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Show Results For
- All HBS Web
(646)
- News (145)
- Research (421)
- Events (15)
- Multimedia (11)
- Faculty Publications (295)
- 24 Jul 2023
- Research & Ideas
Part-Time Employees Want More Hours. Can Companies Tap This ‘Hidden’ Talent Pool?
many such workers are caregivers, excluded from full-time jobs because short-sighted employers don’t offer them the flexibility they need. Filtered out by hiring algorithms due to employment gaps or other hiring “red flags,” these willing... View Details
Keywords: by Kara Baskin
Kris Johnson Ferreira
Kris Ferreira is the Edgerley Family Associate Professor of Business Administration in the Technology and Operations Management (TOM) Unit. She teaches the Supply Chain Management course in the MBA elective curriculum and analytics in numerous Executive Education... View Details
Keywords: retailing
- 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
- 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
- January 2025
- Case
PayJoy: Finance for the Next Billion
By: Boris Groysberg and Sarah L. Abbott
PayJoy, an impact-driven financial technology company founded in 2015, provides smartphone financing and other financial products to customers who lack access to traditional credit products. As of early 2025, PayJoy had issued $2.5 billion in loans to 13 million... View Details
Keywords: Social Impact; Fintech; Developing Countries; Underbanked; Algorithm; Credit; South America; Mission And Purpose; Start-up; Entrepreneurship; Growth; Data Analysis; Technology; Business Ventures; Business Startups; Business Model; Growth and Development; Information Technology; Social Enterprise; Financial Services Industry; South America; South Africa; Asia
- 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
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.)
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.)
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
Kate Kellogg, MIT
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.)
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
Seth 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
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
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.
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
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
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