We develop an overbooking approach for airline revenue management. We estimate a revenue function by employing a statistical modeling approach, specifically a multivariate adaptive regression splines approximation of a stochastic network model. We develop an overbooking cost function using a binomial distribution to model the number of customers that show up for the flight. We implement a hybri...

Demand forecasting is one of the fundamental components a successful revenue management system. This paper provides new model, which inspired by cubic smoothing splines, resulting in smooth demand curves per rate class over time until check-in date.This model makes trade-off between error and smoothness fit, therefore able to capture natural guest behavior. The tested on hospitality data. We al...

The field of revenue management originated within the operations research community and is concerned with demand management and related pricing decisions. Pricing has not traditionally been one of the mainstream operations management (OM) concerns, but revenue management is attracting a substantial amount of OM research. While revenue management has had significant impact on the management of d...

background the non-revenue water refers to a difference between the volume of water entering the system and billed authorized consumption. objectives the main purpose of this study is to determine the volume of non-revenue water in order to recognize the factors influencing water losses so that the information gathered can used in non-revenue water reduction management. materials and methods ka...

This study examines revenue management in terms of a framework adapted from Maguire and Rouse (2004). This framework is used to analyse the way revenue management is organised at a large broadcasting organisation. The aim of this analysis is to investigate the structuring of the revenue and cost management efforts. When selling a product or service revenue and cost are usually known and hence t...