Publications
Publications
Show Results For
- All HBS Web
(117,424)
- Faculty Publications (28)
Page 1 of 28
Results →
- 2024
- Working Paper
Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift
By: Matthew DosSantos DiSorbo and Kris Ferreira
Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). These outliers often originate from covariate shift,... View Details
- October 2023 (Revised June 2024)
- Case
ReUp Education: Can AI Help Learners Return to College?
By: Kris Ferreira, Christopher Thomas Ryan and Sarah Mehta
Founded in 2015, ReUp Education helps “stopped out students”—learners who have stopped making progress towards graduation—achieve their college completion goals. The company relies on a team of success coaches to engage with learners and help them reenroll. In 2019,... View Details
- July–August 2023
- 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
- March–April 2023
- Article
Market Segmentation Trees
By: Ali Aouad, Adam Elmachtoub, Kris J. Ferreira and Ryan McNellis
Problem definition: We seek to provide an interpretable framework for segmenting users in a population for personalized decision making. Methodology/results: We propose a general methodology, market segmentation trees (MSTs), for learning market... View Details
- March 2022
- Teaching Note
JOANN: Joannalytics Inventory Allocation Tool
By: Kris Ferreira
Teaching Note for HBS Case No. 621-055. View Details
- 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
- October 2021
- Case
Diversifying P&G's Supplier Base (A)
By: Kris Ferreira, Kym Lew Nelson, Carin-Isabel Knoop and Sarah Mehta
In February 2003, P&G hosted two meetings—one with its largest woman- and minority-owned suppliers and one with its largest non-minority-owned suppliers. Attendees in each meeting heard the same message: P&G was keen to grow its commitment to inclusive supply chains,... View Details
- October 2021
- Supplement
Diversifying P&G's Supplier Base (B)
By: Kris Ferreira, Kym Lew Nelson, Carin-Isabel Knoop and Sarah Mehta
This (B) case accompanies the (A) case of the same title. View Details
- September 2021 (Revised March 2022)
- Teaching Note
GHN and AhaMove: Last-Mile Delivery in Vietnam
By: Kris Ferreira, Joel Goh and Dawn H. Lau
Teaching Note for HBS Case No. 619-051. View Details
- July 2021 (Revised March 2022)
- Teaching Note
Flashion: Art vs. Science in Fashion Retailing
By: Kris Ferreira
- 2021
- Working Paper
Demand Learning and Pricing for Varying Assortments
By: Kris Ferreira and Emily Mower
- March 2021
- Article
Assortment Rotation and the Value of Concealment
By: Kris J. Ferreira and Joel Goh
Assortment rotation—the retailing practice of changing the assortment of products offered to customers—has recently been used as a competitive advantage for both brick-and-mortar and online retailers. We focus on product categories where consumers may purchase multiple... View Details
- February 2021
- Case
Drizly: Managing Supply and Demand through Disruption
By: Kris Ferreira
It was April 6th, 2020, and the management team at Drizly—an online alcohol marketplace where consumers could browse and purchase alcohol from local liquor retail stores via Drizly’s app for immediate home delivery—were thrilled to see record-breaking sales from the... View Details
- September 2020 (Revised March 2022)
- Case
JOANN: Joannalytics Inventory Allocation Tool
By: Kris Ferreira and Srikanth Jagabathula
Michael Joyce, Vice President of Inventory Management at JOANN, championed an effort to develop and implement an inventory allocation analytics tool that used advanced analytics to predict in-season demand of seasonal items for each of JOANN’s nearly 900 stores and... View Details
Keywords: Analytics; Machine Learning; Optimization; Inventory Management; Mathematical Methods; Decision Making; Operations; Supply Chain Management; Resource Allocation; Distribution; Technology Adoption; Applications and Software; Change Management; Fashion Industry; Consumer Products Industry; Retail Industry; United States; Ohio
- August 2020 (Revised September 2020)
- Technical Note
Assessing Prediction Accuracy of Machine Learning Models
The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools... View Details
- December 2019
- Article
The Impact of Increasing Search Frictions on Online Shopping Behavior: Evidence from a Field Experiment
By: Donald Ngwe, Kris J. Ferreira and Thales Teixeira
Many online stores are designed such that shoppers can easily access any available discounted products. We propose that deliberately increasing search frictions by placing small obstacles to locating discounted items can improve online retailers’ margins and even... View Details
- June 2019 (Revised September 2021)
- Case
GHN and AhaMove: Last-Mile Delivery in Vietnam
By: Kris Ferreira, Joel Goh, Dawn Lau and Tuan Phan
- 2019
- Working Paper
The Impact of Increasing Search Frictions on Online Shopping Behavior: Evidence from a Field Experiment
By: Donald Ngwe, Kris J. Ferreira and Thales Teixeira
Many online stores are designed such that shoppers can easily access any available discounted products. We propose that deliberately increasing search frictions by placing small obstacles to locating discounted items can improve online retailers’ margins and even... View Details