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In creative industries like music, books or video, suppliers face high costs producing original contents and entering in creative markets is highly risky. These markets are structured as oligopolistic with fringes. In the music market, while a few majors control the distribution networks, a competitive fringe, the labels, take risks and finance novelty. But only a few number of artists get to be supported through the production process. Crowdfunding represents today an alternative for creators to be financed by the demand itself. Most of the time, an artist conducts a fundraising campaign on an online platform, like Kickstarter, and people, called backers, can financially support the project. The backers usually get to be rewarded for their support by a physical or symbolic reward or a pre-ordering. Paradoxically, at a time where consumers propensity to pay for cultural goods such as music seems to fall down, the crowd is willing to financially take care of artistic productions. Crowdfunding for artistic projects can be a challenging topic for economics as it brings into play an hybrid system between donation and purchase. Indeed, supporting an artist mix willing to buy his production and willing to donate and help him. More specifically, in the case of reward-based crowdfunding, the creator and the crowd engage in more than a mercantile process but in a real social interaction.
Because of this specific framework, we know little about the real motives to back an artistic project and about backers profiles. Moreover, the subject of crowdfunding refers to several systems (pure donation, rewardbased donation, equity based financing) that may implies different decision process for backers. According to Belleflamme, Lambert and Schwienbacher (2013), besides the satisfaction brought by tangible and symbolical rewards, backers profit from community benefits like belonging to a network with shared values or take part into a project that you estimate. I suggest these community benefit may refers to social preferences, like altruism, cooperation and reciprocity. Along with this hypothesis, Zvilichovsky, Inbar and Barzilay (2013) found that project creators tend to invest in projects held by the backers of their own project. They also show that creators that are also backers have a higher propensity to back projects held by recurrent backers.
This paper aims to study the prosocial foundations of the decision to financially back an artistic project. To do so, I use experimental data measuring social preferences as well as field data describing real investments. By gathering exogenous experimental measures, I want to study what social preferences are in stake when backers decide how much to invest and how many projects to finance.
Hypothesis
H1 Altruism (pure and warm-glow) is correlated with higher level of investment in artistic projects.
H2 Altruism linked with welfare concern is correlated with higher level of investment in artistic projects.
H3 Cooperation is correlated with higher level of investment in artistic projects.
H4 Reciprocity is correlated with higher level of investment in artistic projects for individuals who are project holders.
H5 Risk aversion is negatively correlated with the level of investment in artistic projects
Design
This paper couples data with field data thank to a partnership with the predominant crowdfunding platform in Brazil, Catarse. The platform is mainly presenting artisctical and creative projects (the majority being music, film projects).
Experimental data I set up an online experiment, as Internet turned out to be a good way to replicate lab experiments (Hergueux and Jacquemet, 2012). I am able to measure three standard social preferences :
- Altruism I measure three aspects of altruism thanks to three versions (pure altruism, warm-glow and social welfare) of the dictator game (one standard dictator game, one where the receiver is endowed and one where the transfer is multiplied by 3.)
- Cooperation I measure the propensity to cooperate in two versions of the public good game, the first one being the standard version and the second one with a threshold, replicating the typical all-ornothing frame characterizing the crowdfunding platform.
- Reciprocity I measure reciprocity with a standard trust game.
Besides these measure, I add two measures of risk aversion ( Holt and Laury (2002)'s lotteries and Dohmen et al. (2011)'s context based measure of risk aversion). It is crucial to control for risk aversion when studying crowdfunding decisions since investing in such projects implies the risk of project failure (even in an all-ornothing framework, there is a risk that the project holder do not succeed in delivering his product).
Field data Catarse will provide me with individual data regarding behavior on the platform. More precisely,
for each individual, I will be informed of :
- the number of projects he/she backed since registration
- the total amount invested
- the amount invested per project
- variable linked to the project (field, objective, number of days...)
- his/her will to purely donate
- his/her will to stay anonymous
Results
The online experiment will be launch on the 24th of March. Nevertheless, I would be able to present the first results for the ASFEE conference.
References
Belleflamme, Paul, Thomas Lambert, and Armin Schwienbacher. 2013. “Crowdfunding : Tapping the right crowd.” Journal of Business Venturing.
Dohmen, Thomas, Armin Falk, David Huffman, Uwe Sunde, Jürgen Schupp, and Gert G Wagner. 2011. “Individual risk attitudes : Measurement, determinants, and behavioral consequences.” Journal of the European Economic Association, 9(3) : 522–550.
Hergueux, Jérôme, and Nicolas Jacquemet. 2012. “Social preferences in the online laboratory : a randomized experiment.” Experimental Economics, 1–33.
Holt, Charles A, and Susan K Laury. 2002. “Risk aversion and incentive effects.” American economic review, 92(5) : 1644–1655.
Zvilichovsky, David, Yael Inbar, and Ohad Barzilay. 2013. “Playing Both Sides of the Market : Success and Reciprocity on Crowdfunding Platforms.”
