Network Effects on Music Industry
We all like to think that we are independent free thinkers, and many of us take pride in our ability to “stray from the path”. We are somehow under the impression that we are above the influence of others. In reality, we are social creatures who live, breathe, and make decisions based, at least in part, on the actions of other people. Whether it is a conscious choice or a subconscious drive, we live our lives as part of a herd. One manifestation of this fact is in the phenomenon of network effects, when we explicitly benefit from aligning our behaviors with the behavior of others. Examples of network effects can be found all around us, but I am going to talk about one particular case where network effects tend to play a critical role: the music industry.
What makes a song popular? What makes a musician a superstar? Can someone predict the next hit? In a New York Times article, “Is Justin Timberlake a Product of Cumulative Advantage?” Duncan Watts attempts to address these questions. As Watts correctly points out, “Conventional marketing wisdom holds that predicting success in cultural markets is mostly a matter of anticipating the preferences of the millions of individual people who participate in them.” If this is truly the case, then why do experts fail so frequently when attempting to create the next hit? The answer lies in the fact that the above view assumes that people choose what they like independently of what other people think. Watts proposes that in reality, we lack independence and that this lack of independence stems from the myriad of choices available which precludes us from finding what we want on our own. He states that we don’t really ever know what we want, making us reliant on the aid of others, and that “what we often want is not so much to experience the ‘best’ of everything as it is to experience the same things as other people.”
In order to test this hypothesis of social influence, Duncan Watts, along with Matthew Salganik and Peter Dodds, designed and conducted a web-based experiment which had more than 14,000 subjects. Participants “were asked to listen to, rate and, if they chose, download songs by bands they had never heard of.” One group of subjects only saw the names of the songs and the bands, whereas the second group “saw how many times the songs had been downloaded by previous participants.” Additionally, the second group was broken up into 8 subgroups and was only able to see the prior downloads of people in their subgroup.
The results showed that in all the subgroups of group 2, “the most popular songs were much more popular (and the least popular songs were less popular) than in the independent condition”. Another interesting observation was that the hit songs were different in different subgroups of group 2. This led the researchers to conclude that “introducing social influence into human decision making…didn’t just make the hits bigger; it also made them more unpredictable.” The researchers also made sure to point out that listener’s intrinsic quality did have an effect on which songs became successful, but that “the impact of a listener’s own reactions is easily overwhelmed by his or her reactions to others.”
This article and the results of the experiment it discusses clearly show that network effects play a critical role in the development of hit songs. People’s reactions to a song, and subsequently the song’s popularity, depend not only on the intrinsic value of the song, but also on the reactions that others have to the song.
http://www.nytimes.com/2007/04/15/magazine/15wwlnidealab.t.html?pagewanted=all&_r=0
– Grem