Dynamic pricing and revenue management

Objectif

Ce cours a pour objet de décrire et d’analyser les stratégies de tarification dynamique tels que le revenue management et la tarification algorithmique mises en œuvre par certaines entreprises et d’apprécier leurs effets sur l’ensemble des parties prenantes (consommateurs, entreprises et puissance publique). Il aborde des outils conceptuels et méthodologiques pour mieux comprendre et maitriser ces stratégies tarifaires. La méthode d’enseignement est fondée sur les trois piliers que sont les approches descriptives, théoriques et empiriques. 

Plan

The course is designed to provide a comprehensive understanding of dynamic pricing and revenue management. It is divided into three parts:

1. Expert Analysis (Frédéric Specklin): This segment comprises four 3-hour sessions that dive deep into the intricacies of revenue management practices, with a focus on practical and theoretical frameworks. It serves as the foundational block of the course.

2. Quick Overview of Models (Laurent Linnemer): Over two 2-hour sessions, key models are introduced to provide a mathematical and theoretical grounding. These models highlight the core mechanisms of dynamic pricing and revenue optimization.

3. Student Presentations: In the final segment, students present case studies or research papers. Each presentation lasts 20 minutes, providing an opportunity to explore real-world applications and foster critical discussion.

The models studied in this part of the course are central to understanding dynamic pricing strategies. They include: 1. The K-T (capacity-time) model, which explores optimal pricing strategies given finite capacity and time constraints. 2. The Newsvendor model, focusing on inventory decisions under demand uncertainty. 3. Littlewood’s rule, a classic principle in revenue management. 4. Lazear’s demand learning model, which introduces learning mechanisms in pricing strategies. 5. A brief overview of advanced topics such as: • Strategic consumers, addressing consumer behavior in response to pricing. • Behavior-Based Pricing, where pricing strategies adapt to consumer history.