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October 2022
Exercise

Shanty Real Estate: Updated Confidential Information for Homebuyer

By: Michael Luca, Jesse M. Shapiro and Nathan Sun

Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details

Keywords: Algorithm; Decision Choices and Conditions; Decision Making; Market Timing; Measurement and Metrics

October 2022
Exercise

Shanty Real Estate: Updated Confidential Information for iBuyer

By: Michael Luca, Jesse M. Shapiro and Nathan Sun

Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details

Keywords: Algorithm; Decision Choices and Conditions; Measurement and Metrics; Market Timing; Decision Making

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

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

2022
Article

Towards Robust Off-Policy Evaluation via Human Inputs

By: Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez and Himabindu Lakkaraju

Off-policy Evaluation (OPE) methods are crucial tools for evaluating policies in high-stakes domains such as healthcare, where direct deployment is often infeasible, unethical, or expensive. When deployment environments are expected to undergo changes (that is, dataset... View Details

Keywords: Analytics and Data Science; Research

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2022
Working Paper

Machine Learning Models for Prediction of Scope 3 Carbon Emissions

By: 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

Article

Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)

By: Eva Ascarza and Ayelet Israeli

An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details

Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods

March 2022
Article

Learning to Rank an Assortment of Products

By: 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

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March 2022
Article

Where to Locate COVID-19 Mass Vaccination Facilities?

By: Dimitris Bertsimas, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li and Alessandro Previero

The outbreak of COVID-19 led to a record-breaking race to develop a vaccine. However, the limited vaccine capacity creates another massive challenge: how to distribute vaccines to mitigate the near-end impact of the pandemic? In the United States in particular, the new... View Details

Keywords: Vaccines; COVID-19; Health Care and Treatment; Health Pandemics; Performance Effectiveness; Analytics and Data Science; Mathematical Methods

Article

Adaptive Machine Unlearning

By: Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi and Chris Waites

Data deletion algorithms aim to remove the influence of deleted data points from trained models at a cheaper computational cost than fully retraining those models. However, for sequences of deletions, most prior work in the non-convex setting gives valid guarantees... View Details

Keywords: Machine Learning; AI and Machine Learning

Article

Counterfactual Explanations Can Be Manipulated

By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh

Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate... View Details

Keywords: Machine Learning Models; Counterfactual Explanations

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

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

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

2021
Working Paper

The Demand for Executive Skills

By: Stephen Hansen, Raffaella Sadun, Tejas Ramdas and Joseph B. Fuller

We use a unique corpus of job descriptions for C-suite positions to document skills requirements in top managerial occupations across a large sample of firms. A novel algorithm maps the text of each executive search into six separate skill clusters reflecting... View Details

Keywords: C-Suite; Jobs and Positions; Competency and Skills; Management Skills; Job Search; Job Design and Levels

2021
Working Paper

The Demand for Executive Skills

By: Stephen Hansen, Tejas Ramdas, Raffaella Sadun and Joseph B. Fuller

We use a unique corpus of job descriptions for C-suite positions to document skills requirements in top managerial occupations across a large sample of firms. A novel algorithm maps the text of each executive search into six separate skill clusters reflecting... View Details

Keywords: Executives; Management Skills; Competency and Skills

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2021
Article

To Thine Own Self Be True? Incentive Problems in Personalized Law

By: Jordan M. Barry, John William Hatfield and Scott Duke Kominers

Recent years have seen an explosion of scholarship on “personalized law.” Commentators foresee a world in which regulators armed with big data and machine learning techniques determine the optimal legal rule for every regulated party, then instantaneously disseminate... View Details

Keywords: Personalized Law; Regulation; Regulatory Avoidance; Regulatory Arbitrage; Law And Economics; Law And Technology; Law And Artificial Intelligence; Futurism; Moral Hazard; Elicitation; Signaling; Privacy; Law; Governing Rules, Regulations, and Reforms; Information Technology; AI and Machine Learning

May 2021 (Revised February 2024)
Teaching Note

THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

By: Ayelet Israeli and Jill Avery

THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details

Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States

2021
Article

Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring

By: Tom Sühr, Sophie Hilgard and Himabindu Lakkaraju

Ranking algorithms are being widely employed in various online hiring platforms including LinkedIn, TaskRabbit, and Fiverr. Prior research has demonstrated that ranking algorithms employed by these platforms are prone to a variety of undesirable biases, leading to the... View Details

March 2021
Supplement

Artea (A), (B), (C), and (D): Designing Targeting Strategies

By: Eva Ascarza and Ayelet Israeli

Power Point Supplement to Teaching Note for HBS No. 521-021,521-022,521-037,521-043. 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... View Details

Keywords: Targeted Advertising; Targeting; Algorithmic Data; Bias; A/B Testing; Experiment; Advertising; Gender; Race; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States

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