Integrated optimisation of pricing manufacturing and procurement decisions of a make-to-stock system operating in a fluctuating environment

dc.contributor.author Oktay Karabağ
dc.contributor.author Burak Gökgür
dc.date.accessioned 2025-10-06T17:49:45Z
dc.date.issued 2023
dc.description.abstract Manufacturers experience random environmental fluctuations that influence their supply and demand processes directly. To cope with these environmental fluctuations they typically utilise operational hedging strategies in terms of pricing manufacturing and procurement decisions. We focus on this challenging problem by proposing an analytical model. Specifically we study an integrated problem of procurement manufacturing and pricing strategies for a continuous-review make-to-stock system operating in a randomly fluctuating environment with exponentially distributed processing times. The environmental changes are driven by a continuous-time discrete state-space Markov chain and they directly affect the system's procurement price raw material flow rate and price-sensitive demand rate. We formulate the system as an infinite-horizon Markov decision process with a long-run average profit criterion and show that the optimal procurement and manufacturing strategies are of state-dependent threshold policies. Besides that we provide several analytical results on the optimal pricing strategies. We introduce a linear programming formulation to numerically obtain the system's optimal decisions. We particularly investigate how production rate holding cost procurement price and demand variabilities customers' price sensitivity and interaction between supply and demand processes affect the system's performance measures through an extensive numerical study. Furthermore our numerical results demonstrate the potential benefits of using dynamic pricing compared to that of static pricing. In particular the profit enhancement being achieved with dynamic pricing can reach up to 15% depending on the problem parameters. © 2023 Elsevier B.V. All rights reserved.
dc.identifier.doi 10.1080/00207543.2022.2152127
dc.identifier.issn 1366588X, 00207543
dc.identifier.issn 0020-7543
dc.identifier.issn 1366-588X
dc.identifier.uri https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144090276&doi=10.1080%2F00207543.2022.2152127&partnerID=40&md5=590b577d11776fb432d464efee1d2cbb
dc.identifier.uri https://gcris.yasar.edu.tr/handle/123456789/8592
dc.language.iso English
dc.publisher Taylor and Francis Ltd.
dc.relation.ispartof International Journal of Production Research
dc.source International Journal of Production Research
dc.subject Dynamic Programming, Linear Programming Dynamic Pricing, Manufacturing Systems, Markov Modelling, Stochastic Models, Continuous Time Systems, Costs, Investments, Linear Programming, Markov Processes, Profitability, Stochastic Models, Stochastic Systems, Dynamic Pricing, Environmental Fluctuations, Linear Programming Dynamic Pricing, Linear-programming, Make-to-stock Systems, Markov Modeling, Pricing Decision, Procurement Decisions, Procurement Strategy, Stochastic-modeling, Dynamic Programming
dc.subject Continuous time systems, Costs, Investments, Linear programming, Markov processes, Profitability, Stochastic models, Stochastic systems, Dynamic pricing, Environmental fluctuations, Linear programming dynamic pricing, Linear-programming, Make-to-stock systems, Markov modeling, Pricing decision, Procurement decisions, Procurement strategy, Stochastic-modeling, Dynamic programming
dc.title Integrated optimisation of pricing manufacturing and procurement decisions of a make-to-stock system operating in a fluctuating environment
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gdc.description.endpage 8450
gdc.description.startpage 8423
gdc.description.volume 61
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gdc.oaire.sciencefields 0209 industrial biotechnology
gdc.oaire.sciencefields 0211 other engineering and technologies
gdc.oaire.sciencefields 02 engineering and technology
gdc.openalex.collaboration International
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gdc.opencitations.count 9
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gdc.plumx.mendeley 42
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oaire.citation.endPage 8450
oaire.citation.startPage 8423
person.identifier.scopus-author-id Karabağ- Oktay (57196390808), Gökgür- Burak (55735526000)
project.funder.name We would like to acknowledge Dr. Rommert Dekker from Erasmus University Rotterdam and Dr. Barış Tan from Koç University for their valuable remarks that helped us to improve this work. We also would like to thank the associate editor and the anonymous reviewers for their valuable comments and suggestions.
publicationissue.issueNumber 24
publicationvolume.volumeNumber 61
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