The dynamics of R&D network in the IT industry

Nobuyuki Hanaki; Ryo Nakajima; Yoshiaki Ogura

doi:10.1016/j.respol.2010.01.001

The dynamics of R&D network in the IT industry

Nobuyuki Hanaki, Ryo Nakajima, Yoshiaki Ogura

Faculty of Economics

Research output: Contribution to journal › Article › peer-review

59 Citations (Scopus)

Abstract

In this paper, we provide an empirical analysis of evolving networks of successful R&D collaborations in the IT industry (consisting of firms that obtained patents in the technological category of computers and communication) in the U.S. between 1985 and 1995. We first show that the R&D network has become more extensive, more clustered, and more unequal in the sense that 'stars' have emerged in the network. We then analyze the effect of the existing network structure in the process of new R&D collaboration formation. We control for unobserved similarities among firms based on the community structures within the network that the algorithm developed by Girvan and Newman (2004) identifies and find a significant cyclic closure and preferential-attachment effect.

Original language	English
Pages (from-to)	386-399
Number of pages	14
Journal	Research Policy
Volume	39
Issue number	3
DOIs	https://doi.org/10.1016/j.respol.2010.01.001
Publication status	Published - 2010 Apr

Keywords

Dynamic networks
R&D partnerships

ASJC Scopus subject areas

Strategy and Management
Management Science and Operations Research
Management of Technology and Innovation

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10.1016/j.respol.2010.01.001

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title = "The dynamics of R&D network in the IT industry",

abstract = "In this paper, we provide an empirical analysis of evolving networks of successful R&D collaborations in the IT industry (consisting of firms that obtained patents in the technological category of computers and communication) in the U.S. between 1985 and 1995. We first show that the R&D network has become more extensive, more clustered, and more unequal in the sense that 'stars' have emerged in the network. We then analyze the effect of the existing network structure in the process of new R&D collaboration formation. We control for unobserved similarities among firms based on the community structures within the network that the algorithm developed by Girvan and Newman (2004) identifies and find a significant cyclic closure and preferential-attachment effect.",

keywords = "Dynamic networks, R&D partnerships",

author = "Nobuyuki Hanaki and Ryo Nakajima and Yoshiaki Ogura",

note = "Funding Information: We would like to thank for valuable comments from Gueorgi Kossinets, Hidehiko Ichimura, Daiji Kawaguchi, Tomoya Mori, Ryo Kambayashi, Reiko Aoki, Hiroyuki Chuma, Sadao Nagaoka, and anonymous referees. We are also grateful to Ryuichi Tamura for implementing CMP. Of course, the responsibility of all remaining errors is ours. Financial support from the Japan Securities Scholarship Foundation, Inamori Foundation and the Kikawada Foundation (21-seiki bunka gakujyutsu zaidann) are gratefully acknowledged. This research was also supported by Grant-in-Aid for Young Scientists (B) awarded from The Ministry of Education, Culture, Sports, Science, and Technology of Japan (Grant no. 19730165). ",

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doi = "10.1016/j.respol.2010.01.001",

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AU - Hanaki, Nobuyuki

AU - Nakajima, Ryo

AU - Ogura, Yoshiaki

N1 - Funding Information: We would like to thank for valuable comments from Gueorgi Kossinets, Hidehiko Ichimura, Daiji Kawaguchi, Tomoya Mori, Ryo Kambayashi, Reiko Aoki, Hiroyuki Chuma, Sadao Nagaoka, and anonymous referees. We are also grateful to Ryuichi Tamura for implementing CMP. Of course, the responsibility of all remaining errors is ours. Financial support from the Japan Securities Scholarship Foundation, Inamori Foundation and the Kikawada Foundation (21-seiki bunka gakujyutsu zaidann) are gratefully acknowledged. This research was also supported by Grant-in-Aid for Young Scientists (B) awarded from The Ministry of Education, Culture, Sports, Science, and Technology of Japan (Grant no. 19730165).

PY - 2010/4

Y1 - 2010/4

N2 - In this paper, we provide an empirical analysis of evolving networks of successful R&D collaborations in the IT industry (consisting of firms that obtained patents in the technological category of computers and communication) in the U.S. between 1985 and 1995. We first show that the R&D network has become more extensive, more clustered, and more unequal in the sense that 'stars' have emerged in the network. We then analyze the effect of the existing network structure in the process of new R&D collaboration formation. We control for unobserved similarities among firms based on the community structures within the network that the algorithm developed by Girvan and Newman (2004) identifies and find a significant cyclic closure and preferential-attachment effect.

AB - In this paper, we provide an empirical analysis of evolving networks of successful R&D collaborations in the IT industry (consisting of firms that obtained patents in the technological category of computers and communication) in the U.S. between 1985 and 1995. We first show that the R&D network has become more extensive, more clustered, and more unequal in the sense that 'stars' have emerged in the network. We then analyze the effect of the existing network structure in the process of new R&D collaboration formation. We control for unobserved similarities among firms based on the community structures within the network that the algorithm developed by Girvan and Newman (2004) identifies and find a significant cyclic closure and preferential-attachment effect.

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The dynamics of R&D network in the IT industry

Abstract

Keywords

ASJC Scopus subject areas

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