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- Research Summary
Overview
Professor 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
- Forthcoming
- Article
Personalization and Targeting: How to Experiment, Learn & Optimize
By: Aurelie Lemmens, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela and Oded Netzer
Personalization has become the heartbeat of modern marketing. Advances in causal inference and machine learning enable companies to understand how the same marketing action can impact the choices of individual customers differently. This article provides an academic... View Details
- Research Summary
Selective Attention and Learning
What do we notice, and how does this affect what we learn? Standard economic models of learning ignore memory by assuming that we remember everything. But there is growing recognition that memory is imperfect. Further, memory imperfections do not stem from limited... View Details
- Research Summary
The Value Profit Chain: Treat Employees Like Customers and Customers Like Employees
By: W. Earl Sasser
W. Earl Sasser, Jr., Leonard A. Schlesinger, and James L. Heskett complted a multi-firm study that provides further empirical verification of relationships established in their earlier examinations of 'breakthrough' service and the service profit chain.... View Details
- Teaching Interest
Transforming Customer Experiences - Executive Education
By: Ryan W. Buell
In today's fast-growing service sector, a new set of frameworks are required to build a robust and competitive service business. Transforming Customer Experiences draws upon the latest research and insights to equip senior managers with a new toolkit for leading... View Details
- Research Summary
Understanding the Limitations of Model Explanations
The 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
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