多需求源、多设施服务提供商的价格导向成本分担与需求分配

Hanlin Liu, Yimin Yu, S. Benjaafar, Huihui Wang
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引用次数: 5

摘要

问题定义:我们考虑在拥有多个需求源和多个服务设施的企业之间通过需求分配来实现产能共享。企业决定将来自不同来源的需求分配到不同的设施,以最大限度地减少延迟成本和可能受服务水平要求影响的服务履行成本。如果企业决定联合经营,他们还必须决定分摊总成本的方案。学术/实践相关性:我们通过服务系统中存在服务履行成本的需求分配来研究容量共享。我们的问题是由涉及公私伙伴关系的医疗保健服务合作引起的。方法:我们将问题表述为合作博弈,并确定核心的成本分配。结果:我们确定的成本分配方案是价格导向的,每个企业的成本由三个部分组成:(1)企业内部发生的延迟成本;(二)本企业在其他企业拥有的设施中使用容量所支付的成本;(3)因满足其他企业在本企业拥有的设施上的需求而收到的付款。有趣的是,我们证明了成本分配方案等同于市场均衡——也就是说,它可以以分散的方式实现。我们将分析扩展到每个设施的容量由内部决定的设置,以及部署服务优先级策略的设置。我们的结果对各种推广具有鲁棒性:部分共享、部分传输、作为一般排队系统建模的设施和凸延迟成本。管理启示:我们的研究结果为如何在存在服务履行成本的情况下在不同公司之间进行需求分配和成本分担以促进服务协作提供了指导和见解。特别是,均衡市场价格可以看作是公私伙伴关系中服务合作的价格/补贴。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Price-Directed Cost Sharing and Demand Allocation Among Service Providers with Multiple Demand Sources and Multiple Facilities
Problem definition: We consider capacity sharing through demand allocation among firms with multiple demand sources and multiple service facilities. Firms decide on the allocation of demand from different sources to different facilities to minimize delay costs and service-fulfillment costs possibly subject to service-level requirements. If firms decide to operate collectively as a coalition, they must also decide on a scheme for sharing the total cost. Academic/practical relevance: We study capacity sharing through demand allocation in service systems in the presence of service-fulfillment costs. Our problem is motivated by service collaboration in healthcare involving public–private partnerships. Methodology: We formulate the problem as a cooperative game and identify a cost allocation that is in the core. Results: The cost-allocation scheme we identify is price-directed, and the cost of each firm consists of three components: (1) the delay cost incurred within the firm; (2) a cost paid for the capacity used by the firm at facilities owned by other firms; and (3) a payment received for fulfilling demand of other firms at facilities owned by the firm. Interestingly, we show that the cost-allocation scheme is equivalent to a market equilibrium—that is, it can be implemented in a decentralized fashion. We extend our analysis to settings where the capacity of each facility is endogenously determined and to settings where a service-priority policy is deployed. Our results are robust to a variety of generalizations: partial sharing, partial transfer, facilities modeled as general queueing systems, and convex delay costs. Managerial implications: Our findings provide guidelines for and insights into how to carry out demand allocation and cost sharing among different firms in the presence of service-fulfillment costs to foster service collaboration. In particular, the equilibrium market prices can be viewed as the prices/subsidies for service collaboration in a public–private partnership.
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