IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i3p580-d1043750.html
   My bibliography  Save this article

Deterioration Control Decision Support System for the Retailer during Availability of Trade Credit and Shortages

Author

Listed:
  • Mrudul Y. Jani

    (Department of Applied Sciences, Faculty of Engineering and Technology, Parul University, Vadodara 391760, Gujarat, India)

  • Heta A. Patel

    (Department of Mathematics, M. G. Science Institute, Gujarat University, Ahmedabad 380009, Gujarat, India)

  • Amrita Bhadoriya

    (Prestige Institute of Management and Research, Gwalior 474020, Madhya Pradesh, India)

  • Urmila Chaudhari

    (Government Polytechnic Dahod, Dahod 389151, Gujarat, India)

  • Mohamed Abbas

    (Electrical Engineering Department, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia
    Computers and Communications Department, College of Engineering, Delta University for Science and Technology, Gamasa 35712, Egypt)

  • Malak S. Alqahtani

    (Computer Engineering Department, College of Computer Science, King Khalid University, Abha 61421, Saudi Arabia)

Abstract

The deterioration rate is a significant aspect of perishable goods. Since perishable items will always deteriorate, there are effective methods for reducing the rate of deterioration. Furthermore, in the existing inventory control literature, the deterioration rate is often viewed as an exogenous component. Keeping this problem in mind, this article develops the perishable inventory control system from the retailer’s perspective in which: (i) the deterioration rate is a controllable factor and suggests a new fresh quality technology (FQT) indicator, (ii) demand is determined by the perishable product’s quality, that is controlled by its rate of deterioration, (iii) the credit duration is predefined, and (iv) shortages are expected. The key goal is to demonstrate that there is an ideal quantity of the order that minimizes the retailer’s overall cost in terms of cycle time and deterioration rate. Finally, theoretical results are validated by solving two numerical illustrations and conducting a sensitivity analysis of the main factors resulting from the following managerial implications: (i) if the range of deterioration is between zero and one then the retailer should invest in the preservation factor to preserve the perishable product and if greater than one the retailer should not invest in the preservation factor, (ii) credit period significantly reduces the total cost. Hence, this trade credit strategy is more beneficial to the model.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:3:p:580-:d:1043750
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/3/580/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/3/580/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bhunia, A.K. & Shaikh, Ali Akbar, 2015. "An application of PSO in a two-warehouse inventory model for deteriorating item under permissible delay in payment with different inventory policies," Applied Mathematics and Computation, Elsevier, vol. 256(C), pages 831-850.
    2. Ali Akbar Shaikh & Gobinda Chandra Panda & Satyajit Sahu & Ajit Kumar Das, 2019. "Economic order quantity model for deteriorating item with preservation technology in time dependent demand with partial backlogging and trade credit," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 32(1), pages 1-24.
    3. Md. Abdul Hakim & Ibrahim M. Hezam & Adel Fahad Alrasheedi & Jeonghwan Gwak, 2022. "Pricing Policy in an Inventory Model with Green Level Dependent Demand for a Deteriorating Item," Sustainability, MDPI, vol. 14(8), pages 1-16, April.
    4. Chandan Mahato & Gour Chandra Mahata, 2021. "Optimal inventory policies for deteriorating items with expiration date and dynamic demand under two-level trade credit," OPSEARCH, Springer;Operational Research Society of India, vol. 58(4), pages 994-1017, December.
    5. Biswajit Sarkar & Waqas Ahmed & Seok-Beom Choi & Muhammad Tayyab, 2018. "Sustainable Inventory Management for Environmental Impact through Partial Backordering and Multi-Trade-Credit-Period," Sustainability, MDPI, vol. 10(12), pages 1-28, December.
    6. 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.
    7. Bakker, Monique & Riezebos, Jan & Teunter, Ruud H., 2012. "Review of inventory systems with deterioration since 2001," European Journal of Operational Research, Elsevier, vol. 221(2), pages 275-284.
    8. 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.
    9. Chaitanyakumar N. Rapolu & Deepa H. Kandpal, 2020. "Joint pricing, advertisement, preservation technology investment and inventory policies for non-instantaneous deteriorating items under trade credit," OPSEARCH, Springer;Operational Research Society of India, vol. 57(2), pages 274-300, June.
    10. Anubhav Namdeo & Uttam Kumar Khedlekar & Priyanka Singh, 2020. "Discount pricing policy for deteriorating items under preservation technology cost and shortages," Journal of Management Analytics, Taylor & Francis Journals, vol. 7(4), pages 649-671, October.
    11. Taleizadeh, Ata Allah & Pentico, David W., 2013. "An economic order quantity model with a known price increase and partial backordering," European Journal of Operational Research, Elsevier, vol. 228(3), pages 516-525.
    12. Chandra K. Jaggi & Prerna Gautam & Aditi Khanna, 2018. "Inventory Decisions for Imperfect Quality Deteriorating Items with Exponential Declining Demand Under Trade Credit and Partially Backlogged Shortages," Springer Proceedings in Business and Economics, in: P.K. Kapur & Uday Kumar & Ajit Kumar Verma (ed.), Quality, IT and Business Operations, pages 213-229, Springer.
    13. Chandan Mahato & Gour Chandra Mahata, 2022. "Decaying items inventory models with partial linked-to-order upstream trade credit and downstream full trade credit," Journal of Management Analytics, Taylor & Francis Journals, vol. 9(1), pages 137-168, January.
    14. Ali Akbar Shaikh, 2017. "A two warehouse inventory model for deteriorating items with variable demand under alternative trade credit policy," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 27(1), pages 40-61.
    15. Vandana & S. R. Singh & Dharmendra Yadav & Biswajit Sarkar & Mitali Sarkar, 2021. "Impact of Energy and Carbon Emission of a Supply Chain Management with Two-Level Trade-Credit Policy," Energies, MDPI, vol. 14(6), pages 1-19, March.
    16. Guangshu Xu & Hao Wu & Yongsheng Liu & Chia-Huei Wu & Sang-Bing Tsai, 2020. "A Research on Fresh-Keeping Strategies for Fresh Agricultural Products from the Perspective of Green Transportation," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-12, February.
    17. M. Ghandehari & M. Dezhtaherian, 2019. "An EOQ model for deteriorating items with partial backlogging and financial considerations," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 32(3), pages 269-284.
    18. Fu, Ke & Wang, Ce & Xu, Jiayan, 2022. "The impact of trade credit on information sharing in a supply chain," Omega, Elsevier, vol. 110(C).
    19. Cai, Xiaoqiang & Chen, Jian & Xiao, Yongbo & Xu, Xiaolin & Yu, Gang, 2013. "Fresh-product supply chain management with logistics outsourcing," Omega, Elsevier, vol. 41(4), pages 752-765.
    20. Tiwari, Sunil & Cárdenas-Barrón, Leopoldo Eduardo & Khanna, Aditi & Jaggi, Chandra K., 2016. "Impact of trade credit and inflation on retailer's ordering policies for non-instantaneous deteriorating items in a two-warehouse environment," International Journal of Production Economics, Elsevier, vol. 176(C), pages 154-169.
    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. Alaa Fouad Momena & Rakibul Haque & Mostafijur Rahaman & Sankar Prasad Mondal, 2023. "A Two-Storage Inventory Model with Trade Credit Policy and Time-Varying Holding Cost under Quantity Discounts," Logistics, MDPI, vol. 7(4), pages 1-25, 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. Qingren He & Shuting Li & Fei Xu & Wanhua Qiu, 2022. "Deep-Processing Service and Pricing Decisions for Fresh Products with the Rate of Deterioration," Mathematics, MDPI, vol. 10(5), pages 1-19, February.
    2. Janssen, Larissa & Claus, Thorsten & Sauer, Jürgen, 2016. "Literature review of deteriorating inventory models by key topics from 2012 to 2015," International Journal of Production Economics, Elsevier, vol. 182(C), pages 86-112.
    3. Alaa Fouad Momena & Rakibul Haque & Mostafijur Rahaman & Sankar Prasad Mondal, 2023. "A Two-Storage Inventory Model with Trade Credit Policy and Time-Varying Holding Cost under Quantity Discounts," Logistics, MDPI, vol. 7(4), pages 1-25, October.
    4. Mukunda Choudhury & Sujit Kumar De & Gour Chandra Mahata, 2023. "A pollution-sensitive multistage production-inventory model for deteriorating items considering expiration date under Stackelberg game approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(10), pages 11847-11884, October.
    5. Bouchery, Yann & Ghaffari, Asma & Jemai, Zied & Tan, Tarkan, 2017. "Impact of coordination on costs and carbon emissions for a two-echelon serial economic order quantity problem," European Journal of Operational Research, Elsevier, vol. 260(2), pages 520-533.
    6. Yang, Lei & Tang, Ruihong, 2019. "Comparisons of sales modes for a fresh product supply chain with freshness-keeping effort," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 425-448.
    7. 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.
    8. Mamta Gupta & Sunil Tiwari & Chandra K. Jaggi, 2020. "Retailer’s ordering policies for time-varying deteriorating items with partial backlogging and permissible delay in payments in a two-warehouse environment," Annals of Operations Research, Springer, vol. 295(1), pages 139-161, December.
    9. 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.
    10. Lopez Alvarez, Jose A. & Buijs, Paul & Kilic, Onur A. & Vis, Iris F.A., 2020. "An inventory control policy for liquefied natural gas as a transportation fuel," Omega, Elsevier, vol. 90(C).
    11. Mohsen Lashgari & Ata Allah Taleizadeh & Abbas Ahmadi, 2016. "Partial up-stream advanced payment and partial down-stream delayed payment in a three-level supply chain," Annals of Operations Research, Springer, vol. 238(1), pages 329-354, March.
    12. Tiwari, Sunil & Jaggi, Chandra K. & Gupta, Mamta & Cárdenas-Barrón, Leopoldo Eduardo, 2018. "Optimal pricing and lot-sizing policy for supply chain system with deteriorating items under limited storage capacity," International Journal of Production Economics, Elsevier, vol. 200(C), pages 278-290.
    13. Lianmin Zhang & Lei Guan & Yong-Hong Kuo & Houcai Shen, 2019. "Push or Pull? Perishable Products with Freshness-Keeping Effort," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(01), pages 1-29, February.
    14. Dominika Gajdosikova & Katarina Valaskova & Tomas Kliestik & Veronika Machova, 2022. "COVID-19 Pandemic and Its Impact on Challenges in the Construction Sector: A Case Study of Slovak Enterprises," Mathematics, MDPI, vol. 10(17), pages 1-20, September.
    15. Chaitanyakumar N. Rapolu & Deepa H. Kandpal, 2020. "Joint pricing, advertisement, preservation technology investment and inventory policies for non-instantaneous deteriorating items under trade credit," OPSEARCH, Springer;Operational Research Society of India, vol. 57(2), pages 274-300, June.
    16. Taleizadeh, Ata Allah, 2014. "An EOQ model with partial backordering and advance payments for an evaporating item," International Journal of Production Economics, Elsevier, vol. 155(C), pages 185-193.
    17. Sunil Tiwari & Chandra K. Jaggi & Asoke Kumar Bhunia & Ali Akbar Shaikh & Mark Goh, 2017. "Two-warehouse inventory model for non-instantaneous deteriorating items with stock-dependent demand and inflation using particle swarm optimization," Annals of Operations Research, Springer, vol. 254(1), pages 401-423, July.
    18. Li, Guiping & He, Xiuli & Zhou, Jing & Wu, Hao, 2019. "Pricing, replenishment and preservation technology investment decisions for non-instantaneous deteriorating items," Omega, Elsevier, vol. 84(C), pages 114-126.
    19. Eid Gul & Giorgio Baldinelli & Pietro Bartocci, 2022. "Energy Transition: Renewable Energy-Based Combined Heat and Power Optimization Model for Distributed Communities," Energies, MDPI, vol. 15(18), pages 1-18, September.
    20. V. Radhamani & B. Sivakumar & G. Arivarignan, 2022. "A Comparative Study on Replenishment Policies for Perishable Inventory System with Service Facility and Multiple Server Vacation," OPSEARCH, Springer;Operational Research Society of India, vol. 59(1), pages 229-265, March.

    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:gam:jmathe:v:11:y:2023:i:3:p:580-:d:1043750. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.