel clustering algorithm that systematically generates and assesses sets of cluster definitions (i.e., groups of closely related industries). View Details
Testing SubstitutabilityBy: John William Hatfield, Nicole Immorlica and Scott Duke Kominers
We provide an algorithm for testing the substitutability of a length-N preference relation over a set of contracts X in time O(|X|3⋅N3). Access to the preference relation is essential for this result: We show that a substitutability-testing algorithm with access only... View Details
Keywords: Substitutability; Matching; Communication Complexity; Preference Elicitation; Marketplace Matching; Communication; Mathematical Methods; Economics
Hatfield, John William, Nicole Immorlica, and Scott Duke Kominers. "Testing Substitutability." Games and Economic Behavior 75, no. 2 (July 2012): 639–645.
OverviewProfessor 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
Understanding the Limitations of Model ExplanationsThe goal of this research is to understand how adversaries can exploit various algorithms used for explaining complex machine learning models with an intention to mislead end users. For instance, can adversaries trick these algorithms into masking their racial and... View Details
Learning to Rank an Assortment of ProductsBy: Kris Ferreira, Sunanda Parthasarathy and Shreyas Sekar
We consider the product ranking challenge that online retailers face when their customers typically behave as “window shoppers”: they form an impression of the assortment after browsing products ranked in the initial positions and then decide whether to continue... View Details
Keywords: Online Learning; Product Ranking; Assortment Optimization; Learning; Internet and the Web; Product Marketing; Consumer Behavior; E-commerce
Ferreira, Kris, Sunanda Parthasarathy, and Shreyas Sekar. "Learning to Rank an Assortment of Products." Management Science 68, no. 3 (March 2022): 1828–1848.
First Look at New Research and Ideas, May 8, 2018https://www.hbs.edu/faculty/Pages/item.aspx?num=52570 Algorithm Appreciation: People Prefer Algorithmic to Human Judgment By: Logg, Jennifer M., Julia A. Minson, and Don A. Moore Abstract—Even though... View Details
Keywords: Sean Silverthorne
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