Knowledge networks and innovation policy

The competitiveness in global competition is increasingly more dependent on the ability to create unique products and services. This is achieved through innovation. Innovation is a highly knowledge intensive activity, which requires combining different types of knowledge. Firms require many types of specialized knowledge that they cannot produce themselves. Moreover, knowledge often has a tacit element, which reduces its supply in the market. This calls for collaborative links among firms and between firms and institutions. Knowledge is exchanged, transferred and shared through non-market based knowledge networks. Those organizations which exploit networks as a source of knowledge gain competitive advantage over those which do not. Organizations often underinvest in forming and sustaining network relations. This justifies the public support of networking as part of innovation policy. The current study examines the microstructure of knowledge diffusion and innovation processes and aims to find guidelines for innovation policy design from this perspective. Its goals are to find out (1) what role do knowledge sharing networks play in innovation, (2) how does the micro-level structure of knowledge transfer interactions affect the overall performance of an economic system and (3) what are the implications of the analysis of knowledge sharing networks on innovation policy design? The current study is a theoretical examination on these subjects. Knowledge networks are found to function as extensions to the innovation resources and capabilities of economic agents. The availability of knowledge positively influences innovation in all stages: invention, innovation and diffusion. The benefits from networks include e.g. overcoming path dependency in the direction of technological development, learning about market needs and influencing customer preferences. Agent-based models of the diffusion of knowledge in networks suggest that the structure of a knowledge sharing network and the capabilities of economic agents have an effect on the performance of the network. The best performance is achieved in 'small-world' networks which consist of tightly interrelated groups of agents which have some contacts with other groups. Limitations on the learning capabilities of the agents may prevent knowledge sharing. If the agents require a shared knowledge base to be able to communicate with each other, providing all agents with some basic level of knowledge will ease communication and facilitate the diffusion of knowledge. Innovation policy based on the knowledge network analysis can be divided into promoting the creation of small-world networks and removing barriers to communication between agents. Small-world networks can be understood as local networks such as business clusters or non-local networks such as research networks or professional networks. Barriers to communication can be removed by improving the learning abilities of agents (means to learn) and promoting investments in collaboration (incentives to learn). The policy measures associated with the issues are various. Much attention is paid to providing a suitable institutional set-up which eases networking and knowledge transfer. Many of the relevant policy measures are complementary and should be adopted as packages. Changing one policy variable might have no effect if other variables are not changed at the same time. Furthermore, the knowledge networks are often technology or industry specific and technology neutral policies may overlook their needs. Thus the technology neutral policy measures should be supplemented by technology-specific measures. The identification of bottlenecks in technology-specific networks is needed in order to choose the best policy measure(s). According to a technological innovation system framework, technology fields should be evaluated on functionality: how a technological innovation system fulfils certain common criteria that are considered necessary for the development of innovations in a field. This evaluation helps choose which policy measures should be implemented.

Grantor dc:publisher

Helsingfors universitet

Year dc:date.issued

2012

Author dc:creator

• Pihlajamaa, Matti

Contributors dc:contributor

• Helsingin yliopisto, Valtiotieteellinen tiedekunta, Politiikan ja talouden tutkimuksen laitos
• University of Helsinki, Faculty of Social Sciences, Department of Political and Economic Studies
• Helsingfors universitet, Statsvetenskapliga fakulteten, Institutionen för politik och ekonomi

• networks
• knowledge
• innovation policy
• verkostot
• innovaatiopolitiikka

Language dc:language.iso

eng

Identifier URI

URN:NBN:fi:hulib-201703271940

OAI identifier oai:identifier

oai:helda.helsinki.fi:10138/34087