Shelf space allocation problems: a channel's perspective

货架空间在零售商店中是一种有限的资源，这就是为什么货架空间的优化配置是分销网络（即营销渠道）中最重要的决策之一。以往关于货架空间分配的文献建立了数学分配模型，旨在帮助决策者最优地分配货架。这些模型未能捕捉到问题的一些基本特征。事实上，由于考虑到货架空间分配问题是一个独特的决策者（即零售商）的问题，这些模型忽略了该决策者与其所属的分销网络中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，因为在分销网络的市场成员对定价、促销或广告投资做出决定，这些决定会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，忽视了重要变量对该问题的影响，或者没有充分捕捉渠道中不同类型的行为。在这个研究计划中，我希望从渠道的角度来研究货架空间分配的问题。这将允许我捕捉不同成员之间存在的交互。我还想通过建立动态模型来扩展现有的文献，这些模型可以捕捉到决策是实时做出的这一事实，但也可以捕捉到其中一些决策具有结转效应的事实。文献的另一个扩展是研究充分竞争的分销网络，并考虑渠道成员可以合作或不合作，从成为渠道领导者中受益或不受益等情况。最后，我想调查需求不确定的情况，并为我的模型提供实证验证。为了处理所有这些问题，我将使用静态和动态博弈论作为方法论方法。这种模式在处理决策者的控制和结果相互依赖的情况时具有优势。对于不可能有解析解的情况，我会寻找数值解。

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.