MCDM'23 - paper no. 2
MULTICRITERIA MODELS IN REVENUE MANAGEMENT
Petr Fiala, Renata Majovská
Abstract:
Revenue management (RM) deals with selling the right product to the right customer at the right time at the right price through the right channel to maximize revenue. The innovation of RM lies in the way decisions are made. The performance of revenue management approaches can be evaluated against several criteria. Both discrete and continuous multicriteria models can be used to analyse RM. The performance pyramid is a comprehensive, fully integrated per performance system that captures multiple perspectives such as internal, financial, customer and innovation. The assessment is based on a combination of Analytic Hierarchy Process (AHP), Analytic Network Process (ANP) and Data Envelopment Analysis (DEA) approaches. Customer behaviour modelling is gaining increasing attention in revenue management. Customer choice models can be extended with more inputs and more outputs. Evaluation of alternatives can be performed using DEA based evaluation methods. The search for an efficient frontier in a DEA model can be formulated as a multiobjective linear programming problem. We propose to use an Aspiration Level Oriented Procedure (ALOP) to solve the problem.
Keywords:
revenue management, performance measurement, multiple criteria, Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), Data Envelopment Analysis (DEA), customer behavior, efficient frontier
Reference index:
Petr Fiala, Renata Majovská, (2023), MULTICRITERIA MODELS IN REVENUE MANAGEMENT, Multiple Criteria Decision Making (18), pp. 29-46
Full text:
download
This article is licensed under a Creative Commons Atribution- NonCommercial International License .