File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Nash game model for optimizing market strategies, configuration of platform products in a Vendor Managed Inventory (VMI) supply chain for a product family

TitleNash game model for optimizing market strategies, configuration of platform products in a Vendor Managed Inventory (VMI) supply chain for a product family
Authors
KeywordsNash game model
Supply chain management
Vendor Managed Inventory
Issue Date2010
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/ejor
Citation
European Journal Of Operational Research, 2010, v. 206 n. 2, p. 361-373 How to Cite?
AbstractThis paper discusses how a manufacturer and its retailers interact with each other to optimize their product marketing strategies, platform product configuration and inventory policies in a VMI (Vendor Managed Inventory) supply chain. The manufacturer procures raw materials from multiple suppliers to produce a family of products sold to multiple retailers. Multiple types of products are substitutable each other to end customers. The manufacturer makes its decision on raw materials' procurement, platform product configuration, product replenishment policies to retailers with VMI, price discount rate, and advertising investment to maximize its profit. Retailers in turn consider the optimal local advertising investments and retail prices to maximize their profits. This problem is modeled as a dual simultaneous non-cooperative game (as a dual Nash game) model with two sub-games. One is between the retailers serving in competing retail markets and the other is between the manufacturer and the retailers. This paper combines analytical, iterative and GA (genetic algorithm) methods to develop a game solution algorithm to find the Nash equilibrium. A numerical example is conducted to test the proposed model and algorithm, and gain managerial implications. © 2010 Elsevier B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/74274
ISSN
2023 Impact Factor: 6.0
2023 SCImago Journal Rankings: 2.321
ISI Accession Number ID
Funding AgencyGrant Number
NSFC70501027
70725001
70629002
Hong Kong University Research Committee
national outstanding young researchers (NWO) in the Netherlands451-07-017
Funding Information:

We are grateful to the Grants for national outstanding young researchers (NWO VENI#451-07-017) in the Netherlands, from NSFC (#70501027, #70725001, and #70629002.) and from Hong Kong University Research Committee for the financial supports.

References

 

DC FieldValueLanguage
dc.contributor.authorYu, Yen_HK
dc.contributor.authorHuang, GQen_HK
dc.date.accessioned2010-09-06T06:59:40Z-
dc.date.available2010-09-06T06:59:40Z-
dc.date.issued2010en_HK
dc.identifier.citationEuropean Journal Of Operational Research, 2010, v. 206 n. 2, p. 361-373en_HK
dc.identifier.issn0377-2217en_HK
dc.identifier.urihttp://hdl.handle.net/10722/74274-
dc.description.abstractThis paper discusses how a manufacturer and its retailers interact with each other to optimize their product marketing strategies, platform product configuration and inventory policies in a VMI (Vendor Managed Inventory) supply chain. The manufacturer procures raw materials from multiple suppliers to produce a family of products sold to multiple retailers. Multiple types of products are substitutable each other to end customers. The manufacturer makes its decision on raw materials' procurement, platform product configuration, product replenishment policies to retailers with VMI, price discount rate, and advertising investment to maximize its profit. Retailers in turn consider the optimal local advertising investments and retail prices to maximize their profits. This problem is modeled as a dual simultaneous non-cooperative game (as a dual Nash game) model with two sub-games. One is between the retailers serving in competing retail markets and the other is between the manufacturer and the retailers. This paper combines analytical, iterative and GA (genetic algorithm) methods to develop a game solution algorithm to find the Nash equilibrium. A numerical example is conducted to test the proposed model and algorithm, and gain managerial implications. © 2010 Elsevier B.V. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/ejoren_HK
dc.relation.ispartofEuropean Journal of Operational Researchen_HK
dc.rightsEuropean Journal of Operational Research. Copyright © Elsevier BV.en_HK
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectNash game modelen_HK
dc.subjectSupply chain managementen_HK
dc.subjectVendor Managed Inventoryen_HK
dc.titleNash game model for optimizing market strategies, configuration of platform products in a Vendor Managed Inventory (VMI) supply chain for a product familyen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0377-2217&volume=&spage=&epage=&date=2010&atitle=Nash+game+model+for+optimizing+market+strategies,+configuration+of+platform+products+in+a+vendor+managed+inventory+(VMI)+supply+chain+for+a+product+familyen_HK
dc.identifier.emailHuang, GQ:gqhuang@hkucc.hku.hken_HK
dc.identifier.authorityHuang, GQ=rp00118en_HK
dc.description.naturepostprint-
dc.identifier.doi10.1016/j.ejor.2010.02.039en_HK
dc.identifier.scopuseid_2-s2.0-77950371399en_HK
dc.identifier.hkuros169221en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77950371399&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume206en_HK
dc.identifier.issue2en_HK
dc.identifier.spage361en_HK
dc.identifier.epage373en_HK
dc.identifier.eissn1872-6860-
dc.identifier.isiWOS:000277873300009-
dc.publisher.placeNetherlandsen_HK
dc.identifier.scopusauthoridYu, Y=14822788000en_HK
dc.identifier.scopusauthoridHuang, GQ=7403425048en_HK
dc.identifier.citeulike6825931-
dc.identifier.issnl0377-2217-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats