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On the impact of analyzing customer information and prioritizing in a service system

机译:分析客户信息并确定服务系统优先级的影响

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This paper examines prioritization in a service system and analyzes whether, in the presence of heterogeneous customers who have different needs and a costly sorting process, it pays to prioritize. In particular, in our model, sorting is costly because the task of gathering information to prioritize jobs consumes resources. We investigate a stylized model in which there are two classes of jobs - one whose waiting cost is high, called urgent, and the other whose waiting cost is low, called non-urgent. There are two types of employees, sorters, who collect information on a job and then decide whether it is urgent or non-urgent, and processors, who execute the job or provide the service. We begin by assuming that sorters categorize customers perfectly, and we relax this assumption later in the paper. We optimize two performance metrics, waiting costs (under a given budget) and total costs, and find the conditions under which prioritization is beneficial for these two metrics.
机译:本文研究了服务系统中的优先级,并分析了在存在具有不同需求和成本高昂的排序流程的异构客户的情况下,是否需要为优先级付费。特别地,在我们的模型中,分类是昂贵的,因为收集信息以对作业进行优先排序的任务会消耗资源。我们研究了一种风格化的模型,其中有两类工作-一类的等待成本高,称为紧急工作,另一类的等待成本低,称为非紧急工作。员工有两种类型,一类是分类员,他们收集有关一项工作的信息,然后确定该项目是紧急的还是非紧急的;以及处理者,他们执行工作或提供服务。我们首先假设分类器对客户进行了完美分类,然后在本文稍后的部分放宽了这一假设。我们优化了两个性能指标,即等待成本(在给定的预算下)和总成本,并确定优先级排序对这两个指标有利的条件。

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