Computers in Human Behavior 25 (2009) 718–722

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Computers in Human Behavior

journal homepage: www.elsevier .com/locate /comphumbeh

Adolescent self-control and music and movie piracy

Jenessa Malin a, Blaine J. Fowers b,*

a Duke University, P.O. Box 97291, Wannamaker 213, Durham, NC 27708, USAb Department of Educational and Psychological Studies, P.O. Box 248065, University of Miami, Coral Gables, FL 33124, USA

a r t i c l e i n f o a b s t r a c t

Article history:Available online 4 February 2009

Keywords:AdolescentDeviant peersInternet piracyMusic piracySelf-control

0747-5632/$ - see front matter � 2009 Elsevier Ltd. Adoi:10.1016/j.chb.2008.12.029

* Corresponding author. Tel.: +1 305 284 5261; faxE-mail address: bfowers@miami.edu (B.J. Fowers).

Recent studies have applied Grottfredson and Hirschi’s General Theory of Crime to investigate whether col-lege students’ inclinations toward internet software piracy is related to low self-control and opportunity(i.e., computer ownership). Given the widespread use of the internet to illegally obtain copies of musicand movies, it is important to understand the factors in this form of piracy as well. This study appliedthe self-control perspective to examine the attitudes of high school students toward the internet piracyof music and movies. Attitudes toward the internet piracy of music and movies were related to self-con-trol, biological sex, internet experience, affiliation with deviant peers, and grade level in this study of highschool students. This information is important because studies of internet piracy had not yet confirmedthe presence and predictability of internet piracy in high school students. This study also suggests thatpiracy prevention efforts may be most appropriately focused on high school age individuals and directedtoward increasing self-control.

� 2009 Elsevier Ltd. All rights reserved.

1. Introduction

With the rapid expansion and use of the internet in recentyears, music and movie piracy has grown exponentially, creatingan increasingly serious problem with the casual theft of intellec-tual property. Under U.S. Copyright Law, copyright owners are pro-tected from ‘‘the unauthorized reproduction, adaptation,performance, display or distribution of copyright protected works”(US Copyright 1). Copyright law was enacted and has been adaptedfor decades to protect the rights of artists and other producers ofintellectual property. When consumers unlawfully appropriatecreated works, artists are deprived of the proceeds of their workand may be deterred from creating for the benefit of others.

Unfortunately, the use of the internet for intellectual propertytheft is emerging as a common feature of youth culture(Bhattachariee, Gopal, & Sanders, 2003). This form of theft hasbecome increasingly acceptable and two of the primary targetsare the music and movie industries. Music and movie piracy oc-curs when an individual illegally copies commercially availablemusic or movies in order to avoid fees, or when an individualmakes unauthorized copies of these materials for personal useor distribution. Internet websites provide unauthorized musicand movies online to anyone with access. These downloadedfiles can be replayed indefinitely.

Internet piracy is a particularly insidious crime because individ-uals can engage in it privately in their own homes, which gives pi-

ll rights reserved.

: +1 305 284 3003.

racy a kind of anonymity. Moreover, the crime appears victimlessbecause the misappropriation of the items is a matter of copyingthem rather than taking something away from someone that theyno longer have. This may result in a lower threshold for this kind ofcriminal behavior, making this form of theft seem more acceptableto a broader segment of the population. The more widespread theperception is that piracy is acceptable, the less likely it is for indi-viduals to recognize that the act of copying intellectual property isa crime and is ethically wrong (Evans, Cullen, Burton, Dunaway, &Benson, 1997; Kini, Ramakrishna, & Vijayaraman, 2004; Kini,Rominger, & Vijayaraman, 2000). Given the ease, privacy, and rel-atively faceless nature of this crime, self-control and attitudes to-ward piracy are very important components in this behavior.This study was designed to assess the usefulness of Grottfredsonand Hirschi’s (1990) General Theory of Crime, which focuses onself-control, in accounting for adolescents’ attitudes toward musicand movie piracy.

The stakes of music piracy are very high. During the 1990s thevalue of the music industry grew from $24.1 billion to $38.6 billion(Zentner, 2003). Yet that success is being undermined as manyindividuals routinely obtain songs or complete compact discs ille-gally. Each year millions of dollars are lost in sales of music, andconsumers now buy more blank CDs than recorded discs (Zentner).This practice not only hurts large scale artists but members of theindustry on all levels. Peitz and Waelbroeck (2004) estimate thatthe music industry suffered a 20% reduction of sales in the 1998–2002 period worldwide.

Efforts to counter music and movie piracy have become anincreasing focus of the entertainment industry, which is also

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pressuring the government for greater involvement (Zentner).Beginning in June 1999, Napster allowed for the proliferation of on-line music file sharing and soon became the fastest software adop-tion in history (Zentner). While its popularity was widespread, itsviolation of intellectual property law was soon challenged by theRecording Industry Association of America (2006) when a motionwas filed against Napster for ‘‘engaging in or enabling, facilitatingor assisting others in the copying, downloading, uploading, trans-mission, or distribution of copyrighted musical work or soundrecordings protected by copyright or state law without the expresspermission of the rights owners” (Zentner). Although Napster wasofficially shut down in 2001, other file sharing sites spawned fromit including KaZaA and Morpheus. The film industry is now begin-ning to suffer the damage that piracy can cause. The crime of piracyhas serious negative effects on the music and movie industries eco-nomically and socially, which makes it an important topic forresearch.

In the past, research attention has been largely focused on iden-tifying the predictors of software piracy. Research on software pi-racy indicates that it is most common among college students(Solomon & O’Brian, 1990; Sims, Cheng, & Teegan, 1996). It is mostprevalent among those that have computer experience (Hinduja,2001). Attitudes toward software piracy and associating with peersthat engage in software piracy are also associated with piratingbehavior (Eining & Christensen, 1991). Most researchers have con-centrated on attitudes or intentions toward software piracy be-cause of the tendency to under-report illegal and unethicalbehavior (Liang & Yan, 2005; Rahim, Seyal, & Rahman, 2001).

2. Theoretical background

One of the most widely used and successful theories forexplaining piracy is Gottfredson and Hirschi’s (1990) General The-ory of Crime, which claims that criminality is the absence of self-control. While self-control can help to explain crime, it is not syn-onymous with crime (Longshore, Stein, & Rand, 1998). Those withhigh self-control consider the long-term consequences of theirbehavior, while those with low self-control do not (Gottfredson &Hirschi). This theory suggests that those with low self-control areimpulsive, insensitive, self-centered risk-takers who are morelikely to engage in acts that are physical, simple, and easy. Personswith low self-control are more likely to smoke, drink, have childrenout of wedlock, and gamble (Paternoster & Brame, 2000). Self-con-trol is a person’s ability to resist temptation when opportunityarises. This theory portrays crimes as acts that are committed tosatisfy one’s own interest without consideration of the conse-quences for oneself or others. Many crimes are simple and easyto perform, and provide excitement and instant gratification. Re-search has suggested that there is a link between level of self-con-trol and some criminal behaviors (Pratt & Cullen, 2000; Winfree &Bernat, 1998).

Higgins and his colleagues applied Gottfredson and Hirschi’stheory to software piracy (Higgins & Makin,2004a, 2004b) and dig-ital movie piracy (Higgins, Fell, & Wilson, 2006) because of the par-allel between impulsive criminal acts and software and moviepiracy. This approach appears promising because it provides valu-able conceptual tools for understanding music and movie piracyand for developing effective measures to prevent these crimes. Mu-sic and movie piracy are obviously forms of software piracy, butthe proliferation of music and movies make the repetition of thesecrimes much more likely (Bhattachariee et al., 2003). Researchershave devoted limited attention to whether music piracy can be ex-plained by Gottfredson and Hirschi’s theory (e.g., Higgins, 2007),which is one of the purposes of this study. As Higgins et al. pointout, individuals with low self-control may engage in digital piracy

because they are unwilling to wait to purchase a movie, there maybe an element of risk and excitement, they may not be concernedabout loss of income to creators and producers, and digital piracy iseasy to perform.

There are two other important factors that may predict musicand movie piracy. Criminologists have found that even afteraccounting for low self-control, association with deviant peers isstill related to crime (Higgins & Makin, 2004a, 2004b; Paternoster& Brame, 2000; Skinner & Fream, 1997). Therefore, associationwith deviant peers will be assessed as a potential predictor of mu-sic piracy as well. Although Higgins et al. (2006) linked associationwith deviant peers to social learning theory, other aspects of sociallearning theory such as differential reinforcement and imitationhave not been found to predict software or movie piracy (Higgins& Makin, 2004a, 2004b; Skinner & Fream, 1997). Given the lackof support for the broader social learning theory, we employedthe more parsimonious concept of association with deviant peersto describe this source of explanation for digital piracy. Becauseself-control theory recognizes the importance of opportunity forcrime, deviant peer association can be subsumed within this the-ory as one form of opportunity for criminal acts. Moreover, Gott-fredson and Hirshi (1987) explicitly cite association with deviantpeers as a significant factor in crime. Higgins and Makin (2004b)reported that the relationship between self-control and digital pi-racy was mildly moderated by association with deviant peers. Incontrast, Higgins et al. (2006) presented evidence that associationwith deviant peers partially mediated the relationship betweenself-control and digital piracy. All of these studies make it clearthat the association with deviant peers is a key factor in digitalpiracy.

Past research has also indicated that men commit more prop-erty crimes and violent offenses than women (Greenfield & Snell,2000). A sex difference has also been reported in software piracy(Hagan & Kay, 1990; Hollinger, 1993). Hollinger reported that forevery woman, three men are likely to engage in software piracy.We anticipated that male participants would have more favorableattitudes toward movie and music piracy.

Previous research has focused on software piracy in the collegeage population (Higgins & Makin, 2004a, 2004b; Liang & Yan, 2005;Rahim et al., 2001; Sims et al., 1996; Skinner & Fream, 1997). Be-cause younger individuals have not been studied up to now, it isnot clear when attitudes toward piracy emerge. It is clear that pi-racy is acceptable to a substantial portion of the college age sam-ples studied, but it is unknown whether that permissive attitudeexists before college. Music and movies are popular among highschool students, which suggests that it would be reasonable tostudy attitudes toward music and movie piracy in this age group.We hypothesized that level of adolescent self-control would benegatively associated with attitudes towards piracy of music andmovies, that association with deviant peers would be positively re-lated to attitudes toward piracy, and that adolescent males wouldhave more favorable attitudes toward piracy among high schoolstudents.

3. Research methods

3.1. Participants

The sample included 200 suburban high school students fromthe New York metropolitan area. The respondents included 18freshmen, 76 sophomores, 58 juniors, and 48 seniors. There were97 boys and 103 girls in the sample. The respondents identifiedtheir ethnic background as 143 White, 39 Asian American, twoAfrican American, four Native Hawaiian/Other Pacific Islander,and 14 other.

Table 1Subsample means and standard deviations for attitudes toward piracy.

Mean SD F df p

Sex 12.28 1, 198 .001Male 26.77 4.97Female 24.35 4.81

Grade 3.86 3, 196 .019 23.11 7.3310 25.20 4.4211 25.19 4.5412 27.35 5.04

Deviant peers 10.70 1, 198 .001Yes 27.87 4.22No 24.98 5.05

Ethnicity 2.29 1, 198 .104White 25.48 4.89Non-white 27.70 5.25

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3.2. Measures

3.2.1. Attitudes toward piracy scaleThe dependent measure in this study was Rahim et al.’s (2001)

eleven item Attitudes toward Software Piracy scale. The items wereadapted for this study to examine music and movie piracy. Twoquestions not pertinent to music and movie piracy were not in-cluded as part of the measure. Items include statements such as‘‘I think it is okay to use copied music and/or movies because thecommunity at large is eventually benefited.” Responses were Likertformat, ranging from 1 to 4, with 1 indicating ‘‘strongly disagree”and 4 indicating ‘‘strongly agree”. The alpha coefficient for the Atti-tudes toward Software Piracy scale was .83 with this sample.

3.2.2. Self-control scaleThe self-control measure was the 24 item composite self-con-

trol scale (Grasmick, Tittle, Bursik, & Arneklev, 1993). The itemsare statements such as ‘‘I often act on the spur of the momentwithout stopping to think.” The responses were Likert format rang-ing from 1 (strongly disagree) to 4 (strongly agree). Lower levels ofself-control were indicated by higher scores. Grasmick et al. re-ported that the scale is best viewed as unidimensional with an al-pha reliability of .81. The alpha coefficient was .89 with the currentsample.

3.2.3. Computing experience measureThe computing experience measure was a composite of three

items from Igbaria and Chakrabarti (1990). The students wereasked about their use of software (e.g., spreadsheets, word process-ing, and data bases), the Internet, and e-mail. The response catego-ries were: 1 (never), 2 (sometimes), and 3 (often). The scaleproduced a Cronbach alpha value of .48 in this sample. Due tothe low internal reliability of the three items, the second item(internet experience) was selected as the single item that bestmeasures the most relevant form of computing experience for thisstudy.

3.2.4. Deviant peer measureRespondents were also asked about their association with devi-

ant peers using the following single item taken from the Delin-quent Behavior scale of the Youth Self Report (Achenbach, 1991):‘‘My friends are often in trouble.” The response categories were1 = no and 2 = yes. They were also asked to complete demographicinformation questions that included race, grade, and biological sex.

3.3. Procedures

After receiving Institutional Review Board approval, the re-searcher asked approximately 400 participants, in Social Studiesclasses, to have a parent or guardian sign a separate consent formand voluntarily and anonymously fill out the surveys. Survey andconsent forms were returned to the teachers and were sorted toensure anonymity. This set of procedures produced 212 surveys;after deletion for missing data, 200 surveys remained.

Table 2Descriptive statistics and bivariate correlations.

Mean SD 2 3 4 5 6

1. Internet experience 3.83 .50 .11 .00 .19** .00 .16*

2. Deviant peers 1.81 .39 .34** .23** .14* .27**

3. Self-control 52.60 11.10 .36** .21** -.064. Piracy attitude 25.23 5.02 .24** .21**

5. Sex – – .096. Grade 10.68 .94

* p < .05.** p < .01.

4. Results

4.1. Univariate analyses

The initial stage of hypothesis testing consisted of a series ofone-way ANOVAs to examine the bivariate relationship betweengrade level, sex, deviant peers, race, and attitudes toward piracy(Keppel & Wickens, 2004). The one-way ANOVA with grade levelas the independent variable suggested a difference between gradelevels on attitudes toward piracy of music and movies

(F(3,196) = 3.86, p = .010). A follow-up Scheffe post hoc test indi-cated that the only statistically reliable difference was betweengrades 9 and 12, with 12th grade students expressing moreacceptance of piracy. ANOVA results indicated a difference be-tween boys’ and girls’ attitudes toward piracy (F(1,198) = 12.28,p < .001), with boys having more accepting attitudes toward pi-racy of music and movies than girls. The one-way ANOVA ondeviant peer association indicated a difference between thosewho associate with deviant peers, and those who do not, andtheir attitudes toward piracy (F(1,198) = 10.70, p < .001). Thosewho associate with deviant peers have more positive attitudes to-ward piracy. Due to the limited number of non-White partici-pants, we divided the participants into two categories; Whitesin one and everyone else in another. Results did not indicate adifference between racial/ethnic groups (White and other) andtheir attitudes towards piracy of music and movies(F(1,198) = 2.29, ns). See Table 1 for subsample means and stan-dard deviations and Table 2 for sample descriptive statistics andbivariate correlations.

4.2. Multiple regression analyses

We then conducted a hierarchical linear regression to examinesimultaneously the factors of biological sex, internet experience,self-control, and deviant peer association on attitudes towards pi-racy after including grade level as a control variable (Keith, 2005).Grade level was positively associated with attitudes towards piracy(B = .21, t = 3.06, p = .003). Grade level accounted for 4.5% of thevariance in attitudes toward piracy.

When the primary predictor variables were added to the model,the amount of variance accounted for in the regression model in-creased by 22.0% (F change = 13.87, df = 4, 192, p < .001). All fourpredictor variables were statistically associated with attitudes to-wards piracy after controlling for grade. Self-control was positively

Table 3Hierarchical regression of student variables predicting attitudes toward piracy.

Variable B SEB b R2 DR2

Step 1 0.05**

Grade level 1.161 0.37 0.22**

Step 2 0.27*** 0.22***

Sex 1.31 0.64 0.13*

Internet experience 1.79 0.63 0.18**

Deviant peer association 2.51 0.88 0.20**

Level of self-control 0.13 0.03 0.28***

* p < .05.** p < .01.

*** p < .001.

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associated with attitudes towards piracy (B = .28, t = 4.27,p < .0001). Male students had more favorable attitudes towards pi-racy than female students (B = .13, t = 2.05, p = .04). Those studentswho associated with deviant peers had more positive attitudes to-wards piracy (B = .20, t = 2.87, p = .005). Those students with thehighest internet usage had more favorable attitudes towards piracy(B = .18, t = 2.81, p = .005). The strongest predictor of attitudes to-wards piracy was self-control followed by grade level in the regres-sion analysis. Older adolescents who had less self-control would bemost likely to pirate. See Table 3 for complete results.

5. Discussion

The results of this study are very suggestive regarding factorsaffecting attitudes towards music and movie piracy among highschool students. As hypothesized, self-control was the strongestpredictor of attitudes towards piracy in the regression model. Thisis similar to Higgins and his colleagues’ (Higgins & Makin, 2004a,2004b; Higgins et al., 2006) findings in which low self-controlwas linked with software piracy as well as several other studiesthat demonstrated level of self-control had a relationship withforms of criminal behavior (Paternoster & Brame, 2000; Pratt &Cullen, 2000). Therefore, this finding expands the realm of self-control theory by helping to explain a propensity toward a rela-tively recent form of criminal behavior, music and movie piracy.

5.1. Internet piracy in high school

The study also indicates that permissive attitudes toward piracyemerge among high school students. Higgins and his colleagueshave focused on music and movie piracy among college students,but our results suggest that younger students also indicate willing-ness to participate in piracy. The widespread availability of com-puters to the participants, demonstrated by their responses tothe computer experience measure, indicates the existence of amuch younger group with the means to commit intellectual prop-erty theft. These younger participants may be unable to resist thetemptation of piracy due to a lower level of maturity when themeans to commit piracy are so freely accessible in multiple forms.High school students may be unaware of the consequences of theirbehavior because few legal efforts have been made to punish indi-vidual movie and music pirates because such mass penalties arenot feasible.

Our results indicated that 12th graders had more favorable atti-tudes toward piracy than 9th graders, suggests that permissiveattitudes toward piracy may become more prevalent as high schoolstudents get older. Sims et al. (1996) also found a significant asso-ciation with software piracy and age with undergraduate and grad-uate students. These results suggest that there may be anincreasing tendency to expropriate intellectual property throughcomputers as students age.

5.2. Deviant peers and internet piracy

In line with findings by Skinner and Fream (1997), deviant peerassociation was found to be an important predictor of favorableattitudes toward music and movie piracy. Paternoster and Brame(2000) asserted that deviant peer associations themselves arecaused by low self-control. While Higgins and Makin (2004a,2004b) looked at the significance of friends who pirated, the pres-ent study related the subject’s attitudes towards piracy to theirassociations with generally deviant peers. This provides furthersupport for the idea that exposure to more generally negative atti-tudes about rules and authority through association with deviantpeers encourages permissiveness regarding this form of criminalbehavior (Evans et al., 1997).

The results of this study are consistent with the literature ongender and criminal propensity as well. Consistent with thehypothesis and previous research, boys had more favorable atti-tudes towards piracy than girls. The sex difference present in soft-ware piracy (Hagan & Kay, 1990) is also present in attitudes towardmusic and movie piracy.

5.3. Implications and future research

The most unique contribution of this study is to extend the re-search on digital piracy to high school students. Previous researchhas found important influences on digital piracy among collegestudents, but this is the first study to assess the inclination of highschool students to misappropriate music and movies and to exam-ine the potential application of the General Theory of Crime to thatpiracy. The results of this study were consistent with previous re-search with college students. Therefore, the clearest implications ofthis study is that digital piracy appears to precede entry into col-lege and that efforts to prevent the theft of intellectual propertyshould begin with high school students, if not sooner.

Given the consistent findings in the literature on digital piracy,it seems appropriate to engage in intervention studies to examinewhether this form of crime can be reduced. Efforts to curb digitalpiracy among high school students should include education aboutpiracy as a crime that deprives artists and producers of income thatprovides essential support and incentive for their creative work.This kind of education would target the commonly held belief thatdigital piracy is victimless. Educators must also make it clear toadolescents that digital piracy is a crime. Because digital piracy isgenerally a private crime, committed on personal computers, it isalso important to emphasize to adolescents that it is theft, andtherefore unethical behavior. Studies have indicated that moral be-liefs are negatively correlated with digital piracy, which may meanthat efforts to increase adolescents’ awareness that piracy is uneth-ical may help to curb it.

One way to follow up on the finding that digital piracy is aliveand well among high school students would be to study the prev-alence and sources of digital piracy in a representative sample ofadolescents to gain a clearer understanding of its prevalence andsources. In particular, it would be helpful to know whether digitalpiracy varies by socioeconomic status and to know whether digitalpiracy increases with age, as the results of this study suggest itdoes. Another way to move beyond present knowledge would beto study digital piracy longitudinally across adolescence and earlyadulthood.

5.4. Study limitations

Although this research provides valuable information about theneed to deter music and movie piracy in high school students,several limitations were present in the study. First, the sampleconsists of a majority of White, non-Hispanic participants with a

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small Asian American contingent. Additionally, all participants at-tended one high school in an affluent area of metropolitan NewYork, which raises questions about the generalizability of the find-ings. The response rate was only 50%, which raises questions aboutself-selection into the study. Moreover, information was gatheredusing a self-report survey which raises questions about the accu-racy of the data. In addition, the study relied on a measure of atti-tudes toward piracy rather than piracy behavior.

Despite these limitations, the present study provides new infor-mation that expands our understanding of the music and movie pi-racy tendencies of high school students. Particularly, the resultssuggest that low self-control is important in explaining musicand movie piracy. The results from this study suggest that improv-ing self-control is important in curbing piracy and that preventionefforts should be directed toward high school students.

References

Achenbach, T. M. (1991). Manual for the Youth Self-Report and 1991 Profile. Dept. ofPsychiatry, University of Vermont, Burlington, VT.

Bhattachariee, S., Gopal, R. D., & Sanders, G. L. (2003). Digital music and onlinesharing: Software piracy 2.0? Communication of the ACM, 46(7), 107–111.

Burton, V. S., Cullen, F. T., Evans, T. D., Fiftal-Alarid, L., & Dunaway, R. G. (1998).Gender, self-control, and crime. Journal of Research in Crime and Delinquency, 35,125–147.

Eining, M. M., & Christensen, A. L. (1991). A psycho-social model of software piracy:The development and test of a model. Ethical issues in information systems. Boston,MA: Boyd & Fraser.

Evans, D. T., Cullen, F. T., Burton, V. S., Dunaway, R. G., & Benson, M. L. (1997). Thesocial consequences of self-control: Testing the general theory of crime.Criminology, 35, 475–504.

Gottfredson, M. R., & Hirschi, T. (1987). The methodological adequacy oflongitudinal research on crime. Criminology, 25, 581–614.

Gottfredson, M. R., & Hirschi, T. (1990). A general theory of crime. Stanford, CA:Stanford University Press.

Grasmick, H. G., Tittle, C. R., Bursik, R. J., Jr., & Arneklev, B. J. (1993). Testing the coreempirical implications of Gottfredson and Hirschi’s general theory of crime.Journal of Research in Crime and Delinquency, 30, 5–29.

Greenfield, L., & Snell, T. (2000). About female offenders. Women Police, 34(1),43–44.

Hagan, J., & Kay, F. (1990). Gender and delinquency in white-collar families: Apower control perspective. Crime and Delinquency, 36, 391–407.

Higgins, G. E. (2007). Digital piracy: An examination of low self-control andmotivation using short-term longitudinal data. Cyber Psychology & Behavior, 10,523–529.

Higgins, G. E., Fell, B. D., & Wilson, A. L. (2006). Digital piracy: Assessing thecontributions of an integrated self-control theory and social learning theoryusing structural equation modeling. Criminal Justice Studies, 19, 3–22.

Higgins, G. E., & Makin, D. A. (2004a). Self-control, deviant peers, and softwarepiracy. Psychological Reports, 95(3), 921–931.

Higgins, G. E., & Makin, D. A. (2004b). Does social learning theory condition theeffects of low self-control on college students’ software piracy? Journal ofEconomic Crime Management, 2, 1–22.

Hinduja, S. (2001). Correlates of internet software piracy. Journal of ContemporaryCriminal Justice, 17, 369–382.

Hollinger, R. C. (1993). Crime by computer: Correlates of software piracy andunauthorized account access. Security Journal, 4, 2–12.

Igbaria, M., & Chakrabarti, A. (1990). Computer technology and attitudes towardsmicrocomputer use. Behaviour & Information Technology, 9, 229–241.

Keith, T. Z. (2005). Multiple regression and beyond. Upper Saddle River, NJ: Allyn &Bacon.

Keppel, G., & Wickens, T. D. (2004). Design and analysis: A researcher’s handbook (4thed.). Upper Saddle River, NJ: Prentice Hall.

Kini, R. B., Ramakrishna, H. V., & Vijayaraman, B. S. (2004). Shaping of moralintensity regarding software piracy: A comparison between Thailand and U.S.students. Journal of Business Ethics, 49, 91–104.

Kini, R. B., Rominger, A., & Vijayaraman, B. S. (2000). An empirical study of softwarepiracy and moral intensity among university students. Journal of ComputerInformation Systems, 40, 62–72.

Liang, Z., & Yan, Z. (2005). Software piracy among college students: Acomprehensive review of contributing factors, underlying processes, andtackling strategies. Journal of Educational Computing Research, 33, 115–140.

Longshore, D. L., Stein, J. A., & Rand, S. T. (1998). Reliability and validity of a self-control measure: Rejoinder. Criminology, 36(1), 175–182.

Paternoster, R., & Brame, R. (2000). On the association among self-control, crime,and analogous behaviors. Criminology, 38(3), 971–982.

Peitz, M., & Waelbroeck, P. (2004). The effect of internet piracy on music sales:Cross-sectional evidence. Review of Economic Research on Copyright Issues, 1,71–79.

Pratt, T. C., & Cullen, F. T. (2000). The empirical status of Gottfredson and Hirschi’sgeneral theory of crime: A meta-analysis. Criminology, 38, 931–964.

Rahim, M. M., Seyal, A. H., & Rahman, M. N. A. (2001). Factors affecting softliftingintention of computing students: An empirical study. Journal of EducationalComputing Research, 24, 385–405.

Recording Industry Association of America (2006). Napster Case. 01/19/2006.<riaa.com>.

Sims, R. R., Cheng, H. K., & Teegan, H. (1996). Toward a profile of student softwarepirates. Journal of Business Ethics, 15, 839–849.

Skinner, W. F., & Fream, A. M. (1997). A social learning theory analysis of computercrime among college students. Journal of Research in Crime and Delinquency, 34,495–518.

Solomon, S. L., & O’Brian, J. A. (1990). The effects of demographic factors onattitudes toward software piracy. Journal of Computer Information Systems,Spring, 40–46.

U.S. Copyright Law. Title 17 U.S.C. Section 101 et seq., Title 18 U.S.C. Section2319.

Winfree, L. T., & Bernat, F. P. (1998). Social learning, self-control, and substanceabuse by eighth grade students: A tale of two cities. Journal of Drug Issues, 28,539–558.

Zentner, A. (2003). Measuring the effect of online music piracy on music sales.Available from http://som.utdallas.edu/capri/effect_music_download.pdf.