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Smart Pricing: Linking Pricing Decisions with Operational Insights

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Author Info

  • Fleischmann, M.
  • Hall, J.M.
  • Pyke, D.F.

Abstract

The past decade has seen a virtual explosion of information about customers and their preferences. This information potentially allows companies to increase their revenues, in particular since modern technology enables price changes to be effected at minimal cost. At the same time, companies have taken major strides in understanding and managing the dynamics of the supply chain, both their internal operations and their relationships with supply chain partners. These two developments are narrowly intertwined. Pricing decisions have a direct effect on operations and visa versa. Yet, the systematic integration of operational and marketing insights is in an emerging stage, both in academia and in business practice. This article reviews a number of key linkages between pricing and operations. In particular, it highlights different drivers for dynamic pricing strategies. Through the discussion of key references and related software developments we aim to provide a snapshot into a rich and evolving field.

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Bibliographic Info

Paper provided by Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam. in its series Research Paper with number ERS-2004-001-LIS.

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Date of creation: 12 Dec 2003
Date of revision:
Handle: RePEc:dgr:eureri:30001244

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Web page: http://www.erim.eur.nl/

Related research

Keywords: supply chain management; inventory; capacity; dynamic pricing; operations-marketing interface;

References

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  1. Arnd Huchzermeier & Ananth Iyer & Julia Freiheit, 2002. "The Supply Chain Impact of Smart Customers in a Promotional Environment," Manufacturing & Service Operations Management, INFORMS, vol. 4(3), pages 228-240, November.
  2. E. Andrew Boyd & Ioana C. Bilegan, 2003. "Revenue Management and E-Commerce," Management Science, INFORMS, vol. 49(10), pages 1363-1386, October.
  3. Jan A. Van Mieghem & Maqbool Dada, 1999. "Price Versus Production Postponement: Capacity and Competition," Management Science, INFORMS, vol. 45(12), pages 1639-1649, December.
  4. T. M. Whitin, 1955. "Inventory Control and Price Theory," Management Science, INFORMS, vol. 2(1), pages 61-68, October.
  5. So, Kut C. & Song, Jing-Sheng, 1998. "Price, delivery time guarantees and capacity selection," European Journal of Operational Research, Elsevier, vol. 111(1), pages 28-49, November.
  6. Ananth. V. Iyer & Jianming Ye, 2000. "Assessing the Value of Information Sharing in a Promotional Retail Environment," Manufacturing & Service Operations Management, INFORMS, vol. 2(2), pages 128-143, February.
  7. Stephen A. Smith & Dale D. Achabal, 1998. "Clearance Pricing and Inventory Policies for Retail Chains," Management Science, INFORMS, vol. 44(3), pages 285-300, March.
  8. Guillermo Gallego & Garrett van Ryzin, 1994. "Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons," Management Science, INFORMS, vol. 40(8), pages 999-1020, August.
  9. Tamer Boyaci & Saibal Ray, 2003. "Product Differentiation and Capacity Cost Interaction in Time and Price Sensitive Markets," Manufacturing & Service Operations Management, INFORMS, vol. 5(1), pages 18-36, May.
  10. Jorgensen, Steffen & Kort, Peter M., 2002. "Optimal pricing and inventory policies: Centralized and decentralized decision making," European Journal of Operational Research, Elsevier, vol. 138(3), pages 578-600, May.
  11. 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.
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Cited by:
  1. Sandra Transchel & Stefan Minner, 2008. "Coordinated Lot-sizing and Dynamic Prizing under a Supplier All-units Quantity Discount," BuR - Business Research, German Academic Association for Business Research, vol. 1(1), pages 125-141, May.

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