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Summary Summaries for all mandatory readings for Cultural Entrepreneurship and Innovation. week 5

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One-page summaries of all mandatory readings for Business Administration Master's Entrepreneurship and Management in The Creative Industries track, for the course Cultural Entrepreneurship and Innovation. Week 5 1. Fraiberger 2018: Quantifying reputation and success in art 2. Wachs et al (2018) And Now for Something Completely Different: Visual Novelty in an Online Network of Designers 3. Gervais (2019) The Machine As Author 4. Xu, Zhang & Zhou (2019) Validity concerns in research using organic data

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Week 5- Big data Big art
Fraiberger 2018: Quan fying reputa on and success in art
Paper in a Nutshell
The quality of art is elusive; art appeals to individual senses, pleasures, feelings, and emo ons, yet its
recogni on depends on variables external to the work itself.
Ar s c performance is hard to quan fy; reputa on and network in uences play a key role in determining
successful ar s c performance. This study aims to understand the role of reputa on and network
structures. The authors show how access to pres gious ins tu ons (exhibi ons) early in an ar st’s career
o ered life-long access to high-pres ge venues and reduced dropout rate.
Method
They use advanced learning techniques to study ar sts’ careers in renewed/less renewed art galleries-
network, core and periphery.
They do this by reconstruc ng an exhibi on history of 0.5 million ar sts, mapping out their movements
between art ins tu on around the world.How close-by is determined by how many common ar sts they
showed, colour by country and size means reputa on.
Results
- Clustering of the art world: The network core was a dense community of major European and North
American ins tu ons, underlying their access to a common pool of ar s c talents. Movement between
hubs was very high, re ec ng a highly concentrated movement of selected ar sts between a few
prominent ins tu ons.
- If the ar st started in a core posi on (pres gious museum) they would con nue with pres gious galleries
and oppositely for others. There was also a correla on between network-based ranks and economic
value of the artwork -> network e ects play a de ning role in in uencing the evolu on of an ar st’s
reputa on and valua on.
- Star ng at the periphery has limi ng access to central ins tu ons but their recep on improved with
me, advancing slowly to ins tu ons of increasing pres ge. Overall, high ini al reputa on ar sts had
twice as many exhibi ons as low ini al reputa on ar sts. High dropout rates between low reputa on.
—>Success in the market is path dependent, past reputa on and pres ge of the loca on where the
exhibi on takes place has a meaning. Mul plica ve weight that increases even more the di erence with the
compe tors.
Art market as an example of winners take all market- in this market slightly be er ar sts receive
dispropor onately larger shares of pres ge and revenue.
Issues with the paper:
• The authors don’t inves gate what triggers the ini al success. When does success start? To what extent
do these these self reinforcing loops in uence the ar sts’s career?
• Even in the top echelon the idea of self reinforcing feedback loops are at play




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