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Recycling strategy of green closed-loop supply chain under urban and rural low-carbon planning

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The low-carbon ecological city aims to harmonise sustainable urban development with low-emission planning approaches. Emissions from business production processes are central to low-carbon planning. This paper explores three closed-loop supply chain recycling models - manufacturer, retailer, and third-party considering carbon trading and emission reduction technology investment. Respective Stackelberg game models are developed incorporating carbon emission reduction costs, recycling costs, carbon trading price, emission intensity, and recycling price. The influence of these variables on carbon emission reduction and profit is examined through numerical analysis. Results indicate the government’s free carbon quota does not impact perunit carbon reduction or manufacturer profit, nor optimal recycling mode selection. Under specific remanufacturing emission intensity and production cost saving conditions, carbon quota trading can substantially incentivise manufacturers to invest in emission reduction and recycling. With carbon trading and emission reduction technology investment, manufacturer recycling optimises economic and environmental benefits when remanufactured products provide high production cost savings. This fosters sustainable development supporting low-carbon planning.
Rocznik
Strony
595--615
Opis fizyczny
Bibliogr. 29 poz., rys., wykr.
Twórcy
autor
  • School of Economics and Management, Beijing Jiaotong University, China, 100044
  • School of Economics and Management, Beijing Jiaotong University, China, 100044
Bibliografia
  • [1] Zhou MX, Li X. Low-carbon production control and resource allocation optimization. Int J Simulation Modelling. 2022;21(2):352-63. DOI: 10.2507/IJSIMM21-2-CO9.
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  • [3] Rajesh K, Venkatesh, Zubair RA. A regional feature analysis based deep learning model for improved retail management using block chain. J System Manage Sci. 2023;13(2):316-29. DOI: 10.33168/JSMS.2023.0222.
  • [4] Cicea C, Lefteris T, Marinescu C, Popa ȘC, Albu CF. Applying text mining technique on innovation-development relationship: A joint research agenda. Economic Computat Economic Cybernetics Studies Res. 2021;55(1):5-21. DOI: 10.24818/18423264/55.1.21.01.
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  • [6] Gao MM, Fang SJ, Wang JL, Zhang XM, Cao YA. A dual frequency predistortion adaptive sparse signal reconstruction algorithm. Tehnički Vjesnik. 2022;29(2):580-9. DOI: 10.17559/TV-20210728035851.
  • [7] Wan YM. Amos-based risk forecast of manufacturing supply chain. Int J Simulation Modelling. 2021;20(1):181-91. DOI: 10.2507/IJSIMM20-1-CO3.
  • [8] Jeong AK. A case study of domain engineering in software product line engineering. J Logistics Informatics Service Sci. 2022;9(1):97-115. DOI: 10.33168/LISS.2022.0108.
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  • [14] Xue H, Liu YR, Li C, Gao F. Wheel weighing meter of continuous rail based on BP neural network and symmetric moving average filter. Tehnički Vjesnik. 2022;29(1):278-84. DOI: 10.17559/TV-20210824045232.
  • [15] Wu J. Fault diagnosis of IGBT single-phase bridge arm based on fuzzy logic genetic algorithm. Tehnički Vjesnik. 2022;29(2):395-400. DOI: 10.17559/TV-20210413092639.
  • [16] Lee SY. Medical information sharing applying blockchain technology. J Logistics Informatics Service Sci. 2021;8(2):65-79. DOI: 10.33168/LISS.2021.0204.
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  • [22] Xu W, Sun HY, Awaga AL, Yan Y, Cui YJ. Optimization approaches for solving production scheduling problem: a brief overview and a case study for hybrid flow shop using genetic algorithms. Adv Production Eng Manage. 2022;17(1):45-56. DOI: 10.14743/apem2022.1.420.
  • [23] Sun HY, Xu W, Yu YY, Cai GY. An intelligent mechanism for Covid-19 emergency resource coordination and follow-up response. Computat Intelligence Neurosci. 2022:2005188. DOI: 10.1155/2022/2005188.
  • [24] Jiang LH. Research on low carbon financial support strategies from the perspective of eco-environmental protection. Ecol Chem Eng S. 2021;28(4):525-39. DOI: 10.2478/eces-2021-0035.
  • [25] Li J, Gan JL. The importance of low-carbon landscape design in rural tourism landscape. Ecol Chem Eng S. 2022; 29(3):319-32. DOI: 10.2478/eces-2022-0023.
  • [26] Yang SY, Tan C. Blockchain-based collaborative management of job shop supply chain. Int J Simulation Modelling. 2022;21(2):364-74. DOI: 10.2507/IJSIMM21-2-CO10.
  • [27] Bassam AA, Rasha DH. The effect of information overload, and social media fatigue on online consumers purchasing decisions: the mediating role of technostress and information anxiety. J System Manage Sci. 2022;12(2):195-220. DOI: 10.33168/JSMS.2022.0209.
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  • [29] Lin GH, Feng WX, Yang ZP. Multi-stage green closed-loop supply chain competition model with recycler participation. Chinese J Manage Sci. 2021;29(06):136-48. DOI: 10.16381/j.cnki.issn1003-207x.2018.1773.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-16d23655-3f6f-47ca-93de-0a1f81ef84d3
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