IDEAS home Printed from https://ideas.repec.org/a/spr/opsear/v57y2020i2d10.1007_s12597-019-00427-7.html
   My bibliography  Save this article

Joint pricing, advertisement, preservation technology investment and inventory policies for non-instantaneous deteriorating items under trade credit

Author

Listed:
  • Chaitanyakumar N. Rapolu

    (The Maharaja Sayajirao University of Baroda)

  • Deepa H. Kandpal

    (The Maharaja Sayajirao University of Baroda)

Abstract

To maximize profit in a competitive market environment, for retailers, it became necessary to optimize preservation, pricing, and marketing strategies together with inventory ordering policies. This study deals with the problem of optimizing price, advertisement frequency, preservation technology (PT) investment and ordering policies simultaneously for non-instantaneous deteriorating items whose deterioration rate can be reduced by investing in PT, while demand depends on both selling price and frequency of advertisement. The supplier allows some credit period to settle the account, and under this policy, three possible cases considered separately. We adopt three-parameter Weibull distribution deterioration and partial backlogs of shortages in a general framework to formulate the model. An iterative algorithm is provided to obtain the optimal solution, then the proposed model is illustrated through numerical examples. The concavity of the total profit function with respect to decision variables shown graphically. Sensitivity analysis has been conducted to investigate the impact of each parameter. PT investment and credit period are beneficial for the retailer, and also can earn more profit through advertisement. Value-added food products, such as bottled fruit juice, soft drinks, packed fruits, bread, cake, processed meat, etc., needs preservation technology and their demand depends on the price as well as marketing. Profit maximization of such items can be studied with the help of new model developed in this paper.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:opsear:v:57:y:2020:i:2:d:10.1007_s12597-019-00427-7
    DOI: 10.1007/s12597-019-00427-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12597-019-00427-7
    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/s12597-019-00427-7?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. 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.
    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. Maihami, Reza & Nakhai Kamalabadi, Isa, 2012. "Joint pricing and inventory control for non-instantaneous deteriorating items with partial backlogging and time and price dependent demand," International Journal of Production Economics, Elsevier, vol. 136(1), pages 116-122.
    4. Dye, Chung-Yuan & Yang, Chih-Te, 2016. "Optimal dynamic pricing and preservation technology investment for deteriorating products with reference price effects," Omega, Elsevier, vol. 62(C), pages 52-67.
    5. Chung-Yuan Dye & Tsu-Pang Hsieh, 2013. "A particle swarm optimization for solving lot-sizing problem with fluctuating demand and preservation technology cost under trade credit," Journal of Global Optimization, Springer, vol. 55(3), pages 655-679, March.
    6. Morris A. Cohen, 1977. "Joint pricing and ordering policy for exponentially decaying inventory with known demand," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 24(2), pages 257-268, June.
    7. Sudarshan Bardhan & Haimanti Pal & Bibhas Chandra Giri, 2019. "Optimal replenishment policy and preservation technology investment for a non-instantaneous deteriorating item with stock-dependent demand," Operational Research, Springer, vol. 19(2), pages 347-368, June.
    8. A K Pal & A K Bhunia & R N Mukherjee, 2005. "A marketing-oriented inventory model with three-component demand rate dependent on displayed stock level (DSL)," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(1), pages 113-118, January.
    9. 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.
    10. Steven Nahmias, 1982. "Perishable Inventory Theory: A Review," Operations Research, INFORMS, vol. 30(4), pages 680-708, August.
    11. Shah, Nita H & Soni, Hardik N & Patel, Kamlesh A, 2013. "Optimizing inventory and marketing policy for non-instantaneous deteriorating items with generalized type deterioration and holding cost rates," Omega, Elsevier, vol. 41(2), pages 421-430.
    12. Chung-Yuan Dye & Chih-Te Yang & Chi-Chuan Wu, 2018. "Joint dynamic pricing and preservation technology investment for an integrated supply chain with reference price effects," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(6), pages 811-824, June.
    13. 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.
    14. Hsu, P.H. & Wee, H.M. & Teng, H.M., 2010. "Preservation technology investment for deteriorating inventory," International Journal of Production Economics, Elsevier, vol. 124(2), pages 388-394, April.
    15. 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.
    16. Dye, Chung-Yuan, 2007. "Joint pricing and ordering policy for a deteriorating inventory with partial backlogging," Omega, Elsevier, vol. 35(2), pages 184-189, April.
    17. Yu-Chung Tsao, 2016. "Joint location, inventory, and preservation decisions for non-instantaneous deterioration items under delay in payments," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(3), pages 572-585, February.
    18. Goyal, S. K. & Giri, B. C., 2001. "Recent trends in modeling of deteriorating inventory," European Journal of Operational Research, Elsevier, vol. 134(1), pages 1-16, October.
    19. 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.
    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. Hailemariam Gebru & Baba Abdissa & Betelhem Addis & Sisay Alebachew & Abaysew Ayele, 2023. "Selection of conventional preservation technologies using analytical hierarchy process," OPSEARCH, Springer;Operational Research Society of India, vol. 60(1), pages 217-233, March.
    2. 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.
    3. Nita H. Shah & Pratik H. Shah & Milan B. Patel, 2021. "Retailer’s inventory decisions with promotional efforts and preservation technology investments when supplier offers quantity discounts," OPSEARCH, Springer;Operational Research Society of India, vol. 58(4), pages 1116-1132, December.
    4. Gaurav Nagpal & Udayan Chanda & Himanshu Seth & Namita Ruparel, 2022. "Inventory Replenishment Policies for Two Successive Generations of Technology Products Under Permissible Delay in Payments," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 15(1), pages 1-29, January.
    5. R. Sundararajan & M. Palanivel & S. Vaithyasubramanian, 2023. "On the EOQ Models with Advertisement-Price-Dependent Demand and Quantity Discount with Expiration Date Under Shortage," SN Operations Research Forum, Springer, vol. 4(4), pages 1-31, December.
    6. 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.
    7. 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. Beullens, Patrick & Ghiami, Yousef, 2022. "Waste reduction in the supply chain of a deteriorating food item – Impact of supply structure on retailer performance," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1017-1034.
    2. 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).
    3. Reza Maihami & Behrooz Karimi & Seyyed Mohammad Taghi Fatemi Ghomi, 2017. "Effect of two-echelon trade credit on pricing-inventory policy of non-instantaneous deteriorating products with probabilistic demand and deterioration functions," Annals of Operations Research, Springer, vol. 257(1), pages 237-273, October.
    4. 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.
    5. 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.
    6. 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.
    7. Sudarshan Bardhan & Haimanti Pal & Bibhas Chandra Giri, 2019. "Optimal replenishment policy and preservation technology investment for a non-instantaneous deteriorating item with stock-dependent demand," Operational Research, Springer, vol. 19(2), pages 347-368, June.
    8. Vandana & A. K. Das, 2022. "Two-warehouse supply chain model under preservation technology and stochastic demand with shortages," OPSEARCH, Springer;Operational Research Society of India, vol. 59(4), pages 1587-1612, December.
    9. Chen, Jing & Dong, Ming & Rong, Ying & Yang, Liang, 2018. "Dynamic pricing for deteriorating products with menu cost," Omega, Elsevier, vol. 75(C), pages 13-26.
    10. Zhang, Jianxiong & Wang, Yu & Lu, Lihao & Tang, Wansheng, 2015. "Optimal dynamic pricing and replenishment cycle for non-instantaneous deterioration items with inventory-level-dependent demand," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 136-145.
    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. M. Palanivel & R. Uthayakumar, 2015. "Finite horizon EOQ model for non-instantaneous deteriorating items with price and advertisement dependent demand and partial backlogging under inflation," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(10), pages 1762-1773, July.
    13. Madhukar Nagare & Pankaj Dutta & Pravin Suryawanshi, 2020. "Optimal procurement and discount pricing for single-period non-instantaneous deteriorating products with promotional efforts," Operational Research, Springer, vol. 20(1), pages 89-117, March.
    14. 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.
    15. Chandra K. Jaggi & Sunil Tiwari & Satish K. Goel, 2017. "Credit financing in economic ordering policies for non-instantaneous deteriorating items with price dependent demand and two storage facilities," Annals of Operations Research, Springer, vol. 248(1), pages 253-280, January.
    16. 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.
    17. Qi Chen & Qi Xu & Wenjie Wang, 2019. "Optimal Policies for the Pricing and Replenishment of Fashion Apparel considering the Effect of Fashion Level," Complexity, Hindawi, vol. 2019, pages 1-12, February.
    18. Mou, Shandong & Robb, David J. & DeHoratius, Nicole, 2018. "Retail store operations: Literature review and research directions," European Journal of Operational Research, Elsevier, vol. 265(2), pages 399-422.
    19. Janssen, Larissa & Diabat, Ali & Sauer, Jürgen & Herrmann, Frank, 2018. "A stochastic micro-periodic age-based inventory replenishment policy for perishable goods," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 445-465.
    20. 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).

    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:57:y:2020:i:2:d:10.1007_s12597-019-00427-7. 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.