A Sustainable Vendor–Buyer Supply Chain Framework Integrating Energy Storage Systems and Green Investments with Incentive Policies under Demand Uncertainty
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2026.17.2.14Keywords:
Carbon emission, Fuzzy environment, Varying demand, Energy storage systems, Green technology, Green incentivesDimensions Badge
Issue
Section
License
Copyright (c) 2026 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This research evaluates the effects of integrating energy storage systems into supply chains comprising a vendor and a buyer governed by carbon tax regulations and augmented by green incentives, with an emphasis on promoting sustainability, lowering expenses, and preserving operational efficiency. In this study, a non-linear sustainable supply chain model is developed by incorporating an energy storage system and accounting for carbon emissions from various stages of the supply chain to reflect real-world complexities. In practice, carbon emissions are regulated by a carbon tax policy. Green technology investment is also incorporated to reduce carbon emissions in the supply chain. Besides lowering emissions, such investments can also reduce the energy required in the production process. To support these investments, the government provides green incentives, the amount of which is determined based on the achievement of emission reduction targets. The annual demand is modeled as a fuzzy variable to capture its imprecise nature. To address such uncertainties, Single-valued trapezoidal neutrosophic fuzzy parameters are employed in the model. The Lagrangian method is then applied to derive the optimal solution to the formulated problem. Finally, a numerical example and sensitivity analysis are presented to illustrate the application of the model and examine the impact of key parameters on model behaviour and performance. The proposed model was solved using the prescribed optimization method. The results indicate that the total integrated supply chain cost with investment in energy storage systems amounts to $10,054.23, whereas the cost without such investment is $11,693.77. This substantial reduction in total cost demonstrates that the implementation of energy storage systems significantly enhances the overall performance and cost-efficiency of the supply chain. The simultaneous incorporation of energy storage systems and green technology investments in a supply chain, alongside carbon taxes and green incentives under single-valued trapezoidal Neutrosophic fuzzy environments, has not yet been thoroughly investigated in the existing literature.Abstract
How to Cite
Downloads
Similar Articles
- Sabeerath K, Manikandasaran S. Sundaram, BTEDD: Block-level tokens for efficient data deduplication in public cloud infrastructures , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Deepak K. Sharma, Vandana ., Pankaj Kumar, Ambrish Pandey, Jitender Pal, Investigating physico-chemical characteristics of water and wastewater in the printing industry , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Mithun Vinayaka Kulkarni, Vijayanand M, Syed Mudassir, Said Bakhit Ali Bakhit Tabook, Mohammed Hassan Abdullah Al-Hafeedh, An overview of wastepaper and carton recycling in Oman , The Scientific Temper: Vol. 16 No. Spl-2 (2025): The Scientific Temper
- Vinodini R, Ritha W, Sasitharan Nagapan, An inventory model on the impact of green investment with deteriorating items and planned back orders for economic efficiency and environmental sustainability , The Scientific Temper: Vol. 16 No. 08 (2025): The Scientific Temper
- Neeraj, Anita Singhrova, A critical review of blockchain-based authentication techniques , The Scientific Temper: Vol. 16 No. 04 (2025): The Scientific Temper
- P. John Robinson, P. Susai Alexander, Neural net influenced magdm problem with modified choquet integral aggregation operators and correlation coefficient for triangular fuzzy intuitionistic fuzzy sets , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- P. Janavarthini, Dr. I. Antonitte Vinoline, Green inventory model for growing items with constraints under demand uncertainty , The Scientific Temper: Vol. 16 No. 01 (2025): The Scientific Temper
- Pooja Soni, Vikramaditya Dave, Sujit Kumar, Hemani Paliwal, A comparative study of AI-driven techno-economic analysis for grid-tied solar PV-fuel cell hybrid power systems , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Aman Bora, Akhilesh Dwivedi, From Protectionism to Green Multilateralism: Trade Diplomacy and Environmental Accountability in the Global South , The Scientific Temper: Vol. 16 No. 10 (2025): The Scientific Temper
- B. S. E. Zoraida, J. Jasmine Christina Magdalene, Smart grid precision: Evaluating machine learning models for forecasting of energy consumption from a smart grid , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- U. Johns Praveena, J. Merline Vinotha, The multi-objective solid transshipment problem with preservation technology under fuzzy environment , The Scientific Temper: Vol. 16 No. 01 (2025): The Scientific Temper
- U. Johns Praveena, J. Merline Vinotha, A New Approach for Solving Bilevel Fractional/quadratic Green Transportation Problem by Implementing AI with Multi Choice Parameters Under Uncertainty , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
- M. Monika, J. Merline Vinotha, A Fuzzy Supply Chain Model Evaluating Energy Management Systems under Imperfect Production and Uncertain Costs , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
- U. Johns Praveena, J. Merline Vinotha, Multi-objective Solid Green Trans-shipment Problem for Cold Chain Logistics under Fuzzy Environment , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
- M. Monika, J. Merline Vinotha, A resilient supply chain model integrating demand variability and carbon emissions in imperfect production systems , The Scientific Temper: Vol. 16 No. 08 (2025): The Scientific Temper
- M. Monika, J. Merline Vinotha, Optimization of a Lean Vendor–Buyer Supply Chain Model under Neutrosophic Fuzzy Environment with Transportation, Loading, and Unloading Considerations , The Scientific Temper: Vol. 16 No. 10 (2025): The Scientific Temper
- U. Johns Praveena, J. Merline Vinotha, Bilevel Fractional/Quadratic Green Transshipment Problem by Implementing AI traffic control system with Multi Choice Parameters Under Fuzzy Environment , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper

