Shelf space allocation problems: a channel's perspective

货架空间是零售店的有限资源，这就是为什么它的最佳分配是分销网络（即营销渠道）中最重要的决策之一。以前的文献货架空间分配开发的数学分配模型，旨在帮助决策者最佳分配它的货架。这些模型未能捕捉到问题的一些基本特征。事实上，通过考虑货架空间分配问题是一个独特的决策者（即零售商）的问题，这些模型忽略了这个决策者和他所属的分销网络的其他成员之间存在的相互作用。因此，开发的模型缺乏现实性，因为在市场上的分销网络的成员作出决定的定价，促销，或广告投资，影响零售商的货架空间分配规则。缺乏现实性也是由于这些模型将货架空间分配问题视为静态问题，忽略了重要变量对问题的影响，或者没有充分捕捉渠道中的不同行为。在本研究计划中，我希望从渠道的角度研究货架空间分配问题。这将使我能够捕捉不同成员之间存在的互动。我还想通过建立动态模型来扩展现有的文献，这些模型不仅可以捕捉到决策是在真实的时间内做出的这一事实，而且还可以捕捉到其中一些决策具有遗留效应的事实。在充分竞争的分销网络的研究和考虑的情况下，渠道成员可以合作或不合作，受益或不从渠道领导者，文献的另一个扩展。最后，我想调查的情况下，需求是不确定的，并提供实证验证我的模型。为了解决这些问题，我将使用静态和动态博弈论作为方法论。这种模式的优势在于处理决策者的控制和结果相互依赖的情况。对于解析解不可能的情况，我将寻找数值解。

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.