Knowledge Spillovers and Local Innovation Systems: A Critical Survey

Breschi, Stefano

doi:10.1093/icc/10.4.975

Cited by 1,043 publications

(649 citation statements)

References 74 publications

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“…However, it is more likely that the redundancy of knowledge will actually lead to diminishing returns for individual organisations (γ < 1) (McFadyen and Cannella, 2004;Goerzen and Beamish, 2005). However, as a form of regional system there may also be increasing returns from connections (υ > 1), where the region as a whole performs more strongly as knowledge circulates at a faster rate, allowing the faster diffusion of innovation (Breschi and Lissoni, 2001). It is possible that individual organisations may suffer from knowledge redundancy, whilst the region as a whole benefits, so many well-connected organisations may generate more network capital compared to a few very well connected organisations.…”

Section: Wlr Is Local Network Capital (Connections Within Region R) mentioning

confidence: 99%

A Network-based view of regional growth

Huggins

Thompson

2013

Journal of Economic Geography

132

141

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The need to better understand the mechanisms underlying regional growth patterns is widely recognised. This paper argues that regional growth is partly a function of the value created through inter-organisational flows of knowledge within and across regions. It is proposed that investment in calculative networks by organisations to access knowledge is a form of capital, termed network capital, which should be incorporated into regional growth models. The paper seeks to develop a framework to capture the value of network capital within these models based on the spatial configuration and the nature of the knowledge flowing through networks.

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Section: Wlr Is Local Network Capital (Connections Within Region R) mentioning

confidence: 99%

A Network-based view of regional growth

Huggins

Thompson

2013

Journal of Economic Geography

132

141

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“…Its importance lies also in the fact that the periods of co-location between individuals create conditions for the development of other types of proximity -social, cognitive, organisational (Boschma, 2005) -that are essential for effective knowledge transmission (Breschi and Lissoni, 2001). Social proximity is related with the presence of social ties between actors, which derive from sharing the same origin or affiliation.…”

Section: Mobility Proximity and Knowledge Networkmentioning

confidence: 99%

The Impact of Long-term Scientific Mobility on the Creation of Persistent Knowledge Networks

2013

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International scientific mobility is a strategic element in the science policies of several countries, being often equated with the development of extensive knowledge networks that can be mobilised by the scientists (and their organisations) upon their return. The objective of this paper is to understand whether and in which conditions mobility leads to the development of knowledge links that are long lasting and effectively play a key role in scientists' activities. In conceptual terms, the influence of mobility is explained through the opportunities it provides for temporary co-location in one organisation, and thus for the creation of social, cognitive and organisational proximity between scientists, which are critical for knowledge transmission and which can persist after the individuals draw apart. This conceptual framework supports an empirical analysis of the impact of two types of long term mobility -for training and professional purposes -on the creation of "persistent knowledge networks", in the case of Portuguese scientists. The results show that mobile scientists are more likely to have foreign organisations in their core knowledge network. Even more importantly, they reveal a high incidence of organisations that were part of the scientists' trajectory in these networks, providing some confirmation to the effects of colocation. However, these effects are not always present: the research also identifies some factors -related with personal characteristics, career situation, scientific field, time, geographical distance, motivations to move -that increase the likelihood of network persistence, which differ for the two types of mobility. AcknowledgmentsResearch conducted in the context of the project MOBISCIENCE: Scientists´mobility in Portugal: trajectories and knowledge circulation (PTDC/ESC/64411/2006), funded by the Fundação para a Ciência e Tecnologia, whose support is gratefully acknowledged.2

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“…Knowledge that is transferred unintentionally is largely tacit, i.e. highly contextual and difficult to codify, and happens through personal relationships where social bonds foster reciprocal trust (Breschi and Lissoni, 2001). The challenge when partnering is to share sufficient skills such that an advantage is created for the partners versus companies not part of the partnership, without transferring core skills to the partner.…”

Section: Unintended Knowledge Flowsmentioning

confidence: 99%

Safeguarding SMEs dynamic capabilities in technology innovative SME-large company partnerships in South Africa

Sawers¹,

Pretorius

Oerlemans

2008

Technovation

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This paper focuses on technological collaboration between small and large firms. It is argued that such collaborations can be beneficial for both types of partner, but that small firms often are confronted by the hazards of collaboration as these relationships are typically asymmetric. As a result of this, knowledge embodied in the dynamic (strategic, internal and external) capabilities of SMEs can flow unintentionally to the larger partner.If this occurs, the collaboration would be less successful from the SMEs' point of view.Next, it is proposed that the use of formal and informal safeguards can protect technology innovative SMEs against such knowledge flows. This paper examines to what extent is the number of dynamic capabilities of SMEs associated with partnership success and to what extent is this relationship influenced by the number of safeguards used by the SMEs? A sample of 43 technology innovative SMEs was interviewed by means of a structured questionnaire. Logistic regression analysis was conducted to determine the relationship between the number of dynamic capabilities on the one hand and partnership success on the other. Moreover, the impact of (in)formal safeguards on this relationship openUP was analyzed. The research found that SME's strategic and internal capabilities are negatively associated with partnership success, whereas external capabilities are positively related. The inclusion of safeguards turned out to produce the hypothesized effects. The paper shows, therefore, that unintentional knowledge flows from the SME to the larger partner can be prevented by putting in place formal and informal protection mechanisms.

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Knowledge Spillovers and Local Innovation Systems: A Critical Survey

Cited by 1,043 publications

References 74 publications

A Network-based view of regional growth

A Network-based view of regional growth

The Impact of Long-term Scientific Mobility on the Creation of Persistent Knowledge Networks

Safeguarding SMEs dynamic capabilities in technology innovative SME-large company partnerships in South Africa

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