Skip to main content

Microeconomic Demand Functions Implementation in Java Experiments

  • Conference paper
Agent and Multi-Agent Systems: Technologies and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 296))

Abstract

The aim of this paper is to introduce microeconomic demand functions (Marshallian demand function and Cobb-Douglas utility function) in Java simulation experiments. The motivation is to use these function as a core element in a seller-to-customer price negotiation in an agent-based simulations. Furthermore, multi-agent model is proposed and implemented in Java to serve as a simulation framework to support the virtual company trading processes. The main background of this framework is to be integrated in management information systems as a decision support module. The paper firstly presents some of the existing principles about consumer behavior, agent-based modeling and simulation in the same area and demand function theory. Secondly, presents multi-agent model and demand functions negotiations. Lastly, depicts some of the simulation results in a trading processes throughout one year of selling commodities to consumers. The results obtained show that in some metrics the demand functions could be used to predict the trading results of a company.

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 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
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. Chramcov, B., Bucki, R., Suchánek, P.: Logistic Optimization of the Complex Manufacturing System with Parallel Production Lines. Journal of Applied Economic Sciences VIII(3(25), 17–23 (2013) ISSN: 1843-6110

    Google Scholar 

  2. Šperka, R.: Application of a Simulation Framework for Decision Support Sys-tems. MITTEILUNGEN KLOSTERNEUBURG, Hoehere Bundeslehranstalt und Bundesamt fuer Wein- und Obstbau, Klosterneuburg, Austria 64(1) (2014) ISSN 0007-5922

    Google Scholar 

  3. Šperka, R., Vymětal, D., Spišák, M.: Towards the Validation of Agent-based BPM Simulation. In: Proc. Frontiers in Artificial Intelligence and Applications, 7th International Conference KES-AMSTA 2013, Hue city, Vietnam, vol. 252, pp. 276–283. IOS Press BV, Amsterdam (2013) ISBN 978-1-61499-253-0 (print)

    Google Scholar 

  4. Šperka, R., Spišák, M., Slaninová, K., Martinovič, J., Dráždilová, P.: Control Loop Model of Virtual Company in BPM Simulation. In: Snasel, V., Abraham, A., Corchado, E.S. (eds.) SOCO Models in Industrial & Environmental Appl. AISC, vol. 188, pp. 515–524. Springer, Heidelberg (2013)

    Google Scholar 

  5. Šperka, R., Spišák, M.: Transaction Costs Influence on the Stability of Financial Market: Agent-based Simulation. Journal of Business Economics and Management 14(suppl. 1), S1–S12 (2013), doi:10.3846/16111699.2012.701227 ISSN 1611-1699

    Google Scholar 

  6. Šperka, R., Vymětal, D.: MAREA - an Education Application for Trading Company Simulation based on REA Principles. In: Proc. Advances in Education Research, USA. Information, Communication and Education Application, vol. 30, pp. 140–147 (2013) ISBN 978-1-61275-056-9

    Google Scholar 

  7. Barnett, M.: Modeling & Simulation in Business Process Management’, Gensym Corporation, pp. 6–7 (2003), http://news.bptrends.com/publicationfiles/1103%20WP%20Mod%20Simulation%20of%20BPM%20-%20Barnett-1.pdf (accessed January 16, 2012)

  8. Enis, B.M.: Marketing principles: the management process. Goodyear Pub. Co. (Pacific Palisades, California), 608 p. (1974) ISBN 0876205503

    Google Scholar 

  9. McCarthy, E.J., Perreault, W.D.: Basic marketing: a global-managerial approach. Irwin, 792 p. (1993) ISBN 025610509X

    Google Scholar 

  10. Keegan, W., Moriarty, S., Duncan, T.: Marketing, 193 p. Prentice-Hall, Englewood Cliffs (1992)

    Google Scholar 

  11. Schiffman, L.G., Kanuk, L.L.: Purchasing Behavior, 9th edn. Pearson Prentice Hall, Upper Saddle River (2007)

    Google Scholar 

  12. Gregson, N., Crewe, L., Brooks, K.: Shopping, space, and practice. Environment and Planning D 20(5), 597–617 (2002), doi:10.1068/d270t

    Article  Google Scholar 

  13. Challet, D., Krause, A.: What questions to ask in order to validate an agent-based model. In: Report of the 56th European Study Group with Industry, pp. J1–J9 (2006)

    Google Scholar 

  14. Tay, N., Lusch, R.: Agent-Based Modeling of Ambidextrous Organizations: Virtualizing Competitive Strategy. IEEE Transactions on Intelligent Systems 22(5), 50–57 (2002)

    Article  Google Scholar 

  15. Wilkinson, I., Young, L.: On cooperating: Firms. Relations. Networks. Journal of Business Research (55), 123–132 (2002)

    Google Scholar 

  16. Casti, J.: Would-be Worlds. How Simulation is Changing the World of Science. Wiley (1997)

    Google Scholar 

  17. Goldenberg, J., Libai, B., Muller, E.: The Chilling effect of network external-ities. International Journal of Research in Marketing 27(1), 4–15 (2010)

    Article  Google Scholar 

  18. Heath, B., Hill, R., Ciarallo, F.: A survey of agent-based modeling practices (January 1998 to July 2008). Journal of Artificial Societies and Social Simulation 12(4), 5–32 (2009)

    Google Scholar 

  19. Rahmandad, H., Sterman, J.: Heterogeneity and network structure in the dynamics of diffusion: Comparing agent-based and differential equation models. Management Science 54(5), 998–1014 (2008)

    Article  Google Scholar 

  20. Shaikh, N., Ragaswamy, A., Balakrishnan, A.: Modelling the Diffusion of In-novations Using Small World Networks. Working Paper. Penn State University. Philadelphia (2005)

    Google Scholar 

  21. Toubia, O., Goldenberg, J., Garcia, R.: A New approach to modeling the adoption of new products: Aggregated Diffusion Models. MSI Reports: Working Papers Series 8(1), 65–76 (2008)

    Google Scholar 

  22. Adjali, I., Dias, B., Hurling, R.: Agent based modeling of consumer behavior. In: Proceedings of the North American Association for Computational Social and Organizational Science Annual Conference. University of Notre Dame, Notre Dame (2005)

    Google Scholar 

  23. Ben, L., Bouron, T., Drogoul, A.: Agent-based interaction analysis of con-sumer behavior. In: Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems: Part 1, pp. 184–190. ACM, New York (2002)

    Google Scholar 

  24. Marshall, A.: Principle of Economics, 8th edn. MacMillan, London (1920)

    Google Scholar 

  25. Mas-Colell, A., Whinston, M., Green, J.: Microeconomic Theory. Oxford University Press, Oxford (1995) ISBN 0-19-507340-1

    Google Scholar 

  26. Pollak, R.: Conditional Demand Functions and Consumption Theory. Quarterly Journal of Economics 83, 60–78 (1969)

    Article  MATH  Google Scholar 

  27. Varian, H.R.: Microeconomic Analysis, 3rd edn., ch. 7, 8 and 9. W.W. Norton & Company, New York (1992)

    Google Scholar 

  28. Foundation for Intelligent Physical Agents (FIPA): FIPA Contract Net Interaction Protocol. In: Specification [online]. FIPA (2002), http://www.fipa.org/specs/fipa00029/SC00029H.pdf (cit. June 13, 2011)

  29. Vymětal, D., Spišák, M., Šperka, R.: An Influence of Random Number Generation Function to Multiagent Systems. In: Jezic, G., Kusek, M., Nguyen, N.-T., Howlett, R.J., Jain, L.C. (eds.) KES-AMSTA 2012. LNCS, vol. 7327, pp. 340–349. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Roman Šperka .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Šperka, R., Spišák, M. (2014). Microeconomic Demand Functions Implementation in Java Experiments. In: Jezic, G., Kusek, M., Lovrek, I., J. Howlett, R., Jain, L. (eds) Agent and Multi-Agent Systems: Technologies and Applications. Advances in Intelligent Systems and Computing, vol 296. Springer, Cham. https://doi.org/10.1007/978-3-319-07650-8_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-07650-8_19

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07649-2

  • Online ISBN: 978-3-319-07650-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics