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Production-inventory models considering different carbon policies: a review

Author

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  • Arindam Ghosh
  • J.K. Jha
  • S.P. Sarmah

Abstract

Mitigating carbon emissions in supply chains has become an important issue in the recent era. Recently, companies are looking for solutions to lessen carbon emissions associated with their supply chains mainly due to carbon policies imposed by different regulatory bodies. Apart from regulations, competitive advantage, ISO certification, customer satisfaction also influence organisations to adopt green practices in their supply chains. Production and inventory are two important aspects of supply chains, and they contribute to a significant amount of cost and emissions. Organisations try to optimise their production and inventory related activities with operational adjustments while operating under different carbon policies. Over the last couple of years, authors have incorporated different carbon policies while optimising supply chains, especially production-inventory policies. This paper presents a review of quantitative models on green production-inventory problems considering different carbon policies and ends with suggestions for future research.

Suggested Citation

  • Arindam Ghosh & J.K. Jha & S.P. Sarmah, 2020. "Production-inventory models considering different carbon policies: a review," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 30(1), pages 1-27.
    • Handle: RePEc:ids:ijpqma:v:30:y:2020:i:1:p:1-27
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    Citations

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    Cited by:

    1. Katherinne Salas-Navarro & Paula Serrano-Pájaro & Holman Ospina-Mateus & Ronald Zamora-Musa, 2022. "Inventory Models in a Sustainable Supply Chain: A Bibliometric Analysis," Sustainability, MDPI, vol. 14(10), pages 1-21, May.
    2. Leyla Aliabadi & Seyed Hessameddin Zegordi & Ali Husseinzadeh Kashan & Mohammad Ali Rastegar, 2024. "A sustainable supply chain model for time-varying deteriorating items under the promotional cost-sharing policy and three-level trade credit financing," Operational Research, Springer, vol. 24(2), pages 1-59, June.

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