Year: 2003
Type: article
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.
Source: Information Systems Frontiers
Authors: Rajendra P. Srivastava, Liping Liu
Institutions: Ernst & Young (United States), University of Akron
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,290
OpenAlex ID: W2129456314