Corporate R&D Spillovers and Investment in the Innovation Network

2015 ◽  
Author(s):  
Alex Xi He
Keyword(s):  
Innovation Network

The innovation network (TIN)

1996 ◽  
Vol 18 (1) ◽  
pp. 117-122
Author(s):  
James martin Simmie
Keyword(s):  
Innovation Network

scholarly journals Response of the Trial Innovation Network to the COVID-19 Pandemic

2021 ◽  
pp. 1-21
Author(s):  
Rachel G Greenberg ◽  
Lori Poole ◽  
Daniel E Ford ◽  
Daniel Hanley ◽  
Harry P Selker ◽  
...  
Keyword(s):  
Innovation Network

scholarly journals LEARNING AND INNOVATION NETWORK IN NURSING: A CONCEPT ANALYSIS

2021 ◽  
pp. 104988
Author(s):  
M. Albers ◽  
R.R.J. Gobbens ◽  
M. Reitsma ◽  
O.A.A.M.J. Timmermans ◽  
H.L.G.R. Nies
Keyword(s):  
Concept Analysis ◽  
Innovation Network

scholarly journals Dynamic Evolution Model of a Collaborative Innovation Network from the Resource Perspective and an Application Considering Different Government Behaviors

Information ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 138 ◽  
Author(s):  
Wu ◽  
Shao ◽  
Feng
Keyword(s):  
Network Evolution ◽  
Evolution Model ◽  
Dynamic Evolution ◽  
Innovation Network ◽  
Transfer Policy ◽  
Collaborative Innovation ◽  
Innovation Output ◽  
The Government ◽  
Small Change ◽  
Innovative Behaviors

The evolution of a collaborative innovation network depends on the interrelationships among the innovation subjects. Every single small change affects the network topology, which leads to different evolution results. A logical relationship exists between network evolution and innovative behaviors. An accurate understanding of the characteristics of the network structure can help the innovative subjects to adopt appropriate innovative behaviors. This paper summarizes the three characteristics of collaborative innovation networks, knowledge transfer, policy environment, and periodic cooperation, and it establishes a dynamic evolution model for a resource-priority connection mechanism based on innovation resource theory. The network subjects are not randomly testing all of the potential partners, but have a strong tendency to, which is, innovation resource. The evolution process of a collaborative innovation network is simulated with three different government behaviors as experimental objects. The evolution results show that the government should adopt the policy of supporting the enterprises that recently entered the network, which can maintain the innovation vitality of the network and benefit the innovation output. The results of this study also provide a reference for decision-making by the government and enterprises.

scholarly journals Early Vision for the CTSA Program Trial Innovation Network: A Perspective from the National Center for Advancing Translational Sciences

2017 ◽  
Vol 10 (5) ◽  
pp. 311-313 ◽  
Author(s):  
MR Shah ◽  
MA Culp ◽  
KR Gersing ◽  
PL Jones ◽  
ME Purucker ◽  
...  
Keyword(s):  
Innovation Network ◽  
Early Vision

Complexity, Networks & Learning: Integrative Themes for Research on Innovation Management

1997 ◽  
Vol 01 (01) ◽  
pp. 1-21 ◽  
Author(s):  
Joe Tidd
Keyword(s):  
New Product Development ◽  
Innovation Management ◽  
Innovation Process ◽  
New Product ◽  
Innovation Network ◽  
Comprehensive Model ◽  
Market Knowledge ◽  
Management Of Innovation ◽  
Organisational Factors ◽  
Process Complexity

Research on the management of innovation has been highly fragmented, and to a large extent non-cumulative. Much of the research has been conducted within three separate disciplines, with relatively little overlap or interaction: the management of research and development or technology; new product development and marketing; and organisational development and change. In this paper, we identify a number of emergent themes which have the potential to integrate these diverse streams of research, and result in a more comprehensive model of the innovation process: complexity, networks and learning. We argue that the innovation process is inherently complex, and therefore we need better characterisations of the technological, market and organisational contingencies which affect the opportunity for innovation. With growing complexity, the focus shifts from competencies based on internal assets such as R&D activities and intellectual property, to the position of a firm within an innovation network and competencies based on its relationships with other organisations. Finally, too much research has been pre-occupied with how firms develop and exploit narrow competencies based on prior experience, rather than how firms acquire new competencies. A focus on organisational learning may provide a richer explanation of the organisational factors which affect the acquisition of new technological and market knowledge.

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