An EOQ Model for Deteriorating items with Time and Advertisement dependent demand under the Effect of Learning and Inflation
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ID: 310643
2025
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Abstract
This paper proposes a comprehensive sustainable inventory model tailored for deteriorating items, incorporating multifaceted dynamics such as time, price, and advertisement dependent demand. Amidst the global imperative for sustainability, the model integrates key factors including learning, preservation technology adoption, and the application of carbon cap and trade policy to mitigate carbon emissions. The model is designed to optimize inventory decisions while concurrently addressing environmental concerns and economic viability. By considering the perishable nature of items, demand fluctuations influenced by time, price and advertising effectiveness are incorporated to enhance accuracy in demand forecasting. Preservation technology adoption is integrated as a critical component, offering avenues to extend the shelf life of products and reduce waste. The implementation of carbon cap and trade policy provides a mechanism to internalize environmental costs and incentivize carbon emission reductions within the inventory management framework. Through this policy instrument, firms can strategically allocate emissions allowances, fostering sustainability while maintaining operational efficiency. The proposed model contributes to the sustainability discourse by offering a holistic approach to inventory manage that balances economic objectives with environmental stewardship. Empirical validation and sensitivity analyses demonstrate the efficacy and robustness of the model under various scenarios, highlighting its potential applicability across diverse industries facing similar challenges in managing deteriorating items within a sustainable framework.
| Reference Key |
imported_1768940224_696fe2c05af50
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| Authors | Mukta Vats |
| Journal | International Journal of Science and Social Science Research |
| Year | 2025 |
| DOI |
10.5281/zenodo.16579440
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| URL | |
| Keywords | Keywords not found |
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