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    Predicting the dynamic nature of risk

    20212_downloaded_stream_200.pdf (198.1Kb)
    Access Status
    Open access
    Authors
    Hussain, Omar
    Chang, Elizabeth
    Hussain, Farookh
    Dillon, Tharam S.
    Soh, B.
    Date
    2006
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Hussain, Omar and Chang, Elizabeth and Hussain, Farookh and Dillon, Tharam and Soh, Ben. 2006. : Predicting the dynamic nature of risk, ACS/IEEE International Conference on Computer Systems and Applications (AICCSA), Mar 08 2006, pp. 500-507. Dubai, UAE: IEEE Computer Society Press.
    Source Title
    Proceedings of the 4th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA)
    Source Conference
    ACS/IEEE International Conference on Computer Systems and Applications (AICCSA)
    Faculty
    Curtin Business School
    School
    Centre for Extended Enterprises and Business Intelligence
    Remarks

    Copyright 2006 IEEE

    This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

    URI
    http://hdl.handle.net/20.500.11937/22768
    Collection
    • Curtin Research Publications
    Abstract

    The trusting peer in order to determine the likelihood of the loss in its resources might analyze the Risk before engaging in an interaction with any trusted peer. This likelihood of the loss in the resources is termed as Risk in the interaction. Risk analysis is important in e-commerce transactions because of the vast literature that argues that the decision to buy is based on the Risk-adjusted cost benefit analysis. If the trusting peer can determine the future Riskiness value or reputation of a trusted peer for the time period of its interaction, before engaging in an activity with it, then it can ease its decision making process of whether to interact with the trusted peer or not. In this paper we present such a novel method which predicts the dynamic nature of Risk and determines the future Riskiness value of the trusted peer, before the interaction starts, thus helping the trusting peer considerably in making its decision.

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