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The Usage of Opportunity Cost to Maximize Performance in Revenue Management *
Author(s) -
Deng Honghui,
Wang Qiwen,
Leong G. Keong,
Sun Sherry X.
Publication year - 2008
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.2008.00210.x
Subject(s) - revenue management , revenue , revenue model , revenue assurance , yield management , order (exchange) , capacity management , computer science , heuristic , service (business) , operations research , marginal revenue , business , microeconomics , industrial organization , economics , marketing , finance , engineering , computer network , artificial intelligence
To meet customer requirements efficiently, a manager needs to supply adequate quantities of products, capacity, or services at the right time with the right prices. Revenue management (RM) techniques can help firms use differential pricing strategies and capacity allocation tactics to maximize revenue. In this article, we propose a marginal revenue‐based capacity management (MRBCM) model to manage stochastic demand in order to create improved revenue opportunities. The new heuristic employs opportunity cost estimation logic that is unique and is the reason for the increased performance. The MRBCM model generates order acceptance policies that allocate available capacity to higher revenue generating market segments in both service and manufacturing environments. To evaluate these models, we design and conduct simulation experiments for 64 scenarios using a wide range of operating conditions. The experimental results show that the MRBCM model generates significantly higher revenues over the first come, first served rule when capacity is tight. In addition, we also show that the MRBCM model generally performs better than a recent RM model published in the literature.