Modeling Power Distance in Trade

  • Gert Jan Hofstede
  • Catholijn M. Jonker
  • Tim Verwaart
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5269)

Abstract

Agent-based computational economics studies the nature of economic processes by means of artificial agents that simulate human behavior. Human behavior is known to be scripted by cultural background. The processes of trade partner selection and negotiation work out differently in different communities. Different communities have different norms regarding trust and opportunism. These differences are relevant for processes studied in economics, especially for international trade. This paper takes Hofstede’s model of national culture as a point of departure. It models the effects on trade processes of one of the five dimensions: power distance. It formulates rules for the behavior of artificial trading agents and presents a preliminary verification of the rules in a multi-agent simulation.

Keywords

culture negotiation trust deceit simulation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Hofstede, G.J., Jonker, C.M., Meijer, S., Verwaart, T.: Modeling Trade and Trust across Cultures. In: Stølen, K., Winsborough, W.H., Martinelli, F., Massacci, F. (eds.) iTrust 2006. LNCS, vol. 3986, pp. 120–134. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  2. 2.
    Meijer, S., Hofstede, G.J., Beers, G., Omta, S.W.F.: Trust and Tracing game: learning about transactions and embeddedness in a trade network. Production Planning and Control 17, 569–583 (2006)CrossRefGoogle Scholar
  3. 3.
    Adair, W., Brett, J., Lempereur, A., Okumura, T., Shikhirev, P., Tinsley, C., Lytle, A.: Culture and Negotiation Strategy. Negotiation Journal 20, 87–111 (2004)CrossRefGoogle Scholar
  4. 4.
    Kersten, G.E., Köszegi, S.T., Vetschera, R.: The Effects of Culture in Anonymous Negotiations: Experiment in Four Countries. In: Proceedings of the 35th HICSS, pp. 418–427 (2002)Google Scholar
  5. 5.
    Gorobets, A., Nooteboom, B.: Agent Based modeling of Trust Between Firms in Markets. In: Bruun, C. (ed.) Advances in Artificial Economics. LNEMS, vol. 584, pp. 121–132. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    Triandis, H.C., et al.: Culture and Deception in Business Negotiations: A Multilevel Analysis. International Journal of Cross Cultural Management 1, 73–90 (2001)CrossRefGoogle Scholar
  7. 7.
    Tesfatsion, L., Judd, K.L.: Handbook of Computational Economics Agent-based Computational Economics, vol. 2. North-Holland, Amsterdam (2006)Google Scholar
  8. 8.
    Hofstede, G.: Culture’s Consequence, 2nd edn. Sage Publications, Thousand Oaks (2001)Google Scholar
  9. 9.
    Hofstede, G., Hofstede, G.J.: Cultures and Organizations: Software of the Mind, 3rd Millennium edn. McGraw-Hill, New York (2005)Google Scholar
  10. 10.
    Hofstede, G., McCrae, R.R.: Personality and Culture Revisited: Linking Traits and Dimensions of Culture. Cross-Cultural Research 38, 52–88 (2004)CrossRefGoogle Scholar
  11. 11.
    Brazier, F.M.T., Jonker, C.M., Treur, J.: Principles of Component-Based Design of Intelligent Agents. Data and Knowledge Engineering 41, 1–28 (2002)MATHCrossRefGoogle Scholar
  12. 12.
    Jonker, C.M., Treur, J.: An Agent Architecture for Multi-Attribute Negotiation. In: Nebel, N. (ed.) Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, IJCAI 2001, Seattle, Washington, USA, August 4-10, 2001, pp. 1195–2001. Morgan Kaufmann, San Francisco (2001)Google Scholar
  13. 13.
    March, J.G.: A Primer on Decision Making: How Decisions Happen. Free Press (1994)Google Scholar
  14. 14.
    Bousquet, F., Bakam, I., Proton, H., Le Page, C.: Cormas: Common-Pool Resources and Multi-agent Systems. In: Mira, J., Moonis, A., de Pobil, A.P. (eds.) IEA/AIE 1998. LNCS, vol. 1416, pp. 826–838. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  15. 15.
    Jager, W., Mosler, H.J.: Simulating human behavior for understanding and managing environmental dilemmas. Journal of Social Issues 63(1), 97–116 (2007)CrossRefGoogle Scholar
  16. 16.
    Kónya, I.: Modeling Cultural Barriers in International Trade. Review of International Economics 14(3), 494–507 (2006)CrossRefGoogle Scholar
  17. 17.
    Bala, V., Long, N.V.: International trade and cultural diversity with preference selection. European Journal of Political Economy 21(1), 143–162 (2005)CrossRefGoogle Scholar
  18. 18.
    Guo, R.: How culture influences foreign trade: evidence from the U.S. and China. Journal of Socio-Economics 33, 785–812 (2004)CrossRefGoogle Scholar
  19. 19.
    Kersten, G.E.: Do E-business Systems Have Culture And Should They Have One? In: Proceedings of the 10th European Conference on Information Systems, Information Systems and the Future of the Digital Economy, ECIS 2002, Gdansk, Poland, June 6-8 (2002)Google Scholar
  20. 20.
    Blanchard, E.G.M., Frasson, C.: Making Intelligent Tutoring Systems Culturally Aware: The Use of Hofstede’s Cultural Dimensions. In: Proceedings of the 2005 International Conference on Artificial Intelligence, ICAI 2005, Las Vegas, Nevada, USA, June 27-30, 2005, vol. 2, pp. 644–649 (2005)Google Scholar
  21. 21.
    Razaki, R., Blanchard, E.G.M., Frasson, C.: On the Definition and Management of Cultural Groups of e-Learners. In: Ikeda, M., Ashley, K.D., Chan, T.-W. (eds.) ITS 2006. LNCS, vol. 4053, pp. 804–807. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  22. 22.
    Payr, S., Trappl, R.: Agent culture; Human-Agent Interaction in a Multicultural World. Lawrence Erlbaum Associates, Mahwah (2004)Google Scholar
  23. 23.
    Rehm, M., André, E., Nakano, Y.I., Nishida, T.: Enculturating conversational interfaces by socio-cultural aspects of communication. In: Proceedings of the 2008 International Conference on Intelligent User Interfaces, Gran Canaria, Canary Islands, Spain, January 13-16 (2008)Google Scholar
  24. 24.
    Rehm, M., André, E., Bee, N., Endrass, B., Wissner, M., Nakano, Y.I., Nishida, T., Huang, H.-H.: The CUBE-G approach – Coaching culture-specific nonverbal behavior by virtual agents. In: Proceedings of the 38th Conference of the International Simulation and Gaming Association (ISAGA), Nijmegen (2007)Google Scholar
  25. 25.
    Rehm, M., Nishida, T., André, E., Nakano, Y.I.: Culture-Specific First Meeting Encounters between Virtual Agents. In: Prendinger, H., Lester, J.C., Ishizuka, M. (eds.) IVA 2008. LNCS, vol. 5208, pp. 223–236. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  26. 26.
    Silverman, B.G., Johns, M., Cornwell, J., O’Brien, K.: Human Behavior Models for Agents in Simulators and Games: Part I: Enabling Science with PMFserv. Presence 15(2), 139–162 (2006)CrossRefGoogle Scholar
  27. 27.
    Silverman, B.G., Bharathy, G., Johns, M., Eidelson, R.J., Smith, T.E., Nye, B.: Sociocultural Games for Training and Analysis. IEEE Transactions on Systems, Man, and Cybernetics, Part A 37(6), 1113–1130 (2007)CrossRefGoogle Scholar
  28. 28.
    Hofstede, G.J., Jonker, C.M., Verwaart, T.: Modeling Culture in Trade: Uncertainty Avoidance. In: Proceedings of the 2008 Agent-Directed Simulation Symposium (ADS 2008). SCS, San Diego (2008)Google Scholar
  29. 29.
    Hofstede, G.J., Jonker, C.M., Verwaart, T.: Individualism and Collectivism in Trade Agents. In: Nguyen, N.T., Borzemski, L., Grzech, A., Ali, M. (eds.) IEA/AIE 2008. LNCS, vol. 5027, pp. 492–501. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  30. 30.
    Hofstede, G.J., Jonker, C.M., Verwaart, T.: Long-term Orientation in Trade. In: Schredelseker, K., Hauser, F. (eds.) Complexity and Artificial Markets. LNEMS, vol. 614, pp. 107–118. Springer, Heidelberg (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Gert Jan Hofstede
    • 1
  • Catholijn M. Jonker
    • 2
  • Tim Verwaart
    • 3
  1. 1.Wageningen UniversityWageningenThe Netherlands
  2. 2.Delft University of TechnologyDelftThe Netherlands
  3. 3.LEI Wageningen URden HaagThe Netherlands

Personalised recommendations