Perishable-asset revenue management: Generic and multiple-price yield management with diversion

Bodily, Samuel E.; Weatherford, Larry

doi:10.1016/0305-0483(94)00063-g

Cited by 73 publications

(24 citation statements)

References 7 publications

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“…In what follows, we make a few brief comments about attempts to accomplish these goals. Brumelle et al (1990), Bodily and Weatherford (1995), and Belobaba and Weatherford (1996) consider models in which a customer who requests a ticket in a particular lower-fare class may be willing to purchase a ticket in a higher-fare class if no more tickets in the lower-fare class are available. These models assume that there is exogenous demand for each fare class, while allowing that some customers may buy tickets in a different class if their preferred class is not available.…”

Section: What To Do About the Spiral-down Effectmentioning

confidence: 99%

Models of the Spiral-Down Effect in Revenue Management

Cooper

Homem-de-Mello

Kleywegt

2006

Operations Research

160

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The spiral-down effect occurs when incorrect assumptions about customer behavior cause high-fare ticket sales, protection levels, and revenues to systematically decrease over time. If an airline decides how many seats to protect for sale at a high fare based on past high-fare sales, while neglecting to account for the fact that availability of low-fare tickets will reduce high-fare sales, then high-fare sales will decrease, resulting in lower future estimates of high-fare demand. This subsequently yields lower protection levels for high-fare tickets, greater availability of low-fare tickets, and even lower high-fare ticket sales. The pattern continues, resulting in a so-called spiral down. We develop a mathematical framework to analyze the process by which airlines forecast demand and optimize booking controls over a sequence of flights. Within the framework, we give conditions under which spiral down occurs.

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Section: What To Do About the Spiral-down Effectmentioning

confidence: 99%

Models of the Spiral-Down Effect in Revenue Management

Cooper

Homem-de-Mello

Kleywegt

2006

Operations Research

160

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“…Later by extending these techniques, it allows for passenger flexibility among fare classes. Bodily and Weatherford (1995) also consider overbooking and allow for passenger adjustments. Belobaba and Weatherford (1996) perform a comparison of various decision making rules incorporating passenger adjustments.…”

Section: Introductionmentioning

confidence: 99%

Technology revenue management system for customer groups in hotels

Martín

Cortés

Onieva

et al. 2010

Journal of Business Research

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This paper discusses revenue management; a technique that focuses on decision making that will maximize profit from the sale of perishable inventory units. New technologies management plays an important role in the development of revenue management techniques. Each new advance in technology management leads to more sophisticated revenue business capabilities. Today decision support revenue management systems and technologies management are crucial factors for the success of businesses in service industries. This paper addresses the specific case of customer groups in hotels.The paper introduces a new decision support system that sets the revenue maximization criteria for a hotel. The system includes a set of forecasting demand methods for customers. It addresses a general case considering individual guests and customer groups. The system also incorporates deterministic and stochastic mathematical programming models that help to make the best decisions. The actual revenue depends upon which reservation system the hotel uses. A simulation engine makes a comparison between different heuristics of room inventory control: the results include performance indexes such as occupancy rate, efficiency rate, and yield; it compares results and chooses one of them. The system proves its suitability for actual cases by testing against actual data and thus becomes an innovative and efficient tool in the management of hotels' reservation systems.

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“…Revenue management (RM) deals with the maximization of the revenue or benefit earned from a fixed, perishable resource in uncertain conditions [1]. While revenue management as a formal practice has its foundations in the airline industry, it has spread in the last two decades to cargo services, hotels, car rental companies, and e-commerce.…”

Section: Revenue Managementmentioning

confidence: 99%

Cargo Revenue Management for Space Logistics

Armar

Weck

2009

AIAA SPACE 2009 Conference &Amp; Exposition

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This thesis covers the development of a framework for the application of revenue management, specifically capacity control, to space logistics for use in the optimization of mission cargo allocations, which in turn affect duration, infrastructure availability, and forward logistics. Two capacity control algorithms were developed; the first is based on partitioning of Monte Carlo samples while the second is based on bid-pricing with high-frequency price adjustments. The algorithms were implemented in Java as a plugin module to SpaceNet 2.0, an existing integrated modeling and simulation tool for space logistics. The module was tested on a lunar exploration concept which emphasizes global exploration of the Moon using mobile infrastructure. Results suggest that revenue management produces better capacity allocations in shorter duration missions, while producing nominal capacity allocations (i.e. those in the deterministic case) in the long run.

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Perishable-asset revenue management: Generic and multiple-price yield management with diversion

Cited by 73 publications

References 7 publications

Models of the Spiral-Down Effect in Revenue Management

Models of the Spiral-Down Effect in Revenue Management

Technology revenue management system for customer groups in hotels

Cargo Revenue Management for Space Logistics

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