Creating and managing a high‐performance knowledge‐sharing network: the Toyota case

Dyer, Jeffrey H.; Nobeoka, Kentaro

doi:10.1002/(sici)1097-0266(200003)21:3<345::aid-smj96>3.3.co;2-e

Cited by 593 publications

(906 citation statements)

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“…We thus have a large data sample on which we apply a simple non-parametric estimation technique -Kernel regression (Yatchew, 1998 for a comprehensive presentation) -which basically amounts to local averaging. 6 Regarding the properties of knowledge accumulation, beside the obvious effect that increasing β decreases knowledge levels (see Equation 2), we care about the allocation of knowledge. We employ the knowledge production function φ rather than say the sum over knowledge categories so endowments are projected into a unit in which summing makes more sense.…”

Section: Numerical Experimentsmentioning

confidence: 99%

Evolving networks of inventors

2006

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In this paper a model for the formation of strategic alliances is studied. Innovation results from the recombination of knowledge held by the partners to the collaboration, and from the history of their collaboration. Innovation brings partners closer together, while at the same time the repetition of partnerships fosters trust and helps improving the outcome of each round of cooperation. A tension exists between innovating with people I know in order to reduce uncertainty at the expense of the net benefit from our joint effort, and innovating with strangers with whom the outcome of joint innovation can be greater but at a larger risk of failure. This "organized proximity", built through the experience of cooperation, can be at the origin of strongly structured networks of innovation, where agents' relations focus on limited cliques of partners. JEL Classification: L14, Z13, O3

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Section: Numerical Experimentsmentioning

confidence: 99%

Evolving networks of inventors

2006

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“…For example, it is a mistake to 8 assume that the relevant actors are all attendees at a relevant meeting, or staff in a functional unit or management team (Creswick, Westbrook, & Braithwaite, 2009;Currie et al, 2010;Dyer & Nobeoka, 2000). The problem with snowball sampling is that the process of asking informants to nominate other people to interview is that their nominations effectively determine network connections: the network may simply be an artefact of the sampling strategy.…”

Section: Sampling Step 1: Landscape Mappingmentioning

confidence: 99%

Using the structure of social networks to map inter-agency relationships in public health services

West

House

Keen

et al. 2015

Social Science & Medicine

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“…This is said to describe a paradigm shift in how companies commercialize industrial knowledge (Chesbrough 2003), and it is contrasted with the 'closed innovation' model in which companies are 1 MOZART is a pseudonym, adopted here to protect confidentiality. Despite the growth in the number of R&D collaborations and the interest they have generated, they are also seen as presenting significant governance challenges (Dyer and Nobeoka 2000;Simon and Kotler 2003). Many of these challenges centre on the fundamental transactional problems affecting any traffic in knowledge between parties, as highlighted by Williamson and other economists.…”

Section: Context For the Studymentioning

confidence: 99%

“…Despite the growth in the number of R&D collaborations and the interest they have generated, they are also seen as presenting significant governance challenges (Dyer and Nobeoka 2000;Simon and Kotler 2003). Many of these challenges centre on the fundamental transactional problems affecting any traffic in knowledge between parties, as highlighted by Williamson and other economists.…”

Section: Context For the Studymentioning

confidence: 99%

Knowledge Governance for Open Innovation: Evidence from an EU R&D Collaboration

Scarbrough¹,

Amaeshi²

2009

Knowledge Governance

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IntroductionThis chapter highlights a particularly challenging arena for knowledge governance, by focussing on the governance issues associated with large-scale programmes of what has been termed 'open innovation'. As outlined in more detail below, open innovation -also sometimes labelled synonymously as 'networked' or 'distributed' innovationis an increasingly important component of the wider patterns of innovation in advanced economies. It can be seen in large part as a response to firms' increasing needs to draw on external sources of knowledge in order to remain competitive in a global economy.Issues of knowledge governance are at the heart of open innovation inasmuch as such innovation is acutely dependent on the organization of knowledge flows between and within firms. The ability of firms to acquire externally-sourced knowledge has been a major subject of academic debate since the pioneering work of Cohen and Levinthal on 'absorptive capacity', and Von Hippel's studies of userdriven innovation (Cohen and Levinthal 1990;von Hippel 1988). However, the distinctive challenges posed by an avowedly open approach to innovation processes are still being digested by researchers. These challenges go some way beyond the problem of absorbing knowledge. According to its proponents, open innovation involves a qualitative shift in the way the firm creates, exploits and organizes knowledge. This has wide-ranging implications for the way the focal firm manages itself and its knowledge-base. At the very least, open innovation implies a reduced dependence on internal R&D functions and a greater willingness to trade knowledge with external collaborators. More broadly, though, the serious pursuit of open 2 innovation is likely to extend to radical changes in the structure and management practices of the firm to foster greater interactivity with the expanding ecology of knowledge providers.It is not within the scope of this paper to address all of the many challenges which open innovation creates for established governance arrangements. Rather, our aim is to provide an initial exploration of some of these challenges by analysing a casestudy of a more open form of innovation. This is an important but also especially complex case because it has to do with MOZART 1 , one of the major collaborative research programmes sponsored by the European Union (EU). This programme represents a unique institutional response to the needs of the aerospace industry in Europe, reflecting not only the diverse needs of the participating companies but also the strategic interests formulated by the EU as a political body. As such it raises the challenges of knowledge governance to a new level, since it encompasses not only questions of effective governance for an innovation process, and the inter-firm collaboration underpinning it, but also the wider challenge of linking private enterprise with the strategic objectives of multi-state bodies. The remainder of this chapter then proceeds as follows. We begin, in the following section, by identifying the...

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Creating and managing a high‐performance knowledge‐sharing network: the Toyota case

Cited by 593 publications

References 10 publications

Evolving networks of inventors

Evolving networks of inventors

Using the structure of social networks to map inter-agency relationships in public health services

Knowledge Governance for Open Innovation: Evidence from an EU R&D Collaboration

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