Learning models extend the traditional discrete choice framework by postulating that consumers have incomplete information about product attributes, and that they learn about these attributes over time. In this survey we describe the literature on learning models that has developed over the past...

Over the past ten years there has been increased recognition of the importance of publicity as a means of generating product awareness. Despite this, previous research has seldom investigated the impact of publicity on demand. We contribute to the literature by (i) proposing a new method for the...

In a rapidly changing world, older data is not as informative as the most recent data. This is known as a concept drift problem in statistics and machine learning. How does a firm adapt in such an environment? To address this research question, we propose a generalized revealed preference...

How do people make choices in a dynamic stochastic environment when they face uncertainty about the return of their choices? The classical approach to this problem is to assume consumers use dynamic programming to obtain the optimal decision rule. However, this approach has two drawbacks. First,...

Public policies that intervene or restrict consumer choices for the benefit of the society are often controversial. For instance, the compliance rate of COVID-19 pandemic social distancing rules varied dramatically across cities and states, and these policies even backfired among some consumers...