The Impact of Delay Announcements on Hospital Network Coordination and Waiting Times

Dong, Jing; Yom‐Tov, Elad; Yom-Tov, Galit B.

doi:10.1287/mnsc.2018.3048

Cited by 61 publications

(62 citation statements)

References 34 publications

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“…Moreover, non-verifiable and non-quantifiable information may improve both the firm's profit and the expected utility of customers [5]. Finally, under certain conditions, providing delay information may make the system more volatile and can lead to longer delays on average [10,19,42,66].…”

Section: A Bird's Eye View: Key Insightsmentioning

confidence: 99%

“…Dong et al [19] also consider a network setting with multiple providers, but they focus on a network of hospitals instead. In particular, they study, in the context of an empirical investigation, the impact of delay announcements on coordination in the network.…”

Section: To Reveal or Not To Reveal? Observable Versus Unobservable Qmentioning

confidence: 99%

“…Pender et al [66] also consider the impact of delaying the delay announcements. Specifically, they study the oscillation behavior observed in both He and Down [42] and Dong et al [19]. They use two deterministic fluid models to examine the effect of providing customers with delayed delay information.…”

Section: Granularity Timing and Breadth Of The Delay Informationmentioning

confidence: 99%

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Sharing delay information in service systems: a literature survey

Ibrahim

2018

Queueing Syst

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Service providers routinely share information about upcoming waiting times with their customers, through delay announcements. The need to effectively manage the provision of these announcements has led to a substantial growth in the body of literature which is devoted to that topic. In this survey paper, we systematically review the relevant literature, summarize some of its key ideas and findings, describe the main challenges that the different approaches to the problem entail, and formulate research directions that would be interesting to consider in future work.

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Section: A Bird's Eye View: Key Insightsmentioning

confidence: 99%

Section: To Reveal or Not To Reveal? Observable Versus Unobservable Qmentioning

confidence: 99%

Section: Granularity Timing and Breadth Of The Delay Informationmentioning

confidence: 99%

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Sharing delay information in service systems: a literature survey

Ibrahim

2018

Queueing Syst

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“…This paper is concerned about the impact of time varying arrival rates and delayed information on the queue length process. Thus, it is mostly related to the work by Armony and Maglaras [3], Guo and Zipkin [9], Hassin [11], Armony et al [4], Guo and Zipkin [10], Jouini et al [20,21], Allon and Bassamboo [1], Allon et al [2], Ibrahim et al [18], Whitt [31], Armony et al [5], Dong et al [6].…”

Section: Introductionmentioning

confidence: 99%

An analysis of queues with delayed information and time-varying arrival rates

2018

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Understanding how delayed information impacts queueing systems is an important area of research. However, much of the current literature neglects one important feature of many queueing systems, namely non-stationary arrivals. Non-stationary arrivals model the fact that customers tend to access services during certain times of the day and not at a constant rate. In this paper, we analyze two two-dimensional deterministic fluid models that incorporate customer choice behavior based on delayed queue length information with time varying arrivals. In the first model, customers receive queue length information that is delayed by a constant ∆. In the second model, customers receive information about the queue length through a moving average of the queue length where the moving average window is ∆. We analyze the impact of the time varying arrival rate and show using asymptotic analysis that the time varying arrival rate does not impact the critical delay unless the frequency of the time varying arrival 1 arXiv:1701.05443v1 [math.DS]

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“…Because of this, physicians get so overwhelmed with the large number of patients' requiring service [7]. However, recent works that examined the factors leading to delays suggests otherwise [8][9]. In many cases, delays are not a resource problem; they are a flow problem.…”

Section: Introductionmentioning

confidence: 99%