Belief Functions in Business Decisions

1. Front Matter

   Pages I-X

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2. Foundations

   1. Introduction to Belief Functions

      • Rajendra P. Srivastava, Theodore J. Mock

      Pages 1-16

   2. Decision Making in a Context where Uncertainty is Represented by Belief Functions

      • Philippe Smets

      Pages 17-61

   3. Empirical Models for the Dempster-Shafer-Theory

      • Mieczysław Alojzy Kłopotek, Sławomir Tadeusz Wierzchoń

      Pages 62-112

3. Systems and Auditing Applications

   1. The Descriptive Ability of Models of Audit Risk

      • Gary Monroe, Juliana Ng

      Pages 113-138

   2. The Effectiveness and Efficiency of Belief Based Audit Procedures

      • Maximilian K. P. Jung, Herwig E. Fink

      Pages 139-160

   3. Auditors’ Evaluations of Uncertain Audit Evidence: Belief Functions versus Probabilities

      • Keith E. Harrison, Rajendra P. Srivastava, R. David Plumlee

      Pages 161-183

   4. Conflict, Consistency and Consonance in Belief Functions: Coherence and Integrity of Belief Systems

      • Peter R. Gillett

      Pages 184-221

4. Operations Management, Finance and Economics Applications

   1. Evaluating Mergers and Acquisitions: A Belief Function Approach

      • Rajendra P. Srivastava, Deepak K. Datta

      Pages 222-251

   2. Possibilistic Belief Network Constructed by Operators of Composition and its Application to Financial Analysis

      • Radim Jiroušek, Jiřina Vejnarová, Jozef Gemeľa

      Pages 252-280

   3. Using Belief Functions to Forecast Demand for Mobile Satellite Services

      • Peter McBurney, Simon Parsons

      Pages 281-315

   4. Modeling Financial Portfolios Using Belief Functions

      • Catherine Shenoy, Prakash P. Shenoy

      Pages 316-332

   5. Futures Hedging under Prospect Utility and Knightian Uncertainty

      • Donald Lien

      Pages 333-345

5. Back Matter

   Pages 346-346

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The book focuses on applications of belief functions to business decisions. Section I introduces the intuitive, conceptual and historical development of belief functions. Three different interpretations (the marginally correct approximation, the qualitative model, and the quantitative model) of belief functions are investigated, and rough set theory and structured query language (SQL) are used to express belief function semantics. Section II presents applications of belief functions in information systems and auditing. Included are discussions on how a belief-function framework provides a more efficient and effective audit methodology and also the appropriateness of belief functions to represent uncertainties in audit evidence. The third section deals with applications of belief functions to mergers and acquisitions; financial analysis of engineering enterprises; forecast demand for mobile satellite services; modeling financial portfolios; and economics.

• Audit
• Auditing
• Belief Functions
• Evidential Reasoning
• Mergers and Acquisitions
• Rough Set Theory
• SQL
• auditor
• calculus
• decision theory
• information system
• modeling
• uncertainty

• School of Business, Ernst & Young Center for Auditing Research and Advanced Technology, The University of Kansas, Lawrence, USA

  Rajendra P. Srivastava

• Laventhal School of Accounting, University of Southern California, Los Angeles, USA

  Theodore J. Mock

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