In recent years there has been a growing stream of literature in marketing and economics that models consumers as Bayesian learners. Such learning behavior is often embedded within a discrete choice framework that is then calibrated on scanner panel data. At the same time, it is now accepted...

Ordinal preference measures have a number of advantages relative to cardinal measures in the estimation of individual level multi-attribute utility functions. This paper: (a) outlines a theoretical foundation for estimating a cardinal scaled utility function from ordinal preference data, in...

Marketers routinely make use of stated consumer preferences and the relative attribute-importance weights implied by these preferences when making decisions on issues such as advertising messages and product design. Using this information as a basis for managerial decision making is risky,...

Marketers routinely make use of stated consumer preferences and the relative attribute importance weights implied by these preferences when making decisions on issues such as advertising messages and product design. Using this information as a basis for managerial decision-making is risky,...

We present an empirical framework to analyze real-world sales-force compensation schemes. The model is flexible enough to handle quotas and bonuses, output-based commission schemes, as well as "ratcheting" of compensation based on past performance, all of which are ubiquitous in actual...