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Discussion and Conclusion
There were three primary findings. First, high tail novelty papers had higher impact
than low tail novelty papers, an impact advantage that occurred at any level of con-
ventionality and regardless of authorship structure. Second, peak impact occurs in
the 85–95th percentile of median conventionality, an exceptionally high level. This
peak and its position appeared irrespective of tail novelty/no tail novelty or author-
ship structure. These generic features suggest fundamental underlying rules relating
combinations of prior work to the highest impact science.
Finally, Fig. 12.4 indicates that for virtually all possible mixes of tail novelty and
median conventionality, larger teams were associated with higher impact. Thus,
while teams incorporated the highest impact mixes more frequently (Fig. 12.3),
teams also tended to obtain higher impact for any particular mix (Fig. 12.4).
Nonetheless, despite this advantage in citations across virtually all fields of science
(Wuchty et al., 2007), even teams had low impact at low levels of median conven-
tionality and tail novelty.
0.030
0.025
0.020
5
Percentiles of median z-score Percentiles of median z-score
25 45 55
653515 75 85 95 99 5 25 45 55
653515 75 85 95 99
Pair Authors, High Tail Novelty
Pair Authors, Low Tail Novelty
Solo Author, High Tail Novelty
Solo Author, Low Tail Novelty
Percentiles of median z-score
5 25 45 55
653515 75 85 95 99
Team Authors, Low Tail Novelty
Team Authors, High Tail Novelty
0.015
0.010
0.005
0.000
0.030
0.025
0.020
0.015
0.010
0.005
0.000
Fig. 12.10 Novelty, authorship and impact for top 1 % of papers. This figure repeats Fig. 12.9 but
defines hit papers as those that receive citations within 8 years of publication that are in the upper
1 % of all papers published that year. From Uzzi et al. (2013b, p. 16). Copyright 2013 by Science.
Adapted with permission from the authors and Science
12 How Atypical Combinations of Scientific Ideas Are Related to Impact:…
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Buch Knowledge and Networks"
Knowledge and Networks
- Titel
- Knowledge and Networks
- Autoren
- Johannes Glückler
- Emmanuel Lazega
- Ingmar Hammer
- Verlag
- Springer Open
- Ort
- Cham
- Datum
- 2017
- Sprache
- deutsch
- Lizenz
- CC BY 4.0
- ISBN
- 978-3-319-45023-0
- Abmessungen
- 15.5 x 24.1 cm
- Seiten
- 390
- Schlagwörter
- Human Geography, Innovation/Technology Management, Economic Geography, Knowledge, Discourse
- Kategorie
- Technik