can low self-control help with the understanding of the software piracy problem?

ABSTRACT

Computer crime—specifically, software piracy—is growing, and no research in criminology examines whether low self-control can help us understand the behavior. This study examines the link that Gottfredson and Hirschi's (1990) idea of low self-control has with software piracy. Using a nonrandom sample of college students and measures of low self-control, software pirating peers, software pirating attitudes, and moral beliefs toward software piracy, the findings show that low self-control has a link with software piracy. This finding expands the scope of self-control theory and provides an understanding of why the behavior occurs.

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Acknowledgments

Notes

¹Important to Gottfredson and Hirschi's (1990) theory is opportunity. In this study, the scenarios provide the student with access to the software and the means to pirate the software, making opportunity equal for all of the students in the study (see Bichler-Robertson et al. 2003 for a similar view).

²Some may argue that this measure has problems with validity (see Piquero, MacIntosh, and Hickman 2001; DeLisi et al. 2003; Weibe 2003). However, others show that the attitude measure performs as well as behavioral measures (Pratt and Cullen 2000; Unnever, Cullen, and Pratt 2003). To examine the Grasmick et al. (1993) scale for the current study, each factor (impulsivity, simple tasks, risk-taking, physical, self-centered, and temper) were correlated. The findings from this correlation showed that all the factors had positive significant correlations with each other. Further, regression analysis was performed using each factor and the dependent measure to determine if any of the factors would have any opposite effects from the other factors. The findings from this analysis showed that all the factors had a positive influence on the dependent measure. Thus, the findings from these analyses show that the Grasmick et al. scale is suitable for use in the current study. Due to the conservation of space, specific coefficients are not presented here, but they are available from the author upon request.

³This measure may not accurately capture the full range of differential association measures (see Tittle, Burk, and Jackson 1986; Mazerolle et al. 2000). However, research of differential association contains several studies that use measures similar to these (see Akers et al. 1979; Krohn et al. 1985; Winfree, Griffiths, and Sellers 1989; Skinner and Fream 1997; Reed and Rose 1998; Akers and Lee 1999). In addition, the measure captures the exposure to deviant attitudes similar to other studies that use deviant peer association as a control variable in self-control theory (see Evans et al. 1997; Winfree and Bernat 1998; Burton et al. 1998).

*Denotes statistical significance at the .05 level.

*Denotes statistical significance at the .05 level.

*p < .05

⁴An additional subsample analysis was conducted that combined both software pirating peers and software pirating attitudes. In this analysis, low self-control was not significant in any of the subsamples. This suggests that this combination of measures may not completely condition the effect of low self-control on this particular form of software piracy. Due to space limits, these findings are available from the author upon request.