论混合双寡头服务体系中私有化的利益

Manag. Sci. Pub Date : 2022-05-05 DOI:10.1287/mnsc.2022.4424
Wenhui Zhou, Weixiang Huang, V. Hsu, Pengfei Guo
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引用次数: 3

摘要

我们考虑一个由两个服务提供商(sp)组成的混合双寡头服务系统:一个是私人的,另一个是公共的。公共SP的目标是福利最大化,而私人SP的目标是利润驱动。顾客的品质品味是异质的,有三种选择,分别是加入私人队列、加入公共队列和犹豫(或选择外部选项)。我们首先考虑私人服务提供商提供高级服务而公共服务提供商提供常规服务的情况。矛盾的是,我们发现尽管公共SP的目标是福利最大化,但系统中的福利可能比只有追求利润的私人SP所获得的福利要少。我们进一步证明,通过将公共SP部分私有化,即通过将福利最大化和利润最大化作为其目标函数的参数来实现最大的社会福利。在公共社会服务能力非常小的极端情况下,将公共社会服务完全私有化可能是社会可取的。然后,我们考虑了公共服务提供商提供高级服务和私人服务提供商提供常规服务的替代设置,并得到了类似的结论。然而,这些发现依赖于一个假设,即犹豫不决的客户存在一个外部选择,人们应该谨慎地将其推广到没有犹豫不决的情况。这篇论文被运营管理的Jayashankar Swaminathan接受。
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On the Benefit of Privatization in a Mixed Duopoly Service System
We consider a mixed duopoly service system with two service providers (SPs): one private and the other public. The public SP’s objective is welfare maximization, whereas the private SP is profit driven. Customers are heterogeneous in terms of their quality tastes and choose from three options, namely, joining the private queue, joining the public queue, and balking (or taking an outside option). We first consider the scenario where the private SP provides a premium service and the public SP provides a regular service. Paradoxically, we find that although the public SP’s objective is welfare maximization, welfare in the system can be less than that obtained with only profit-seeking private SPs. We further demonstrate that the maximum social welfare is achieved by partially privatizing the public SP, that is, by including both welfare and profit maximization as arguments in its objective function. In extreme cases in which the public SP’s capacity is very small, fully privatizing the public SP can be socially desirable. We then consider the alternate setting where the public SP provides a premium service and the private SP provides a regular service and obtain similar conclusions. These findings, however, rely on the assumption that an outside option exists for balking customers, and one should be cautious in generalizing to no-balking situations. This paper was accepted by Jayashankar Swaminathan, operations management.
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