In the article “Do Artists Benefit from Online Music Sharing?”, which is based on a 2003 working paper, Gopal et al. (2006) present a model of music file sharing to explain the impact of technological and economic incentives to sample, purchase, and pirate music. The results of the model indicate that lowering the cost of sampling by file sharing will motivate more music consumers to purchase music online. In contrast, the restriction or even prevention of sampling will hurt the music industry in the long run. Read more here:
Gopal et al. (2006) assumed in their model that Internet sharing technology enables consumers to reduce information uncertainty regarding music. The costs involved in file sharing for sampling music are sunk costs and contain time and effort in searching, downloading, and listening to the unauthorized copy. A consumer decides to sample if the expected net benefit from sampling is larger than that from buying. After downloading, a consumer has three different choices: (1) to buy a version of the song; (2) to keep the unauthorized copy; (3) to discard the copy.
The decision model considers two cases: A decison under low risk, if the consumer downloads music from a well-known superstar, and a decision under high risk, if music from relatively unknown artists is downloaded. The model proposes (see Gopal et al. 2006: 1513-1515) that if market price of the music item increases, consumers are more likely to sample first, rather than directly purchase. Sampling, therefore, allows consumers to make a purchase decision on the actual value of music. A lower actual value results in a smaller proportion of samplers that purchase the music. As sampling costs decrease with increasing availability of free music online, more consumers engage in sampling prior to the purchase decision.
However, the revenue impact of file sharing on music purchases depends on the actual value, which is attributed to the music. If music is highly valued, the revenue will increase due to file sharing, whereas low valued music will see decreasing revenues in the presence of file sharing. This proposition also implies that efforts by producers to increase the value of music constitute a more effective strategy than raising the costs of sampling (e.g. by Digital Rights Management or the enforcement of copyright). Overall, the propositions of the models imply that the welfare is higher with the presence of file sharing than without.
However, this holds true for relatively unknown artists. For superstar acts, the information uncertainty tends to disappear. According to the model, a consumer will never sample a perfect superstar music item if she/he is aware of the true value a priori. Thus, downloading music of superstars is more likely to result in piracy than the downloading of music of unknown artists.
In order to test the model, the authors conducted a pilot study with a sample of 76 graduate students. Based on this feedback a revised questionnaire was sent to 200 other students. The respondents were asked to reveal their online music behavior and to specify preferences for online music activities. For a given sampling and price setting, the respondents were asked to take one of six actions: (1) Download and sample, delete from computer, buy CD (sampling); (2) Download and sample, delete from computer, do not buy CD (sampling); (3) Download and sample, keep in computer, buy CD (sampling); (4) Download and sample, keep in computer, do not buy CD (piracy), (4) Do not download, buy CD (direct buy); (5) Do not download, do not buy CD.
Music value uncertainty was captured by 5 choice settings with known and unknown music: (1) choice of one of top 5 known music items; (2) choice of one of top 50 known music items; (3) choice of unheard music from favorite artist; (4) choice of unheard music item from genre of music I like; (5) choice of unheard music item recommended by friends.
The results of the data analysis indicate that an increase of the retail price for unknown music decreases both sampling and buying. On the other hand, a decrease of sampling costs for unknown music increases sampling and leads more samplers to buy music. However, higher valued music is sampled more than lower valued music.
With the advent of sharing technology, which lowers sampling costs, the authors found that “(…) consumers become aware of more new albums that they like, leading to more artists and albums being ranked on the charts” (Gopal et al. 2006: 1526). This implies that file sharing increased the diversity of music. However, the results also indicate that with the advent of music file sharing technologies the impact of stardom on music sales eroded (Gopal et al. 2006: 1528).
To sum up, file sharing decreased sampling costs, and this would lead more consumers to buy music they sampled. However, sampling of higher valued songs has a positive impact on music sales, whereas sampling of low valued music leads to piracy. And finally, the superstar status is threatened by file sharing, since a greater proportion of sampling superstar songs leads to more piracy, and decreasing sampling costs leads to the erosion of superstardom.
In part 17 Norbert J. Michel’s article “Digital File Sharing and Music Industry: Was There a Substitution Effect?”, which is based on his 2003 Ph.D-thesis will be reviewed.