Running Head: SOFTWARE PIRACY

Software Piracy 7

Running Head: SOFTWARE PIRACY

Software Piracy and Gender

Chris Inman

The University of Alabama

Software Piracy and Gender

In 2006, businesses lost more than $5 billion worldwide due to software piracy, representing a percentage increase in losses of 15% (Business Software Alliance, 2006). Several attributes are believed to be connected to people who engage in software pirating, including gender, age, family income, and attitude (Leonard, Cronan, & Kreie, 2004; Moores & Dhillon, 2000; Rahim, Seyal, & Rahman, 2001). In this paper the role gender plays in software piracy is investigated. It is hypothesized that males are more likely to pirate software and to use pirated software than are females. The following literature reviews attempt to demonstrate and support the above stated hypothesis.

In a two-part study by Tang and Fam (2005), researchers attempted to discover how interpersonal influence impacted personal software piracy use. In part one, a lab experiment with 54 subjects (43 males and 11 females) was conducted in which participants were asked to evaluate software. However, researchers secretly measured the subjects’ intention to pirate software under different levels of pressure and possible financial gain. Researchers hypothesized that groups would positively affect intention to pirate software, that financial gains positively affect intention to pirate software, and that the impact of group pressure on intention to pirate software would be lessened by possible financial gain. The results in part one of the studies confirmed the researchers’ hypotheses, thus prompting the researchers to conduct part two. In part two, 206 students (69% male and 31% female) from two public undergraduate universities in Taiwan completed a survey in which two questions were examined. First, what type of interpersonal influence affects an individual’s intention to pirate software? Second, is interpersonal influence directly related to pirating software behavior? Researchers hypothesized that normalizing behavior positively influences intention to pirate software, that information positively influences pirating software behavior, and that pirating intention is positively related to pirating behavior. The survey results supported two of three hypotheses, but did not support the hypothesis that information positively influences pirating software behavior. However, in regards to this literature review, the results confirmed the hypothesis that males are more likely to pirate software and to use pirated software by finding that males are typical software pirates. Additionally, researchers found that some demographic data, such as gender, may influence both intention and behavior (Tang and Fam, 2005)

Several limitations of Tang and Fam’s (2005) study are present. First, respondents came exclusively from undergraduate public schools in Taiwan. Second, respondents held majors exclusively in information systems and computer science. Third, an overwhelming majority of respondents were male. Fourth, several factors were excluded from study, such as cultural factors. These limitations impact the ability to use this information in making generalizations, but it would be possible to compare the data to similar business schools students at other public universities.

The next study, conducted by Rahim, Rahman, and Seyal (2000) focuses much more upon gender when compared to the previous study. The researchers attempted to answer whether intention to pirate software was influenced by several factors, including attitude, gender, degree major, family income, computer ownership, computer experience, institutional staff attitude, and institutional monitoring (Rahim et al., 2000, p. 49-50). A total of 490 students in the country of Brunei Darussalam were sent questionnaire surveys, and 432 students (205 males and 227 females) responded. The surveys contained three sections. Section A collected background information, section B two software piracy scenarios, and section C contained statements intended to measure attitudes and beliefs in relation to software piracy. The results were also subjected to correlation analysis, t-tests, and multiple regression analysis.

The data revealed mixed results. In the first scenario, a t-test showed that males displayed a greater intention to use pirated software than did females. In the second scenario, a multiple regression analysis revealed no statistical significance between gender and intention to pirate software (Rahim et al, 2000). Therefore, it is difficult to claim that these results support the hypothesis that males are more likely than females to pirate software and to use pirated software. There are also several limitations to the study. First, results are restricted to college students from one small country, Brunei Darussalam. Second, the survey was not administered to students at Brunei Darussalam’s one university due to unexpected procedural problems. Third, the students surveyed majored only in computing, business, or engineering.

The results of the third study, by Sims, Cheng, and Teegen (1996) more strongly support the hypothesis that males are more likely to pirate software and to use pirated software. The primary goal of the study was to identify the difference between students who pirate software and those who do not pirate software. Further, the researchers hypothesized that male students were more likely to pirate software than female students. The research instrument used to conduct the study was a survey questionnaire, which was pilot-tested and then revised. The sample included 73 Masters in Business Administration (MBA) students, 27 Executive MBA students, and 240 undergraduate business students.

The results of the survey indicated a statistically significant difference between males and females in terms of software piracy. Males indicated they had pirated software more than females had in the past year. Males also indicated that they had pirated, overall, more different types of software than did females. Therefore, the results support the hypothesis that males are more likely than females to pirate software and to use pirated software. The study, however, did have several limitations. First, the study focused only business school students. Second, the study used students from only one institution. Third, the study does not include non-students. Fourth, the results of the survey are completely dependent upon student self-reporting. Applying these results to all males and females is difficult, since only students from one school (business school) at one institution are studied.

The next study by Higgins (2006) supports the results found by Sims et al (1996 ) and Tang and Fam (2005). The main goal of this study was to determine whether low self-control and/or social learning theory could reduce the software piracy gender gap. However, Higgins (2006) first had to confirm that such a gap existed, and that males were more likely to pirate software than females. The main research instrument used was a survey questionnaire requiring students to self-report. Only students at one university who were present the day of class in which the survey was administered were asked to complete the survey, and 392 students responded. Of the 392 respondents, 61% were males and 39% were females (Higgins, 2006), and all students were liberal arts majors. The results of the survey supported the hypothesis that a gender gap exists in regards to software piracy. In fact, gender was found to have a statistically significant relationship to software piracy, and was found to be directly linked to software piracy (Higgins, 2006).

These results support the hypothesis that males are more likely than females to engage in acts of software piracy. There are limitations to this study, however. One limitation is that the study presents information from only one university. Another limitation is that the study is one time study, and no longitudinal data is included. A third limitation is that only liberal arts majors were surveyed. A fourth limitation is that survey results are entirely dependent upon student self-reporting. Despite these limitations, the results do support the findings of other studies with similar limitations (Sims et al, 1996; Tang and Fam, 2005) and therefore warrant consideration.

Resources

Business Software Alliance. (2006). Fourth annual BSA and IDC global software piracy study. BSA.org. Article retrieved November 27, 2007: http://w3.bsa.org/globalstudy//upload/2007-Global-Piracy-Study-EN.pdf

Higgins, G.E. (2006). Gender differences in software piracy: The mediating roles of self-control theory and social learning theory. Journal of Economic Crime Management, 4(1), p. 1-30.

Leonard, L.N.K., Cronan, T.P., & Kreie, J. (2004). What influences IT ethical behavior intentions—planned behavior, reasoned action, perceived importance, or individual characteristics. Information & Management, 42(1), p. 143-158.

Moores, T. & Dhillon, G. (2000). Software piracy: A view from Hong Kong. Communications of the ACM, 43(12), p. 88-93

Rahim, M.M., Rahman, M.NA., & Seyal, A.H.,. (2000). Softlifting intention of students in academia: A normative model. Malaysian Journal of Computer Science, 13(1), p. 28-55.

Rahim, M.M., Seyal, A.H., & Rahman, M.NA. (2001). Factors affecting softlifting intentions of students: An empirical study. Journal of Educational Computing Research, 24(4), p. 385-405.

Sims, R.R., Cheng, H.K., & Teegen, H. (1996). Toward a profile of student software piraters. Journal of Business Ethics, 15(8), p. 839-849.

Tang, J.H., & Fam, C.K. (2005). The effect of interpersonal influence on softlifting intention and behavior. Journal of Business Ethics, 56(2), p. 149-161.