Rajendra P. Srivastava

A conceptual framework and belief-function approach to assessing overall information quality

We develop an information quality model based on a user‐centric view adapted from Financial Accounting Standards Board,1 Wang et al.,2 and Wang and Strong.3 The model consists of four essential attributes (or assertions): accessibility, interpretability, relevance, and integrity. Four subattributes lead to an evaluation of integrity: accuracy, completeness, consistency, and existence. These subattributes relating to integrity are intrinsic in nature and relate to the process of how the information was created and the first three attributes: (accessibility, interpretability, and relevance) are extrinsic in nature. We present our model as an evidential network under the belief‐function framework to permit user assessment of quality parameters. Two algorithms for combining assessments into an overall IQ measure are explored, and examples in the domain of medical information are used to illustrate key concepts. We discuss two scenarios, online user and assurance provider, which reflect two likely and important aspects of IQ evaluation currently facing information users—concerns about the impact of poor quality online information and the need for IQ assurance.

An Information Systems Security Risk Assessment Model Under the Dempster-Shafer Theory of Belief Functions

This study develops an alternative methodology for the risk analysis of information systems security (ISS), an evidential reasoning approach under the Dempster-Shafer theory of belief functions. The approach has the following important dimensions. First, the evidential reasoning approach provides a rigorous, structured manner to incorporate relevant ISS risk factors, related countermeasures, and their interrelationships when estimating ISS risk. Second, the methodology employs the belief function definition of risk--that is, ISS risk is the plausibility of ISS failures. The proposed approach has other appealing features, such as facilitating cost- benefit analyses to help promote efficient ISS risk management. The paper elaborates the theoretical concepts and provides operational guidance for implementing the method. The method is illustrated using a hypothetical example from the perspective of management and a real-world example from the perspective of external assurance providers. Sensitivity analyses are performed to evaluate the impact of important parameters on the models results.

Does the Year 2000 XBRL Taxonomy Accommodate Current Business Financial‐Reporting Practice?

XBRL (eXtensible Business Reporting Language) is an application of XML (eXtensible Markup Language) intended for use in digital business reporting. Observers predict XBRL will provide benefits to f...

Belief-Function Formulas for Audit Risk

This article relates belief functions to the structure of audit risk and provides formulas for audit risk under certain simplifying assumptions. These formulas give plausibilities of error in the belief-function sense.

Applications of Belief Functions in Business Decisions: A Review

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.

The Belief-Function Approach to Aggregating Audit Evidence

In this article, we present the belief‐function approach to aggregating audit evidence. the approach uses an evidential network to represent the structure of audit evidence. In turn, it allows us to treat all types of dependencies and relationships among accounts and items of evidence, and thus the approach should help the auditor conduct an efficient and effective audit. Aggregation of evidence is equivalent to propagation of beliefs in an evidential network. the article describes in detail the three major steps involved in the propagation process. the first step deals with drawing the evidential network representing the connections among variables and items of evidence, based on the experience and judgment of the auditor. We then use the evidential network to determine the clusters of variables over which we have belief functions. the second step deals with constructing a Markov tree from the clusters of variables determined in step one. the third step deals with the propagation of belief functions in the Markov tree. We use a moderately complex example to illustrate the details of the aggregation process.

An Expert System Approach to Audit Planning and Evaluation in the Belief-Function Framework

The main purpose of this article is to discuss an expert system approach for audit planning and evaluation using belief functions. First, we show how to use belief functions to represent strengths of various types of evidence such as positive, negative, or mixed items of evidence in an audit. The situation where one item of evidence relates to more than one audit objective or account is of special interest here, particularly the evidence that provides different levels of support to different audit objectives or accounts. Second, we illustrate the use of Auditors Assistant, an expert system shell, for planning and evaluation of an audit. For this illustration, we use an actual audit program of one of the Big Six accounting firms for the accounts receivable account of a health care unit. Third, two types of sensitivity analyses are performed on the evidential network (audit program) created above. The first one determines the effects of the location of evidence in the network and the second one deals with the effects of variations in the auditors judgment of the strength of evidence on the overall belief on each variable in the network. Finally, practical implications of the findings of the sensitivity analyses are discussed in the article.

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

Recently, Shafer and Srivastava [1], Srivastava and Shafer [2], Srivastava [3]–[4], and Van den Acker [5] have identified appealing features of belief function evidential networks. These networks can express the support that audit evidence provides for assertions, accounts and financial statements. These networks can also aggregate many pieces of evidence into an overall level of support for a particular assertion, account or an entire set of financial statements.

Belief functions in accounting behavioral research

Behavioral accounting research deals with a complex set of phenomenon including the broad domain of human decision making under uncertainty. Two aspects of decision making of particular relevance to accounting and auditing research are two constructs that are inexorably interrelated: uncertainty and information (evidence). This paper introduces a theoretical perspective that enriches the knowledge-set that may be used in behavioral accounting research when confronting decision contexts that involve uncertainly. The main body of the paper is an introduction to belief functions. The introduction includes a discussion of the fundamental constructs and then illustrates the use of belief functions in two audit settings: traditional financial statement audit planning and the evaluation of evidence in a cascaded-inference setting involving the ebaluation of internal accounting control. The paper concludes with a brief exploration of some of the research issues and opportunities that are related to the potential use of belief functions in behavioral accounting research.

An evidential reasoning approach to Sarbanes-Oxley mandated internal control risk assessment

In response to the enactment of the Sarbanes-Oxley Act 2002 and of the release of the Public Company Accounting Oversight Board (PCAOB) Auditing Standard No. 5, this study develops a risk-based evidential reasoning approach for assessing the effectiveness of internal controls over financial reporting (ICoFR). This approach provides a structured methodology for assessing the effectiveness of ICoFR by considering relevant factors and their interrelationships. The Dempster-Shafer theory of belief functions is utilized for representing risk.