Optimal Pricing of Priority Services

Rao, Sadineni Rama; Petersen, E. R.

doi:10.1287/opre.46.1.46

Cited by 60 publications

(32 citation statements)

References 24 publications

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“…See Nonlinear Pricing by Robert Wilson (1993) that offers an invaluable set of methodologies and insights to tariff design in the electric power industry. In the queueing context, see Rao and Peterson (1998) who demonstrate that a special form of nonlinear tariff (i.e., two-part tariff) exists to induce optimal output rates and priority assignment for a service facility.…”

Section: Introductionmentioning

confidence: 99%

On the Optimality of Fixed-up-to Tariff for Telecommunications Service

Masuda

Whang

2006

Information Systems Research

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A tariff is the total charge payable by a customer for services provided. We study the design of tariffs for a telecommunications service provider. We develop an economic model that captures the negative externalities of the network and the diversity of customers. The tariff is designed so that it reflects the expected response of different customers and the system congestion it would induce. We study a simple tariff structure in wide use by mobile phone carriers-a menu of "fixed-up-to (FUT)" plans like "fixed access fee $35 up to 300 minutes, and $0.40 per minute beyond the limit." We derive the optimal menu of FUT plans and show that such a simple FUT menu structure delivers as good performance to the monopolistic carrier as any nonlinear pricing schedule.

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Section: Introductionmentioning

confidence: 99%

On the Optimality of Fixed-up-to Tariff for Telecommunications Service

Masuda

Whang

2006

Information Systems Research

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“…Well-cited research on priority pricing in priority queues can be found in Dolan (1978), Mendelson and Whang (1990) and Rao and Petersen (1998). In these articles, the authors propose a priority pricing mechanism based on self-revelation theory so that each arriving customer is dispatched with the proper priority, and the target of the proposed priority pricing mechanism is to maximize either social welfare (Dolan, 1978;Mendelson and Whang, 1990) or the firm's profit (Rao and Petersen, 1998). In the research on priority pricing in priority queues, the firm does not guarantee the delivery dates, and customers make decisions only based on the expected leadtime.…”

Section: Background Literaturementioning

confidence: 99%

A dynamic pricing strategy for a 3PL provider with heterogeneous customers

Zhang

Nault

2015

International Journal of Production Economics

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a b s t r a c tWe study the pricing problem for a third-party-logistics (3PL) provider that provides ware-housing and transportation services. When customers arrive at the 3PL provider, they specify the delivery dates for their freight, and before the specified delivery dates, their freight is stocked in the 3PL provider's warehouse. We propose a dynamic pricing strategy (DPS) and develop a stochastic-nonlinearprogramming (SNLP) model which computes the optimal freight rates for different delivery dates incorporating the 3PL provider's current holding cost and available transportation capacity for each route. As customers are heterogeneous in their valuations and price sensitivities for delivery dates, and the distributions of the customers' delivery date preferences are unknown to the 3PL provider, we modify the standard multinomial logit (MNL) function to predict customer choices. Through a simulation experiment, we show that the proposed MNL function can be a good replacement for the mixed MNL function when the mixed MNL function is not applicable. Through simulation we also compare the proposed DPS with a static pricing strategy. We show that with our DPS both the 3PL provider and its customers are better off, and the 3PL provider has different investment incentives for increasing transportation capacity. Our results can be also applied in similar settings that feature holding costs, limited production capacity and delivery-date-sensitive customers.

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“…Queueing systems in which customers can purchase priorities have been studied in [14,10,13,2,7,12]. The bribing model for priority in queues, introduced in [12] is as follows.…”

Section: Introductionmentioning

confidence: 99%

“…Such systems are considered in [2,14,4]. Systems with multiple FIFO queues, each with its own server were considered in, among others, [9,6] and such a system with an admission price for each queue was analyzed in [8].…”

Section: Introductionmentioning

confidence: 99%

A System with a Choice of Highest-Bidder-First and FIFO Services

Bodas

Ali

Manjunath

2015

Proceedings of the 8th International Conference on Performance Evaluation Methodologies and Tools

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Service systems using a highest-bidder-first (HBF) policy have been studied in queueing literature for various applications and in economics literature to model corruption. Such systems have applications in modern problems like scheduling jobs in cloud computing scenarios or placement of ads on web pages. However, using a HBF service is like using a spot market and may not be preferred by many users. For such users, it may be good to provide a simple scheduler, e.g., a FIFO service. Further, in some situations it may even be necessary that a free service queue operates alongside a HBF queue. Motivated by such a scenario, we propose and analyze a service system with a FIFO server and a HBF server in parallel. Arriving customers are from a heterogeneous population with different valuations of their delay costs. They strategically choose between FIFO and HBF service; if HBF is chosen, they also choose the bid value to optimize an individual cost. We characterize the Wardrop equilibrium in such a system and analyze the revenue to the server. We see that when the total capacity is fixed and is shared between the FIFO and HBF servers, revenue is maximised when the FIFO capacity is non zero. However, if the FIFO server is added to an HBF server, then the revenue decreases with increasing FIFO capacity. We also discuss the case when customers are allowed to balk.

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Optimal Pricing of Priority Services

Cited by 60 publications

References 24 publications

On the Optimality of Fixed-up-to Tariff for Telecommunications Service

On the Optimality of Fixed-up-to Tariff for Telecommunications Service

A dynamic pricing strategy for a 3PL provider with heterogeneous customers

A System with a Choice of Highest-Bidder-First and FIFO Services

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