Applications of Belief Functions in Business Decisions: A Review
Issue Date
2003Author
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/Metadata
Show full item recordAbstract
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/>.
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Citation
Srivastava, Rajendra. (2003) Applications of Belief Functions in Business Decisions: A Review.
Information Systems Frontiers, 5 (4), 359-378.
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