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Coordinating Service-Sensitive Demand and Capacity by Adaptive Decision Making: An Application of Case-Based Decision Theory

机译：通过自适应决策协调服务敏感需求和容量：基于案例的决策理论的应用

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The subject of this article is the simultaneous choice of product price and manufacturing capacity if demand is stochastic and service-level sensitive. In this setting, capacity as well as price have an impact on demand because several aspects of service level depend on capacity. For example, delivery time will be reduced if capacity is increased given a constant demand rate. We illustrate the relationship between service level, capacity, and demand reaction by a stylized application problem from the after-sales services industry. The reaction of customers to variations in service level and price is represented by a kinked price-demand-rate function. We first derive the optimal price-capacity combination for the resulting decision problem under full information. Subsequently, we focus on a decision maker (DM) who lacks complete knowledge of the demand function. Hence the DM is unable to anticipate the service level and consequently cannot identify the optimal solution. However, the DM will acquire additional information during the sales process and use it in subsequent revisions of the price-capacity decision. Thus, this decision making is adaptive and based on experience. In contrast to the literature, which assumes certain repetitive procedures somewhat ad hoc, we develop an adaptive decision process based on case-based decision theory (CBDT) for the price-capacity problem. Finally, we show that a CBDT DM in our setting eventually finds the optimal solution, if the DM sets the price based on absorption costs and adequately adjusts the capacity with respect to the observed demand.
机译：本文的主题是，如果需求是随机的且对服务水平敏感的，则同时选择产品价格和生产能力。在这种情况下，容量和价格会对需求产生影响，因为服务水平的几个方面都取决于容量。例如，如果在需求率恒定的情况下增加容量，则交货时间将减少。我们通过售后服务行业中一个典型的应用问题来说明服务水平，容量和需求反应之间的关系。顾客对服务水平和价格变化的反应是由价格需求率函数引起的。我们首先在充分信息的情况下，针对由此产生的决策问题得出最优的价格能力组合。随后，我们将重点介绍对需求功能缺乏全面了解的决策​​者（DM）。因此，DM无法预期服务水平，因此无法确定最佳解决方案。但是，DM将在销售过程中获取其他信息，并将其用于价格容量决策的后续修订中。因此，该决策是自适应的并且基于经验。与假设某些重复程序有些特殊的文献相反，我们针对价格-容量问题开发了基于案例决策理论（CBDT）的自适应决策过程。最后，我们证明，如果DM根据吸收成本确定价格并根据观察到的需求适当调整容量，则CBDT DM最终会找到最佳解决方案。

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