尺度
竞赛(生物学)
报销
排队论
激励
服务(商务)
微观经济学
业务
经济
降低成本
计算机科学
运筹学
产业组织
医疗保健
营销
工程类
计算机网络
生物
经济增长
数学
生态学
几何学
作者
Nicos Savva,Tolga Tezcan,Özlem Yıldız
出处
期刊:Management Science
[Institute for Operations Research and the Management Sciences]
日期:2019-01-31
卷期号:65 (7): 3196-3215
被引量:64
标识
DOI:10.1287/mnsc.2018.3089
摘要
Yardstick competition is a regulatory scheme for local monopolists (e.g., hospitals), where the monopolist’s reimbursement is linked to performance relative to other equivalent monopolists. This regulatory scheme is known to provide cost-reduction incentives and serves as the theoretical underpinning behind the hospital prospective reimbursement system used throughout the developed world. This paper uses a game-theoretic queueing model to investigate how yardstick competition performs in service systems (e.g., hospital emergency departments), where in addition to incentivizing cost reduction the regulator wants to incentivize waiting time reduction. We first show that the form of cost-based yardstick competition used in practice results in inefficiently long waiting times. We then demonstrate how yardstick competition can be appropriately modified to achieve the dual goal of cost and waiting-time reduction. In particular, we show that full efficiency (first-best) can be restored if the regulator makes the providers’ reimbursement contingent on their service rates and is also able to charge a provider-specific “toll” to consumers. More important, if such a toll is not feasible, as may be the case in healthcare, we show that there exists an alternative and particularly simple yardstick-competition scheme, which depends on the average waiting time only, that can significantly improve system efficiency (second-best). This scheme is easier to implement because it does not require the regulator to have detailed knowledge of the queueing discipline. We conclude with a numerical investigation that provides insights on the practical implementation of yardstick competition for hospital emergency departments, and we also present a series of modelling extensions. The e-companion is available at https://doi.org/10.1287/mnsc.2018.3089 . This paper was accepted by Serguei Netessine, operations management.
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