Track: Academic Research on XBRL, Session 82,

1. 22nd XBRL International Conference“Sharing Economic Information in a Global World: the XBRL Contribution”17-19 May 2011Brussels, Belgium Track: Academic Research on XBRL, Session 82, XBRL-Enabled, Excel or PDF? The Effects of Technology Choice on the Analysis of Financial Information Diane Janvrin, Maureen Mascha, and Robert Pinsker May 19, 2011

2. Overview Motivation Purposes Design Results Implications

3. Motivation • CFOs question value of furnishing XBRL-tagged financial information • Proponents argue that financial statements created in the XBRL format will provide more transparent data for investors performing financial statement analysis (tagged info leads to drill-down capabilities) • SEC mandated that publicly-traded companies furnish financial information in XBRL format beginning in June 2009 • Given that firms’ websites and the SEC’s site post firms’ financial information in multiple data formats, will investors choose to use an XBRL-enabled tool to analyze information using the XBRL data format or a technology (presentation formats) they are more experienced with (PDF or Excel)? Why? • User choice theory suggests that technology created for a specific purpose was not chosen by the intended users • Hodge et al. (2004) finds that XBRL-formatted data provides a better data search functionality; however, almost 50 percent of participants did not choose it

4. Problem with Prior Research • Prior research did not require participants to choose among XBRL-enabled technological tools or other technological tools (henceforth, “technologies”) to perform financial analysis • Important since in general investors will choose between technologies due to efficiency issues, minimize cognitive effort, heuristics, habit, or belief that additional technology will result in only marginal gains

5. Purposes • Expand user choice theory to technology choice (defined as decision among alternative technologies) • Examine whether investors will choose XBRL-formatted data using an XBRL-enabled technological tool for financial statement analysis • Examine whythey choose the specific technology

6. Hypothesis Development – User Choice Theory Evolved from rational choice theory: assumes decision-makers pursue behaviors at lowest possible costs, given beliefs. Prevailing thought: to the extent decision maker chooses rationally, choice should improve task performance But, multiple studies found that decision-makers do NOT make optimal decisions due to ambiguity avoidance, perceived high domain expertise, high self-determination Also, evoking one’s own mental model is big Investors presented with multiple technologies engage in some form of choice behavior, either Rely on one technology to the exclusion of the others **** Use one technology for one instance of a task, but use other technologies subsequently H1: The technology nonprofessional investors choose to complete the financial analysis task will be directly related to perceived task efficiency (i.e., perceived less time to complete task).

7. Hypothesis Development - Experience and Cognitive Fit Theory • Cognitive fit suggests that task effectiveness increases as the three-way match among (problem representation), (2) problem solving tasks, and (3) user problem solving skill set increases • Users may resist giving up familiar software and learning new software even though the new software is perceived to be better (Hayes 2004) • Jones and Schkade (1995) find that decision makers tend to choose the problem representation with which they have the most experience • Arkes et al. (1986) find that those with perceived higher levels of domain expertise tend not to use a given decision rule • H2: Consistent with cognitive fit theory, a nonprofessional investor’s technology choice will be directly related to his/her experience with that technology.

8. Hypothesis Development – Technology Acceptance Model (TAM) Proposes that when users are provided new technology (e.g. XBRL-enabled technology, XBRL data format), their perceptions of the technology’s usefulness and ease of use significantly influences their acceptance and assumed usage of the technology (Davis 1989; Bagozzi et al. 1992 ) Perceived usefulness Degree to which a person believes that using a technology could enhance his / her job performance Perceived ease of use Degree to which a person believes that using a technology could be free from effort But, user choice theory contradicts this (acceptance is a necessary, but NOT sufficient condition for usage) H3a: The technology nonprofessional investors choose to complete the financial analysis task will be directly related to perceived usefulness.  H3b: The technology nonprofessional investors choose to complete the financialanalysis task will be directly related to perceived ease of use.

9. Experimental Procedure FIGURE 1 Experimental Procedure Part 1 Part 2 Train XBRL Perform Task Part 3Complete Questions Introduction Make Choice Train Excel Train PDF

10. Participants • 53 graduate business students enrolled in financial statement analysis course • Completed the task online (out-of-lab), symbolic of day-traders • Made initial investment judgment for two companies – viewed financial information in Word format • Chose one of the “technologies” to complete investment analysis task • Completed investment analysis task (investment decision model comprised of 3 weighted ratios) using chosen “technology” • Completed at least two undergraduate financial accounting courses • Over 30 percent had previously bought or sold common stock or mutual funds • 66 percent intended on buying stock in the next five years • On average, analyzed financial statements over five times

11. Variables • Dependent: Technology choice (PDF, Excel, or XBRL-enabled (I-Metrix)) • Independent: • Efficiency • Takes less time to perform task • Perceived usefulness (TAM, one-question, direct measure) • Perceived ease of use (TAM, one-question, direct measure) • Prior technology experience (Cognitive fit) • Researchers wanted me to choose it (Demand effect) • Latest state-of-the-art technology (Demand effect)

12. Correlation Analysis TABLE 2 Pearson Correlations for All Variables of Interest Trying to Predict Technology Choice * p-value < 0.10 ** p-value < 0.05 *** p-value < 0.01

13. Results – Kruskal-Wallis TABLE 3 Results of Kruskal-Wallis Testing for Technology Choice Factors

14. Further Analysis • We do not find statistical significance in identifying a single reason for Technology Choice: either in aggregate or separating into Excel vs. XBRL-enabled choosers • Mean prior experience was higher with Excel (7.21) than XBRL-enabled (3.38); t = 27.40, p < .0001, supplementing H2 testing • Chi-square testing did not find any relationship between choosing the “correct” company to invest in (either initially or after calculating the investment decision model) and Technology Choice (no accuracy effect) • Similarly, we found no affect on Technology choice for those who 1) changed their minds on which company to invest in initially to ending or 2) those who changed from incorrect/correct company to invest in to the opposite

15. Further Analysis • With regard to perceived importance of using the Investor Decision Model and Technology Choice… • We found that the mean of the Excel choosers (7.17, S.D. = 1.25) was only marginally higher than the XBRL-enabled technology choosers (6.23, S.D. = 1.86; t = 1.92, p-value = 0.06): weak evidence • Lastly, motivated by Hodge et al. (2004)’s argument that XBRL-formatted data will facilitate information acquisition, we asked participants which technology (PDF, Excel, or XBRL-enabled tool) they would prefer to use to acquire a company’s financial information • Thirty participants chose XBRL-enabled (56.6 percent), 21 chose Excel (39.6 percent), and two chose PDF (3.8 percent), but former two choices not significantly different (χ2 = 1.59, p-value = 0.21)

16. Summary • We extend user choice lit to more specific “Technology Choice” • Extend Hodge et al. 2004 • We provide evidence of nonprofessional investors’ choice of XBRL-formatted data using an XBRL-enabled tool over Excel and PDF • We provide evidence as to why nonprofessional investors would choose a specific technology • Users who chose the XBRL-enabled tool perceive that it reduces time required to complete the task (increases task efficiency) • Users who chose Excel base their choice on greater experience working with Excel than XBRL-enabled tool

17. Research Limitations • Time constraints • We may have missed a common technology/format • Experiment assumes a cost-free investing environment • Use of graduate business students as nonprofessional investor proxies • While we pilot tested our experiment using both Savanet and I-Metrix as our proxies for XBRL-enabled technological tools, we used only I-Metrix which provides users with additional financial statement items not available via XBRL format for the actual experiment.   • Use of single task to measure non professional investor technology choice • Could choice be impacted by task complexity?

18. Implications Need to increase knowledge of benefits a combination of XBRL formatted data and XBRL-enabled tools provide Training may be helpful