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Sustainable Supply Chain System for Defective Products with Different Carbon Emission Strategies

Author

Listed:
  • Pitchaikani Mala

    (Department of Mathematics, National Engineering College, Kovilpatti 628503, India)

  • Muthusamy Palanivel

    (Department of Mathematics, Mepco Schlenk Engineering College, Sivakasi 626005, India)

  • Siluvayan Priyan

    (Department of Information Technology & Engineering, Faculty of Mathematics, Amity University, Tashkent 100028, Uzbekistan)

  • Anuwat Jirawattanapanit

    (Department of Mathematics, Faculty of Science, Phuket Rajabhat University (PKRU), Phuket 83000, Thailand)

  • Grienggrai Rajchakit

    (Department of Mathematics, Faculty of Science, Maejo University, Chiang Mai 50290, Thailand)

  • Pramet Kaewmesri

    (Geo-Informatics and Space Technology Development Agency (GISTDA), Bangkok 10210, Thailand)

Abstract

Many nations have created ecological policies and regulations to prevent industries from emitting excessive amounts of carbon emissions into the environment. While significant progress has been achieved in the direction of sustainable growth, many nations still rely on nonrenewable energy sources. This study explores the viability of investing in green technology to achieve the optimal decisions (lot sizes, lead time, and green investment amount) in a two-echelon supply chain system by considering human error with two carbon emission strategies: carbon taxes and limited carbon emissions. It entails the inspection of every shipped lot by the buyer to identify defective products that could have resulted from the vendor’s production process. We show a constrained non-linear program and design a calculus-optimization technique to solve it. The methodology used in this research is the quantitative method, which is based on the principles of operations research, and the models are built on mathematically oriented inventory theory. The results imply that an outsized ecological carbon footprint can be reduced without compromising customer service by designing optimal inventory strategies. The findings also confirm that green investment is the greatest economical method for reducing carbon emissions and system costs.

Suggested Citation

  • Pitchaikani Mala & Muthusamy Palanivel & Siluvayan Priyan & Anuwat Jirawattanapanit & Grienggrai Rajchakit & Pramet Kaewmesri, 2022. "Sustainable Supply Chain System for Defective Products with Different Carbon Emission Strategies," Sustainability, MDPI, vol. 14(23), pages 1-22, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:16082-:d:990641
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    References listed on IDEAS

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    1. Khan, Mehmood & Jaber, Mohamad Y. & Bonney, Maurice, 2011. "An economic order quantity (EOQ) for items with imperfect quality and inspection errors," International Journal of Production Economics, Elsevier, vol. 133(1), pages 113-118, September.
    2. Yang, Wen & Pan, Yanchun & Ma, Jianhua & Yang, Tianyue & Ke, Xiao, 2020. "Effects of allowance allocation rules on green technology investment and product pricing under the cap-and-trade mechanism," Energy Policy, Elsevier, vol. 139(C).
    3. Tang, Shaolong & Wang, Wenjie & Cho, Stella & Yan, Hong, 2018. "Reducing emissions in transportation and inventory management: (R, Q) Policy with considerations of carbon reduction," European Journal of Operational Research, Elsevier, vol. 269(1), pages 327-340.
    4. Tempelmeier, Horst & Bantel, Oliver, 2015. "Integrated optimization of safety stock and transportation capacity," European Journal of Operational Research, Elsevier, vol. 247(1), pages 101-112.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Priyan, S. & Matahen, Reem & Priyanshu, Deepa & Mouqdadi, Mahera, 2024. "Environmental strategies for a healthcare system with green technology investment and pandemic effects," Innovation and Green Development, Elsevier, vol. 3(1).
    2. Hongzhi Meng & Xiaoke Zhang & Xindong Du & Kaiyuan Du, 2023. "Spatiotemporal Heterogeneity of the Characteristics and Influencing Factors of Energy-Consumption-Related Carbon Emissions in Jiangsu Province Based on DMSP-OLS and NPP-VIIRS," Land, MDPI, vol. 12(7), pages 1-17, July.
    3. Muthusamy Palanivel & Murugesan Venkadesh, 2025. "Integrated Strategies for Sustainable Production Inventory Model with Carbon Emission Reduction with Green Technology," SN Operations Research Forum, Springer, vol. 6(2), pages 1-40, June.
    4. Priyan, S. & Udayakumar, R., 2025. "Sustainable supply chain system for defective products with uncertain resources and environmental impacts," Innovation and Green Development, Elsevier, vol. 4(1).
    5. Millie Liew & June Cao, 2025. "Accounting for Carbon Emissions Through Green Supply Chain Management: A Systematic Literature Review," Business Strategy and the Environment, Wiley Blackwell, vol. 34(7), pages 8281-8304, November.
    6. Erfan Nobil & Leopoldo Eduardo Cárdenas-Barrón & Dagoberto Garza-Núñez & Gerardo Treviño-Garza & Armando Céspedes-Mota & Imelda de Jesús Loera-Hernández & Neale R. Smith & Amir Hossein Nobil, 2023. "Machine Downtime Effect on the Warm-Up Period in an Economic Production Quantity Problem," Mathematics, MDPI, vol. 11(7), pages 1-23, April.
    7. Chefi Triki & Md. Rakibul Hasan & Adel Elomri, 2025. "Solving the winner determination problem with discounted bids in transportation auctions," Annals of Operations Research, Springer, vol. 351(1), pages 35-58, August.

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