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The Usage of Opportunity Cost to Maximize Performance in Revenue Management
ABSTRACT 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 maxim...
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Published in: | Decision sciences 2008-11, Vol.39 (4), p.737-758 |
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container_title | Decision sciences |
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creator | Deng, Honghui Wang, Qiwen Leong, G. Keong Sun, Sherry X. |
description | ABSTRACT
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. |
doi_str_mv | 10.1111/j.1540-5915.2008.00210.x |
format | article |
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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.</description><identifier>ISSN: 0011-7315</identifier><identifier>EISSN: 1540-5915</identifier><identifier>DOI: 10.1111/j.1540-5915.2008.00210.x</identifier><identifier>CODEN: DESCDQ</identifier><language>eng</language><publisher>Malden, USA: Blackwell Publishing Inc</publisher><subject>and Stochastic Demand ; Capacity Allocation ; Cost estimates ; Decision making ; Heuristic ; Heuristics ; Management ; Opportunity Cost ; Opportunity costs ; Pricing ; Revenue ; Revenue Management ; Simulation ; Stochastic models ; Stochastic processes ; Studies</subject><ispartof>Decision sciences, 2008-11, Vol.39 (4), p.737-758</ispartof><rights>2008, The Author Journal compilation © 2008, Decision Sciences Institute</rights><rights>Copyright American Institute for Decision Sciences Nov 2008</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4940-9c8ed56f921d321a9721a65c78921a1fd0fa220e0d66c8a5155c07bf6a78aa413</citedby><cites>FETCH-LOGICAL-c4940-9c8ed56f921d321a9721a65c78921a1fd0fa220e0d66c8a5155c07bf6a78aa413</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904,33202,33203</link.rule.ids></links><search><creatorcontrib>Deng, Honghui</creatorcontrib><creatorcontrib>Wang, Qiwen</creatorcontrib><creatorcontrib>Leong, G. Keong</creatorcontrib><creatorcontrib>Sun, Sherry X.</creatorcontrib><title>The Usage of Opportunity Cost to Maximize Performance in Revenue Management</title><title>Decision sciences</title><description>ABSTRACT
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. 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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.</abstract><cop>Malden, USA</cop><pub>Blackwell Publishing Inc</pub><doi>10.1111/j.1540-5915.2008.00210.x</doi><tpages>22</tpages></addata></record> |
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source | International Bibliography of the Social Sciences (IBSS); Business Source Ultimate; Wiley-Blackwell Read & Publish Collection |
subjects | and Stochastic Demand Capacity Allocation Cost estimates Decision making Heuristic Heuristics Management Opportunity Cost Opportunity costs Pricing Revenue Revenue Management Simulation Stochastic models Stochastic processes Studies |
title | The Usage of Opportunity Cost to Maximize Performance in Revenue Management |
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