IDEAS home Printed from https://ideas.repec.org/a/jas/jasssj/2005-13-2.html

On the Simulation of Global Reputation Systems

Author

Listed:

Abstract

Reputation systems evolve as a mechanism to build trust in virtual communities. In this paper we evaluate different metrics for computing reputation in multi-agent systems. We present a formal model for describing metrics in reputation systems and show how different well-known global reputation metrics are expressed by it. Based on the model a generic simulation framework for reputation metrics was implemented. We used our simulation framework to compare different global reputation systems to find their strengths and weaknesses. The strength of a metric is measured by its resistance against different threat-models, i.e. different types of hostile agents. Based on our results we propose a new metric for reputation systems.

Suggested Citation

  • Andreas Schlosser & Marco Voss & Lars Brückner, 2005. "On the Simulation of Global Reputation Systems," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-4.
    • Handle: RePEc:jas:jasssj:2005-13-2
    as

    Download full text from publisher

    File URL: https://www.jasss.org/9/1/4/4.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dellarocas, Chrysanthos, 2003. "Efficiency and Robustness of Binary Feedback Mechanisms in Trading Environments with Moral Hazard," Working papers 4297-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. Eric J. Friedman* & Paul Resnick, 2001. "The Social Cost of Cheap Pseudonyms," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 10(2), pages 173-199, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bruce Edmonds, 2012. "Context in social simulation: why it can’t be wished away," Computational and Mathematical Organization Theory, Springer, vol. 18(1), pages 5-21, March.
    2. Behrooz Hassani-Mahmooei & Brett W. Parris, 2014. "Dynamics of effort allocation and evolution of trust: an agent-based model," Computational and Mathematical Organization Theory, Springer, vol. 20(2), pages 133-154, June.

    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. Luís Cabral & Ali Hortacsu, 2004. "The Dynamics of Seller Reputation: Theory and Evidence from eBay," Working Papers 04-05, New York University, Leonard N. Stern School of Business, Department of Economics.
    2. Drew Fudenberg & David K. Levine & Satoru Takahashi, 2008. "Perfect public equilibrium when players are patient," World Scientific Book Chapters, in: Drew Fudenberg & David K Levine (ed.), A Long-Run Collaboration On Long-Run Games, chapter 16, pages 345-367, World Scientific Publishing Co. Pte. Ltd..
    3. Gary E. Bolton & Elena Katok & Axel Ockenfels, 2004. "How Effective Are Electronic Reputation Mechanisms? An Experimental Investigation," Management Science, INFORMS, vol. 50(11), pages 1587-1602, November.
    4. Claudia Keser & Maximilian Späth, 2020. "The Value of Bad Ratings: An Experiment on the Impact of Distortions in Reputation Systems," CIRANO Working Papers 2020s-22, CIRANO.
    5. Gaudeul, Alexia & Giannetti, Caterina, 2017. "The effect of privacy concerns on social network formation," Journal of Economic Behavior & Organization, Elsevier, vol. 141(C), pages 233-253.
    6. Sezgin Ayabakan & Indranil R. Bardhan & Zhiqiang (Eric) Zheng, 2024. "Impact of Telehealth and Process Virtualization on Healthcare Utilization," Information Systems Research, INFORMS, vol. 35(1), pages 45-65, March.
    7. Chrysanthos Dellarocas, 2005. "Reputation Mechanism Design in Online Trading Environments with Pure Moral Hazard," Information Systems Research, INFORMS, vol. 16(2), pages 209-230, June.
    8. Chrysanthos Dellarocas, 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science, INFORMS, vol. 49(10), pages 1407-1424, October.
    9. Paul Resnick & Richard Zeckhauser & John Swanson & Kate Lockwood, 2006. "The value of reputation on eBay: A controlled experiment," Experimental Economics, Springer;Economic Science Association, vol. 9(2), pages 79-101, June.
    10. Chrysanthos Dellarocas, 2006. "Strategic Manipulation of Internet Opinion Forums: Implications for Consumers and Firms," Management Science, INFORMS, vol. 52(10), pages 1577-1593, October.
    11. Scott Fay, 2004. "Partial-Repeat-Bidding in the Name-Your-Own-Price Channel," Marketing Science, INFORMS, vol. 23(3), pages 407-418, February.
    12. Chrysanthos Dellarocas, 2006. "How Often Should Reputation Mechanisms Update a Trader's Reputation Profile?," Information Systems Research, INFORMS, vol. 17(3), pages 271-285, September.
    13. Hristo Katrandjiev & Ivo Velinov, 2014. "Investigation of Online Visual Merchandising (OVM) Elements of Apparel Web Stores," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 1, pages 84-98, January.
    14. Hortacsu, Ali, 2005. "Trust and Reputation on eBay: Micro and Macro Perspectives," Department of Economics, Working Paper Series qt8vj7d50q, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    15. Antonio Moreno & Christian Terwiesch, 2014. "Doing Business with Strangers: Reputation in Online Service Marketplaces," Information Systems Research, INFORMS, vol. 25(4), pages 865-886, December.
    16. Lingfang (Ivy) Li & Erte Xiao, 2014. "Money Talks: Rebate Mechanisms in Reputation System Design," Management Science, INFORMS, vol. 60(8), pages 2054-2072, August.
    17. Richard Arena & Bernard Conein, 2008. "On virtual communities: individual motivations, reciprocity and we-rationality," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 55(1), pages 185-208, April.
    18. Dellarocas, Chrysanthos, 2003. "Efficiency and Robustness of Binary Feedback Mechanisms in Trading Environments with Moral Hazard," Working papers 4297-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    19. Yan Chen & Joseph Konstan, 2015. "Online field experiments: a selective survey of methods," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 1(1), pages 29-42, July.
    20. Nicole Immorlica & Brendan Lucier & Brian W. Rogers, 2010. "Emergence of Cooperation in ANonymous Social Networks through Social Capital," 2010 Meeting Papers 1134, Society for Economic Dynamics.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:jas:jasssj:2005-13-2. 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: Francesco Renzini (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.