1. B-sides and Behavioral Biases:
Why Artists Are Better Off With Shorter Albums
Kevin Bessey
Mathew Madsen
Nathalia Myrrha
12 April 2016
Abstract
Several experimental papers have been written regarding the conjunction bias which leads to
a reversal of consumer preferences and the average bias which carries a “more is less” result in
some situations. This paper seeks to add to the literature on preference reversal and explore
the possibility of the average bias extending beyond the primary choice to have residual
effects on subsequent, related market interactions. This hypothesis is tested in the context
of digital music and live concert sales. The results support the established understanding of
conjunction and average biases with participants valuing shorter albums of only high quality
songs over strictly superior albums including incremental, inferior tracks. Moreover, there
is evidence that this average bias extends to willingness to pay for live concert tickets for
the artist of the evaluated songs. This result has direct implications for artists seeking to
maximize earnings, but also suggests that the average bias has more far-reaching effects than
previously understood.
1

2. B-sides and Behavioral Biases: Why Artists Are Better Off With Shorter Albums
1 Introduction
Much has been written on the presence of behavioral aberrations such as preference reversals
and the average bias. These biases have been observed in a variety of settings: options to
gamble (Grether and Plott, 1979), dinnerware (Hsee, 1998), and sports cards (List, 2002).
This paper seeks to investigate the average bias in the context of digital music sales, and the
potential effects on subsequent market interactions such as concert sales.
File sharing and streaming has lead to interesting changes in intellectual property
markets. The market for music in particular has significantly changed with such practices
gaining popularity. Goldman (2010) showed that record companies have suffered an eight
percent decrease per year in physical album sales. Many in the industry wonder whether
they will receive a return on their investments.
These changes have created some interesting forms of redistribution. Mortimer,
Nosko, and Sorensen (2012) find that file sharing has lead to huge increases in concert
attendance for smaller artists. They conclude that recorded music and live concerts are
complements and that lesser known bands benefit from the exposure of their recorded music
through increased revenue from live performances.
File sharing has also influenced redistribution through sampling. In the current
market, independent album sales make up 34.4% of the total market. Peitz and Waelbroeck
(2006) show that file sharing can help consumers evaluate the quality of the artist. This leads
to greater heterogeneity in the music market. In order for firms to more clearly distinguish
their product and increase popularity, they need to let each single be a clear indicator of
quality. Increased value through sampling would lead to increased album sales for individual
2

3. B-sides and Behavioral Biases: Why Artists Are Better Off With Shorter Albums
artists.
Record companies and artists album need to be concerned about the valuation of
their albums as they contribute to ticket sales and radio-based royalties. As demonstrated by
Mortimer et. al (2012) increased sharing of music files leads to increased demand for ticket
sales. In this paper we will explore the valuation methods of consumers and will test for
conjunction bias in album purchases. We will also test to see how these valuations influence
the valuations that artists would have for future shows.
In the following experiment we will look at the valuation of Extended Plays (EPs)
by common consumers and their impact on future concert attendance. EPs are essentially
bundles of three to seven songs that are sold at a lower price than the cost of individual
songs. This is a common practice in the music industry, by this method an artist can sell a
group of songs to increase interest in their group. In our model, we use music recorded by an
upcoming indie band. Using a relatively unknown artist reduces the risk of valuations being
anchored to a know album or concert price for a particular artist, as might be expected with
a more well-known group. In this experiment we will use two versions of their EP. In the
first EP, we will include four of their most catchy and best recorded songs. In the second
EP, we will include these four songs and three more songs that are neither as catchy nor as
well recorded. These three songs are referred to in the music community as filler songs.
2 Experimental Design
The experiment was conducted through iTunes, an online software used to organize and buy
music. The advantage of conducting the experiment through iTunes is that individuals do
3

4. B-sides and Behavioral Biases: Why Artists Are Better Off With Shorter Albums
not have to sign up for a new account in other to participate in the experiment. Another
advantage is that customers have already purchased credit in their account, which reduces
transaction costs. The opening page of iTunes offers a right-side menu with features such
as Purchased, Explore, Recommended For You, and My Wish List. For our experiment we
added a “How Much Would You Pay?” tab, prominent placed on the top of the page and
right above “Explore” on the right menu.
The How Much Would You Pay feature offered albums of starting artists that
were not offered elsewhere, and allowed customers to listen to a minute and a half of each
song. Songs were previously rated and the ratings appeared horizontally after name, artist,
and time, and before price. The tab had the following description “We are working with
recording companies to determine album prices for starting bands. We would love your help
in picking the price you would pay for each album.” Customers were then instructed to bid
on albums’ prices taking into consideration the following criteria: after two days each person
had submitted his/her bid, the system would rank bids from highest to lowest. It would
then select a random number (j) between 2 and k (k bidders) and it would sell the album for
the price the j-bidder proposed. For example, if the system chose j = 690 and this person
had valued the album at $5.65, all customers between j and k (who had placed a bid higher
than $5.65) would automatically buy the album at j’s price.
The iTunes app randomly assigned customers to one of three treatments. In treat-
ment IS (inferior separate) we auctioned off an album with four tracks, all rated 70% and
above in popularity. The combined value of the songs as rated by music reviewers was ap-
proximately $4. In treatment SS (superior separate) we auctioned off an album with seven
tracks: the identical four tracks offered for treatment IS, plus three tracks rated below 30%
4

5. B-sides and Behavioral Biases: Why Artists Are Better Off With Shorter Albums
in popularity. This album was previously valued at $5.25. In treatment J (joint) customers
were faced with the two previous track bundles side by side. Accordingly, each individual
submits two bids, one for each album. They were informed that in case they won both bids,
the system would randomly determine which action was binding.
After each customer placed his/her bid, iTunes asked them how much they would be
willing to pay to watch the same artists concert. Individuals elected a price and were thanked
by their participation in the experiment. Because the valuation was not binding, users may
not have revealed their true willingness to pay. However, this second evaluation allows us to
learn the effects of album valuation on pricing of concerts, which leads to interesting insights
not only for record companies, but artists themselves.
A couple of observations are worth mentioning before proceeding to the next section.
First, to prevent individuals from participating in more than one treatment group only those
already logged in with their iTunes account were able to participate in the experiment.
Second, in order for artists to have their music as part of the experiment they signed a
contract binding them not to sell anywhere else until the experiment was over. That measure
prevented customers from comparing prices with other websites, which would lead to bias in
their bidding.
3 Results
The experiment was very effective and was conducted without issue. Table 1 shows the sum-
mary statistics for our experimental data. In all, we collected 240 observations with roughly
an equal split between treatment groups. The experiment was targeted toward demographics
5

6. B-sides and Behavioral Biases: Why Artists Are Better Off With Shorter Albums
most likely to purchase music online. Accordingly, most respondents are between the ages
of 16 and 30 with a nearly even split between males and females. Valuations of the shorter
4 track EP were collected for the IS and J groups while valuations of the longer 7 track EP
were collected for the SS and J groups. Concert valuations were recorded for all participants.
The most striking observation from the results of the experiment is shown in Table
2 by a comparison between the average willingness-to-pay of respondents exposed to the
EP composed of purely high-quality songs versus those exposed to the longer EP including
several “B-side” tracks in addition to the core songs. Those exposed to only the shorter (IS)
setlist had an average valuation $1.23 higher than those exposed to only the longer (SS)
setlist ($3.80 vs $2.57). A t-test on the difference in means yields a statistically significant
result at the p < .05 level with a test statistic of t = 7.40. This shows a “more is less”
result. Theoretically, since the shorter setlist is a strict subset of the longer version, unless
the incremental tracks somehow provide negative utility, the longer version should be strictly
preferred to the shorter version. This prediction is supported by the results from the joint
group who were exposed to both versions of the EP, where respondents consistently placed
a higher valuation on the longer EP. Respondents in the J group gave an average valuation
of $3.83 for the longer EP compared to $2.99 for the shorter EP. A t-test on this difference
in means yields a statistically significant result at the p < .05 level with a test statistic
of t = 5.51. The results of the treatment groups, however, reinforce the “more is less”
hypothesis showing a reversal of preferences compared to the joint group. Thus, respondents
valuations are subject to the average bias where the inclusion of incremental substandard
tracks lowers the average perceived quality of each track leading to a lower overall valuation
of the EP. Again, this perverse result is not evident in the group exposed to both versions
6

7. B-sides and Behavioral Biases: Why Artists Are Better Off With Shorter Albums
of the EP where respondents, on average, placed a higher value on the longer setlist.
Results for the second portion of the experiment are also given in Table 2. Again, a
comparison between the average value that respondents place on a live concert for the artist
in question shows that the average bias has implications extending beyond the primary
transaction. A t-test on the difference in means for the IS and SS groups ($9.06 vs $7.70)
yields a statistically significant result at the p < .05 level with a test statistic of t = 3.20.
Interestingly, the mean concert valuation for the group exposed to both versions of the EP
side-by-side was also lower than those who were solely exposed to the short, high-quality
version. This further reinforces the more is less hypothesis.
4 Conclusion
The average bias and preference reversal have been documented in a variety of settings. The
results of our experiment reinforce existing research and show that the bias can have residual
effects as evidenced by the continued bias in concert valuation. Other studies have shown
this bias to be attenuated in more experienced individuals (List, 2002). While resistance
to bias is generally considered to be a desirable trait, is not clear it would be desirable
in this setting. Record label executives who are making track inclusion decisions may be
less susceptible to the bias than consumers. This would lead to suboptimal outcomes for all
parties since record labels may choose to include lower quality tracks assuming that they offer
incremental value while consumers perceive lower value due to the average bias. Further, our
results have implications for artists themselves. Many artists view album sales as building
awareness to drive concert sales, where they make most of their money. Accordingly, artists
7

8. B-sides and Behavioral Biases: Why Artists Are Better Off With Shorter Albums
may wish to restrict creative output to only their highest quality work in an effort to avoid
the adverse effects of the average bias on potential concert revenues. This is an area where
more extensive research could validate these findings and further explore the residual effects
of the average bias on subsequent decisions. For instance, future studies might attempt
to make the valuation on the secondary transaction more binding than the simple survey
question employed herein.
The average bias is one of many cognitive biases which, when understood, can shed
light on why people make the choices they do. Aside from this particular application of our
findings, there are many business and policy settings where these results can affect change.
Perhaps one of of the most relevant applications, however, would be in other markets for
creative and artistic goods like books, movies and the like. We would expect that simi-
lar biases would be found in such areas, and these results can better inform the decision
making of agents these fields. Further research could validate this claim and provide more
understanding of this widespread and relevant bias.
8

9. B-sides and Behavioral Biases: Why Artists Are Better Off With Shorter Albums
Variable n Mean SD
EPval4 163 3.36 1.10
EPval7 166 3.25 1.18
Conval 240 8.22 2.57
Age 240 23.51 4.62
Female 240 0.47 0.50
Table 1: Summary Statistics
Valuations
Treatment 4 Songs 7 Songs Concert
IS (n=74) $3.80 (1.03) — $9.06 (2.63)
SS (n=77) — $2.57 (1.01) $7.70 (2.58)
J (n=89) $2.99 (1.02) $3.83 (1.00) $7.97 (2.37)
Table 2: Experimental Results
Figure 1: Distribution of valuations by treatment
9

10. B-sides and Behavioral Biases: Why Artists Are Better Off With Shorter Albums
References
Goldman, D. (2010). Musics lost decade: Sales cut in half. CNN Money, 3.
Grether,David M. and Plott, Charles. (1979) Economic theory of choice and the preference
reversal phenomenon. American Economic Review, 69(4), 623-38.
Hsee, Christopher K. (1998). Less is better: when low-value options are valued more highly
than high-value options. Journal of Behavioral Decision Making. 11, 107-121.
List, John A. (2002). Preference reversals of a different kind: the “more is less” phenomenon.
The American Economic Review. 95(5), 1636-1643.
Mortimer, J. H., Nosko, C., Sorensen, A. (2012). Supply responses to digital distribution:
Recorded music and live performances. Information Economics and Policy, 24(1), 3-
14.
Peitz, M., Waelbroeck, P. (2006). Why the music industry may gain from free downloadingthe
role of sampling. International Journal of Industrial Organization, 24(5), 907-913.
10