Electronic Commerce Research

, Volume 5, Issue 2, pp 267–292 | Cite as

Dynamic Pricing for Time-Limited Goods in a Supplier-Driven Electronic Marketplace

  • Prithviraj DasguptaEmail author
  • Louise E. Moser
  • P. Michael Melliar-Smith


Existing e-commerce systems employ a pull model of marketing where buyers, possibly through agents, search the e-market for suppliers offering the product of their choice. In contrast, the push model where suppliers’ agents approach buyers with their products, has been relatively less investigated. Push strategies are particularly appropriate for commodities that have a short shelf-life and, therefore, an elastic demand curve, allowing suppliers to exploit unexpected supply. The speed and low cost of e-commerce makes it particularly suited to the push paradigm. In this paper, we consider time-limited goods in a supplier driven marketplace that employs the push model of marketing. When constrained by a strict deadline to sell the good, the supplier uses a mobile sales agent that visits every buyer and estimates the short run demand curve of the good. At every buyer, the sales agent also employs a heuristic technique called the Maximum Returns Algorithm to recalculate the price of the good, so that the supplier can obtain the best possible gross returns from trading with the buyers. On the other hand, when the deadline to sell is not stringent, the sales agent negotiates the exchange at a point that improves both the buyer’s utility and the supplier’s profit, as compared to the exchange point without negotiation.


dynamic pricing push model of marketing agent mediated e-commerce 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
  2. 2.
    Amazon Inc., URL:
  3. 3.
  4. 4.
    Bachem, A., W. Hochstattler, and M. Malich. (1992). “Simulated Trading: A New Approach For Solving Routing Problems.” Technical Report 92.125, Mathematics Institute, University of Koln.Google Scholar
  5. 5.
    Bailey, J. and Y. Bakos. (1997). “An Exploratory Study of the Emerging Role of Electronic Intermediaries,” International Journal of Electronic Commerce 1(3), 7–20.Google Scholar
  6. 6.
    BargainFinder, URL:
  7. 7.
    Belobaba, P. (1999). “Application of a Probabilistic Decision Model to Airline Seat Invetory Control,” Operations Research 37, 183–197.Google Scholar
  8. 8.
    Brumelle, S. and M. McGill. (1993). “Airline Seat Allocation with Multiple Nested Fare Classes.” Operations Research 41, 127–137.CrossRefGoogle Scholar
  9. 9.
    Chavez, A. and P. Maes. (1996). “Kasbah: An Agent Marketplace for Buying and Selling Goods.” In Proceedings of the First International Conference on the Practical Application of Intelligent Agents and Multi-Agent Technology. London, UK, pp. 75–90.Google Scholar
  10. 10.
    Dasgupta, P., N. Narasimhan, L.E. Moser, and P. M. Melliar-Smith. (1999). “MAgNET: Mobile Agents for Networked Electronic Trading.” IEEE Transactions on Knowledge and Data Engineering 11(4), 509–525.Google Scholar
  11. 11.
    Dasgupta, P. and R. Das. (2000). “Dynamic Pricing with Limited Competitor Information in a Multi-agent Economy.” In Cooperative Information Systems, Lecture Notes in Computer Science 1910. Springer Verlag, pp. 299–310.Google Scholar
  12. 12.
    Dasgupta, P., L. Moser, and P. M. Melliar-Smith. (2001). “Dynamic Tiered Pricing in a Multi-agent Economy.” In International Conference on Artificial Intelligence. Las Vegas, NV, pp. 1142–1148.Google Scholar
  13. 13.
    Dealtime, URL:
  14. 14.
    Dolan, R. and H. Simon. (1996). Power Pricing. Free Press, New York, NY.Google Scholar
  15. 15.
    Doorenbos, R., O. Etzioni, and D. Weld. (1997). “A Scalable Comparison/Shopping Agent for the World Wide Web.” In Proceedings of the First International Conference on Autonomous Agents. Marina del Rey, CA, pp. 39–48.Google Scholar
  16. 16.
    E-Bay Inc., URL:
  17. 17.
  18. 18.
    Guttman, R. and P. Maes. (1998). “Cooperative vs. Competitive Multi-Agent Negotiations in Retail Electronic Commerce.” In Proceedings of the Second International Workshop on Cooperative Information Agents. Paris, France pp. 135–147.Google Scholar
  19. 19.
    Guttman, R., A. Moukas, and P. Maes. (1998). “Agent-Mediated Electronic Commerce: A Survey.” Knowledge Engineering Review 13(2), 147–159.Google Scholar
  20. 20.
  21. 21.
    Kephart, J., J.E. Hanson, and A.R. Greenwald. (2000). “Dynamic Pricing by Software Agents.” Computer Networks 32(6), Elsevier, 731–752.Google Scholar
  22. 22.
    Lange, D.B. and M. Oshima. (1998). Programming and Developing Java Mobile Agents with Aglets, Addison-Wesley, Menlo Park, CA.Google Scholar
  23. 23.
    Lange, D., M. Oshima, G. Karjoth, and K. Kosaka. (1997). “Aglets: Programming Mobile Agents in Java.” In Proceedings of the International Conference on Worldwide Computing and Its Applications. Tsukuba, Japan. Lecture Notes in Computer Science 1274, Springer-Verlag, Berlin, Germany, pp. 253–266.Google Scholar
  24. 24.
  25. 25.
    Miller, G., J. M. Rosenblatt, and L. J. Hushak. (1988). “The Effects of Supply Shifts on Producer’s Surplus.” American Journal of Agricultural Economics 70(4), 886–891.Google Scholar
  26. 26.
    My Simon, URL:
  27. 27.
    Nicholson, W. (1989). Microeconomic Theory, Fourth Edition. The Dry den Press, Orlando, FL.Google Scholar
  28. 28.
    Papaioannou, T. (2000). “On the Structuring of Distributed Systems: The Argument for Mobility.” Ph.D Thesis, University of Loughborough, UK.Google Scholar
  29. 29.
    Price Line, URL:
  30. 30.
    Shardanand, U. and P. Maes. (1995). “Social Information Filtering: Algorithms for Automating ‘Word of Mouth’. In Proceedings of the Computer-Human Interaction Conference. Denver, CO, pp. 210–217.Google Scholar
  31. 31.
    Smith, R. (1980). “The Contract Net Protocol: High-Level Communication and Control and a Distributed Problem Solver.” IEEE Transactions on Computers 29(12), 1104–1113.Google Scholar
  32. 32.
    Site Sell Inc., URL:
  33. 33.
    Talus Solutions, URL:
  34. 34.
    Tsvetovatyy, M., B. Mobasher, M. Gini, and Z. Wieckowski. (1997). “MAGMA: An Agent-Based Virtual Market for Electronic Commerce.” Applied Artificial Intelligence 11(6), 501–523.Google Scholar
  35. 35.
    Wurman, P., M. P. Wellman, and W. E. Walsh. (1998). “The Michigan Internet AuctionBot: A Configurable Auction Server for Human and Software Agents.” In Proceedings of the Second International Conference on Autonomous Agents. Minneapolis, MN, pp. 301–308.Google Scholar
  36. 36.
    Yahoo Store, URL:

Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • Prithviraj Dasgupta
    • 1
    Email author
  • Louise E. Moser
    • 2
  • P. Michael Melliar-Smith
    • 2
  1. 1.Department of Computer ScienceUniversity of NebraskaOmaha
  2. 2.Department of Electrical and Computer EngineeringUniversity of CaliforniaSanta Barbara

Personalised recommendations