IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v116y2008i2p190-198.html
   My bibliography  Save this article

Joint optimization on pricing, promotion and inventory control with stochastic demand

Author

Listed:
  • Zhang, Ju-Liang
  • Chen, Jian
  • Lee, Chung-Yee

Abstract

Firms often utilize and coordinate dynamic adjustment of price, non-price promotions such as advertisement and recruitment of excellent salespeople and proper inventory replenishment policies to satisfy customer demands and achieve maximal profit. This paper provides an analytical model for obtaining optimal decisions jointly on pricing, promotion and inventory control. Specifically, we study a single item, finite horizon, periodic review model in which the demand is influenced by price and promotion, and the objective is to maximize the total profit. We characterize the optimal policy and provide solution for coordinating promotion, pricing and inventory replenishment. We show that the optimal promotion policy is a threshold policy under some reasonable assumptions and once the promotion is determined the optimal inventory/pricing policy is a base-stock-list-price policy. Numerical study is also provided to demonstrate the contribution of our model.

Suggested Citation

  • Zhang, Ju-Liang & Chen, Jian & Lee, Chung-Yee, 2008. "Joint optimization on pricing, promotion and inventory control with stochastic demand," International Journal of Production Economics, Elsevier, vol. 116(2), pages 190-198, December.
    • Handle: RePEc:eee:proeco:v:116:y:2008:i:2:p:190-198
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925-5273(08)00314-9
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Aram G. Sogomonian & Christopher S. Tang, 1993. "A Modeling Framework for Coordinating Promotion and Production Decisions within a Firm," Management Science, INFORMS, vol. 39(2), pages 191-203, February.
    2. Nicholas C. Petruzzi & Maqbool Dada, 1999. "Pricing and the Newsvendor Problem: A Review with Extensions," Operations Research, INFORMS, vol. 47(2), pages 183-194, April.
    3. Karakul, M., 2008. "Joint pricing and procurement of fashion products in the existence of clearance markets," International Journal of Production Economics, Elsevier, vol. 114(2), pages 487-506, August.
    4. Wedad Elmaghraby & P{i}nar Keskinocak, 2003. "Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions," Management Science, INFORMS, vol. 49(10), pages 1287-1309, October.
    5. Awi Federgruen & Aliza Heching, 1999. "Combined Pricing and Inventory Control Under Uncertainty," Operations Research, INFORMS, vol. 47(3), pages 454-475, June.
    6. Evan L. Porteus, 1971. "On the Optimality of Generalized (s, S) Policies," Management Science, INFORMS, vol. 17(7), pages 411-426, March.
    7. Webster, Scott & Kevin Weng, Z., 2008. "Ordering and pricing policies in a manufacturing and distribution supply chain for fashion products," International Journal of Production Economics, Elsevier, vol. 114(2), pages 476-486, August.
    8. T. M. Whitin, 1955. "Inventory Control and Price Theory," Management Science, INFORMS, vol. 2(1), pages 61-68, October.
    9. Jean-Pierre Dubé & Günter Hitsch & Puneet Manchanda, 2005. "An Empirical Model of Advertising Dynamics," Quantitative Marketing and Economics (QME), Springer, vol. 3(2), pages 107-144, June.
    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. Xiaomin Zhao & Shuhui Hu & Xiaoxiao Meng, 2020. "Who should pay for return freight in the online retailing? Retailers or consumers," Electronic Commerce Research, Springer, vol. 20(2), pages 427-452, June.
    2. Wang, Qiang & Zhao, Nenggui & Wu, Jie & Zhu, Qingyuan, 2021. "Optimal pricing and inventory policies with reference price effect and loss-Averse customers," Omega, Elsevier, vol. 99(C).
    3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. Wei, Ying & Chen, Youhua (Frank), 2011. "Joint determination of inventory replenishment and sales effort with uncertain market responses," International Journal of Production Economics, Elsevier, vol. 134(2), pages 368-374, December.
    5. Hardik N. Soni & Dipali N. Suthar, 2020. "Optimal pricing and replenishment policy for non-instantaneous deteriorating items with varying rate of demand and partial backlogging," OPSEARCH, Springer;Operational Research Society of India, vol. 57(3), pages 986-1021, September.
    6. Gürel, Yücel & Güllü, Refik, 2019. "Effect of a secondary market on a system with random demand and uncertain costs," International Journal of Production Economics, Elsevier, vol. 209(C), pages 112-120.
    7. Terzi, Mourad & Ouazene, Yassine & Yalaoui, Alice & Yalaoui, Farouk, 2023. "Lot-sizing and pricing decisions under attraction demand models and multi-channel environment: New efficient formulations," Operations Research Perspectives, Elsevier, vol. 10(C).
    8. Gupta, Vishal Kumar & Ting, Q.U. & Tiwari, Manoj Kumar, 2019. "Multi-period price optimization problem for omnichannel retailers accounting for customer heterogeneity," International Journal of Production Economics, Elsevier, vol. 212(C), pages 155-167.
    9. Armando Meza & Paolo Latorre & Milena Bonacic & Héctor López-Ospina & Juan Pérez, 2024. "Optimizing Inventory and Pricing for Substitute Products with Soft Supply Constraints," Mathematics, MDPI, vol. 12(11), pages 1-23, June.
    10. Udayan Chanda & Alok Kumar, 2019. "Optimization of EOQ Model for New Products Under Multi-Stage Adoption Process," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(02), pages 1-25, April.
    11. Ma, Shaohui & Fildes, Robert & Huang, Tao, 2016. "Demand forecasting with high dimensional data: The case of SKU retail sales forecasting with intra- and inter-category promotional information," European Journal of Operational Research, Elsevier, vol. 249(1), pages 245-257.
    12. 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).
    13. Tunuguntla, Vaishnavi & Basu, Preetam & Rakshit, Krishanu & Ghosh, Debabrata, 2019. "Sponsored search advertising and dynamic pricing for perishable products under inventory-linked customer willingness to pay," European Journal of Operational Research, Elsevier, vol. 276(1), pages 119-132.
    14. Tsao, Yu-Chung, 2015. "Cooperative promotion under demand uncertainty," International Journal of Production Economics, Elsevier, vol. 167(C), pages 45-49.
    15. Kim, Sang-Won & Bell, Peter C., 2011. "Optimal pricing and production decisions in the presence of symmetrical and asymmetrical substitution," Omega, Elsevier, vol. 39(5), pages 528-538, October.
    16. Xiaxia Ma & Wenliang Bian & Xiqing Yang & Shengnan Niu & Yongming Cai & Jie Guan & Wenbin Wang, 2022. "Online Retailer’s Contingent Free-Shipping Decisions under Large-Scale Promotions Considering Delayed Delivery," Sustainability, MDPI, vol. 14(17), pages 1-22, August.
    17. Tal Avinadav & Tatyana Chernonog & Yael Lahav & Uriel Spiegel, 2017. "Dynamic pricing and promotion expenditures in an EOQ model of perishable products," Annals of Operations Research, Springer, vol. 248(1), pages 75-91, January.
    18. Zhu, Stuart X., 2013. "Dynamic replenishment, production, and pricing decisions, in the face of supply disruption and random price-sensitive demand," International Journal of Production Economics, Elsevier, vol. 146(2), pages 612-619.

    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. Mitra, Subrata, 2018. "Newsvendor problem with clearance pricing," European Journal of Operational Research, Elsevier, vol. 268(1), pages 193-202.
    2. Shi, Jianmai & Zhang, Guoqing, 2010. "Multi-product budget-constrained acquisition and pricing with uncertain demand and supplier quantity discounts," International Journal of Production Economics, Elsevier, vol. 128(1), pages 322-331, November.
    3. Boxiao Chen & Xiuli Chao & Cong Shi, 2021. "Nonparametric Learning Algorithms for Joint Pricing and Inventory Control with Lost Sales and Censored Demand," Mathematics of Operations Research, INFORMS, vol. 46(2), pages 726-756, May.
    4. Qing Li & Shaohui Zheng, 2006. "Joint Inventory Replenishment and Pricing Control for Systems with Uncertain Yield and Demand," Operations Research, INFORMS, vol. 54(4), pages 696-705, August.
    5. Ornella Tarola & Sandro Trento, 2010. "Timing of Investment and Dynamic Pricing in Privatized Sectors," DISA Working Papers 1005, Department of Computer and Management Sciences, University of Trento, Italy, revised 20 Oct 2010.
    6. Wang, Chong & Chen, Jing & Chen, Xu, 2017. "Pricing and order decisions with option contracts in the presence of customer returns," International Journal of Production Economics, Elsevier, vol. 193(C), pages 422-436.
    7. Georgia Perakis & Melvyn Sim & Qinshen Tang & Peng Xiong, 2023. "Robust Pricing and Production with Information Partitioning and Adaptation," Management Science, INFORMS, vol. 69(3), pages 1398-1419, March.
    8. Qi Feng, 2010. "Integrating Dynamic Pricing and Replenishment Decisions Under Supply Capacity Uncertainty," Management Science, INFORMS, vol. 56(12), pages 2154-2172, December.
    9. Fernando Bernstein & Yang Li & Kevin Shang, 2016. "A Simple Heuristic for Joint Inventory and Pricing Models with Lead Time and Backorders," Management Science, INFORMS, vol. 62(8), pages 2358-2373, August.
    10. Hyun-soo Ahn & Mehmet Gümüş & Philip Kaminsky, 2007. "Pricing and Manufacturing Decisions When Demand Is a Function of Prices in Multiple Periods," Operations Research, INFORMS, vol. 55(6), pages 1039-1057, December.
    11. Hanzhang Qin & David Simchi-Levi & Li Wang, 2022. "Data-Driven Approximation Schemes for Joint Pricing and Inventory Control Models," Management Science, INFORMS, vol. 68(9), pages 6591-6609, September.
    12. Hemant K. Bhargava & Daewon Sun & Susan H. Xu, 2006. "Stockout Compensation: Joint Inventory and Price Optimization in Electronic Retailing," INFORMS Journal on Computing, INFORMS, vol. 18(2), pages 255-266, May.
    13. Chen, Jing & Bell, Peter C., 2009. "The impact of customer returns on pricing and order decisions," European Journal of Operational Research, Elsevier, vol. 195(1), pages 280-295, May.
    14. Xin Chen & Sean X. Zhou & Youhua (Frank) Chen, 2011. "Integration of Inventory and Pricing Decisions with Costly Price Adjustments," Operations Research, INFORMS, vol. 59(5), pages 1144-1158, October.
    15. Yunzeng Wang, 2006. "Joint Pricing-Production Decisions in Supply Chains of Complementary Products with Uncertain Demand," Operations Research, INFORMS, vol. 54(6), pages 1110-1127, December.
    16. Gurkan, M. Edib & Tunc, Huseyin & Tarim, S. Armagan, 2022. "The joint stochastic lot sizing and pricing problem," Omega, Elsevier, vol. 108(C).
    17. Adam Copeland & George Hall, 2011. "The response of prices, sales, and output to temporary changes in demand," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(2), pages 232-269, March.
    18. Qi Feng & Sirong Luo & J. George Shanthikumar, 2020. "Integrating Dynamic Pricing with Inventory Decisions Under Lost Sales," Management Science, INFORMS, vol. 66(5), pages 2232-2247, May.
    19. Serel, Doğan A., 2017. "A single-period stocking and pricing problem involving stochastic emergency supply," International Journal of Production Economics, Elsevier, vol. 185(C), pages 180-195.
    20. Gal Raz & Evan L. Porteus, 2006. "A Fractiles Perspective to the Joint Price/Quantity Newsvendor Model," Management Science, INFORMS, vol. 52(11), pages 1764-1777, November.

    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:eee:proeco:v:116:y:2008:i:2:p:190-198. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.