<p> Fictitious revenue recognition is the most prevalent upward fraudulent revenue recognition technique top executives utilize especially in the computer software industry. Examined in this quantitative research is the moderating effect of managerial overprecision (one of three forms of overconfidence) when top executives engage in fictitious revenue recognition to obtain a cash bonus and or to ensure the same level of salary. Participants are 29 graduate students in Business and Economics Department from a reputable university in New York. All participants are highly overconfident at a hit rate of 90%. Ten participants (approximately 35%) display a lower level of overconfidence at the lower 25–40% hit rates. At the 25–40% hit rates there was a statistically significant difference between means for overconfident executives who choose to manage earnings to influence their compensation and executives who do not exhibit overconfidence. Results from binary logistic regression showed opportunity is the better predictor variable of future earnings management, followed by rationalization (displacing responsibility), and then incentive. Incentive is the fictitious revenue technique of recording as sales items shipped to other locations. These three factors of the fraud triangle accounted for approximately 74% of the variability of the outcome variable rationalization behavior. Rationalization behavior is the tendency for perpetrators to change their beliefs about the ethicality of engaging in an unacceptable behavior and an attempt to negate the negative affect (emotion resulting from a decision or behavior). Recommendation for future research should include executives in companies in the computer hardware industry and computer software industry, diffusion of responsibility (another form of rationalization), and other fictitious revenue techniques. Companies should include those that the Securities and Exchange Commission (SEC) issued an Accounting and Auditing Enforcement Release (AAER) and those that did not receive an AAER.</p><p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:13426754 |
| Date | 12 February 2019 |
| Creators | Dass, Parmanand |
| Publisher | Northcentral University |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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