Skip to main content

Agent System for Online Ticket Resale

  • Conference paper
Agent and Multi-Agent Systems: Technologies and Applications (KES-AMSTA 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4953))

  • 1603 Accesses

Abstract

This study has tried to suggest a new model that can effectively redistribute the tickets in the online ticket resale market, while suggesting a new allocation mechanism based on an agent negotiation. To this end, this study has analyzed and simulated the secondary ticket market through System dynamics. As a result of these simulations, it has been proved that the price stability of ticket resale market leads to an increase in revenue. An agent negotiation helps to stabilize the ticket prices that are usually inclined to rise at auction, benefiting all the participants in the negotiations, consequently showing a Pareto solution.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bertsekas, P.D.: The Auction Algorithm: A Distributed Relaxation Method for the Assignment Problem. Annals of Operations Research 14, 105–123 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  2. David, V.H.: e-Commerce economics. Thomson Learning (2002)

    Google Scholar 

  3. Fischer, K., Jorg, P., Pischel, M.: Cooperative Transportation Scheduling: an Application Domain for DAI. Journal of Applied Artificial Intelligence, Special Issue on Intelligent Agents 10(1), 1–31 (1996)

    Google Scholar 

  4. Kawamura, H., Yamamoto, M., Ohuchi, A.: Multiagent Analysis of Customer-Driven Reservation Adjustment System. In: APIEMS Conference, 26.4.1–26.4.14 (2004)

    Google Scholar 

  5. Kim, H.S., Cho, J.H., Choi, H.R., Hong, S.G., Kang, M.H.: Optimal Supply Chain Formation Using Agent Negotiation in a SET Model-Based Make-To-Order. In: Harper, R., Rauterberg, M., Combetto, M. (eds.) ICEC 2006. LNCS, vol. 4161, pp. 579–583. Springer, Heidelberg (2006)

    Google Scholar 

  6. Korea Institute of Science and Technology Information: Briefing on global developments (2007)

    Google Scholar 

  7. Michael, P.W., Willian, E.W.: Auction Protocols for Decentralized Scheduling. Games and Economics Behavior 35, 271–303 (2001)

    Article  MATH  Google Scholar 

  8. Russ, C., Vierke, G.: The Matrix Auction: A Mechanism for the Market-Based Coordination of Enterprise Networks. German Research Center for Artificial Intelligence, Research Report RR-99-04 (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Ngoc Thanh Nguyen Geun Sik Jo Robert J. Howlett Lakhmi C. Jain

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Cho, J.H., Kim, H.S., Choi, H.R., Jung, J.U. (2008). Agent System for Online Ticket Resale. In: Nguyen, N.T., Jo, G.S., Howlett, R.J., Jain, L.C. (eds) Agent and Multi-Agent Systems: Technologies and Applications. KES-AMSTA 2008. Lecture Notes in Computer Science(), vol 4953. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78582-8_62

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-78582-8_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78581-1

  • Online ISBN: 978-3-540-78582-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics