IDEAS home Printed from https://ideas.repec.org/a/sae/envirb/v30y2003i3p391-410.html
   My bibliography  Save this article

A Multiagent Model of Negotiation Processes between Multiple Actors in Urban Developments: A Framework for and Results of Numerical Experiments

Author

Listed:
  • Theo Arentze
  • Harry Timmermans

Abstract

We propose a multiagent model in which developers and suppliers negotiate and generate proposals for developing a site, given multiple candidate locations in an urban area. In the model, the developer takes the initiative and coordinates the negotiation process with the aim of obtaining commitments from suppliers to open an outlet at a location. In this process, suppliers indicate their preferences and make yes – no decisions to participate in a proposal. We formulate and investigate two alternative negotiation protocols and various possible decision strategies for the developer and supplier agents. The model is applied to a hypothetical study area to investigate long-term dynamics as a function of the choice of protocol and strategies. We show that the model is capable of reproducing the typical hierarchical structure of real retail systems. Furthermore, it appears that the choice of protocol and strategy has an impact on the degree of spatial clustering of outlets as well as on the performance of each individual supplier. The choice of strategy is particularly critical for relatively weak suppliers. We conclude that the multiagent model is useful for planners, developers, and suppliers to explore the impacts their choices have on outcomes, and we identify promising avenues of future research.

Suggested Citation

  • Theo Arentze & Harry Timmermans, 2003. "A Multiagent Model of Negotiation Processes between Multiple Actors in Urban Developments: A Framework for and Results of Numerical Experiments," Environment and Planning B, , vol. 30(3), pages 391-410, June.
  • Handle: RePEc:sae:envirb:v:30:y:2003:i:3:p:391-410
    DOI: 10.1068/b12950
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1068/b12950
    Download Restriction: no

    File URL: https://libkey.io/10.1068/b12950?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Loewenstein, George, 2001. "The Creative Destruction of Decision Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(3), pages 499-505, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dellaert, Benedict G.C. & Arentze, Theo A. & Timmermans, Harry J.P., 2008. "Shopping context and consumers’ mental representation of complex shopping trip decision problems," Journal of Retailing, Elsevier, vol. 84(2), pages 219-232.
    2. Shambhavi Tiwari & Morten Moshagen & Benjamin E. Hilbig & Ingo Zettler, 2021. "The Dark Factor of Personality and Risk-Taking," IJERPH, MDPI, vol. 18(16), pages 1-18, August.
    3. Chioveanu, Ioana, 2008. "Advertising, brand loyalty and pricing," Games and Economic Behavior, Elsevier, vol. 64(1), pages 68-80, September.
    4. Wiktor Adamowicz & David Bunch & Trudy Cameron & Benedict Dellaert & Michael Hanneman & Michael Keane & Jordan Louviere & Robert Meyer & Thomas Steenburgh & Joffre Swait, 2008. "Behavioral frontiers in choice modeling," Marketing Letters, Springer, vol. 19(3), pages 215-228, December.
    5. Pourakin Djarius Dieudonné BAMA, 2020. "Portfolio Management on an Emerging Market: Dynamic Strategy or Passive Strategy?," Business and Management Studies, Redfame publishing, vol. 6(2), pages 1526-1526, December.
    6. Simonson, Itamar, 2005. "In Defense of Consciousness: The Role of Conscious and Unconscious Inputs in Consumer Choice," Research Papers 1883, Stanford University, Graduate School of Business.
    7. T.A. Arentze & H.J.P. Timmermans, 2005. "An Analysis of Context and Constraints-dependent Shopping Behaviour Using Qualitative Decision Principles," Urban Studies, Urban Studies Journal Limited, vol. 42(3), pages 435-448, March.
    8. Ioana Chioveanu, 2005. "Advertising, Brand Loyalty and Pricing," UFAE and IAE Working Papers 639.05, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    9. Koumakhov, Rouslan, 2009. "Conventions in Herbert Simon's theory of bounded rationality," Journal of Economic Psychology, Elsevier, vol. 30(3), pages 293-306, June.
    10. Yan Li & Neal Ashkanasy & David Ahlstrom, 2014. "The rationality of emotions: A hybrid process model of decision-making under uncertainty," Asia Pacific Journal of Management, Springer, vol. 31(1), pages 293-308, March.
    11. DeLong, Karen L. & Syrengelas, Konstantinos G. & Grebitus, Carola & Nayga, Rodolfo M., 2021. "Visual versus Text Attribute Representation in Choice Experiments," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 94(C).
    12. Crusius, Jan & van Horen, Femke & Mussweiler, Thomas, 2012. "Why process matters: A social cognition perspective on economic behavior," Journal of Economic Psychology, Elsevier, vol. 33(3), pages 677-685.
    13. Paola Manzini, 2001. "Time Preferences: Do They Matter in Bargaining?," Working Papers 445, Queen Mary University of London, School of Economics and Finance.
    14. Crittenden, Victoria L. & Woodside, Arch G., 2006. "Mapping strategic decision-making in cross-functional contexts," Journal of Business Research, Elsevier, vol. 59(3), pages 360-364, March.
    15. Cui, Xin & Sensoy, Ahmet & Nguyen, Duc Khuong & Yao, Shouyu & Wu, Yiyao, 2022. "Positive information shocks, investor behavior and stock price crash risk," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 493-518.
    16. Linda Court Salisbury & Fred M. Feinberg, 2010. "Alleviating the Constant Stochastic Variance Assumption in Decision Research: Theory, Measurement, and Experimental Test," Marketing Science, INFORMS, vol. 29(1), pages 1-17, 01-02.
    17. Butler, John C. & Dyer, James S. & Jia, Jianmin & Tomak, Kerem, 2008. "Enabling e-transactions with multi-attribute preference models," European Journal of Operational Research, Elsevier, vol. 186(2), pages 748-765, April.
    18. Onesun Steve Yoo & Rakesh Sarin, 2018. "Consumer Choice and Market Outcomes Under Ambiguity in Product Quality," Marketing Science, INFORMS, vol. 37(3), pages 445-468, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:envirb:v:30:y:2003:i:3:p:391-410. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.