Graduation Year

2008

Document Type

Dissertation

Degree

Ph.D.

Degree Granting Department

Accounting

Major Professor

Uday Murthy, Ph.D.

Co-Major Professor

Jacqueline Reck, Ph.D.

Committee Member

Stephanie Bryant, Ph.D.

Committee Member

Brad Schafer, Ph.D.

Committee Member

Rosann Collins, Ph.D.

Keywords

Three-dimensional, Trend analysis, Pattern recognition, Cognitive fit

Abstract

This study is the first in a series of planned studies on the application of multidimensional visualization of business information and data within the context of accounting. The study's research question is: When is multidimensional visualization of information a better problem representation, improving both the effectiveness and efficiency of a spatial accounting judgment?

To examine when multidimensional visualization can assist auditors in configural cue pattern recognition, the study employs the traditional DuPont analysis as the three pieces of key information to be represented on the X, Y, and Z axes of a single 3-D perspective display. To help determine when use of 3-D perspective display is beneficial in combining pieces of information, I rely on Vessey's (1991) Cognitive Fit Theory, and the Proximity Compatibility Principle (PCP) proposed by Wickens and Carswell (1995).

The study has two hypotheses. Hypothesis H1 predicted that participants viewing a set of 2-D displays will be the most effective or most efficient in generating hypotheses for what caused the changes in the trend of accounting data or in estimating values. Hypothesis H2 predicted that participants viewing a single 3-D perspective display will be the most effective or most efficient in recognizing patterns of accounting data or in generating hypotheses for what caused the emerged pattern.

To test the hypotheses of the study a 3 x 2 between-subjects design (display format x task) is used. The independent variables are display types and task types. Graphical display was manipulated at three levels: no graphical display (table only), 2-D display, and 3-D perspective display. Task was manipulated at two levels: trend analysis and pattern recognition task.

The need for a fit between different types of spatial tasks and display formats is demonstrated by the findings of this study: 1) that 2-D displays appear to be more suitable for spatial tasks involving the generation of hypotheses for causes of trends in accounting data, while 2) 3-D perspective displays appear to be more suitable for spatial tasks involving pattern recognition in accounting data.

Download

Share

COinS