IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/1621395.html
   My bibliography  Save this article

A Study on Supply Chain Emission Reduction Level Based on Carbon Tax and Consumers’ Low-Carbon Preferences under Stochastic Demand

Author

Listed:
  • Liang Wang
  • Tingjia Xu
  • Longhao Qin

Abstract

This article focuses on the level of supply chain emission reduction, taking into account consumers’ low-carbon preferences, stochastic market demand, and carbon tax policy. By introducing the emission reduction penalty mechanism and adopting reverse derivation method, it derives the revenue model of the retailer and the manufacturer in decentralized and centralized supply chain when the supply chain reduces emissions or is not under stochastic market demand. The research results are as follows. (i) The optimal retailer’s revenue is strictly monotonous increasing with respect to the consumers’ low-carbon preferences in the decentralized supply chain. However, in the centralized supply chain, the optimal revenue of the retailer and the manufacturer are strictly monotonously decreasing of the consumers’ low-carbon preferences respectively. (ii) The retailer’s revenue is a concave function of the order quantity, and there exists a unique order quantity that can maximize retailer’s revenue. The manufacturer’s revenue is a concave function of the wholesale price, and there exists a unique wholesale price that can maximize manufacturer’s revenue. (iii) When consumers’ low-carbon preferences are given, there is an optimal emission reduction level that maximizes the overall revenue of the supply chain. Furthermore, as the carbon tax increases, the optimal emission reduction level gradually rises. (iv) As the level of emission reduction in the supply chain increases, the range of the revenue sharing coefficient becomes larger, and it is easier for supply chain members to reach a revenue sharing contract. However, when consumers’ low-carbon preferences and carbon tax increase, the opposite is true.

Suggested Citation

  • Liang Wang & Tingjia Xu & Longhao Qin, 2019. "A Study on Supply Chain Emission Reduction Level Based on Carbon Tax and Consumers’ Low-Carbon Preferences under Stochastic Demand," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-20, May.
  • Handle: RePEc:hin:jnlmpe:1621395
    DOI: 10.1155/2019/1621395
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2019/1621395.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/MPE/2019/1621395.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2019/1621395?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sina Abbasi & Babek Erdebilli, 2023. "Green Closed-Loop Supply Chain Networks’ Response to Various Carbon Policies during COVID-19," Sustainability, MDPI, vol. 15(4), pages 1-30, February.
    2. Xiaojing Liu & Wenyi Du & Yijie Sun, 2020. "Green Supply Chain Decisions Under Different Power Structures: Wholesale Price vs. Revenue Sharing Contract," IJERPH, MDPI, vol. 17(21), pages 1-18, October.
    3. Zhi-Hua Hu & Shu-Wen Wang, 2022. "An Evolutionary Game Model Between Governments and Manufacturers Considering Carbon Taxes, Subsidies, and Consumers’ Low-Carbon Preference," Dynamic Games and Applications, Springer, vol. 12(2), pages 513-551, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:1621395. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.