IDEAS home Printed from https://ideas.repec.org/a/taf/tjmaxx/v10y2023i1p38-88.html
   My bibliography  Save this article

An integrated fuzzy production inventory model for manufacturer–retailer coordination under simple carbon tax system

Author

Listed:
  • G. Durga Bhavani
  • G. S. Mahapatra
  • Akhilesh Kumar

Abstract

This paper develops twin models towards integrated production inventory planning for manufacturer–retailer ecosystem in a sustainable supply chain setup. Decision-making models are developed in fuzzy environment and under purview of carbon taxation system. Novel conception of Fermatean fuzzy numbers is introduced for handling parameters imprecision. The first model addresses planning problem without considering green investments, whereas the second one additionally identifies optimal green investments for each player of ecosystem. Models are formulated as nonlinear optimization problems with objective of maximizing profit. Comparison of results from both models enables decision-makers to figure out the profitability of green investment option. Numerical instance with data from the existing literature is solved using Mathematica 12.1. Computational results for studied case report profitability of green investments for supply chain partners and significant reduction in carbon emissions as well. Variation analysis demonstrates stability of the proposed model. Developed models equip small-scale retailer-manufacture tie-ups prevalent in developing economies for discussed decisions.

Suggested Citation

  • G. Durga Bhavani & G. S. Mahapatra & Akhilesh Kumar, 2023. "An integrated fuzzy production inventory model for manufacturer–retailer coordination under simple carbon tax system," Journal of Management Analytics, Taylor & Francis Journals, vol. 10(1), pages 38-88, January.
    • Handle: RePEc:taf:tjmaxx:v:10:y:2023:i:1:p:38-88
    DOI: 10.1080/23270012.2023.2179432
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23270012.2023.2179432
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/23270012.2023.2179432?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:taf:tjmaxx:v:10:y:2023:i:1:p:38-88. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjma .

    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.