Match!

Knowledge creation in collaboration networks: Effects of tie configuration

Published on Feb 1, 2016in Research Policy5.42
· DOI :10.1016/j.respol.2015.09.003
Jian Wang11
Estimated H-index: 11
(Katholieke Universiteit Leuven)
Abstract
This paper studies the relationship between egocentric collaboration networks and knowledge creation at the individual level. For egocentric networks we focus on the characteristics of tie strength and tie configuration, and knowledge creation is assessed by the number of citations. Using a panel of 1042 American scientists in five disciplines and fixed effects models, we found an inverted U-shaped relationship between network average tie strength and citation impact, because an increase in tie strength on the one hand facilitates the collaborative knowledge creation process and on the other hand decreases cognitive diversity. In addition, when the network average tie strength is high, a more skewed network performs better because it still has a “healthy” mixture of weak and strong ties and a balance between exploration and exploitation. Furthermore, the tie strength skewness moderates the effect of network average tie strength: both the initial positive effect and the later negative effect of an increase in tie strength are smaller in a more skewed network than in a less skewed one.
  • References (136)
  • Citations (35)
References136
Newest
#1John Walsii (Georgia Institute of Technology)H-Index: 28
#2You-Na Lee (Georgia Institute of Technology)H-Index: 6
#1Jian Wang (Katholieke Universiteit Leuven)H-Index: 11
#2Bart Thijs (Katholieke Universiteit Leuven)H-Index: 23
Last.GlänzelWolfgang (Katholieke Universiteit Leuven)H-Index: 55
view all 3 authors...
#1Kota Murayama (NU: Northwestern University)H-Index: 1
#2Makoto Nirei (Hitotsubashi University)H-Index: 9
Last.Hiroshi Shimizu (Hitotsubashi University)H-Index: 4
view all 3 authors...
#1You-Na Lee (Georgia Institute of Technology)H-Index: 6
#2John Walsii (GRIPS: National Graduate Institute for Policy Studies)H-Index: 28
Last.Jian Wang (Katholieke Universiteit Leuven)H-Index: 11
view all 3 authors...
#1Jian Wang (Katholieke Universiteit Leuven)H-Index: 11
#2Diana Hicks (Georgia Institute of Technology)H-Index: 27
Cited By35
Newest
#1Omid Askarisichani (UCSB: University of California, Santa Barbara)
#2Jacqueline Ng Lane (Harvard University)
Last.Brian Uzzi (NU: Northwestern University)H-Index: 34
view all 6 authors...
#1Piergiuseppe Morone (Sapienza University of Rome)H-Index: 12
#2Pasquale Marcello Falcone (Sapienza University of Rome)H-Index: 8
Last.Valentina Elena Tartiu (Sapienza University of Rome)H-Index: 3
view all 0 authors...
#1Felix Nti Koranteng (Ghana Institute of Management and Public Administration)H-Index: 1
#2Isaac Wiafe (University of Ghana)H-Index: 4
Last.Eric Kuada (Ghana Institute of Management and Public Administration)H-Index: 1
view all 3 authors...
2019 in FSE (Foundations of Software Engineering)
#1Shurui Zhou (CMU: Carnegie Mellon University)H-Index: 4
#2Bogdan Vasilescu (CMU: Carnegie Mellon University)H-Index: 2
Last.Christian Kästner (CMU: Carnegie Mellon University)H-Index: 41
view all 0 authors...
#1Feifei Wang (Beijing University of Technology)H-Index: 1
#2Chenran Jia (Beijing University of Technology)
view all 7 authors...
#1Xuemei Xie (SHU: Shanghai University)H-Index: 6
#2Yanru Gao (SHU: Shanghai University)
Last.Xiaohua Meng (Soochow University (Suzhou))
view all 4 authors...
View next paperMore than network structure: how knowledge heterogeneity influences managerial performance and innovativeness