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Optimal deterioration control and greening level policies for perishable products under carbon tax

Treść / Zawartość
Identyfikatory
Języki publikacji
EN
Abstrakty
EN
Background: Any perishable product's demand on the market nowadays depends not only on its level of freshness, but also on how well it is protected from extraneous environments and level of greening. The rate of deterioration determines the freshness level of products, and products are protected from environmental influence by increasing their green level. Methods: This study develops a perishable inventory control method from the perspective of a retailer, in which (i) the demand rate depends on the rate of deterioration, as well as the greening level of the products. (ii) The rate of deterioration is a controllable variable, indicating the need for a new fresh quality technology (FQT) indicator. (iii) To improve the level of greening through green operations, carbon tax policy and government subsidies for green investment are employed. Results: The objectives of the study are to determine the optimal period for replenishment, an optimal greening level, and an optimal rate of deterioration simultaneously while taking into account retailers’ total cost minimization. The results of this study indicate that the retailer should make an investment in the preservation factor when the perishable product's rate of deterioration is between 0 and 1, and retailers wouldn’t need to invest in quality maintenance technology if the deterioration rate is zero. Similarly, if the rate of deterioration is 1, it’s not necessary to spend money on preservation. Increasing the greening levels results in an increased order quantity of products. Conclusions: A mathematical model is developed and validated using numerical results to reflect actual situations. To examine the reliability of the model, sensitivity analysis with regard to parameters is undertaken. Some key managerial insights are presented, and the article concludes with a discussion of the future scope of related research.
Czasopismo
Rocznik
Strony
263--279
Opis fizyczny
Bibliogr. 29 poz., rys., tab.
Twórcy
  • Shantilal Shah Engineering College, Bhavnagar, Gujarat, India
  • Vishwakarma Government Engineering College, Ahmedabad, Gujarat, India
  • Government Engineering College, Rajkot, Gujarat, India
  • L.D. College of Engineering, Ahmedabad, Gujarat, India e-mail: sandipbhatt26@gmail.com
Bibliografia
  • 1. Bakker, M., Riezebos, J., & Teunter, R. H. (2012). Review of inventory systems with deterioration since 2001. European Journal of Operational Research, 221(2), 275–284. https://doi.org/10.1016/j.ejor.2012.03.004
  • 2. Barman, H., Pervin, M., & Roy, S. K. (2022). Impacts of green and preservation technology investments on a sustainable EPQ model during COVID-19 pandemic. RAIRO-Operations Research, 56(4), 2245–2275. https://doi.org/10.1051/ro/2022102
  • 3. Cai, X., Chen, J., Xiao, Y., & Xu, X. (2010). Optimization and coordination of fresh product supply chains with freshness keeping effort. Production and Operations Management, 19(3), 261–278. https://doi.org/10.1111/j.1937-5956.2009.01096.x
  • 4. Covert, R. P., & Philip, G. C. (1973). An EOQ model for items with Weibull distribution deterioration. AIIE Transactions, 5(4), 323–326. https://doi.org/10.1080/05695557308974918
  • 5. Dye, C.-Y., & Hsieh, T.-P. (2012). An optimal replenishment policy for deteriorating items with effective investment in preservation technology. European Journal of Operational Research, 218(1), 106–112. https://doi.org/10.1016/j.ejor.2011.10.016
  • 6. Ghare, P., & Schrader, G. (1963). An inventory model for exponentially deteriorating items. Journal of Industrial Engineering, 14(2), 238–243.
  • 7. Ghosh, D., & Shah, J. (2015). Supply chain analysis under green sensitive consumer demand and cost sharing contract. International Journal of Production Economics, 164, 319–329. https://doi.org/10.1016/j.ijpe.2014.11.005
  • 8. Goyal, S. K., & Giri, B. C. (2001). Recent trends in modeling of deteriorating inventory. European Journal of Operational Research, 134(1), 1–16. https://doi.org/10.1016/S0377-2217(00)00248-4
  • 9. Hsu, P., Wee, H., & Teng, H. (2010). Preservation technology investment for deteriorating inventory. International Journal of Production Economics, 124(2), 388–394. https://doi.org/10.1016/j.ijpe.2009.11.034
  • 10. Jamali, M.-B., & Rasti-Barzoki, M. (2018). A game theoretic approach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channel supply chains. Journal of Cleaner Production, 170, 1029–1043. https://doi.org/10.1016/j.jclepro.2017.09.181
  • 11. Jani, M. Y., Patel, H. A., Bhadoriya, A., Chaudhari, U., Abbas, M., & Alqahtani, M. S. (2023). Deterioration control decision support system for the retailer during availability of trade credit and shortages. Mathematics, 11(3), 580. https://doi.org/10.3390/math11030580
  • 12. Janssen, L., Claus, T., & Sauer, J. (2016). Literature review of deteriorating inventory models by key topics from 2012 to 2015. International Journal of Production Economics, 182, 86–112. https://doi.org/10.1016/j.ijpe.2016.08.019
  • 13. Li, B., Zhu, M., Jiang, Y., & Li, Z. (2016). Pricing policies of a competitive dual-channel green supply chain. Journal of Cleaner Production, 112, 2029–2042. https://doi.org/10.1016/j.jclepro.2015.05.017
  • 14. Li, R., Lan, H., & Mawhinney, J. R. (2010). A review on deteriorating inventory study. Journal of Service Science and Management, 3(01), 117. https://doi.org/10.4236/jssm.2010.31015
  • 15. Lin, T.-Y., & Sarker, B. R. (2017). A pull system inventory model with carbon tax policies and imperfect quality items. Applied Mathematical Modelling, 50, 450–462. https://doi.org/10.1016/j.apm.2017.06.001
  • 16. Mashud, A. H. M., Pervin, M., Mishra, U., Daryanto, Y., Tseng, M.-L., & Lim, M. K. (2021). A sustainable inventory model with controllable carbon emissions in green-warehouse farms. Journal of Cleaner Production,298,126777. https://doi.org/10.1016/j.jclepro.2021.126777
  • 17. Panja, S., & Mondal, S. K. (2020). Exploring a two-layer green supply chain game theoretic model with credit linked demand and mark-up under revenue sharing contract. Journal of Cleaner Production, 250,119491. https://doi.org/10.1016/j.jclepro.2019.119491
  • 18. Paul, A., Pervin, M., Pinto, R. V., Roy, S. K., Maculan, N., & Weber, G. W. (2023). Effects of multiple prepayments and green investment on an EPQ model. Journal of Industrial and Management Optimization, 19(9),6688–6704. https://doi.org/10.3934/jimo.2022234
  • 19. Paul, A., Pervin, M., Roy, S. K., Maculan, N., & Weber, G.-W. (2022). A green inventory model with the effect of carbon taxation. Annals of Operations Research, 309(1), 233–248. https://doi.org/10.1007/s10479-021-04143-8
  • 20. Raafat, F. (1991). Survey of literature on continuously deteriorating inventory models. Journal of the Operational Research Society, 42, 27–37. https://doi.org/10.1057/jors.1991.4
  • 21. Saha, S., Nielsen, I., & Moon, I. (2017). Optimal retailer investments in green operations and preservation technology for deteriorating items. Journal of Cleaner Production,140,1514–1527. https://doi.org/10.1016/j.jclepro.2016.09.229
  • 22. Shah, N. H., & Shah, Y. (2000). Literature survey on inventory models for deteriorating items. 44(-), 221-237. SID. https://sid.ir/paper/622914/en
  • 23. Tadikamalla, P. R. (1978). An EOQ inventory model for items with gamma distributed deterioration. AIIE Transactions, 10(1), 100–103. https://doi.org/10.1080/05695557808975189
  • 24. Tsao, Y.-C. (2016). Designing a supply chain network for deteriorating inventory under preservation effort and trade credits. International Journal of Production Research, 54(13), 3837–3851. https://doi.org/10.1080/00207543.2016.1157272
  • 25. Xu, G., Wu, H., Liu, Y., Wu, C.-H., & Tsai, S.-B. (2020). A research on fresh-keeping strategies for fresh agricultural products from the perspective of green transportation. Discrete Dynamics in Nature and Society, 2020, 1–12. https://doi.org/10.1155/2020/1307170
  • 26. Yang, Y., Chi, H., Zhou, W., Fan, T., & Piramuthu, S. (2020). Deterioration control decision support for perishable inventory management. Decision Support Systems, 134,113308. https://doi.org/10.1016/j.dss.2020.113308
  • 27. Yu, C., Qu, Z., Archibald, T. W., & Luan, Z. (2020). An inventory model of a deteriorating product considering carbon emissions. Computers & Industrial Engineering, 148, 106694. https://doi.org/10.1016/j.cie.2020.106694
  • 28. Zand, F., Yaghoubi, S., & Sadjadi, S. J. (2019). Impacts of government direct limitation on pricing, greening activities and recycling management in an online to offline closed loop supply chain. Journal of Cleaner Production, 215, 1327–1340. https://doi.org/10.1016/j.jclepro.2019.01.067
  • 29. Zhang, C.-T., & Liu, L.-P. (2013). Research on coordination mechanism in three-level green supply chain under non-cooperative game. Applied Mathematical Modelling, 37(5), 3369–3379. https://doi.org/10.1016/j.apm.2012.08.006
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
Identyfikator YADDA
bwmeta1.element.baztech-9d20967d-c7e2-4cf2-aaef-50e73161bd54