A Stackelberg-based repurchase strategy for rail freight options (BRFO)
This study presents a novel Buyback Rail Freight Option (BRFO), leveraging Stackelberg game theory to enhance the strategic management of rail freight transactions. By integrating traditional buyback theory with a multi-phase trigeminal tree pricing model and parameter identification through a nonpa...
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| Veröffentlicht in: | PloS one 2024-09, Vol.19 (9), p.e0307215 |
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| creator | Shen, Qi Kuang, Tingyue Guo, Jingwei |
| description | This study presents a novel Buyback Rail Freight Option (BRFO), leveraging Stackelberg game theory to enhance the strategic management of rail freight transactions. By integrating traditional buyback theory with a multi-phase trigeminal tree pricing model and parameter identification through a nonparametric Ito stochastic method, the research addresses key challenges of information asymmetry and market uncertainty. The proposed methodology emphasizes dynamic pricing strategies and market adaptation, constructing a Nash equilibrium framework within railway freight pricing. The findings suggest significant strategic benefits for railway enterprises, positioning BRFO as a crucial tool for improving competitiveness in the face of alternative transport options. |
| doi_str_mv | 10.1371/journal.pone.0307215 |
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By integrating traditional buyback theory with a multi-phase trigeminal tree pricing model and parameter identification through a nonparametric Ito stochastic method, the research addresses key challenges of information asymmetry and market uncertainty. The proposed methodology emphasizes dynamic pricing strategies and market adaptation, constructing a Nash equilibrium framework within railway freight pricing. The findings suggest significant strategic benefits for railway enterprises, positioning BRFO as a crucial tool for improving competitiveness in the face of alternative transport options.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0307215</identifier><identifier>PMID: 39302950</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Bank technology ; Competitiveness ; Costs ; Customers ; Decision making ; Emissions ; Energy consumption ; Equilibrium ; Flexibility ; Freight ; Game Theory ; Greenhouse gases ; Humans ; Leadership ; Management ; Models, Economic ; Parameter estimation ; Parameter identification ; Parameter uncertainty ; Power ; Pricing ; Railroads ; Revenue sharing ; Stochastic methods ; Strategic management ; Transaction processing</subject><ispartof>PloS one, 2024-09, Vol.19 (9), p.e0307215</ispartof><rights>Copyright: © 2024 Shen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2024 Public Library of Science</rights><rights>2024 Shen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 Shen et al. 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| subjects | Bank technology Competitiveness Costs Customers Decision making Emissions Energy consumption Equilibrium Flexibility Freight Game Theory Greenhouse gases Humans Leadership Management Models, Economic Parameter estimation Parameter identification Parameter uncertainty Power Pricing Railroads Revenue sharing Stochastic methods Strategic management Transaction processing |
| title | A Stackelberg-based repurchase strategy for rail freight options (BRFO) |
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