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    Applications of Belief Functions in Business Decisions: A Review

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    Srivastava_ApplicationsofBeliefFunctions.pdf (674.6Kb)
    Issue Date
    2003
    Author
    Srivastava, Rajendra P.
    Liu, Liping
    Publisher
    Springer
    Type
    Article
    Article Version
    Scholarly/refereed, author accepted manuscript
    Published Version
    http://www.som.buffalo.edu/isinterface/ISFrontiers/
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    Abstract
    In this paper, we review recent applications of Dempster-Shafer theory (DST) of belief functions to auditing and business decision-making. We show how DST can better map uncertainties in the application domains than Bayesian theory of probabilities. We review the applications in auditing around three practical problems that challenge the effective application of DST, namely, hierarchical evidence, versatile evidence, and statistical evidence. We review the applications in other business decisions in two loose categories: judgment under ambiguity and business model combination. Finally, we show how the theory of linear belief functions, a new extension of DST, can provide an alternative solution to a wide range of business problems.
    Description
    This is the author's final draft. The publisher's official version is available from: <http://www.som.buffalo.edu/isinterface/ISFrontiers/>.
    URI
    http://hdl.handle.net/1808/10998
    DOI
    https://doi.org/10.1023/B:ISFI.0000005651.93751.4b
    Collections
    • School of Business Scholarly Works [207]
    Citation
    Srivastava, Rajendra. (2003) Applications of Belief Functions in Business Decisions: A Review. Information Systems Frontiers, 5 (4), 359-378.

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    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

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