In this paper we establish a link between probabilistic cost efficiency and bounded rationality in the newsvendor model. This establishes a framework where bounded rationality can be examined rigorously by statistical methods. The paper offers a relatively deep theoretical analysis of...

In this paper, we discuss discrete choice theory and show how this theory can be used to quantify learning effects in experimental studies. We argue why the ordering quantities in newsvendor experiments should follow a multinomial logit distribution. We provide a robustness analysis to explain...

In this paper, we use probabilistic methods to analyze learning effects in a behavioral experiment on the newsvendor model. We argue why we should believe that suggested orders follow a multinomial logit distribution, and use the single parameter in that model to extract information on learning...

In this paper, we consider the newsvendor model under partial information, i.e., where the demand distribution D is partly unknown. We focus on the classical case where the retailer only knows the expectation and variance of D. The standard approach is then to determine the order quantity using...