The effects of information on a queue with balking and phase‐type service times

Guo, Pengfei; Zipkin, Paul

doi:10.1002/nav.20291

Cited by 30 publications

(17 citation statements)

References 11 publications

(10 reference statements)

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“…The complementary cumulative distribution function isḠ (i) = β T e Bi 1, where 1 denotes a column vector of 1's. It can be shown that the distribution for f (i) can still be expressed explicitly, as in [13]. We omit the detail here and give the final result: …”

Section: Discussionmentioning

confidence: 99%

Pricing Perishable Products With Compound Poisson Demands

Guo¹,

Lian²,

Wang³

2011

Prob. Eng. Inf. Sci.

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We consider the dynamic pricing problem of perishable products in a system with a constant production rate. Potential demands arrive according to a compound Poisson process, and are price-sensitive. We carry out the sample path analysis of the inventory process and by using level-crossing method, we derive its stationary distribution given a pricing function. Based on the distribution, we express the average profit function. By a stochastic comparison approach, we characterize the pricing strategy given different customers willingness-to-pay functions. Finally, we provide an approximation algorithm to calculate the optimal pricing function.

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Section: Discussionmentioning

confidence: 99%

Pricing Perishable Products With Compound Poisson Demands

Guo¹,

Lian²,

Wang³

2011

Prob. Eng. Inf. Sci.

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“…From a human psychology angle, customers do not always prefer more granular information [7,47]. For both social welfare and throughput, less granular delay information may be beneficial ( [15,16,28,29,33,45,69], etc.). Moreover, non-verifiable and non-quantifiable information may improve both the firm's profit and the expected utility of customers [5].…”

Section: A Bird's Eye View: Key Insightsmentioning

confidence: 99%

“…The main takeaway is that more information may or may not be beneficial, depending on the distribution of customer delay sensitivity. In subsequent papers, the above results are generalized to systems with phase-type service times [29], different levels of information [30], and alternative cost functions [31].…”

Section: Granularity Timing and Breadth Of The Delay Informationmentioning

confidence: 99%

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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“…From = 0.6, the maximal availability of the process, which is a production rate when all orders from customers are accepted, is set as / = 0.6. From the setting of parameters, we have max = / = 4, and by (16) the expected utility of customers becomes…”

Section: Numerical Experimentsmentioning

confidence: 99%

“…As one of the customer's utility on waiting time, the effect of delay information on the customer's satisfaction is formulated in Guo and Zipkin [15,16]. In these papers, the utility function of each customer is defined, which shows the degree of his/her satisfaction on waiting time in a queue.…”

Section: Introductionmentioning

confidence: 99%

Optimization and Customer Utilities under Dynamic Lead Time Quotation in an M/M Type Base Stock System

Nakade

Niwa

2017

Mathematical Problems in Engineering

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In a manufacturing and inventory system, information on production and order lead time helps consumers’ decision whether they receive finished products or not by considering their own impatience on waiting time. In Savaşaneril et al. (2010), the optimal dynamic lead time quotation policy in a one-stage production and inventory system with a base stock policy for maximizing the system’s profit and its properties are discussed. In this system, each arriving customer decides whether he/she enters the system based on the quoted lead time informed by the system. On the other hand, the customer’s utility may be small under the optimal quoted lead time policy because the actual lead time may be longer than the quoted lead time. We use a utility function with respect to benefit of receiving products and waiting time and propose several kinds of heuristic lead time quotation policies. These are compared with optimal policies with respect to both profits and customer’s utilities. Through numerical examples some kinds of heuristic policies have better expected utilities of customers than the optimal quoted lead time policy maximizing system’s profits.

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The effects of information on a queue with balking and phase‐type service times

Cited by 30 publications

References 11 publications

Pricing Perishable Products With Compound Poisson Demands

Pricing Perishable Products With Compound Poisson Demands

Sharing delay information in service systems: a literature survey

Optimization and Customer Utilities under Dynamic Lead Time Quotation in an M/M Type Base Stock System

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