Grant: Discovery Grants Program - Individual

Shelf space is a limited resource in retail outlets, that's why it's optimal allocation is one of the most important decisions that take place in the distribution network (i.e. the marketing channel). Previous literature on shelf space allocation developed mathematical allocation models designed to help the decision maker to allocate optimally it's shelf. Those models fail to capture some essential features of the problem. Indeed, by considering that the shelf space allocation problem is a matter of a unique decision maker (i.e. the retailer), these models ignore the interactions existing between this decision maker and the other members of the distribution network to which he belongs. As a consequence, the developed models lack of realism, since in the marketplace members of the distribution network make decisions on pricing, promotions, or advertising investments, that affect the shelf space allocation rules of retailers. The lack of realism is also due to the fact that these models consider the issue of shelf space allocation as a static problem, neglect the impact of important variables on the issue, or do not capture fully the different kinds of behaviours in the channel. In this research proposal, I wish to study the issue of shelf space allocation from a channel's perspective. This will allow me to capture the interactions existing between the different members. I would like also to extend the existing literature by building dynamic models that capture the fact that decisions are taken in real time, but also, the fact that some of them have carry-over effects. Another extension of the literature in the study of fully competitive distribution networks and the consideration of scenarios where channel members could cooperate or not, benefit or not from being channel leaders,..etc. Finally, I would like to investigate situations where demand is uncertain, and provide empirical validation for my models. In order to deal with all these issue, I will use static and dynamic game theory as a methodological approach. This paradigm has the advantage of dealing with situations where the decisions makers' controls and outcomes are interdependent. For situations where analytical solutions are not possible, I will look for numerical solutions.