Dr. Garrow teaches several graduate courses in travel demand modeling, airline economics, and revenue management and demand modeling.
CEE 8813 – Airline Revenue Management
Revenue management (RM) integrates multiple concepts from demand modeling, operations research, and economics. The sheer volume of booking transactions combined with limitations of distribution channels has shaped the historical evolution of demand forecasting and optimization algorithms used in RM. This course covers a variety of topics including demand forecasting and demand unconstraining methods for differentiated and undifferentiated products, leg-based and path-based inventory control methods, and overbooking approaches. Students will gain practical experience in implementing these approaches in Python and explore how RM demand forecasting and optimization approaches used by one airline influence revenue outcomes for that airline as well as its competitors using a competitive RM simulator. Click here for the course syllabus and here for the course website (note the course website is password protected).
CEE 8813 – Introduction to Airline Economics and Management
The modern airline industry combines the challenges of running multiple types of businesses. A large airline can be as operationally complex as a major freight forwarder, with simultaneous operations in all time zones. It can utilize advanced predictive analytics and harness big data like a technology firm. It can manage international relationships and interface with global customers like a consumer-packaged goods company. A manager at an airline must have a broad-based skill set to tackle multiple business challenges in a fast-paced, extremely competitive environment.
This course co-taught with Ben Bubnovich, Director of International Network Planning at Delta Air Lines, provides a survey overview of key competencies required to successfully manage an airline. We will touch on issues of corporate strategy, finance, economics, organization, revenue management, and network theory and optimization.
CEE 6650 – Discrete Choice Modeling
This graduate course presents the theory and practice underlying the formulation and estimation of models of individual discrete choice behavior. The course will provide students with an understanding of the theory, methods, application and interpretation of multinomial logit (MNL), nested logit (NL) and other members of the Generalized Extreme Value (GEV) family of models. It will also include an introduction to mixed logit models, latent class models, and advanced modeling concepts (e.g., methods to account for price endogeneity). This course — as it is taught by Dr. Garrow — is particularly relevant for students who are pursuing research in airline revenue management as it relates to modeling airline passenger behavior, offer management, and ancillary pricing. Click here for the course website (note the course website is password protected).