The Impact of Hypothesis Set Size on the Time Efficiency and Accuracy of Analytical Review Judgments

Bhattacharjee, Sudip; Kida, Thomas; Hanno, Dennis M.

doi:10.2307/2491397

Cited by 25 publications

(21 citation statements)

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“…13. As reported in Bhattacharjee et al (1999), the time spent on data search and evaluation (in minutes) for each group was as follows: one hypothesis group (mean = 11.23; SD = 5.82; Range = 4.87 to 23.93), three hypotheses group (mean = 7.41; SD = 3.07; Range = 4.02 to 15.51), six hypotheses group (mean = 8.64; SD = 4.14; Range = 3.55 to 18.64), and no-restriction group (mean = 12.06; SD = 5.89; Range = 3.61 to 22.51). 14.…”

Section: Notessupporting

confidence: 54%

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The Impact of Generating Initial Hypothesis Sets of Different Sizes on the Quality of the Initial Set, and the Resulting Time Efficiency and Final Judgment Accuracy

Bhattacharjee

Machuga

2004

Int J Auditing

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This study examines the impact of generating initial hypothesis sets of different sizes on the quality of the hypotheses generated (i.e., the ability to consider both the direction and accounts that are over-or understated). We also examine the time efficiency, information search effectiveness, and the final judgment accuracy, conditional on the quality of the initial hypothesis set. Sixty auditors performed an analytical procedures task where they were asked to generate and test either a specific number of initial hypotheses (one, three, or six), or any number of hypotheses desired in order to uncover an error seeded in the financial statements. The results indicate that the three hypotheses group initially generated hypotheses of the highest quality and maintained the hypothesis quality after efficiently searching information and generating additional causes. The one hypothesis group improved the quality of their hypotheses only after generating and testing several causes. However, auditors who generated six hypotheses or any number desired (as in audit practice) considered hypotheses of lower quality in the initial set, and did not improve the hypotheses quality after going through the information search stage. These results suggest that the size of the initial hypothesis set can lead to differences in the gains that accrue from the hypothesis generation and information search stages of diagnostic decisions. SUMMARYWhen auditors observe an amount in a company's financial statement that is different from their expectation, professional standards require that they investigate the fluctuation and identify its true cause (e.g., SAS No. 56, AICPA 1988; SAS No. 99, AICPA 2002). In so doing, auditors engage in a diagnostic process where potential causes (i.e., hypotheses) for the observed deviations are generated. Thereafter, auditors perform a detailed information search to determine the cause of the fluctuation. Once the auditor is relatively certain that there is enough evidence to support a hypothesis, he/she may stop the search and select the hypothesis as the believed true cause, otherwise the process of generating and testing hypotheses continues.Research suggests that generating the correct cause in the initial set increases the chances of identifying the true cause of a fluctuation. However, in the absence of initially generating the correct cause, auditors may be able to rely on their causal understanding of the financial statements to make 'educated guesses.' That is, generating hypotheses of high quality (i.e., hypotheses that correctly identify both the direction and accounts that are over-or understated) may induce an information search that can ultimately lead to the discovery of the correct cause. One factor that could impact both the hypotheses generated and the information searched is the size of the initial hypothesis set. This study investigates the impact of asking auditors to generate and test initial hypothesis sets of different sizes on the quality of the initial set as well as the quality of...

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Section: Notessupporting

confidence: 54%

“…9. This study uses data from Bhattacharjee et al (1999) but significantly extends that study in ways mentioned in the text. 10.…”

Section: Notesmentioning

confidence: 93%

The Impact of Generating Initial Hypothesis Sets of Different Sizes on the Quality of the Initial Set, and the Resulting Time Efficiency and Final Judgment Accuracy

Bhattacharjee

Machuga

2004

Int J Auditing

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“…Learners have difficulty when the novel cases involve more than minor changes from what they encountered in the training materials (Catrambone 1998). Because the amount and type of information searched and the information search processes used depend on the initial hypothesis being evaluated (Nendaz, Gut, Perrier, Louis-Simonet, Reuille, Junod, and Vu 2005;Bhattacharjee et al 1999), the hypothesis-evaluation process during analytical procedures varies from problem to problem depending on the type of hypotheses being evaluated. For example, the evaluation process for one hypothesis may involve synthesizing information from budgeted and industry data, while evaluation for a different hypothesis could involve accessing ratio information from analytical procedures on a specific account and, if necessary, generating a new set of hypotheses if the initial hypothesis is inadequate.…”

Section: Knowledge Acquisition Through Examples and Self-explanationmentioning

confidence: 99%

“…Senior auditing students in the six training groups received training in both the hypothesis-generation and hypothesis-evaluation stages when completing three detailed cases validated in prior research (Cohen and Kida 1989;Cohen 1994). Thereafter, all participants used a comprehensive set of working papers to uncover a complex seeded error in a final analytical procedures case that has been used in prior research with practicing auditors (Bhattacharjee, Kida, and Hanno 1999). A senior manager and an audit partner evaluated each response on the final case to assess decision accuracy.…”

Section: Introductionmentioning

confidence: 99%

The Effectiveness of Alternative Training Techniques on Analytical Procedures Performance*

Moreno

Bhattacharjee

Brandon

2007

Contemporary Accting Res

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“…However, since data were not gathered on the probability assessments of competing hypotheses, direct evidence was not provided to determine the precise nature of the probability revision process employed. Bhattacharjee et al (1999) examine the impact of hypothesis set size on hypothesis evaluation. They posit that there is an optimal number of hypotheses for the auditor to consider in balancing effectiveness and efficiency.…”

Section: Hypothesis Evaluationmentioning

confidence: 99%

Multiple hypothesis evaluation in auditing

Srivastava

Wright

Mock

2002

Accounting & Finance

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In many audit tasks, auditors evaluate multiple hypotheses to diagnose the situation. Research suggests this is a complex task that individuals have difficulty performing. Further, there is little guidance in professional standards or literature dealing with the many complexities present in the audit environment. Using probability theory, this study derives the appropriate revision of likelihoods for multiple hypotheses given different realistic audit conditions. The analysis shows that the relationships among the hypotheses dramatically impact the use of audit evidence and the resulting pattern of probability revisions. We also identify testable hypotheses to guide future research and discuss practice implications regarding ways to improve the effectiveness of analytical procedures.

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The Impact of Hypothesis Set Size on the Time Efficiency and Accuracy of Analytical Review Judgments

Cited by 25 publications

References 0 publications

The Impact of Generating Initial Hypothesis Sets of Different Sizes on the Quality of the Initial Set, and the Resulting Time Efficiency and Final Judgment Accuracy

The Impact of Generating Initial Hypothesis Sets of Different Sizes on the Quality of the Initial Set, and the Resulting Time Efficiency and Final Judgment Accuracy

The Effectiveness of Alternative Training Techniques on Analytical Procedures Performance*

Multiple hypothesis evaluation in auditing

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