IDEAS home Printed from https://ideas.repec.org/a/spr/opsear/v58y2021i1d10.1007_s12597-020-00474-5.html
   My bibliography  Save this article

An inventory model under price and stock dependent demand for controllable deterioration rate with shortages and preservation technology investment: revisited

Author

Listed:
  • Priyamvada

    (University of Delhi)

  • Rini

    (University of Delhi)

  • Aditi Khanna

    (University of Delhi)

  • Chandra K. Jaggi

    (University of Delhi)

Abstract

Mishra et al. (Ann Oper Res 254(1–2):165–190, 2017) proposed an EOQ model for a deteriorating seasonal product where demand was considered as a function of stock and selling price. Their model practiced preservation technology in order to control the deterioration rate. Further, shortages were allowed and two different scenarios, complete backordering and partial backordering were dealt with in individual cases. The model jointly optimized selling price, ordering frequency and investment in preservation technology under a profit maximization scenario. The problem they investigated depicts a practical real-life scenario, but the mathematical modelling is incorrect. Thus, the numerical results, special cases and managerial insights are debatable. Realizing the significant contribution of the model in question to the existing literature, we revisit the model to provide a corrected comprehensive version. The present model’s optimality has been proved mathematically. Further, the model has been validated using numerical analysis. Sensitivity analysis has been performed to test the robustness of the model.

Suggested Citation

  • Priyamvada & Rini & Aditi Khanna & Chandra K. Jaggi, 2021. "An inventory model under price and stock dependent demand for controllable deterioration rate with shortages and preservation technology investment: revisited," OPSEARCH, Springer;Operational Research Society of India, vol. 58(1), pages 181-202, March.
    • Handle: RePEc:spr:opsear:v:58:y:2021:i:1:d:10.1007_s12597-020-00474-5
    DOI: 10.1007/s12597-020-00474-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12597-020-00474-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12597-020-00474-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Umakanta Mishra & Leopoldo Eduardo Cárdenas-Barrón & Sunil Tiwari & Ali Akbar Shaikh & Gerardo Treviño-Garza, 2017. "An inventory model under price and stock dependent demand for controllable deterioration rate with shortages and preservation technology investment," Annals of Operations Research, Springer, vol. 254(1), pages 165-190, July.
    2. Dye, Chung-Yuan & Hsieh, Tsu-Pang, 2012. "An optimal replenishment policy for deteriorating items with effective investment in preservation technology," European Journal of Operational Research, Elsevier, vol. 218(1), pages 106-112.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mrudul Y. Jani & Heta A. Patel & Amrita Bhadoriya & Urmila Chaudhari & Mohamed Abbas & Malak S. Alqahtani, 2023. "Deterioration Control Decision Support System for the Retailer during Availability of Trade Credit and Shortages," Mathematics, MDPI, vol. 11(3), pages 1-27, January.
    2. Jiaguo Liu & Huida Zhao & Yibing Lyu & Xiaohang Yue, 2023. "The provision strategy of blockchain service under the supply chain with downstream competition," Annals of Operations Research, Springer, vol. 327(1), pages 375-400, August.
    3. Md Sadikur Rahman & Subhajit Das & Amalesh Kumar Manna & Ali Akbar Shaikh & Asoke Kumar Bhunia & Leopoldo Eduardo Cárdenas-Barrón & Gerardo Treviño-Garza & Armando Céspedes-Mota, 2021. "A Mathematical Model of the Production Inventory Problem for Mixing Liquid Considering Preservation Facility," Mathematics, MDPI, vol. 9(24), pages 1-19, December.
    4. Cynthia Griselle De-la-Cruz-Márquez & Leopoldo Eduardo Cárdenas-Barrón & J. David Porter & Imelda de Jesús Loera-Hernández & Neale R. Smith & Armando Céspedes-Mota & Gerardo Treviño-Garza & Rafael Ern, 2023. "An Inventory Model for Growing Items When the Demand Is Price Sensitive with Imperfect Quality, Inspection Errors, Carbon Emissions, and Planned Backorders," Mathematics, MDPI, vol. 11(21), pages 1-45, October.
    5. Amisha Patel & Isha Talati & Ankit D. Oza & Dumitru Doru Burduhos-Nergis & Diana Petronela Burduhos-Nergis, 2022. "A Profit Maximization Inventory Model: Stock-Linked Demand Considering Salvage Value with Tolerable Deferred Payments," Mathematics, MDPI, vol. 10(20), pages 1-16, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ajoy Hatibaruah & Sumit Saha, 2023. "An inventory model for two-parameter Weibull distributed ameliorating and deteriorating items with stock and advertisement frequency dependent demand under trade credit and preservation technology," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 951-1002, June.
    2. Kartick Dey & Debajyoti Chatterjee & Subrata Saha & Ilkyeong Moon, 2019. "Dynamic versus static rebates: an investigation on price, displayed stock level, and rebate-induced demand using a hybrid bat algorithm," Annals of Operations Research, Springer, vol. 279(1), pages 187-219, August.
    3. Sebatjane, Makoena, 2022. "The impact of preservation technology investments on lot-sizing and shipment strategies in a three-echelon food supply chain involving growing and deteriorating items," Operations Research Perspectives, Elsevier, vol. 9(C).
    4. Chandra K. Jaggi & Mamta Gupta & Amrina Kausar & Sunil Tiwari, 2019. "Inventory and credit decisions for deteriorating items with displayed stock dependent demand in two-echelon supply chain using Stackelberg and Nash equilibrium solution," Annals of Operations Research, Springer, vol. 274(1), pages 309-329, March.
    5. Mohd Fahmi Bin Mad Ali & Mohd Khairol Anuar Bin Mohd Ariffin & Aidin Delgoshaei & Faizal Bin Mustapha & Eris Elianddy Bin Supeni, 2023. "A Comprehensive 3-Phase Framework for Determining the Customer’s Product Usage in a Food Supply Chain," Mathematics, MDPI, vol. 11(5), pages 1-20, February.
    6. Rabin Kumar Mallick & Kartik Patra & Shyamal Kumar Mondal, 2020. "Mixture inventory model of lost sale and back-order with stochastic lead time demand on permissible delay in payments," Annals of Operations Research, Springer, vol. 292(1), pages 341-369, September.
    7. Saha, Subrata & Chatterjee, Debajyoti & Sarkar, Biswajit, 2021. "The ramification of dynamic investment on the promotion and preservation technology for inventory management through a modified flower pollination algorithm," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    8. Wang, Wan-Chih & Teng, Jinn-Tsair & Lou, Kuo-Ren, 2014. "Seller’s optimal credit period and cycle time in a supply chain for deteriorating items with maximum lifetime," European Journal of Operational Research, Elsevier, vol. 232(2), pages 315-321.
    9. Jingci Xie & Jianjian Liu & Xin Huo & Qingchun Meng & Mengyu Chu, 2021. "Fresh Food Dual-Channel Supply Chain Considering Consumers’ Low-Carbon and Freshness Preferences," Sustainability, MDPI, vol. 13(11), pages 1-29, June.
    10. Guowei Liu & Jianxiong Zhang & Wansheng Tang, 2015. "Joint dynamic pricing and investment strategy for perishable foods with price-quality dependent demand," Annals of Operations Research, Springer, vol. 226(1), pages 397-416, March.
    11. Feng, Lin & Wang, Wan-Chih & Teng, Jinn-Tsair & Cárdenas-Barrón, Leopoldo Eduardo, 2022. "Pricing and lot-sizing decision for fresh goods when demand depends on unit price, displaying stocks and product age under generalized payments," European Journal of Operational Research, Elsevier, vol. 296(3), pages 940-952.
    12. Mohd Fahmi Bin Mad Ali & Mohd Khairol Anuar Bin Mohd Ariffin & Faizal Bin Mustapha & Eris Elianddy Bin Supeni, 2021. "An Unsupervised Machine Learning-Based Framework for Transferring Local Factories into Supply Chain Networks," Mathematics, MDPI, vol. 9(23), pages 1-31, December.
    13. Bo Yan & Jiwen Wu & Zijie Jin & Shiyou He, 2020. "Decision-making of fresh agricultural product supply chain considering the manufacturer’s fairness concerns," 4OR, Springer, vol. 18(1), pages 91-122, March.
    14. Priyamvada & Prerna Gautam & Aditi Khanna, 2021. "Sustainable production strategies for deteriorating and imperfect quality items with an investment in preservation technology," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(5), pages 910-918, October.
    15. Dye, Chung-Yuan, 2013. "The effect of preservation technology investment on a non-instantaneous deteriorating inventory model," Omega, Elsevier, vol. 41(5), pages 872-880.
    16. Mrudul Y. Jani & Manish R. Betheja & Urmila Chaudhari & Biswajit Sarkar, 2021. "Optimal Investment in Preservation Technology for Variable Demand under Trade-Credit and Shortages," Mathematics, MDPI, vol. 9(11), pages 1-12, June.
    17. Zhang, Jianxiong & Liu, Guowei & Zhang, Qiao & Bai, Zhenyu, 2015. "Coordinating a supply chain for deteriorating items with a revenue sharing and cooperative investment contract," Omega, Elsevier, vol. 56(C), pages 37-49.
    18. Naoufel Cheikhrouhou & Biswajit Sarkar & Baishakhi Ganguly & Asif Iqbal Malik & Rafael Batista & Young Hae Lee, 2018. "Optimization of sample size and order size in an inventory model with quality inspection and return of defective items," Annals of Operations Research, Springer, vol. 271(2), pages 445-467, December.
    19. Lin Feng & Konstantina Skouri & Wan-Chih Wang & Jinn-Tsair Teng, 2022. "Optimal selling price, replenishment cycle and payment time among advance, cash, and credit payments from the seller’s perspective," Annals of Operations Research, Springer, vol. 315(2), pages 791-812, August.
    20. Lin, Feng & Jia, Tao & Wu, Feng & Yang, Zhen, 2019. "Impacts of two-stage deterioration on an integrated inventory model under trade credit and variable capacity utilization," European Journal of Operational Research, Elsevier, vol. 272(1), pages 219-234.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:opsear:v:58:y:2021:i:1:d:10.1007_s12597-020-00474-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.