Applications of Belief Functions in Business Decisions: A Review

Rajendra P. Srivastava () and Liping Liu ()
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Rajendra P. Srivastava: The University of Kansas
Liping Liu: University of Akron

Information Systems Frontiers, 2003, vol. 5, issue 4, No 4, 359-378

Abstract: Abstract In this paper, we review recent applications of the Dempster-Shafer theory (DST) of belief functions to auditing and business decision-making. We show how DST can better map uncertainties in 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 to DST, can provide an alternative solution to a wide range of business problems.

Keywords: Dempster-Shafer theory of belief functions; linear belief functions; audit decision; hierarchical evidence; versatile evidence; statistical evidence; judgment under ambiguity (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (4)

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DOI: 10.1023/B:ISFI.0000005651.93751.4b

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