Factors influencing music piracy

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  • This article was downloaded by: [Northeastern University]On: 19 November 2014, At: 08:14Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

    Criminal Justice Studies: A CriticalJournal of Crime, Law and SocietyPublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/gjup20

    Factors influencing music piracyJames Popham aa Department of Sociology , University of Saskatchewan , 1019-9Campus Drive/Saskatoon, Saskatoon SK, S7N 5A5, CanadaPublished online: 03 May 2011.

    To cite this article: James Popham (2011) Factors influencing music piracy, CriminalJustice Studies: A Critical Journal of Crime, Law and Society, 24:2, 199-209, DOI:10.1080/1478601X.2011.561648

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  • Criminal Justice StudiesVol. 24, No. 2, June 2011, 199209

    ISSN 1478-601X print/ISSN 1478-6028 online 2011 Taylor & FrancisDOI: 10.1080/1478601X.2011.561648http://www.informaworld.com

    Factors influencing music piracy

    James Popham*

    Department of Sociology, University of Saskatchewan, 1019-9 Campus Drive/Saskatoon, Saskatoon SK S7N 5A5, Canada

    Taylor and FrancisGJUP_A_561648.sgm10.1080/1478601X.2011.561648Criminal Justice Studies1478-601X (print)/1478-6028 (online)Article2011Taylor & Francis2420000002011JamesPophamJames.popham@usask.ca

    A number of studies have illustrated that age, sex, computer skills, access tobroadband Internet services, and number of devices owned by a respondent areeffective predictors of engagement in electronic music piracy. However, thesefindings have relied on data collected from undergraduate student samples. Thispaper reassesses factors of music piracy using a more representative sample of thegeneral population. Using a logistic regression model, the findings suggest thatmost of the variables considered in past research significantly increase the oddsconnected with public engagement in electronic music piracy.

    Keywords: digital piracy; downloading; MP3; cybercrime; logistic regression;public engagement

    Introduction

    Past research has identified several factors that contribute to electronic music piracy(e.g., Gopal, Sanders, Bhattacharjee, Agrawal, & Wagner, 2004; Hinduja, 2001;Hinduja & Ingram, 2009; Morris & Higgins, 2009). The factors include the respon-dents computer skills, access to broadband Internet services, age, gender, and race.However, most studies were conducted within post-secondary institutions, usingsamples of undergraduate students (e.g., Higgins & Makin, 2004; Hinduja, 2006;Ingram & Hinduja, 2008). Since the student population is different from the generalpublic in demographic features, exposure to computer technology, and social activities(Ogan, Ozakca, & Groshek, 2008; Skinner & Fream, 1997), conclusions based onstudent samples may not apply to the general population (Flere & Lavric, 2008; Payne& Chappell, 2008).

    This paper uses variables identified in past research to see if they predictparticipation in music piracy in the Canadian general population. The 2007 CanadianInternet Use Survey (CIUS) (Statistics Canada, 2006) provides data from a nationalrepresentative sample that can be used to conduct the test. There is some evidence toindicate that music piracy in Canada extends beyond the student population. TheOrganization for Economic Co-operation and Development (OECD) found that Cana-dians have the highest per-capita rate of music piracy among nations surveyed(Wunsch-Vincent & Vickery, 2005); furthermore, 40% of Canadian households usethe Internet to download music legitimately or otherwise, yet only 17% of Canadianhouseholds report having a student present (Statistics Canada, 2006).

    Electronic music piracy refers to the illegitimate computer-aided copying, storage,and distribution of digitally compressed copyrighted audio tracks, commonly called

    *Email: james.popham@usask.ca

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  • 200 J. Popham

    MP3s. Persons engaging in music piracy can make use of specialized computer soft-ware to copy music tracks from a compact disc (CD) and store them on their personalcomputer hard drive as MPEG-1 Audio Layer 3 (MP3)-formatted files. These filespose only a small demand on electronic storage resources, thus making it easy andconvenient to collect numerous MP3s, usually of pop music, and share them via theInternet (Okin, 2005). This technology has been accessible to the public since theearly 1990s; however, the enormity of its impact on music piracy was not known untilspecialized software called Napster emerged in 1999 (Knopper, 2009). The individualcould now easily collect and distribute MP3 files en masse, giving birth to peer-to-peer (P2P) file sharing between strangers around the world. Napster was first designedto promote music sharing on computer campuses leading the Recording IndustryAssociation of America (RIAA) to place blame for this phenomenon, and subsequentsales losses, on post-secondary campuses (Knopper, 2009; RIAA, 2010). Thisperspective has, perhaps, been excessively propagated to the public because of thelack of exploratory research noted above.

    Literature review

    It is estimated that the US economy loses $12.5 billion annually due to music piracy,and that as many as 70% of downloaded songs are illegal downloads that directlyreplace legitimate purchases of music (Siwek, 2007). The OECD states that more than24% of Canadian households download music illegitimately (Wunsch-Vincent &Vickery, 2005). The RIAA has taken exception to this form of deviance and initiateda number of litigious campaigns against music downloaders (Hinduja, 2006; Knopper,2009). The RIAA claims that the lions share of music piracy is attributable to post-secondary campuses throughout the world (2010). While occasional small claims havebeen filed against individuals, the most frequent and exorbitant lawsuits have beenleveled at post-secondary educational institutions (e.g., Lockwood & Oliver, 2008).

    Research has provided some support for the RIAAs claims. Skinner and Fream(1997) found a 35% participation rate in piracy among undergraduate students;Rumbough (2001) found that 60% of students admitted to using the Internet to illegallydownload music files. Recent studies have found even higher participation rates rang-ing from 75% to 85% of students (Ingram & Hinduja, 2008; Selwyn, 2008a). Thesefindings have prompted leading studies of electronic music piracy to focus on the post-secondary campus (e.g., Higgins & Makin, 2004; Hinduja, 2006; Ingram & Hinduja,2008; LaRose, Lai, Lange, Love, & Wu, 2006). Although this research has producedreplicable findings for campus-based samples, no effort has been made to test its viabil-ity for non-student populations.

    While some authors have suggested that results from student-based samples forsociological studies can be applied more broadly (Mazerolle & Piquero, 1998, cited inHinduja, 2006; Nagin & Paternoster, 1993), recent arguments have stated that theseapproaches should be used cautiously at best (Bouffard, Bry, Smith, & Bry, 2008; Flere& Lavric, 2008; Payne & Chappell, 2008). The debate over undergraduate samples hascontinued for decades Gordon, Slade, and Schmitt (1986) introduced the science ofthe sophomore as a longstanding issue in studies of the science of human behaviorwith early concerns dating back to the 1940s (p. 191). Their study on the subject foundthat the social background of participants in a number of studies significantly impactedtheir responses to questionnaires, rather than factors identified in applied theory. Theauthors then suggested that phenomenological differences between the somewhat

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  • Criminal Justice Studies 201

    narrowed histories of students versus the wide range of experiences in the public callsthe experimental approach of extracting data from convenience samples into question(Gordon et al., 1986). The experimental approach has more recently been explored byKam, Wilking, and Zechmeister, who discuss the use of students as a reliance on anarrow data base (2007, p. 416), making external validity the Achilles heel of human-ities research (p. 435). While they maintain that in some instances student conveniencesamples can be effective, they suggest that this Achilles heel can be mitigated throughthe use of other relative conveniences such as readily available sources at the library,or equally accessible university employees (Kam et al., 2007). The debate on general-ization from specific samples is of particular importance to this study. Electronic musicpiracy is not confined to the campus, and consequently the external validity of existingstudies and their samples must be tested before policy implications can beestablished (Knopper, 2009).

    Findings have emerged from many of the above-mentioned studies that suggestelectronic music piracy is a result of factors not directly connected to post-secondarycampuses, such as the respondents level of skill when using a computer, access tobroadband Internet services, age, gender, and race (e.g., Gopal et al., 2004; Hinduja,2001; Hinduja & Ingram, 2009; Morris & Higgins, 2009; Skinner & Fream, 1997).Skinner and Fream (1997) found that respondents with specialized skills, such asaccessing unique file-sharing resources, were more likely to report a higher level ofInternet piracy. Additionally, Hinduja (2001) demonstrates that access to a broadbandInternet connection is a predictor of participation in software piracy. Using a bivariatecorrelation matrix, Hinduja (2001) illustrates that electronic piracy is significantlycorrelated with access to high-speed Internet access. Furthermore, his findingssuggested that computer ability, in this case experience using computer hardware tocreate CDs that contained copyrighted software, accounts for 14% of the variation inInternet piracy among students (Hinduja, 2001). Hinduja (2001) remains somewhatunsure of the applicability of these findings to broader populations, noting that thisparticular crime has been predominantly studied among college-aged individuals in auniversity setting. As such, additional research examining other populations mightretrieve different results and would provide interesting material for comparative anal-yses (p. 379).

    A more recent study using a logistic regression model found that ownership of aniPod or a similar portable music device increases the odds of a person participating inmusic piracy (Holt & Morris, 2009). Holt and Morris (2009) research developed amodel which indicated that among other factors, multiple-computer ownership, self-reported computer skill, and race as well as the above-mentioned iPod ownershipsignificantly increased respondents odds of engaging in music piracy. These factorsare not strictly limited to the post-secondary campus, and if they prove to be significantin determining piracy among a non-student sample they will provide insight into theapplicability of a predictive model generated from post-secondary student datasets.

    Other studies have established a connection between factors not necessarily relatedto undergraduate students and music piracy. Hinduja and Ingram (2009) have developedan ordinary least squares regression model indicating that a combination of electroni-cally developed peer networks, gender, Internet skill, and access to high-speed Internetaccount for 26% of the variation in respondents level of music piracy. Research byHiggins and Makin (2004) has also contributed to this model; the authors found thatengagement in music piracy is negatively correlated with age and females, and that SESand participation in copyrighted video piracy positively correlate with music piracy.

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  • 202 J. Popham

    Some researchers have confirmed the relevance of certain demographic variables.Gopal et al. (2004) found that younger males are most likely to engage in piracy; Morris,Johnson, and Higgins (2009) reported that non-whites are more likely to participate.Selwyn (2008b) found that gender and computer skills strongly correlated with musicpiracy. An interesting element added by Selwyn (2008b) is his qualitative finding thatInternet pirates feel safe to act illegally because of the anonymity of the Internet.

    A model to explain music piracy has emerged. Mitigating factors aside, pastresearch has illustrated that access to high-speed Internet services, technical skill in anInternet-based environment, ownership of multiple technologies including computersand iPods, gender, race, and age all significantly contribute to engagement in musicpiracy (Gopal et al., 2004; Hinduja, 2001; Hinduja & Ingram, 2009; Morris &Higgins, 2009; Skinner & Fream, 1997). These findings have been so common thatthey have often been used as control variables when producing theoretical tests.However, as noted, supporting research has relied on samples based on post-secondarystudents. The effectiveness of this model to explain public engagement in musicpiracy remains tenuous.

    Data and methods

    The 2007 Canadian Internet Use Survey (CIUS) was conducted in conjunction withthe 2007 Labour Force Survey (LFS) by Statistics Canada. CIUS participants werecontacted by Statistics Canada representatives using telephon...

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