Predictive factors of music piracy: An exploration of personality using the HEXACO PI-R

Deterrents and predictive factors

Anti-piracy campaigns have largely failed to address the phenomenon of widespread engagement in music piracy, with Wikstrom (2011) suggesting that: “Perhaps the single most enduring effect of these initiatives has been a negative impact on the reputation of the music industry” (p.155). Traditional anti-piracy campaigns focus on the punitive measures that could be taken if caught downloading copyrighted media illegally, with the majority of research centering on deterrents via technological and legislative changes. Recent real-life events suggest that individuals engaging in piracy adapt well to such changes. For example, while P2P (illegal sharing of copyrighted files over the Internet) usage in the USA dropped after file-sharing giant Limewire was closed, usage on other P2P services increased (Forde, 2011). Empirically, Lauinger et al. (2012) conclude – having exposed the ineffectiveness of conventional “takedown” approaches – that reducing the demand for pirated content by providing legitimate alternatives is the best means to address piracy.

Most technical measures, at best, inconvenience individuals engaging in music piracy. For example, it is commonplace for record companies to flood file-sharing networks with seemingly authentic files that can be white noise or a loop of a small portion of a track, appearing as the correct duration for the actual songs (DeVoss & Porter, 2006). In direct response to Madonna’s decision to adopt this strategy, a hacker uploaded pirated versions of tracks from her new album on her official website. As such, conventional punitive measures can accomplish counter-intuitive outcomes that can only serve to antagonize individuals. This is commonly referred to as the “Streisand effect” (see Masnick, 2005).

The continued presence of widespread DP raises questions over the effectiveness of these conventional anti-piracy approaches. d’Astous, Colbert & Montpetit (2005), using vignettes, observed that emphasizing the negative consequences of piracy (such as getting caught and fined) had no significant impact on the behavioral dynamics underlying music piracy. The authors conclude that this may be because of the varied nature of often incongruent messages from different sources concerning DP behavior.

More interestingly however, are the findings from three studies by Sinha & Mandel (2008), who observed that negative incentives are only a strong deterrent for certain consumers but can actually increase the propensity to pirate for others. Conversely, positive incentives, such as improved functionality, were observed to significantly reduce the tendency to pirate among all the consumer segments studied, with 56% of Swedish file-sharers citing Spotify (a popular Swedish music-streaming service) as the reason they had curbed their habit (Jones, 2011). Exploring the ethical component involved in choosing whether or not to pirate a CD, Grolleau, Mzoughi & Sutan (2008) noted that 30% of participants would buy a CD if over 75% of proceeds went to charity. This represents a common belief that (despite being cheaper than ever) music is overpriced, with consumers often seeking supplemental content such as exclusive content to justify the price – with music effectively being free elsewhere if downloaded illegally.

Research more focused on predictive factors has spawned a wealth of individual differences, including gender and age (Malin & Flowers, 2009; Mishra, Akman & Yazici, 2006), with the profile of the “music pirate” being a young male. There has been a rise in deluxe and re-mastered versions of albums in recent years (representing the sort of added value desired by consumers, as noted above), with research by McIntyre (2011) suggesting a preference for recorded music in general amongst older music fans. Such relics are likely to appeal to a minority of music fans, given the perceived increased value and functionality of digital music such as convenience/economic utility and storage utility (Kinnally, Lacayo, McClung & Sapolsky, 2008), which have also been identified as predictive factors of piracy engagement.

Attitudes toward DP, the frequency of past DP behaviors, and the motivations and intentions underlying DP (Taylor, Ishida & Wallace, 2009) have been established as predictive factors. Crucially, the intention to swap music online has been demonstrated as depending on one’s attitude toward music piracy, one’s perception that important others want that this behavior be performed, and one’s perceived competency in doing so (d’Astous et al., 2005). This finding is consistent with the theory of planned behavior (see Ajzen, 1991), which argues that an attitude towards a particular behavior, in conjunction with subjective norms and perceived behavioral control, shape an individual’s intentions to perform this behavior (and the behavior itself). As such, music piracy emerges as a largely considered activity. This is notable as impulsivity, by contrast, is typically over-represented amongst criminal populations.

As such, and given that it has been largely neglected in piracy research, personality is of interest as a potential predictive factor. Research findings suggest that Costa & McCrae’s (1992) “Big Five” model of personality (a trait approach to personality comprising five broad domains of human personality) and particularly the domains of Neuroticism, Openness to Experience, and Extraversion, mediates individuals’ choice and motives for listening to music (Chamorro-Premuzic & Furnham, 2007; Chamorro-Premuzic, Swami, Furnham & Maakip, 2009; McCown, Keiser, Mulhearn & Williamson, 1997; Rentfrow & Gosling, 2003). More recently, personality has been found to moderate the perception of emotion in music (Vuoskoski & Eerola, 2011a, 2011b), representing the influence of personality in music listening. More directly related to music piracy is the finding that lower willingness to buy counterfeit goods has been shown to be moderated by conscientiousness (Swami, Chamorro-Premuzic & Furnham, 2009).

Corroborated by Egan & Taylor (2010) in their research into unethical consumer behavior and shoplifting, other personality traits have been identified as predictors. An expanding area of research, investigation into personality and consumer behavior would benefit from a consideration of music piracy as it does not fit conventional models of theft in as much as individuals engaging in piracy actively share copyrighted content with others. As such, piracy is a fundamentally social activity.

Building on the so-called “Big Five” (Costa & McCrae, 1992), Lee & Ashton’s (2004) HEXACO PI-R and in particular the honesty–humility dimension, has been shown to more strongly predict outcomes that may be associated with disinhibited behavior, with individuals reporting low honesty–humility tending not to feel bound by conventional rules and restrictions, increasing their likelihood to violate societal conventions, laws, and norms (Weller & Tikir, 2011). With six broad domains of personality, the HEXACO PI-R is closely modeled on other trait approaches. It is the honesty–humility dimension that elevates it above others in terms of its suitability to considering music piracy, with Weller and Tikir explaining that the honesty–humility dimension showed the strongest associations with behaviors that offer rewards that are generally considered to run counter to moral and legal conventions, and is unrelated to social risk-taking behaviors that are considered more socially acceptable. The applicability of this dimension to understanding piracy therefore appears optimal.

Research questions

The present research aims to draw together the two conventional lines of research in music piracy – deterrents and predictive factors – in a novel way, by exploring: the impact of positive incentives on attitudes towards music piracy and whether personality is a predictive factor in attitudes towards music piracy. The research also aims to measure attitudes towards music piracy using a new instrument, to minimize bias (see “Materials”, below).

Method

Results

Hierarchical regression model

A hierarchical regression analysis was performed to explore the predictive capacity of variables of interest on AMP-12 scores. In step 1, the six facet scores of the personality inventory used were entered as predictors. The model was significant (adjusted R² = .09, F = 5.43, p < .001). Participants scoring higher on the AMP-12 scored lower on Honesty–Humility, Conscientiousness and higher on Openness facets. In step 2, demographic variables (age and gender) were entered into the model as predictors, on the basis of being significant predictors in other studies. This model was significant (adjusted R² = .12, F = 5.47, p < .001). Whilst no differences were observed amongst males and females, participants 24 years old or younger demonstrated higher scores on the AMP-12, in line with previous research findings. In the final step, preference for digital music was entered into the model as a predictor, on the basis that music piracy is most easily accessed in digital formats (online). The model was significant (adjusted R² = .18, F = 6.58, p < .001). Participants favoring digital music scored higher on the AMP-12, as expected. Table 1 summarizes the regression analyses.

OPEN IN VIEWER

Table 1.

Hierarchical regression of predictive factors on AMP-12 scores ^† .

	Regression on variable	T	R 2 adj.
Step 1: HEXACO a			.09
Honesty–Humility	.15*	−2.35
Conscientiousness	.19**	−2.97
Openness	.25***	4.10
Step 2: Demographics b			.12
Age	.17**	−2.82
Step 3: Format preference			.17
Digital	.23***	3.97

Note. ^† (N = 261); a = Variables excluded: Extraversion; Emotionality; Agreeableness; b = Variables excluded: Gender. *p < .05 (2-tailed), **p < .01 (2-tailed), ***p < .001 (2-tailed).

Exploring personality further, the Honesty–Humility factor of Fairness was observed to be significant using ANOVA (F(1, 256) = 41.84, p < .001, η2p = .14) with participants scoring higher on the AMP-12 scoring lower on this factor. As such, participants favoring music piracy could be argued as being less fair. Table 2 presents correlation scores on all of the factor scores from the three significant facets of Honesty–Humility, Conscientiousness and Openness, with Fairness having the highest correlation coefficient. This test, correlating seven items novel to the HEXACO PI-R, sheds further light on the relationship between personality and attitudes towards DP.

OPEN IN VIEWER

Table 2.

Correlation between AMP-12 and HEXACO PI-R factor scores.

AMP-12	Fairness a	Organization b	Diligence b	Creativity c	Inquisitiveness c	Unconventionality c
Pearson correlation	−.34***	−.16**	−.15*	.16*	.16*	−.16**

Note. a = Honesty–Humility; b = Conscientiousness; c = Openness; *p < .05 (2-tailed), **p < .01 (2-tailed), ***p < .001 (2-tailed).

Discussion

This study aimed to draw together two prominent lines of research on music piracy – deterrents and predictive factors. These two particular areas shed light on who engages in piracy and the relative success and failures of approaches to amend the behaviors of these individuals. The research also aimed to introduce potential new predictive factors and individual differences, using an original construct (the AMP-12) to unobtrusively measure attitudes toward music piracy. The study also builds on research into personality and consumer behavior.

The results do not support the hypothesis that positive anti-piracy messages can be used effectively to manipulate attitudes towards music piracy. Modeled on d’Astous et al. (2005) who used anti-piracy vignettes containing conventional punitive messages, the results suggest that anti-piracy messages, even framed in a positive way, are not a valid resource to amend piracy attitudes and behaviors. The ease of engaging in piracy behaviors has likely generated a habitual pattern of illegal music consumption activity, and as such, superficial messages aiming to persuade individuals to change their behaviors are unlikely to address root causes of piracy motivations. Without further exploration, however, this assumption remains speculative. The approach taken in this study may prove to be successful if implemented in a real-life context, perhaps made salient at frequent intervals throughout a particular “piracy session”.

Findings on the HEXACO PI-R (Lee & Ashton, 2004) add substantially to literature on predictive factors, proposing a personality profile of individuals favoring music piracy. Such individuals scored low on Honesty–Humility, low on Conscientiousness and high on Openness: to levels of statistical significance. A lower score on Honesty–Humility amongst these individuals is intuitive, given that piracy is an unfair activity that does not ensure copyright owners secure the profits they are legally entitled to. Unfairness emerged as the key factor contributing to the significant finding of lower scores on the Honesty–Humility facet, with the significant results supporting the decision to use the HEXACO PI-R over alternative trait models (with this facet being unique to the model). Jambon & Smetana (2012) observed using an online survey that the majority of their sample indicated that the current price of music is unfairly high, with 90% of participants suggesting that music should cost no more than $10/CD or 30c/song. The authors note that the belief that the music industry treats its musicians unfairly may have an influence on the way individuals approach downloading. As such, the relationship between unfairness and piracy appears to be a complex one and is explored in some depth later.

A lower score on conscientiousness amongst participants observed using the AMP-12 as holding more pro-piracy attitudes is less intuitive. Individuals scoring low on this facet would be expected to be more careless, making decisions impulsively. As has been stated previously, findings from literature point towards engagement in piracy as a largely considered activity (see Holt & Copes, 2010). Findings on conscientiousness are, however, consistent with Swami et al.’s (2009) finding that lower willingness to buy counterfeit goods is being moderated by the trait.

The most compelling outcome of the exploration into personality is that higher scores on openness predicted pro-piracy attitudes. Such participants can be assumed to be more open to experiencing music in its many forms, with music piracy merely facilitating this. Indeed, preference for digital music was a significant predictor of pro-piracy attitudes where it is likely that the ease of exchanging digital music illegally encourages a preference for this format.

To add to the literature on age, and to move beyond more obvious reasons such as an increased familiarity and competence with computing, music plays a particularly strong role in the lives of adolescents and young adults, such as helping the formation of identities and meeting emotional needs (see North, Hargreaves & O’Neill, 2000). As such, this group may have stronger motivations to listen to a wider variety of music than older populations. This observation suggests that the motivations for younger individuals to engage in music piracy come from needs, not wants. This is a controversial (though informed) suggestion and it requires empirical support.

Returning to the issue of unfairness, de Vries et al. (2009) have established that unfairness was strongly related to disinhibition, as measured using the 52-item Sensation Seeking Scale (Van den Berg & Feij, 2002). As such, the negative relationship between fairness and pro-piracy attitudes observed in the present study could be mediated by the disinhibition effect of the internet, where much music piracy occurs. As explained by Brown (2013), the most common technique to rationalize DP is the denial of injury (see Sykes & Matza, 1957). In other words, with offline consequences to online behaviors being difficult to perceive, it is easier to underestimate or even reject the negative outcome of engaging in piracy. As such, and with links made between unfairness and dishinbition, future research could explore personality in more depth to reveal the underpinnings of this complex area that holds the potential to inform suitable deterrent approaches.

Supplemental Material