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Revenue management under randomly evolving economic conditions
Author(s) -
Xia Yusen,
Yang Jian,
Zhou Tingting
Publication year - 2019
Publication title -
naval research logistics (nrl)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 68
eISSN - 1520-6750
pISSN - 0894-069X
DOI - 10.1002/nav.21635
Subject(s) - pace , randomness , revenue , value (mathematics) , revenue management , state (computer science) , dynamic pricing , process (computing) , economics , operations research , current (fluid) , markov process , microeconomics , computer science , econometrics , mathematics , finance , statistics , engineering , geodesy , algorithm , machine learning , electrical engineering , geography , operating system
We consider a dynamic pricing model in which the instantaneous rate of the demand arrival process is dependent on not only the current price charged by the concerned firm, but also the present state of the world. While reflecting the current economic condition, the state evolves in a Markovian fashion. This model represents the real‐life situation in which the sales season is relatively long compared to the fast pace at which the outside environment changes. We establish the value of being better informed on the state of the world. When reasonable monotonicity conditions are met, we show that better present economic conditions will lead to higher prices. Our computational study is partially calibrated with real data. It demonstrates that the benefit of heeding varying economic conditions is on par with the value of embracing randomness in the demand process. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 66:73–89,2019