A Sustainable Retailer Inventory Model for Deteriorating Green Products with Time-Dependent Advertising and Carbon Emission Taxation

  • Authors

    • Ruba priyadharshini Department of Mathematics, The Gandhigram Rural Institute-Deemed to be University, Gandhigram, Dindigul, Tamil Nadu-624302, India
    • R Uthayakumar Department of Mathematics, The Gandhigram Rural Institute-Deemed to be University, Gandhigram, Dindigul, Tamil Nadu-624302, India
    https://doi.org/10.14419/e48n0n84

    Received date: July 31, 2025

    Accepted date: September 18, 2025

    Published date: October 2, 2025

  • Carbon emission, Deterioration, Dynamic Advertisement, Green product, Preservation technology
  • Abstract

    This study presents a sustainable inventory model tailored for a retailer managing deteriorating green products, where demand evolves and is influenced by environmental factors. The model incorporates a linearly increasing advertising schedule to reflect the impact of dynamic promotional efforts on eco-conscious consumer behavior. To curb product deterioration, the retailer can invest in preservation technologies that effectively slow the deterioration rate through a factorial reduction mechanism. The cost framework accounts for both time-sensitive reordering efforts and the diminishing returns of financial investment. Additionally, the model factors in carbon emissions from advertising activities, along with penalties for excess emissions and tax credits for adopting green technologies. The retailer aims to maximize overall profit by jointly optimizing selling price, replenishment timing, advertising intensity, and green investments. Analytical insights demonstrate that coordinated decision-making enhances profitability and reduces product obsolescence and environmental impact. The findings highlight the critical role of integrating marketing strategies with sustainability initiatives, offering a practical guide for retailers aiming to achieve economic efficiency and environmental stewardship.

  • References

    1. Bai, Y. (2024). Machine learning implementation for demand forecasting in supply chain management. Proceedings of the 13th International Con-ference on Operations Research and Enterprise Systems (ICORES 2024), 248–255.
    2. Barman, H., Pervin, M., & Roy, S. K. (2022). Impacts of green and preservation technology investments on a sustainable EPQ model during the COVID-19 pandemic. RAIRO-Operations Research, 56(4), 2245–2275.
    3. Gao, H., Tang, J. K., Gong, D., Zhao, X., & Yan, X. (2024). Optimising low-carbon inventory decisions and coordination for used clothing under the carbon tax and carbon labelling system. Ecological Chemistry and Engineering, 31(4), 507–525.
    4. Hossen, M. A. (2022). Impact of inflation and advertisement dependent demand in an inventory system. Journal of the Calcutta Mathematical So-ciety, 18(1), 69–78.
    5. Jia, M., Schrotenboer, A. H., & Chen, F. (2025). Scenario predict-then-optimize for data-driven online inventory routing. Transportation Science.
    6. Kausar, A., Hasan, A., Maheshwari, S., Gautam, P., & Jaggi, C. K. (2024). Sustainable production model with advertisement and market price de-pendent demand under salvage option for defectives. Opsearch, 61(1), 315–333.
    7. Kumar, S. (2021). An inventory model for decaying items under preservation technological effect with advertisement dependent demand and trade credit. International Journal of Applied and Computational Mathematics, 7(4), 128.
    8. Mahato, F., Choudhury, M., & Mahata, G. C. (2023). Inventory models for deteriorating items with fixed lifetime, partial backordering and carbon emissions policies. Journal of Management Analytics, 10(1), 129–190.
    9. Manna, A. K., Dey, J. K., & Mondal, S. K. (2017). Imperfect production inventory model with production rate dependent defective rate and ad-vertisement dependent demand. Computers & Industrial Engineering, 104, 9–22.
    10. Mishra, N. K. (2022). A supply chain inventory model for deteriorating products with carbon emission-dependent demand, advanced payment, carbon tax and cap policy. Mathematical Modelling of Engineering Problems, 9(3).
    11. Mohammed, A., et al. (2025). An optimized single warehouse inventory model for decaying goods with time and price dependent demand and time dependent holding cost using the ABC algorithm. International Journal of Basic and Applied Sciences, 14(2), 219–225. DOI: 10.14419/vz3h5m62
    12. Namwad, R. S., Mishra, N. K., & Sangle, S. (2024). Optimizing inventory management with seasonal demand forecasting in a fuzzy environment. Journal of Environmental Science and Engineering A, 57(4), 437–445.
    13. Palanivel, M., Vetriselvi, S., & Venkadesh, M. (2024). Green inventory strategies for perishable goods: Integrating preservation, carbon emission, demand dynamics, and payment latency. Process Integration and Optimization for Sustainability, 8(4), 1237–1258.
    14. Pervin, M. (2024). A sustainable deteriorating inventory model with backorder and controllable carbon emission by using green technology. Envi-ronment, Development and Sustainability, 1–37.
    15. Rathore, H. (2019). An inventory model with advertisement dependent demand and reliability consideration. International Journal of Applied and Computational Mathematics, 5(2), 33.
    16. Rani, N., Maheshwari, S., & Sharma, M. K. (2025). A sustainable inventory model: Integrating eco-packaging, advertising, and pricing strategies under carbon tax policies. International Journal of System Assurance Engineering and Management, 1–18.
    17. Sepehri, A., Mishra, U., Tseng, M. L., & Sarkar, B. (2021). Joint pricing and inventory model for deteriorating items with maximum lifetime and controllable carbon emissions under permissible delay in payments. Mathematics, 9(5), 470.
    18. Singh, S. R., & Zaidi, U. (2025). A sustainable supply chain model with price and advertisement dependent demand utilizing a hybrid carbon poli-cy and multi-trade credit in an inflationary environment. Discover Sustainability, 6(1), 612.
    19. Utami, D. S., Jauhari, W. A., & Rosyidi, C. N. (2020). An integrated inventory model for deteriorated and imperfect items considering carbon emissions and inflationary environment. AIP Conference Proceedings, 2217(1), 030018.
    20. Zhang, Q., Li, Y., & Wang, Z. (2024). A multi-MLP prediction for inventory management in manufacturing execution systems. Journal of Manu-facturing Systems, 72, 456–468.
  • Downloads

  • How to Cite

    priyadharshini, R. ., & Uthayakumar, R. . (2025). A Sustainable Retailer Inventory Model for Deteriorating Green Products with Time-Dependent Advertising and Carbon Emission Taxation. International Journal of Basic and Applied Sciences, 14(6), 1-11. https://doi.org/10.14419/e48n0n84