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Impact of Energy and Carbon Emission of a Supply Chain Management with Two-Level Trade-Credit Policy

Author

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  • Vandana

    (Department of Mathematics, Inderprastha Engg. College, Ghaziabad 201010, India)

  • S. R. Singh

    (Department of Mathematics, Chaudhary Charan Singh University, Meerut 250001, India)

  • Dharmendra Yadav

    (Department of Mathematics, Vardhaman College, MJP Rohilkhand University, Uttar Pradesh 246701, India)

  • Biswajit Sarkar

    (Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Sinchon-dong, Seodaemun-gu, Seoul 03722, Korea)

  • Mitali Sarkar

    (Information Technology Research Center, Chung-Ang University, Seoul 06974, Korea)

Abstract

Supply chain management aims to integrate environmental thinking with efficient energy consumption into supply chain management. It includes a flexible manufacturing process, more product delivery to customers, optimum energy consumption, and reduced waste. The manufacturing process can be made more flexible through volume agility. In this scenario, production cannot be constant, and with the concept of volume agility, production is taken as a decision variable under the effect of optimum energy consumption. Considering a two-echelon supply chain, we consider a producer and supplier with two-level-trade-credit policies (TLTCP) with the optimum consumption. To reduce the integrated total inventory cost, we believe that demand is a function of the credit period and selling price. The cost function is analyzed, either with the credit period dependent demand rate or with the selling price dependent demand rate through the numerical examples under energy costs. Energy and carbon emission costs are introduced in setup/ordering cost, holding cost, and item cost for producer and supplier. The effect of inflation on the total cost cannot be ignored; this model is being developed for deteriorating items with the simultaneous impact of volume agility, energy, carbon emission cost, and two-level-trade-credit policies with inflation. This supply chain model was solved analytically and obtained the optimum decision variables in a quasi-closed form solution. An illustrative theorem is being utilized to analyze the optimum result for all the decision parameters. The convexity of the objective function is being obtained analytically as well as graphically. Finally, numerical examples and sensitivity analysis are employed to illustrate the present study and with managerial insights.

Suggested Citation

  • Vandana & S. R. Singh & Dharmendra Yadav & Biswajit Sarkar & Mitali Sarkar, 2021. "Impact of Energy and Carbon Emission of a Supply Chain Management with Two-Level Trade-Credit Policy," Energies, MDPI, vol. 14(6), pages 1-19, March.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:6:p:1569-:d:515602
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    References listed on IDEAS

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    1. Jaggi, Chandra K. & Goyal, S.K. & Goel, S.K., 2008. "Retailer's optimal replenishment decisions with credit-linked demand under permissible delay in payments," European Journal of Operational Research, Elsevier, vol. 190(1), pages 130-135, October.
    2. Kun-Jen Chung, 2013. "The EPQ model under conditions of two levels of trade credit and limited storage capacity in supply chain management," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(9), pages 1675-1691.
    3. Himani Dem & S.R. Singh, 2015. "Joint replenishment modelling of a multi-item system with greening policy and volume flexibility," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 22(2), pages 148-166.
    4. Dharmendra Yadav & S.R. Singh & Rachna Kumari, 2015. "Retailer's optimal policy under inflation in fuzzy environment with trade credit," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(4), pages 754-762, March.
    5. Cárdenas-Barrón, Leopoldo Eduardo & Sana, Shib Sankar, 2014. "A production-inventory model for a two-echelon supply chain when demand is dependent on sales teams׳ initiatives," International Journal of Production Economics, Elsevier, vol. 155(C), pages 249-258.
    6. Khanra, S. & Mandal, Buddhadev & Sarkar, Biswajit, 2013. "An inventory model with time dependent demand and shortages under trade credit policy," Economic Modelling, Elsevier, vol. 35(C), pages 349-355.
    7. Biswajit Sarkar & Sharmila Saren & Leopoldo Cárdenas-Barrón, 2015. "An inventory model with trade-credit policy and variable deterioration for fixed lifetime products," Annals of Operations Research, Springer, vol. 229(1), pages 677-702, June.
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