Using revealed‐ and stated‐preference customer choice models for making pricing decisions in services: An illustration from the hospitality industry

This article presents an overview of discrete choice modeling for making pricing decisions in services. During recent years, discrete choice modeling has emerged as an effective approach for developing analytical models and for estimating relative weights of parameters based on empirical data. For estimation purposes, typically one of two forms of data is used: transactional data captured in databases (revealed‐preference data); or primary experimental data (stated‐preference data). In this article, we provide detailed illustration of both approaches for pricing decisions for hospitality services. Finally, we discuss the managerial implications of the discrete choice modeling approach described earlier in the article.